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ArcUSA User's Guide - University of Waterloo Library

1. Value Livestock Poultry 1K LVSTPOUL_S 1100 17 N 6 528 Farms Selling Poultry POULTRYFAR 1117 17 N 6 536 Value of Poultry Sold 1 000 POULTRYSAL 1134 17 N 6 544 Farms Selling Dairy Products DAIRYFARMS 1151 17 N 6 552 Value Dairy Products 1K DAIRYSALES 1168 17 N 6 Farms Selling Cattle CATTLEFARM 1185 17 N 6 Value of Cattle Sold 1 000 CATTLESALE 1202 17 N 6 576 Farms Selling Hogs and Pigs HOGFARMS 1219 17 N 6 584 Value of Hogs Sold 1 000 HOGSALES 1236 17 N 6 592 Farms Selling Sheep etc SHEEPFARMS 1253 17 N 6 HI t t ti H eo Hg g oooooocoo OO OO OO O0 O0 O0 00 00 00 OC ph ph pb p ph pb ph pb pad fd Value of Sheep Sold 1 000 SHPWOOLSAL 1270 17 N 6 Farms Selling Other Livestock OTHLVSTFAR 1287 17 N 6 Value of Other Livestock Sold OTHLVSTSAL 1304 17 N 6 Farms by SIC Cash Grain SICCASHGRN 1321 17 N 6 Farms in SIC Field Crops SICFLDCROP 1338 17 N 6 Farms in SIC Cotton SICCOTTON 1355 17 N 6 Farms in SIC Tobacco SICTOBACCO 1372 17 N 6 Farms in SIC Other Field Crops SICOTHFLD 1389 17 N 6 Farms in SIC Vegetables SICVEG 1406 17 N 6 Farms in SIC Fruits Nuts SICFRTNUT 1423 17 N 6 HI Ble t t H eo Hg g oooooooccoco ph ph pd p ph p ph pd pd pah Farms in SIC Horticulture SICHORTSP 1440 17 N 6 Farms in SIC General Crops SICGENCROP 1457 17 N 6 Farms in SIC Livestock SICLVSTOCK 1474 17 N 6 Farms in SIC Beef Cattle SICBEEF 1491 17 N 6 Farms in
2. Name Net Migration 1980 66 by state o Faini Theme Data Source GS ADHOME arcusa us_25m stats_s Line Legend Definition W stat_flag 1 al Polygon to z Comments 1 Apply Revert Setting the stat_flag attribute equal to 1 through the Query Builder provides accurate summary statistics for any selected state See the note on the next page for more information about the stat_flag attribute April 1992 2 3 Chapter 2 Exploring the ArcUSA database 3 Inthe Table of Contents select the Table option from the theme specific menu for Net Migration 1980 86 by state This allows you to access information about the total number of people who migrated into or out of a given state from 1980 to 1986 Use the scroll bar to view the full extent of the attributes contained within the stat_s coverage 4 Select the Query Builder icon in the Net Migration 1980 86 by state table Attributes Values Attributes 44704 000 Select 215851991040 000 381321248768 000 83084836864 000 218831044608 000 183398154240 000 251166014336 000 239986631 36 000 173612744704 000 perimeter lt and gt stats_s id state_fips state_name sub_region stat_flag births_64 net_migr lt or gt Cancel New Selection Add to Selection Take from Selection Logical Expression area 173612744704 000 2407 29292 10 0007 445
3. with the lowest income per capita also te Colors experienced the highest loss due to migration 3 Click off the check box for Income per Capita 1985 4 Click on the check box for Unemployment Rate 1986 Again examine the relationship between the two variables Did the counties with high unemployment rates also experience high loss due to net migration The dark shade light pattern combination indicates loser counties with high unemployment On your own Explore the relationships between other 1 2M pop88c and soc88c variables and net migration or introduce a new dependent variable and examine its potential as a causal factor 2 14 ArcUSA User s Guide and Data Reference Landfall of a large oceanic storm This exercise displays information that would be useful for emergency planning if a large oceanic storm were expected to come ashore along a portion of the U S coast Some of the themes in this view would be appropriate for drawing a coastal basemap 1 Begin by opening the view coast av County boundaries in the southern portion of Texas draw to the screen with the Gulf of Mexico shaded by using a theme that references the land2m coverage Within the Table of Contents note that the land attribute for the theme Gulf of Mexico is symbolized with white Because the land is drawn first the graphic display will appear blank until the wate
4. groups Statistical flag polygons Classification attributes lines Feature Number of Polygons Coterminous states 49 features represented by 336 polygons plus District of Columbia All boundaries Represented by 472 lines oa Polygon attributes Geographic reference attributes STATE FIPS The state FIPS code state name or U S subregion can be used STATE NAME to select one or a group of state polygons for display or study SUB_REGION The U S subregions are shown on the map on page 1 2 Statistical flag STAT FLAG Flag to identify a unique polygon for each county and county equivalent The codes are as follows Codes Definitions 0 Additional polygon 1 Largest polygon April 1992 5 21 Chapter 5 The ArcUSA 1 25M layers State Boundaries 5 22 m T_FIPS T_FIPS D nn ST_NAMES BNDY_TYPE Line attributes Geographic reference attributes The FIPS codes of the states on the left and right sides of a boundary are contained in these attributes For state boundaries the left and right FIPS codes are different The left and right sides of a boundary are defined by the direction in which that line segment was digitized so both attributes must be checked when querying for boundaries of a particular state The state on either side of a boundary is identified by name in this attribute Two states are listed for state boundaries e g Wisconsin Minnesota Only one state is identified for interna
5. In addition to being useful as an index for determining the geographic coverage or names of particular quadrangles this medium scale index grid can be a handy visual reference for regional displays Setting the map extent to the limits of one or more quadrangle units is also a simple way to display an area of interest The 2 or 5 degree grids can be overlaid on this index to aid in geographic reference or to create displays of blocks of quadrangles 4 51 Chapter 4 ArcUSA 1 2M index layers USGS 1 100 000 Topographic Quadrangle Series Summary of the USGS 1 100 000 Topographic Quadrangle Series Index coverage Coverage name dBASE UNIX and size MB Q_100K 1 18 1 35 Source and currency Attributes and origin from USGS Topographic Names Database Published Map Sheet Data File also known as the T 70 file and various published indexes Grid from an ESRI algorithm Current to 1986 Thematic attribute groups Classification attributes Feature Number of features Number ol class attributes Polygons Areas covered by Represented by 1 809 polygons 12 USGS 1 100 000 quadrangles Polygon attributes Quadrangle identification attributes USGS QD_ID The quadrangle identification number As shown in the sketch below the ID number incorporates latitude longitude and an alphanumeric grid cell code ID numbers are included for theoretical quadrangles those that do not correspond exactly to published map sheets 37076 ane
6. 0 Nota county seat 1 A county seat Elevation A feature s elevation with respect to sea level expressed in feet is listed for some features 4 21 Chapter 4 ArcUSA 1 2M cartographic layers Place Names CNTY_NAME STATE_FIPS STATE_NAME SUB_REGION 4 22 Geographic reference attributes The name of the county state and U S subregion in which the point feature is located are provided in these attributes The state FIPS code is also given ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA 1 2M cartographic layers Railroads Railroads Layer description Railroad lines are represented in this layer They are identified as main or branch lines based on U S Department of Transportation definitions and are classified based on the annual volume of traffic they bear Other railroad lines such as sidings and railroad ferries are also identified Using the Railroads coverage The general decline of the U S railroad industry has resulted in significant reduction in rail line usage since the National Atlas was prepared in 1973 The features in this coverage are those represented in the DLG database April 1992 4 23 Chapter 4 ArcUSA 1 2M cartographic layers Railroads Summary of the Railroads coverage Coverage name dBASE UNIX and size MB RR2M 4 94 4 37 Source and currency USGS DLG 1979 Thematic attribute Classification attributes groups Geographic reference attributes Feature N
7. 720 728 736 744 752 760 768 7716 784 792 800 808 816 824 832 840 848 856 864 8 11 F 0 INFO Items Begin Column 17 20 23 29 49 81 88 89 97 Item 3 3 3 3 6 6 C 20 20 C 32 32 C 7 7 C 1 1 8 11 F 0 8 11 F 0 continued Definition B 23 Appendix B ArcUSA 1 2M state and county statistical attribute layers Agricultural Product Inventory continued Polygon Attribute Table County Level Coverage continued dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Average Farm Size in Acres AVG_SIZE 155 17 N 6 105 8 11 F 0 Value of Land etc per Farm LAND_BLD_F 172 17 N 6 113 Value of Land etc per Acre LAND_BLD_A 189 17 N 6 121 Value of Machinery per Farm MACHINE _F 206 17 N 6 129 Farms 1 to 9 Acres in Size F_1_9ACRE 223 17 N 6 137 Farms 10 to 49 Acres in Size F_10_49 240 17 N 6 145 Farms 50 to 179 Acres in Size F_50_179 257 17 N 6 153 Farms 180 to 499 Acres in Size F_180_499 274 17 N 6 161 Farms 500 to 999 Acres in Size F_500_999 291 17 N 6 169 Farms Over 999 Acres in Size F_OVER_999 308 17 N 6 177 No of Farms with Cropland CROP_FARMS 325 17 N 6 185 Cropland in Acres CROP_ACRES 342 17 N 6 193 Farms with Harvested Cropland HARVSTED_F 359 17 N 6 201 Harvested Cropland in Acres HARVSTED_A 376 17 N 6 209 Farms with Irrigated Land IRRIGATE_F 393 17 N 6 Irrigated Land in Acres IRRIGATE_A 410 17 N 6 V
8. 80 3 N 0 83 3 N 0 86 41 C 0 127 11 N 0 Note The state level and county level AATs are identical Agricultural Product Market Value Coverage Names Layer Type AGVL_S AGVL_C Polygon and Line 29 3 3 32 35 76 Polygon Attribute Table State Level Coverage Item Description State FIPS Code State Name U S Subregion Code Statistical Flag Farms with Agricultural Sales Total Ag Sales 1 000 Average Sales per Farm Farms Selling lt 1 000 Products Product Value Farms w lt 1K Farms Selling 1 000 2 500 Sales by Farms w 1K 2 5K Farms Selling 2 500 5 000 Sales by Farms w 2 500 5K Farms Selling 5 000 10 000 Sales by Farms w 5K 10K Farms Selling 10 000 20 000 Sales by Farms w 10K 20K Farms Selling 20 000 25 000 ltem Name dBASE Columns Begin Column Column Definition INFO Items Begin Item Column Definition STATE_FIPS STATE_NAME SUB_REGION STAT_FLAG SALESFARMS SALES_1K AVG_SALES FARM_UNDIK SALE UNDIK F_1K_2500 S_1K_2500 F_2500_5K S_2500_5K FARM_5_10K SALE _5_10K F_10_20K S_10_20K F_20_25K 3 N 0 20 C 0 7 C 0 1 N 0 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 3 3 1 20 20 20 C continued April 1992 B 27 Appendix B ArcUSA 1 2M state and county statistical attribute layers Agricultural Product Market Value continued Polygon Attribute Table St
9. Begin Column Column 49 5 C 0 Annotation Includes country water body and other major place names Arc Attribute Table Item Description Feature Grid Identifier ltem Name dBASE Columns Begin Column Column Definition Definition 29 3 3 3 3 41 41 C 4 5 B INFO Items Begin Item Column Definition 17 5 5 C INFO Items Begin Item Column Definition BND_GRID 80 1 N 0 29 1 1 April 1992 B 47 Appendix B ArcUSA 1 25M layers Map Elements Coverage Name Layer Type SC_25M Polygon and Line Polygon Attribute Table Item Description Fill Area Code ltem Name Column dBASE Columns Begin Column Definition INFO Items Begin Item Column Definition FILL1 49 2 N 0 Annotation Includes labels for scale bar North arrow and display title Arc Attribute Table Item Description ltem Name dBASE Columns Begin Column Column Definition 17 2 2 1 INFO Items Begin Item Column Definition All items are ARC INFO generated Rivers Coverage Name Layer Type Arc Attribute Table Item Description RIV_25M Line River Classification Code River Classification Code Name RIVER_TYPE State FIPS Code State Name U S Subregion Code B 48 ltem Name dBASE Columns Begin Column Column Definition INFO Items Begin Item Column Definition TYPE STATE_FIPS STATE_NAME SUB_REGION 80
10. C J Emerson and M K Nungesser 1980 Geoecology A County Level Environmental Data Base for the Conterminous United States ORNL TM 7351 Oak Ridge Tenn Oak Ridge National Laboratory U S Bureau of the Census 1991 Public Law 94 171 Washington D C 1990 Census data on total population age sex race available in listings and computer files U S Geological Survey 1990 Digital Line Graphs from 1 2 000 000 Scale Maps Data Users Guide 3 Reston Va Political boundaries and other geographic data were derived from the 1972 73 update of the National Atlas sectional maps U S Geological Survey 1970 The National Atlas of the United States of America Washington D C April 1992 D 1 Appendix D Bibliography U S Geological Survey Catalog of Topographic and Other Published Maps and the Index to Topographic and Other Map Coverage Reston Va Book pairs for all fifty states dates vary Reference data The following printed publications were used to verify the accuracy and consistency of the database Atlas of North America Space Age Portrait of a Continent 1985 Washington D C National Geographic Society Handy Railroad Atlas of the United States 1988 Chicago Rand McNally amp Company National Geographic Atlas of the World Sixth Edition 1990 Washington D C National Geographic Society Rand McNally Road Atlas 1990 Chicago Rand McNally amp Company The New International Atlas 198
11. Farms with Corn for Grain etc Acres of Corn Bushels of Corn Harvested SHEEPFARMS SHEEP CHICKENFAR CHICKENS BROILSLD_F BROIL_SOLD CORNFARMS CORNACRES CORN_BU 784 801 818 835 852 869 886 903 920 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 401 409 417 425 433 441 449 457 SILAGEFARM 937 SILAGEACRE 954 SILAGE_TON 971 SORGHMFARM 988 SORGHMACRE 1005 SORGHM_BU 1022 WHEATFARMS 1039 WHEATACRES 1056 WHEAT_BU 1073 BARLEYFARM 1090 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 p Farms with Corn for Silage Acres of Corn for Silage Tons of Corn Silage Produced Farms with Sorghum Acres of Sorghum Bushels of Sorghum Harvested Number of Farms with Wheat Acres of Wheat Bushels of Wheat Harvested Farms with Barley p pt _ p p HI t t ti H eo Hg g oooooocoo ph ph pb p ph pb ph pb fm fd p PO GO OO PO OO 09 O9 200 OP BARLEY ACRE 1107 BARLEY_BU 1124 OATSFARMS 1141 OATSACRES 1158 OATS_BU 1175 RICEFARMS 1192 Acres of Rice RICEACRES 1209 Rice Harvested 100 pounds RICE_CWT 1226 Farms with Sunflowers for Seed SUNFLWFARM 1243 Acres of Sunflowers for Seed SUNFLWACRE 1260 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 p Acres of Barley Bushels of Barley Harvested Farms with Oats Acres of Oats Bushels of Oats Harvested Farms with Rice pt j
12. Florence SC MSA Fort Collins Loveland CO MSA Fort Lauderdale Hollywood Pompano FL PMSA Fort Myers Cape Coral FL MSA Fort Pierce FL MSA Fort Smith AR OK MSA Fort Walton Beach FL MSA Fort Wayne IN MSA Fort Worth Arlington TX PMSA Fresno CA MSA Gadsden AL MSA Gainesville FL MSA Galveston Texas City TX PMSA Gary Hammond IN PMSA Glens Falls NY MSA Grand Forks ND MSA Grand Rapids MI MSA Great Falls MT MSA Greeley CO MSA Green Bay WI MSA Greensboro Winston Salem HighPoint NC MSA Greenville Spartanburg SC MSA Hagerstown MD MSA Hamilton Middletown OH PMSA Harrisburg Lebanon Carlisle PA MSA Hartford CT PMSA Hartford New Britain Middletown CT Hartford New Britain Middletown Bristol CT NECMA Hickory NC MSA Honolulu HI MSA Houma Thibodaux LA MSA Houston TX PMSA Houston Galveston Brazoria TX CMSA Huntington Ashland WV KY OH MSA Huntsville AL MSA Indianapolis IN MSA Iowa City IA MSA April 1992 Appendix C FIPS codes 3520 3560 3580 3600 3605 3620 3640 3660 3680 3690 3710 3720 3740 3760 3800 3810 3840 3850 3870 3880 3920 3960 3965 3980 4000 4040 4080 4100 4120 4150 4160 4200 4240 4243 4280 4320 4360 4400 4420 4440 4472 4480 4520 4560 4600 4640 4680 4720 4760 Jackson MI MSA Jackson MS MSA Jackson TN MSA Jacksonville FL MSA Jackson
13. Shannon 115 Spink 117 Stanley 119 Sully 121 Todd 123 Tripp 125 Turner 127 Union 129 Walworth 135 Yankton 137 Ziebach Tennessee 1 Anderson 3 Bedford 5 Benton 7 Bledsoe 9 Blount 11 Bradley 13 Campbell 15 Cannon 17 Carroll 19 Carter 21 Cheatham 23 Chester 25 Claiborne 27 Clay 29 Cocke 31 Coffee 33 Crockett 35 Cumberland 37 Davidson 39 Decatur 41 De Kalb 43 Dickson 45 Dyer 47 Fayette 49 Fentress 51 Franklin 53 Gibson 55 Giles 57 Grainger 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 Greene Grundy Hamblen Hamilton Hancock Hardeman Hardin Hawkins Haywood Henderson Henry Hickman Houston Humphreys Jackson Jefferson Johnson Knox Lake Lauderdale Lawrence Lewis Lincoln Loudon McMinn McNairy Macon Madison Marion Marshall Maury Meigs Monroe Montgomery Moore Morgan Obion Overton Perry Pickett Polk Putnam Rhea Roane Robertson Rutherford Scott Sequatchie Sevier Shelby Smith Stewart Sullivan Sumner Tipton Trousdale Unicoi Union 175 177 179 181 183 185 187 189 Van Buren Warren Washington Wayne Weakley White Williamson Wilson Anderson Andrews Angelina Aransas Archer Armstrong Atascosa Austin Bailey Bandera Bastrop Baylor Bee Bell Bexar Blanco Borden Bosque Bowie Brazoria
14. A window pops up that contains all attributes within the stat_s coverage for Michigan Scroll to the attribute tax_cap within the pop up window Comparing this figure to the average of 429 for California may help explain the difference in net migration between the two states The people of Michigan paid an average of 560 per capita to local government during 1981 1982 Attributes area perimeter stats_s id state_fips state_name sub_region stat_flag births_64 Logical Expression Values Attributes 105000 15000 14000 gt 13000 ea 72000 15000 43000 67000 4 gt A 500000 Select lt and gt lt 0r gt Cancel New Selection Add to Selection Take from Selection net_migr lt 500000 IELI 0 11 24872329216 000 44527986208 000 21981296640 000 2099593 500 99931396096 000 806736 938 igseda9 875 39 52 A E BOO BOB T 2 8 ArcUSA User s Guide and Data Reference Exploring U S migration trends 1980 to 1986 by county You have seen how you can use the ArcUSA database to look at summary level migration patterns by state You can also use the database to see finer resolution patterns at the county level Begin by opening the existing view mig25mc av A thematic map showing county level migration
15. April 1992 4 117 Chapter 4 ArcUSA state and county statistical attribute layers Socioeconomic Attributes CNTY_FIPS FIPS CNTY_NAME STAT_FLAG CNTY_TYPE MET_ST_AR PR_MT_ST_A 4 118 These geographic reference attributes appear only in the county level coverages The county polygon coverages contain the county FIPS code the combined state and county FIPS code and the county name Statistical flag Flag to identify a unique polygon for each state or county The codes are as follows Codes Definitions 0 Other polygon 1 Largest polygon Metropolitan area attributes These attributes appear only in the county level coverages This attribute allows the user to select counties according to census geography The metropolitan area terms are explained on page 4 91 The codes are as follows e County within a CMSA PMSA e County within an MSA e County within an NECMA e County not in a metro area Metropolitan Statistical Area MSA or Consolidated MSA CMSA FIPS code This attribute is blank for counties that are not included in an MSA or CMSA and for MSA counties in New England Primary Metropolitan Statistical Area PMSA FIPS code In general a PMSA is a county that contains a city of over 100 000 population ArcUSA User s Guide and Data Reference LAND_AREA HSEHOLD_85 P_CHG_HHLD PERS_HHLD HSEHOLD_80 P_FEM_HHLD P_1PER_HH SSEC_RECIP SSRECIP_1K SSPAYMT_1K April 1992
16. April 1992 4 3 Chapter 4 ArcUSA 1 2M cartographic layers County Boundaries County Boundaries Layer description The County Boundaries layer serves as a county base map for the coterminous United States Two new counties for Arizona and New Mexico as well as several independent cities primarily in Virginia were added by ESRI to the DLG source data These additions brought the currency of the layer from 1973 to 1988 More than 3 100 substate political units are represented A line attribute classifies boundaries as shorelines or as county state or international boundaries Attributes that permit states or counties to be selected for display are contained in both the line and polygon attribute tables Using the County Boundaries coverage Some counties such as those that include offshore islands are represented by multiple polygons A flag attribute is provided so that the largest polygon can be used to represent the county for choroplethic mapping or text labeling The county name attribute can be used to provide the text for labeling the polygons in a base map April 1992 4 5 Chapter 4 ArcUSA 1 2M cartographic layers County Boundaries Summary of the County Boundaries coverage Coverage name dBASE UNIX and size MB CTY2M 5 37 4 78 Source and currency USGS DLG 1988 Thematic attribute Geographic reference attributes polygons and lines groups Statistical flag polygons Classificat
17. Brazos Brewster Briscoe Brooks Brown Burleson Burnet Caldwell Calhoun Callahan Cameron Camp Carson Cass Castro Chambers Cherokee Childress Clay Cochran Coke Coleman Collin Collingsworth Colorado Comal Comanche Concho 97 99 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 175 177 179 181 183 185 187 189 191 193 195 197 199 201 203 205 207 209 211 Cooke Coryell Cottle Crane Crockett Crosby Culberson Dallam Dallas Dawson Deaf Smith Delta Denton De Witt Dickens Dimmit Donley Duval Eastland Ector Edwards Ellis El Paso Erath Falls Fannin Fayette Fisher Floyd Foard Fort Bend Franklin Freestone Frio Gaines Galveston Garza Gillespie Glasscock Goliad Gonzales Gray Grayson Gregg Grimes Guadalupe Hale Hall Hamilton Hansford Hardeman Hardin Harris Harrison Hartley Haskell Hays Hemphill April 1992 C 13 Appendix C FIPS codes 213 215 217 219 221 223 225 227 229 231 233 235 237 239 241 243 245 247 249 251 253 255 25T 259 261 263 265 267 269 271 213 275 277 279 281 283 285 287 289 291 293 295 297 299 301 303 305 307 309 311 313 315 317 319 321 323 325 327 Henderson Hidalgo Hill Hockley Hood Hopkins Houston Howard Hudspeth Hunt Hutchinson Irion Jack Jackso
18. Bureau of the Census Washington D C 1991 U S Census of Agriculture 1987 The U S Census of Agriculture is a statistical report developed at fixed intervals by the U S Bureau of the Census The census provides summary statistical information for all farms with sales of 1 000 or more The data are presented in more than fifty tables and are available in digital form Only a subset of these data are included in the ArcUSA database the Agricultural Product Inventory layers contain state and county attributes from Table 1 of the census and the Agricultural Product Market Value layers contain attributes from Table 2 The reference document for this data source is Census of Agriculture 1987 on CD ROM U S Bureau of the Census Data User Services Division Washington D C 1990 County and City Data Book 1988 The County and City Data Books are interim that is non census year statistical products developed by the U S Bureau of the Census They provide data for states counties cities of 25 000 or more residents and places with 2 500 or more residents The data are tabular and available in digital form The ArcUSA User s Guide and Data Reference April 1992 Chapter 3 Database concepts and organization ArcUSA database employs state and county data from the 1988 County and City Data Book which contains statistics that vary in currency from 1979 to 1986 These data are the basis for the attributes in three groups of ArcUSA co
19. CA MSA Salt Lake City Ogden UT MSA San Angelo TX MSA San Antonio TX MSA San Diego CA MSA San Francisco CA PMSA 7362 7400 7480 7485 7490 7500 7510 7520 7560 7600 7602 7610 7620 7640 7680 7720 7760 7800 7840 7880 7920 8000 8003 8040 8050 8080 8120 8160 8200 8240 8280 8320 8360 8400 8440 8480 8520 8560 8600 8640 8680 8720 8725 8750 8760 8780 San Francisco Oakland San Jose CA CMSA San Jose CA PMSA Santa Barbara Santa Maria Lompoc CA MSA Santa Cruz CA PMSA Santa Fe NM MSA Santa Rosa Petaluma CA PMSA Sarasota FL MSA Savannah GA MSA Scranton Wilkes Barre PA MSA Seattle WA PMSA Seattle Tacoma WA CMSA Sharon PA MSA Sheboygan WI MSA Sherman Denison TX MSA Shreveport LA MSA Sioux City IA NE MSA Sioux Falls SD MSA South Bend Mishawaka IN MSA Spokane WA MSA Springfield IL MSA Springfield MO MSA Springfield MA MSA Springfield MA NECMA Stanford CT PMSA State College PA MSA Steubenville Weirton OH WV MSA Stockton CA MSA Syracuse NY MSA Tacoma WA PMSA Tallahassee FL MSA Tampa St Petersburg Clearwater FL MSA Terre Haute IN MSA Texarkana TX Texarkana AR MSA Toledo OH MSA Topeka KS MSA Trenton NJ PMSA Tucson AZ MSA Tulsa OK MSA Tuscaloosa AL MSA Tyler TX MSA Utica Rome NY MSA Vallejo Fairfield Napa CA PMSA Vancouver WA PMSA Victor
20. Chapter 4 ArcUSA state and county statistical attribute layers Socioeconomic Attributes County land area This attribute appears only in the county level coverages The land area of the county in 1980 Land area excludes the areas of water bodies The value in this item is measured in square miles Households Number of households in the state or county in 1985 The percentage of change in the number of households in the state or county between 1980 and 1985 Average number of people per household in the state or county in 1985 Number of households in the state or county in 1980 Percentage of households with a female family householder in the state or county in 1980 Percentage of all households that were comprised of one person in the state or county in 1980 Social Security The number of Social Security beneficiaries in the state or county in 1985 This figure includes retired and disabled workers and their dependents and survivors of insured workers who receive monthly benefits under the Social Security program The number of Social Security beneficiaries per 1 000 population in the state or county in 1985 Social Security payments to people in the state or county in thousands of dollars 1985 4 119 Chapter 4 ArcUSA state and county statistical attribute layers Socioeconomic Attributes 4 120 SUPP_RECIP SERIOUS_CR VIOLENT_CR SR_CR_100K PUPILS86 PUPILS80 P_HS_GRADS Su
21. EOSAT EOSAT provided ESRI with an algorithm for generating two types 3 17 Chapter 3 Database concepts and organization 3 18 of index information for Landsat 4 and 5 scenes nominal scene center points and nominal scene footprints Nominal indicates that the center points and footprints represent an average not an absolute geographic location The center points and footprints are averaged because the orientation of the satellite varies slightly from one orbit to the next Nominal scene center points were calculated first then scene footprints were mathematically generated with the center points as the focus The footprints are rectangular outlines whose exact dimensions vary with satellite orientation In the ArcUSA database these data are the basis for the Landsat Nominal Scene Index coverages U S Census of Population and Housing 1990 The U S Census of Population and Housing is a compilation of statistical data on population and housing that is developed every ten years by the U S Bureau of the Census The data are tabular and available in digital form The ArcUSA database employs a subset of the 1990 Census known as Public Law 94 171 data These data support congressional and legislative redistricting and are the first data to be released from the new census The ArcUSA 1990 Census Public Law 91 171 Data layers contain these data for states and counties The reference document for this data source is Public Law 94 171 U S
22. In instances where a county boundary was coincident with a state or international boundary or coastline multiple arcs were occasionally present in the DLG source data i e one arc for each boundary type For the ArcUSA database all such duplicates were eliminated leaving only one arc representing the feature The DLG source data were updated by ESRI to contain two new counties for Arizona and New Mexico as well as several independent cities primarily in Virginia Attribution County names CNTY_NAME and U S subregions SUB_REGION were added to the database as new items All lines in the layer were attributized with boundary type BNDY_TYPE identifying the type of boundary Some boundaries were coincident for example a county boundary might also be a state boundary and an international boundary Thus the boundary mentioned above would be attributized as an international boundary In such cases priority was assigned as follows 1 coastline 2 international boundary 3 state boundary 4 county boundary Data quality review County and combined state and county FIPS codes were reviewed visually and corrected when found to be invalid or missing ArcUSA User s Guide and Data Reference April 1992 Appendix A Data quality information Federal Lands layer Topological edits The Federal Lands data were integrated with the State Boundaries data through an overlay process Attribution The multiple coding scheme employed
23. Lakes Represented by 513 points Reservoirs Represented by 787 points All point features Represented by 5 062 points represented as areas in the Federal Lands layer The lakes and reservoirs named here are represented as polygons in the Lakes and Other Water Bodies layer Point attributes Classification attributes NAME This attribute stores the name of the populated place or named area feature that corresponds to a point location 4 20 ArcUSA User s Guide and Data Reference April 1992 FEAT_TYPE MAJ_CITY CAPITAL CTY_SEAT ELEVATION Chapter 4 ArcUSA 1 2M cartographic layers Place Names The name of the feature The five feature types available in this layer are as follows Names Definitions City City or other populated place Forest National forest Park National park Lake Lake Reservoir Reservoir This attribute contains codes that identify the seventy four most populous cities in the coterminous United States Codes Definitions 0 Nota major city 1 A major city This attribute contains codes that identify the capital cities of the forty eight states in the database plus the national capital Codes Definitions 0 Nota capital 1 A state capital 2 The national capital Washington D C This attribute contains codes that identify which of the major cities and state capital cities are also county seats There are ninety six county seats in this coverage Codes Definitions
24. MAJ CITY This attribute contains codes that identify the seventy four most populous cities in the coterminous United States Codes Definitions 0 Not a major city 1 A major city CAPITAL This attribute contains codes that identify the capital cities of the forty eight states in the database plus the national capital Codes Definitions 0 Nota capital 1 A state capital 2 The national capital Washington D C 5 4 ArcUSA User s Guide and Data Reference April 1992 CTY_SEAT ELEVATION CNTY_NAME STATE_FIPS STATE_NAME SUB_REGION Chapter 5 The ArcUSA 1 25M layers Cities This attribute contains codes that identify which of the major cities and state capital cities are also county seats There are ninety six county seats in this coverage Codes Definitions 0 Nota county seat 1 A county seat Elevation A city s elevation with respect to sea level expressed in feet Elevation is listed for some cities only Geographic reference attributes Cities can be selected by the county name state name state FIPS code or the subregion in which they are located 5 5 Chapter 5 The ArcUSA 1 25M layers County Boundaries Polygons Lines 5 6 Layer description The County Boundaries layer serves as a small scale county basemap for the coterminous United States The cartographic representation of political boundaries and shorelines has been generalized from the ArcUSA 1 2M County Boundaries layer
25. Percent Non Hispanic Black P_NHBLACK 492 13 N 6 213 4 5 F 2 Non Hispanic Amer Ind NHAMIND 505 11 N 0 217 4 9 B Percent Non Hispanic Am Ind P_NHAMIND 516 13 N 6 221 4 5 F 2 Non Hispanic Asian NHASIAN 529 11 N 0 225 Percent Non Hispanic Asian P_NHASIAN 540 13 N 6 229 Non Hispanic Other NHOTHER 553 11 N 0 233 Percent Non Hispanic Other P_NHOTHER 564 13 N 6 237 Total Hispanic 18 Years and Older HISPAN18 577 11 N 0 241 Percent Hispanic 18 P_HISPAN18 588 13 N 6 245 Total Non Hispanic 18 NHISPN18 601 11 N 0 Percent Non Hispanic 18 P_NHISPN18 612 13 N 6 Non Hispanic White 18 NHWHIT18 625 11 N 0 Non Hispanic White 18 P_NHWHIT18 636 13 N 6 Non Hispanic Black 18 NHBLK18 649 11 N 0 Non Hispanic Black 18 P_NHBLK18 13 N 6 Non Hispanic Am Ind 18 NHAMIN18 11 N 0 Non Hisp Am Ind 18 P_NHAMIN18 13 N 6 Non Hispanic Asian 18 NHASIA18 11 N 0 Non Hispanic Asian 18 P_NHASIA18 13 N 6 Non Hispanic Other 18 NHOTHE18 11 N 0 Non Hispanic Other 18 P_NHOTHE18 13 N 6 Housing Units 1990 HSE_UNITS 11 N 0 April 1992 B 19 Appendix B ArcUSA 1 2M state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data continued Arc Attribute Table dBASE Columns Begin Column Begin Item Column Definition Column Definition 3 N 0 29 3 3 1 3 N 0 32 41 C 0 35 11 N 0 76 INFO Items Item Name L_ST_FIPS R_ST_FIPS ST_NAMES BNDY_TYPE Item Description Left State FIPS Code Right
26. ST_FIPS2 scene covers to a maximum of six The FIPS codes are y always stored beginning with ST_FIPS1 but the states are ST FIPS5 _ Not listed in any particular order For a complete listing of ST_FIPS6 state FIPS codes see Appendix C ST NAME1 The names of the states the scene covers are stored in these ST_NAME2 attributes The state names are always stored beginning with ST_NAME3 i ST NAME4 ST_NAME 1 but they are not listed in any particular order ST_NAME5 ST_NAME6 April 1992 4 41 Chapter 4 ArcUSA 1 2M index layers Latitude Longitude Grids Lines 4 42 Layer description The Latitude Longitude Grids layer contains lines that represent geographic parallels lines of latitude and meridians lines of longitude at intervals of 2 degrees 5 degrees and 10 degrees The grids for the three intervals are contained in separate coverages Attributes include the latitude or longitude value of each line and codes indicating whether a line segment is inside the continental United States Using the Latitude Longitude Grids coverages The U S Non U S attribute gives you the flexibility to symbolize the latitude longitude grid differently in the foreground and background of a display For example you might choose to display the graticule in the ocean areas background and to exclude it from the area inside the United States to avoid obscuring other map features The scale of
27. and not a code or designation For example the values in the measurement attribute PERS_HHLD persons per household 1985 represent the average number of people per household Measurement values are usually continuous such as 3 145 or 6 2 or 43 8 but may be ordinal first second etc In the ArcUSA database measurement attributes are most common in the statistical attribute layers Measurements can be expressed either as raw values or as percentages Raw or nonstandardized attributes such as the number of active physicians in ArcUSA User s Guide and Data Reference Chapter 3 Database concepts and organization Geographic reference Measurement m Flag attribute attribute attribute v Socioeconomic Attributes All Ta Selected EJ W cnty_type met_st_ar ipr_mt_st_a land_area i pop1986 pop_rank pop_sqmile Nebraska contain values indicating the original count or measurement Such attributes cannot be compared across counties or states because no standard for comparison has been established Raw values can be standardized to a unit of area or population size For example the number of physicians in Nebraska could be divided by the total number of people in the state resulting in the value for the number of physicians per capita This standardized value can then be meaningfully compared to the number of physicians per capita in other states Many raw values in the ArcUSA statistical attri
28. because they are of recent origin Soil order histosol Histosols develop in poorly drained areas such as peat bogs and they are rich in organic matter Soil order inceptisol Inceptisols are very young soils that are just beginning to form They are commonly found in tundra areas Soil order mollisol These dark soils are rich in organic matter and are very productive for agriculture Mollisols typically develop in grasslands such as the Great Plains 4 105 Chapter 4 ArcUSA state and county statistical attribute layers Environmental Attributes SPODOSOL P_SPODOSOL ULTISOL P_ULTISOL VERTISOL P_VERTISOL L_ST_FIPS R_ST_FIPS ST_NAMES BNDY_TYPE 4 106 Soil order spodosol Spodosols are commonly found in cool humid forest areas They are acidic and not very fertile Soil order ultisol Ultisols are commonly found in warm humid areas such as the southeastern United States They are weathered acidic and typically red or yellow Ultisols can be productive for agriculture when treated with lime and fertilizers Soil order vertisol Vertisols are rich in clay and form cracks when they become dry Line attributes Geographic reference attributes The FIPS code of the states on the left and right sides of a boundary segment The states on either side of a boundary are identified by name in this attribute Classification attribute The type of boundary the line represents The codes are
29. data source for 3 15 3 16 3 17 item definitions B 46 to B 47 Coverages see also ArcUSA 1 2M data layers ArcUSA 1 25M data layers defined 3 2 in ArcUSA database 1 4 to 1 9 Data quality review procedures for accuracy of attribution A 14 A 20 for completeness A 15 A 21 for correctness of topology A 14 A 20 for DLG derived data A 6 A 7 for logical consistency A 14 A 20 for nominal scene footprints A 13 layer specific County Boundaries 1 2M A 8 Lakes and Other Water Bodies A 9 Roads A 11 State Boundaries 1 2M A 12 Data sources 3 15 to 3 19 D 1 to D 2 A 5 to A 13 A 18 to A 19 table listing 3 16 Data suppressed 3 9 4 73 4 80 4 89 to 4 90 Database size x 1 4 to 1 9 ArcUSA User s Guide and Data Reference Datums 3 21 A 4 A 17 Decimal degrees See Projection systems Demographic and Health Attributes layer 1 2M 4 89 to 4 99 data sources for 3 16 3 17 3 18 to 3 19 4 98 item definitions B 33 to B 36 meaning of zero values in 4 89 digital meaning of in quadrangle name 4 48 4 53 4 56 Digital Line Graphs characteristics of 3 15 3 17 layers employed in 3 17 production processing applied to A 5 to A 12 A 18 Disk space requirements for ArcUSA database x Display See Color Graphics Downloading the database 6 3 to 6 4 Drainage network how to display 4 26 Drawing order 6 6 Environmental Attributes layer 1 2M 4 100 to 4 106 data sources for 3 16 3 17 3 19 item definitions B 37 to B 39 EOSAT
30. emmer field seeds flaxseed lentils mustard seed oats popcorn rye safflower sorghum and other small grains Field crops other than cash grains SIC 013 Cotton and cottonseed SIC 0131 Tobacco SIC 0132 Other field crops SIC 0133 0134 0139 Includes sugar cane sugar beets Irish potatoes alfalfa broomcorn clover flax hay hops mint peanuts sweet potatoes and timothy Vegetables and melons SIC 016 Fruits and tree nuts SIC 017 Includes berries grapes tree nuts citrus fruits deciduous tree fruits avocados dates figs olives pineapples and tropical fruit Horticultural specialties SIC 018 Includes ornamental plants nursery products such as bulbs florists greens flowers shrubbery flower and vegetable seeds and plants and sod mushrooms and vegetables grown under cover General farms that primarily raise crops SIC 019 Includes crop farms where less than 50 of sales came from any single three digit industry group Livestock except specialties SIC 021 Includes cattle calves hogs sheep goats goat s milk wool and mohair Beef cattle except feedlots SIC 0212 4 87 Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Market Value SICDAIRY Dairy SIC 024 Includes production of cow s milk and other dairy products and raising of dairy heifer replacements SICPOULTRY Poultry and eggs SIC 025 Includes chickens chicken eggs
31. from the true correct position of the map feature as indicated on the stable base copy of the USGS source graphic The original USGS source conformed to the requirement that 90 of the well defined points tested be in error by no more than 1 30 in 0 85 mm A root sum square calculation indicates that the expected positional error of the DLGs is 0 034 in 0 86 mm or a ground distance of 1720 m Additional ESRI processes that could introduce error include the application of fuzzy tolerances of 50 8 m Fuzzy tolerances have the potential of offsetting lines from their original positions by the amount specified although the effects are extremely localized Therefore a conservative estimate of the accuracy of the ArcUSA 1 2M data derived from the DLGs is SQRT 1720 m 2 50 8 m 2 or 1722 m The positional accuracy of the ArcWorld 1 3M data is not known No detailed evaluation of the positional accuracy of this database has been made and knowledge of the source of the WDBII data is insufficient to make a determination in this regard Attribute accuracy The accuracy of most attributes in the ArcUSA 1 2M database has not been explicitly tested against independent sources However all of the data have been reviewed for anomalous visual patterns both on line and in hard copy Before attribute restructuring into the 1 2M design road rail and drainage features were plotted with various attribute combinations symbolized and reviewed aga
32. in Table 1 of Getting Started are larger than the sum of the component coverages 1 3 Chapter 1 What is ArcUSA Table 1 ArcUSA 1 2M cartographic layers Features County Boundaries Federal Lands Lakes and Other Water Bodies Polygons 4 409 counties independent cities Lines 10 485 county and independent city boundaries Polygons 2 741 national parks recreation areas Indian reservations Polygons 6 365 lakes reservoirs marshes islands Land Ocean Display Polygons 1 471 land water Lines 1 860 features grid Annotation Canada Mexico Map Elements Rivers and Streams Polygons 15 scale bar North arrow Lines 43 scale bar North arrow Annotation map title scale Points 5 062 county seats national forest and park names lake locations Lines 12 182 railroad lines Lines 38 734 perennial intermittent and braided rivers canals Lines 28 730 Interstates U S and state highways unimproved roads State Boundaries Polygons 1 295 states Lines 1 607 state and international boundaries shorelines Polygon attributes 7 county and state names FIPS codes U S subregion Line attributes 4 boundary type geogr reference Polygon attributes 9 area type codes and names state name FIPS subregion Polygon attributes 5 type type name state state FIPS subregion Polygon attributes 1 land water code Line attributes 1 feature gri
33. one or more attributes are blank The names of the states the quadrangle covers are stored in these attributes The state names are always stored beginning with ST_NAME1 but they are not listed in any particular order Publication data Most recent date of publication expressed as the last two digits of the year 4 53 Chapter 4 ArcUSA 1 2M index layers USGS 1 250 000 Topographic Quadrangle Series USGS 1 250 000 Topographic Quadrangle Series Index Polygons 4 54 Layer description The USGS 1 250 000 Topographic Quadrangle Series Index layer contains polygons that represent the geographic extent of USGS 1 250 000 topographic maps Quadrangle names publication data and map coverage by state are given for each quadrangle Using the USGS 1 250 000 Topographic Quadrangle Series Index coverages The quadrangle index contained in this layer is a systematic grid based on the graticule The relationship between this quadrangle index the graticule and the other two quadrangle series in the ArcUSA database are explained in Using the USGS Topographic Quadrangle Index Layers page 4 45 In addition to its being useful as an index for determining the geographic coverage or names of particular quadrangles this small scale index grid can be a handy visual reference for regional displays Setting the map extent to the limits of one or more quadrangle units is also a simple way to display an area of inte
34. 1 to 4 123 characteristics 3 7 4 1 A 3 to A 4 table lists of 1 4 to 1 7 4 3 4 37 4 59 A 3 resolution of A 3 units of measure used in 6 5 ArcUSA 1 25M data layers 5 1 to 5 31 characteristics 3 8 5 1 A 16 to A 17 table lists of 1 8 to 1 9 5 1 A 16 resolution of A 16 units of measure used in 6 5 use of to optimize performance 2 13 2 15 5 6 6 2 ArcUSA database applications ix data sources and currency table 3 16 introduced 1 1 modifications made to source data A 2 positional accuracy of A 13 to A 14 A 19 to A 20 production process for A 5 to A 7 A 8 to A 12 quality assurance review procedures A 7 to A 8 regions and subregions for 1 2 units of measure in 6 5 use with other software 1 1 6 4 ArcView use with ArcUSA xii ArcWorld 1 3M data A 12 A 19 Area defined 3 1 3 3 Asterisk meaning of in Demographic and Health Attributes layer 4 91 Attributes accuracy of A 7 to A 8 A 14 A 20 alphabetic use of 3 10 classification defined 3 12 code defined 3 10 to 3 11 downloading 6 3 flag See Flag attribute April 1992 Index 1 Index Attributes cont geographic reference defined 3 12 introduction into index and statistical layers A 6 listed 3 13 measurement defined 3 8 lack of standardization 3 8 to 3 9 suppression of 3 9 metropolitan area 4 91 to 4 93 5 23 name 3 11 numeric 3 10 prioritized 3 11 4 8 4 10 types of 3 8 to 3 12 Background polygons suppression of 4 11 Bivariate mappin
35. 25 000 000 Resolution Lines Polygons Resolution of statistical data To county level Number of layers Cartographic 7 7 coverages Statistical attribute 2 2 coverages A 16 ArcUSA User s Guide and Data Reference April 1992 Appendix A Data quality information Characteristic ArcUSA coverage characteristics Attribute types Measurement interval or ordinal values Suppressed values 0 1 2 3 4 5 6 Missing values 0 Code numeric or alphabetic codes Null values numeric 9 99 999 9999 Not applicable values alphabetic blanks Name alphabetic or alphanumeric names Missing values blanks Naming conventions Coverages 10 alphanumeric characters only A Z 1 9 or allowed Tables 10 primary and 3 extension alphanumeric characters xxxxxxxx PAT or AAT with A Z 1 9 or _ allowed Attributes 10 alphanumeric characters Indexing Tabular all attributes sorted by value Spatial all coverages spatially subdivided into quadrangles by feature density Projection system Albers Conic Equal Area Standard parallels 259 30 N 45 30 N Origin 96 00 W 230 00 N Appendix A Data quality information A 18 Lineage The lineage of ArcUSA 1 25M data includes three main sources e Data derived primarily from 1 2 000 000 scale USGS DLG e Data derived from ESRI s ArcWorld 1 3M database e Data derived from tabular files published by the U S Bureau of the Census ArcUSA 1 25M
36. 295 states Lines 1 607 state boundaries Polygons 4 409 counties Lines 10 485 county boundaries Polygon attributes 57 population by race ethnicity and age Line attributes 4 boundary types Polygon attributes 60 Line attributes 4 Poly attributes 107 farm size number products raised by farm and area or number Line attributes 4 boundary types Poly attributes 110 Line attributes 4 Poly attributes 92 farms by value of products products by value and quantity sold Line attributes 4 boundary types Polygon attributes 95 Line attributes 4 Polygon attributes 48 population vital statistics migration Line attributes 4 Boundary types Polygon attributes 55 Line attributes 4 Source Coverage Size MB Currency Names dBASE UNIX USGS DLG POP90S 2 49 1 87 1973 U S Census Bureau 1990 USGS DLG POP90C 8 17 1988 U S Census Bureau 1990 USGS DLG AGIN_S 3 94 2 1973 U S Census of Agriculture 1987 USGS DLG AGIN_C 13 11 8 1988 U S Census of Agriculture 1987 USGS DLG AGVL_S 3 61 2 1973 U S Census of Agriculture 1987 USGS DLG AGVL_C 11 97 1988 U S Census of Agriculture 1987 USGS DLG POP88S 2 36 1973 U S Census County amp City Data Book 1988 91 USGS DLG POP88C 7 1988 U S Census County amp City Data Book 1988 5 69 64 33 49 7 81 1 82 5 67 1 6 ArcUSA User s Guide and Data Referen
37. 600 April 1992 2 11 Chapter 2 Exploring the ArcUSA database 12 13 14 2 12 Scroll farther down to the attribute sr_cr_100k This attribute represents the number of serious crimes per 100 000 people The occurrence of serious crime in Philadelphia was higher than in Montgomery County For comparison the average occurrence of serious crime per 100 000 people within the nine selected counties is 6 170 for this time period the national average is 2 706 These figures can be determined by using the Statistics tool for sr_cr_100k in the attribute table for Net Migration 1980 86 by county Continue scrolling down in the windows to the attribute inc_cap_85 This attribute represents income per capita 1985 Per capita income was higher in Mont gomery County than in Philadelphia and is another possible factor in the difference in migration between the two counties You may continue to explore differences in attributes between these two counties ArcUSA User s Guide and Data Reference Bivariate mapping using ArcUSA 1 2M attributes The views presented thus far in this tour have used data from the ArcUSA 1 25M coverages The ArcUSA 1 2M coverages include a much greater variety of statistical data as well as a much higher level of detail for cartographic features like roads or rivers In the following exercise a sample data set using the 1 2M attributes for the state of Georgia
38. Antrim 11 Arenac 13 Baraga 15 Barry 17 Bay 19 Benzie 21 Berrien 23 Branch 25 Calhoun 27 Cass 29 Charlevoix 31 Cheboygan 33 Chippewa 35 Clare 37 Clinton 39 Crawford 41 Delta 43 Dickinson 45 Eaton 47 Emmet 49 Genesee 51 Gladwin 53 Gogebic 55 Grand Traverse 57 Gratiot 59 Hillsdale 61 Houghton 63 Huron 65 Ingham 67 Ionia 69 Iosco 71 Iron 73 Isabella 75 Jackson 77 Kalamazoo 79 Kalkaska 81 Kent 83 Keweenaw 85 Lake 87 Lapeer 89 Leelanau 91 Lenawee 93 Livingston 95 Luce 97 Mackinac 99 Macomb 101 Manistee 103 Marquette 105 Mason 107 Mecosta 109 Menominee April 1992 C 7 Appendix C FIPS codes 111 Midland 113 Missaukee 115 Monroe 117 Montcalm 119 Montmorency 121 Muskegon 123 Newaygo 125 Oakland 127 Oceana 129 Ogemaw 131 Ontonagon 133 Osceola 135 Oscoda 137 Otsego 139 Ottawa 141 Presque Isle 143 Roscommon 145 Saginaw 147 St Clair 149 St Joseph 151 Sanilac 153 Schoolcraft 155 Shiawassee 157 Tuscola 159 Van Buren 161 Washtenaw 163 Wayne 165 Wexford Minnesota 1 Aitkin 3 Anoka 5 Becker 7 Beltrami 9 Benton 11 Big Stone 13 Blue Earth 15 Brown 17 Carlton 19 Carver 21 Cass 23 Chippewa 25 Chisago Dik Clay 29 Clearwater 31 Cook 33 Cottonwood 35 Crow Wing 37 Dakota 39 Dodge 41 Douglas 43 Faribault 45 Fillmore 47 Freeborn 49 Goodhue 51 Grant 53 Hennepin
39. ArcUSA data were closely reviewed to ensure completeness of shorelines and of state and county boundaries River and road layer completeness are less well defined since some cartographic judgment has been used to create a visually pleasing product Statistical data are incomplete in the sense that selected records in the database may be not have data for some attributes April 1992 A 21 Appendix B ArcUSA item definitions The tables in this appendix present the definition of each item in the ArcUSA database The sample feature attribute tables immediately below illustrate the way in which the item definitions are presented The columns in all tables are the same but the ARC INFO generated items for point and polygon features differ somewhat from the ARC INFO generated items for line features The notes below the sample tables provide information about these and other table characteristics Item definitions are presented for each set of ArcUSA coverages The coverages appear in the same order as in Chapters 4 and 5 first the 1 2M cartographic index and statistical attribute layers and then the 1 25M layers In order to reduce repetition the ARC INFO generated items are omitted from the feature attribute tables in this appendix Polygon or point feature tables Coverage Names FTP2M FTP2M_N FTP2M_S FTP2M_W Layer Type 2 Polygon or Point Polygon or Point Attribute Table dBASE Columns INFO ltems Begin Column Begin Item Ite
40. ArcUSA state and county statistical attribute layers Environmental Attributes Nonfederal land in rural land use in hectares and percentage of nonfederal land in rural land use in 1977 Percentage is computed by dividing NFD_R_LD by CNTY_AREA Total county land area federal and nonfederal in rural land use in hectares and percentage of county land area considered rural in 1977 Percentage is computed by dividing RUR_LND by CNTY_AREA Total county land area federal and nonfederal in urban land use in hectares and percentage of county land area considered urban in 1977 Percentage is computed by dividing URB_LND by CNTY_AREA Water area of the county in hectares and percentage of the county area covered by water in 1977 Percentage is computed by dividing WATER by CNTY_AREA Land capability These attributes contain the nonfederal land area in hectares and percentage of the county area in soils with certain characteristics Percentages are calculated by dividing the soil area by CNTY_AREA Soils with few limitations restricting land use Soils with some limitations restricting land use These soils are generally capable of producing cultivated crops Limitations may include dryness high erosion potential shallowness salinity low fertility or excess water Soils with severe limitations restricting land use These soils are generally capable of producing cultivated crops Limitations may include dryness high
41. ArcWorld land ocean and coastline features that occur adjacent to the coterminous United States Index coverages Latitude longitude grids and index grids that correspond to the 1 24 000 1 100 000 and 1 250 000 USGS Topographic Quadrangle Series were mathematically generated using the ARC INFO GENERATE command with the GRID option In this manner the theoretical location of the quadrangles was computed Occasionally USGS actual quadrangles depart from a completely ArcUSA User s Guide and Data Reference April 1992 Appendix A Data quality information rectangular format mainly because of map sheet production considerations Especially near shorelines this results in offset over edge and insert sheet layouts These are not represented precisely by the ArcUSA grid but the correct attribute information is included The USGS Topographic Names database was used as the source for quadrangle names and the geographic coordinates that were used to calculate the identification number for each map The ArcUSA map edition numbers publication dates and state FIPS codes were derived from the USGS Published Map Sheet File Indexes are current to 1986 The generated indexes were spot checked visually to verify the validity of the generated quadrangle coordinates The Landsat Nominal Scene Index was generated mathematically by using the nominal scene center points and an algorithm provided by EOSAT The nominal scene index generated by the algo
42. Index 1 vii Getting started with ArcUSA Welcome The ArcUSA database contains the data needed to generate thematic maps of the coterminous United States at the state and county levels It contains cartographic tabular and index information and is designed for a wide range of business educational and scientific GIS applications The ArcUSA database is formatted for UNIX and MS DOS systems Use ArcUSA data to e Create county and state level thematic maps e Generate simple outline maps for use as insets or locators e Identify demographic and socioeconomic patterns by county and state e Display a road map of your state e Create basemaps for use with raster data e Serve as a cartographic base for your own tabular data e Find out which USGS topographic maps cover your study area e Observe how selected geographic features and patterns are related e Experiment with a variety of mapping techniques What is in your ArcUSA package e CD ROM or other distribution medium that contains the ArcUSA database and some preconstructed ArcView views e ArcUSA 1 2M User s Guide and Data Reference e ArcUSA 1 2M Installation Instructions e ArcUSA license agreement April 1992 ix Getting started with ArcUSA To get started you ll need For UNIX systems For MS DOS systems e ArcView or e ArcView for Windows or ARC INFO 6 0 or higher PC ARC INFO 3 4D or higher or e CD player for CD ROM or drive ArcCAD version 11 or higher
43. Lines River shorelines River centerlines Perennial rivers Intermittent rivers Centerlines of perennial rivers through water bodies Centerlines of intermittent rivers through water bodies Braided rivers Navigable canals Other canals Ditches All line features April 1992 attributes Geographic reference attributes Number of attributes Represented by 2 361 lines Represented by 3 253 lines Represented by 23 456 lines Represented by 3 541 lines Represented by 3 893 lines Represented by 46 lines Represented by 1 325 lines Represented by 304 lines Represented by 350 lines Represented by 205 lines Represented by 38 734 lines The Rivers and Streams layer and the Lakes and Water Bodies layer are fully consistent with one another A river centerline through a water body has an associated water body polygon and the endpoints of the river centerline terminate at the boundary of the water body polygon 4 27 Chapter 4 ArcUSA 1 2M cartographic layers Rivers and Streams TYPE RIVER_TYPE STATE_FIPS STATE_NAME SUB_REGION 4 28 At the original scale of 1 2 000 000 some rivers are wide enough to be represented by two shorelines Such shorelines are coded 1 In addition an artificial centerline was digitized between the two shorelines code 2 This centerline may be used to represent the river at smaller scales Line attributes Classification attributes The class number of the river or
44. MSA McAllen Edinburg Mission TX MSA Medford OR MSA Melbourne Titusville Palm Bay FL MSA Memphis TN AR MS MSA Merced CA MSA Miami Fort Lauderdale FL CMSA Miami Hialeah FL PMSA Middlesex Somerset Hunterdon NJ PMSA Middletown CT PMSA Midland TX MSA Milwaukee WI PMSA Milwaukee Racine WI CMSA Minneapolis St Paul MN WI MSA Mobile AL MSA Modesto CA MSA Monmouth Ocean NJ PMSA Monroe LA MSA Montgomery AL MSA Muncie IN MSA Muskegon MI MSA Naples FL MSA Nashua NH PMSA Nashville TN MSA Nassau Suffolk NY PMSA New Bedford MA MSA New Bedford Fall River Atteboro MA NECMA New Britain CT PMSA New Haven Meriden CT MSA New Haven Waterbury Meriden CT NECMA New London Norwich CT RI MSA New London Norwich CT NECMA New Orleans LA MSA New York NY PMSA New York Northern New Jersey Long Island NY NJ CT CMSA Newark NJ PMSA Niagara Falls NY PMSA Norfolk Virginia Beach Newport News VA MSA Norwalk CT PMSA Oakland CA PMSA Ocala FL MSA Odessa TX MSA Oklahoma City OK MSA Olympia WA MSA Omaha NE IA MSA Orange County NY PMSA Orlando FL MSA Owensboro KY MSA Oxnard Ventura CA PMSA C 18 ArcUSA User s Guide and Data Reference Appendix C FIPS codes 6015 6020 6025 6060 6080 6120 6160 6162 6200 6240 6280 6282 6320 6323 6400 6403 6440 6442 6450 6453
45. Russell St Clair Shelby Sumter Talladega Tallapoosa Tuscaloosa Walker Washington Wilcox Winston 31 Nebraska 32 Nevada 33 New Hampshire 34 New Jersey 35 New Mexico 36 New York 37 North Carolina 38 North Dakota 39 Ohio 40 Oklahoma 41 Oregon 42 Pennsylvania 44 Rhode Island Arizona 1 Apache 3 Cochise 5 Coconino 7 Gila 9 Graham 11 Greenlee 12 La Paz 13 Maricopa 15 Mohave 17 Navajo 19 Pima 21 Pinal 23 Santa Cruz 25 Yavapai 27 Yuma Arkansas 1 Arkansas 3 Ashley gt Baxter 7 Benton 9 Boone 11 Bradley 13 Calhoun 15 Carroll 17 Chicot 19 Clark 21 Clay 23 Cleburne 25 Cleveland 27 Columbia 29 Conway 31 Craighead South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming Crawford Crittenden Cross Dallas Desha Drew Faulkner Franklin Fulton Garland Grant Greene Hempstead Hot Spring Howard Independence Izard Jackson Jefferson Johnson Lafayette Lawrence Lee Lincoln Little River Logan Lonoke Madison Marion Miller Mississippi Monroe Montgomery Nevada ArcUSA User s Guide and Data Reference Appendix C FIPS codes 101 Newton 103 Ouachita 105 Perry 107 Phillips 109 Pike 111 Poinsett 113 Polk 115 Pope 117 Prairie 119 Pulaski 121 Randolph 123 St Francis 125 Saline 127 Scott 129 Searcy 131 Sebastian 133 Sevier 135 Sharp 137 Stone 139 Union 141 Van Buren
46. SIC Dairy SICDAIRY 1508 17 N 6 Farms in SIC Poultry SICPOULTRY 1525 17 N 6 Farms SIC Animal Specialties SICANIMLSP 1542 17 N 6 Farms SIC General Livestock SICGENLVST 1559 17 N 6 OO OO O0 O0 O0 O0 O0 CO April 1992 B 29 Appendix B ArcUSA 1 2M state and county statistical attribute layers Agricultural Product Market Value continued Polygon Attribute Table County Level Coverage dBASE Columns Begin Column INFO Items Begin Item Item Description State FIPS Code County FIPS Code Combined FIPS Code State Name County Name U S Subregion Code Statistical Flag Farms with Agricultural Sales Total Agricultural Sales 1 000 Average Sales per Farm Farms with lt 1 000 in Products Product Value Farms w lt 1K Farms Selling 1 000 2 500 Value by Farms w 2 500 Farms Selling 2 500 5 000 Sales by Farms w 2 500 5K Farms Selling 5 000 10 000 Sales by Farms w 10K Farms Selling 10 000 20 000 Sales by Farms w 10K 20K Farms Selling 20 000 25 000 Sales by Farms w 20K 25K Farms Selling 25 000 40 000 Sales by Farms w 25K 40K Farms Selling 40 000 50 000 Sales by Farms w 40K 50K Farms Selling 50K 100K Sales by Farms w 50K 100K Farms Selling 100K 250K Sales by Farms w 100K 250K Farms Selling 250K 500K Sales by Farms w 250K 500K Farms Selling 500 000 Sales by Farms w 500K No of Farms Selling Crops Total Value of Crops 1K B 30 lte
47. ST_NAME1 ST_FIPS2 ST_NAME2 ST_FIPS3 ST_NAME3 ST_FIPS4 ST_NAME4 ST_FIPS5 ST_NAME5 ST_FIPS6 ST_NAME6 Landsat Nominal Scene Footprints Coverage Name Layer Type Arc Attribute Table Item Description Path Number Row Number Scene Center State FIPS Code One State Name One SAT_BND Line ltem Name PATH ROW SCN_CENTER ST_FIPS1 ST_NAME1 dBASE Columns Begin Column Column Definition Begin Column INFO Items Item Definition 80 4 C 0 84 4 C 0 88 21 C 0 109 3 N 0 112 20 C 0 4 4 C continued April 1992 Appendix B ArcUSA 1 2M index layers Landsat Nominal Scene Footprints continued Arc Attribute Table continued dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition State FIPS Code Two ST_FIPS2 132 3 N 0 81 3 3 1 State Name Two ST_NAME2 135 20 C 0 84 20 20 C State FIPS Code Three ST_FIPS3 155 3 N 0 104 3 3 1 State Name Three ST_NAME3 158 20 C 0 107 20 20 C State FIPS Code Four ST_FIPS4 178 127 3 3 1 State Name Four ST_NAME4 181 130 20 20 C State FIPS Code Five ST_FIPS5 150 State Name Five ST_NAMES5 153 State FIPS Code Six ST_FIPS6 150 State Name Six ST_NAME6 153 Latitude Longitude Grids Coverage Names LTLG2 LTLG5 LTLG10 Layer Type Line Arc Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Defi
48. State FIPS Code Adjacent States Boundary Type Code Note The state level and county level AATs are identical Agricultural Product Inventory AGIN_S AGIN_C Polygon and Line Coverage Names Layer Type Polygon Attribute Table State Level Coverage dBASE Columns Begin Column Column Definition INFO Items Begin Item Item Description Item Name Column Definition State FIPS Code State Name U S Subregion Code Statistical Flag Number of Farms Acres of Farmland Average Farm Size in Acres Value of Land etc per Farm Value of Land etc per Acre Value of Machinery per Farm Farms 1 to 9 Acres in Size Farms 10 to 49 Acres in Size Farms 50 to 179 Acres in Size STATE_FIPS STATE_NAME SUB_REGION STAT_FLAG NO_FARMS FARM_ACRES AVG_SIZE LAND_BLD_F LAND_BLD_A MACHINE_F F_1_9ACRE F_10_49 F_50_179 Farms 180 to 499 Acres in Size F_180_499 Farms 500 to 999 Acres in Size F_500_999 Farms Over 999 Acres in Size B 20 F_OVER_999 49 52 72 79 80 97 114 131 148 165 182 199 216 233 250 267 3 N 0 20 C 0 7 C 0 1 N 0 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 ArcUSA User s Guide and Data Reference 3 3 20 20 C continued Appendix B ArcUSA 1 2M state and county statistical attribute layers Agricultural Product Inventory continued Polygon Attribute Table State Level Coverage continued I
49. Surveying and Mapping April 1992 D 3 Appendix D Bibliography Peuquet D and D Marble 1990 Introductory Readings in Geographic Information Systems New York Taylor amp Francis Raper J ed 1989 Three Dimensional Applications in Geographical Information Systems New York Taylor amp Francis Ripple W J ed 1989 Fundamentals of Geographic Information Systems A Compendium Bethesda Md American Congress on Surveying and Mapping Collection of papers Ripple W ed 1987 GIS for Resource Management A Compendium Bethesda Md American Congress on Surveying and Mapping Star J L and J E Estes 1990 Geographic Information Systems An Introduction Englewood Cliffs N J Prentice Hall Tomlin D 1990 Geographic Information Systems and Cartographic Modelling Englewood Cliffs N J Prentice Hall D 4 ArcUSA User s Guide and Data Reference Appendix E Other data sources The Landsat satellite imagery indexed in the ArcUSA 1 2M database can be obtained from the Earth Observation Satellite Company EOSAT Lanham Maryland Digital data in ARC INFO compatible format for specified areas can be obtained by calling 800 344 9933 The U S Geological Survey topographic maps indexed in the ArcUSA 1 2M database can be purchased by writing to USGS Map Sales Box 25286 Denver CO 80225 telephone 303 236 7477 The ArcData Catalog distributed by ESRI is a handy reference to high quality database
50. This layer contains the same number of counties and county equivalent areas as the ArcUSA 1 2M layer more than 3 100 entities The layer contains new counties for Arizona and New Mexico as well as several independent cities primarily in Virginia that were added by ESRI to the DLG source data These additions brought the currency of the layer from 1973 to 1988 In the line theme boundaries are classified as to whether they are county state or international boundaries or shorelines Attributes that may be used to select certain geographic areas for display are contained in both the line and polygon themes Using the County Boundaries coverage The more generalized cartography and fewer offshore islands in this layer make it especially useful for fast display of small scale thematic maps with the ArcUSA 1 2M statistical attribute data Some counties such as those that include offshore islands are represented by multiple polygons A flag attribute is provided so that the largest polygon can be used to represent the county for choroplethic mapping or text labeling The county name attribute can be used to provide the text for labeling the polygons in a base map ArcUSA User s Guide and Data Reference Chapter 5 The ArcUSA 1 25M layers County Boundaries Summary of the County Boundaries coverage Coverage name dBASE UNIX and size MB CTY_25M 3 20 2 73 Source and currency DLG 1988 Thematic attribute Geographic refere
51. a Sas OD D 37076E1 Lathude 37 Longitude 76 Index number E 1 Se Oo c FP mnn g are Ly wee 7 65 43 2 1yo 4 52 ArcUSA User s Guide and Data Reference April 1992 QUAD_NAME MAP_EDIT ST_FIPS1 ST_FIPS2 ST_FIPS3 ST_FIPS4 ST_NAME1 ST_NAME2 ST_NAME3 ST_NAME4 DATE_PUB Chapter 4 ArcUSA 1 2M index layers USGS 1 100 000 Topographic Quadrangle Series The quadrangle name The names of theoretical quadrangles indicate the quadrangle s relationship to the published map on which the land area appears Charleston OE W for example The word digital in a quadrangle name also indicates that the quadrangle is theoretical It is usually used for quadrangles that show islands that are distant from the map sheets on which they are inserted A single number or letter code for the type of map If several types of maps exist for the same quadrangle the lowest code value is listed The codes are as follows Codes Definitions Topographic contour Planimetric Surface management status BLM Surface minerals BLM Topography bathymetry line map Hou ub ue ul Quadrangle coverage attributes These attributes contain the FIPS codes for the states the quadrangle covers up to four The FIPS codes are always stored beginning with ST_FIPS1 but the states are not listed in any particular order For a complete listing of state FIPS codes see Appendix C If a quadrangle covers fewer than four states
52. and line features and thus require two feature attribute tables 3 A brief descriptive variable item name The attribute descriptions in Chapters 4 and 5 provide complete definitions for the attributes and the attribute codes 4 Inall feature attribute tables the first few items are generated automatically by the ARC INFO software In a Polygon Attribute Table PAT four items are software generated The four items and their definitions are shown in the PAT example above In a Point Attribute Table PAT the ARC INFO generated items are the same as in a polygon attribute table and the area and perimeters are set to zero Although some documentation refers to the point attribute table as XAT to differentiate it from the polygon attribute table INFO software does not distinguish between point and polygon attribute B 2 ArcUSA User s Guide and Data Reference Appendix B ArcUSA item definitions tables and so polygons and points cannot be combined in one coverage nor can point and polygon coverages have the same name In an Arc Attribute Table AAT seven items are assigned automatically The seven items and their definitions are shown in the sample AAT above 5 The defined variable item name INFO or dBASE uses this name to read the item In INFO the item name may be up to sixteen characters long may not include spaces must begin with a letter and is case sensitive Because dBASE has slightly different requirements for
53. and Lines April 1992 Chapter 4 ArcUSA 1 2M index layers Landsat Nominal Scene Index Layer description The Landsat Nominal Scene Index layer contains an index to the coverage area for more than 700 nominal satellite scenes The scene outlines apply to both Thematic Mapper panchromatic and Multispectral Scanner color data acquired by Landsats 4 and 5 The index is composed of two coverages one containing the scene center points and the other containing scene footprints The attributes in both coverages are the same they include numbers row numbers latitude longitude coordinates and states covered A scene footprint is a rectangular outline that represents the geographic extent of the Earth s surface for which data are collected during a particular Landsat orbit Each footprint is identified by an orbital path number and scene row number and each footprint has a corresponding center point Using the Landsat Nominal Scene Index coverages This index is termed nominal because minor fluctuations in the satellite s orbit from one pass to the next can cause the actual scene center points and coverages to vary slightly The index itself was generated through an algorithm supplied by EOSAT and indicates an average orbital pass Landsat 4 or 5 digital data and imagery are available from EOSAT at the address listed in Appendix E 4 39 Chapter 4 ArcUSA 1 2M index layers Landsat Nominal Scene Index Summary of
54. and percentage of population in the state or county identified as being black not of Hispanic origin and 18 years of age or older Percentage is computed by dividing NHBLACK18 by TOTAL18 4 67 Chapter 4 ArcUSA state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data NHAMIN1g Number of people and percentage of population in the state P_NHAMIN18 or county identified as being American Indian not of Hispanic origin and 18 years of age or older Percentage is computed by dividing NHAMIN18 by TOTALI8 NHASIA18 Number of people and percentage of population in the state P_NHASIA18 or county identified as Asian not of Hispanic origin and 18 years of age or older Percentage is computed by dividing NHASIA18 by TOTALI18 NHOTHE18 Number of people and percentage of population in the state P_NHOTHE18 or county identified as being of a race other than white black American Indian or Asian as not being of Hispanic origin and as being 18 years of age or older Percentage is computed by dividing NHOTHE18 by TOTAL18 Housing units HSE UNITS Total number of housing units in the state or county in 1990 Line attributes Thorough definitions of these attributes are given on page 4 7 Geographic reference attributes L ST FIPS The FIPS code of the states on either the left or right side of R_ST_FIPS a boundary segment are contained in these attributes ST NAMES __ The states on either side of a boundary a
55. appear Use the scroll bar at the right of the comments box to move to the top of the text block 2 20 ArcUSA User s Guide and Data Reference April 1992 Chapter 2 Exploring the ArcUSA database Ideas for other ways to use ArcUSA The exercises in this guided tour provide only an introduction to the content and the capabilities of the ArcUSA database The following table lists just a few of the many other issues you might want to explore by using the data Next to each issue are some of the attributes in the ArcUSA 1 2M coverages that might be of interest Table 1 Other views Layer Planning new schools Pop Under 5 Yrs 1984 Demographic and Health Attributes Planning care facilities for Pop 65 to 74 Yrs 1984 Demographic and elderly Pop Over 74 Yrs 1984 Health Attributes Areas gaining political clout Pop 18 Yrs or Older 1990 1990 Census Public Law 94 171 Areas most concerned Farms with Beef Cows 1987 Agricultural Product about animal growth Inventory hormone regulations Areas where water Irrigated Land in Acres 1987 Agricultural Product shortages may affect Farms with Irrigated Land 1987 Inventory agriculture Areas potentially most Acres of Rice 1987 Agricultural Product affected by greater access Rice Harvested 100 lbs Inventory to Japanese rice market Areas potentially most Farms with Tobacco 1987 Agricultural Product affected by changes in Acres of Tobacco Harvested Inventory fe
56. appropriate for the distribution e CD player for CD ROM or drive media you received appropriate for the distribution e Disk space appropriate to your media you received version of ArcUSA see table e Disk space appropriate to your below if you wish to copy the version of ArcUSA see table entire database onto your hard drive below if you wish to copy the entire database onto your hard drive Table 1 Disk space requirements for the ArcUSA database Size MB ArcUSA 1 2M Full Extent 215 270 ArcUSA 1 25M 13 14 Sample data views 3 2 The database sizes shown in Table 1 apply to only one projection or coordinate system the second set of data for ArcUSA 1 2M requires approximately the same amount of disk space The ArcUSA 1 2M Installation Instructions give instructions about copying individual coverages to another storage space x ArcUSA User s Guide and Data Reference Getting started with ArcUSA How to access the database Depending upon the amount of disk space you have available and the applications you plan for your ArcUSA data you may read data directly from the CD ROM or decide to copy all or some of the data to your hard drive Copying the data onto your hard drive will significantly improve performance but requires extra storage space Data copying and storage options for your particular hardware platforms are discussed in the ArcUSA 1 2M Installation Instructions How to use this guide If you re new to geogra
57. blue for water and beige for land A U S coastline display using the State Boundaries or County Boundaries coverages can be continued into Canada and Mexico with the line features in this layer The processing grid can be omitted from the display if you select only the feature lines The annotation features associated with this layer include the names of major countries and water bodies The annotation for this layer looks best for displays that show the full extent of the database so the names are entirely visible The annotation is suited for a detailed display of the Great Lakes region however because the annotation text for those features is relatively small 4 14 ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA 1 2M cartographic layers Land Ocean Display Summary of the Land Ocean Display coverage Coverage name dBASE UNIX and size MB LAND2M 1 53 1 47 Source and currency ESRI ArcWorld 1992 Thematic attribute groups Classification attributes polygons and lines Annotation text Mexico Canada Atlantic Ocean Lake Superior Lake Michigan Gulf of Mexico Gulf of California etc Feature Number of cass Feature Number of features attributes Polygons Land Represented by 1 431 polygons Water Represented by 40 polygons Lines Artificial grid lines Represented by 103 lines 1 Feature boundaries Represented by 1 757 lines Polygon attributes Classification attribute LND WAT E
58. children under one year of age they exclude fetal deaths Number of deaths per 1 000 persons in the state or county in 1984 Number of infant deaths per 1 000 live births in the state or county in 1984 4 97 Chapter 4 ArcUSA state and county statistical attribute layers Demographic and Health Attributes MARRIAGES MARRIAG_1K DIVORCES DIVORCG_1K DOCTORS DOCT_100K HOSPITALS HOSP_BEDS HBEDS_1000 NURSEHOMES 4 98 Number of marriages and number of marriages per 1 000 people in the state or county in 1984 Number of divorces and number of divorces per 1 000 people in the state or county in 1984 Health attributes Number of physicians and number of physicians per 100 000 people in the state or county in 1985 The figures include active nonfederal physicians and are based on information maintained by the American Medical Association AMA about members and nonmembers of the AMA and graduates of foreign medical schools who are in the United States and meet U S educational standards for physicians Number of hospitals in the state or county in 1985 A hospital is defined as a facility with at least six beds that is licensed by the state as a hospital or that is operated as a hospital by a federal or state agency and is therefore not subject to state and local licensing laws The data cover hospitals of all types Number of hospital beds and number of hospital beds per 1 000 people in the sta
59. common in the cartographic and index layers Numeric codes generally begin with 1 and rise sequentially The code order may be random in which case the codes have no inherent numeric meaning However the order may also reflect frequency or relative significance For example in the Railroads coverage main lines are numbered 1 and 2 and branch lines are numbered 3 and 4 Features that are inadvertently created and are not the focus of the classification scheme such as background polygons are usually represented by extreme value codes such as 9 or 99 Alphabetic codes are used sometimes instead of numeric codes For example in the USGS 1 24 000 Topographic Quadrangle coverages the MAP_EDIT attribute has the codes G for Surface management status and H for Surface minerals 3 10 ArcUSA User s Guide and Data Reference Chapter 3 Database concepts and organization Two special types of code attributes prioritized and flag attributes require discussion Prioritized attributes share a common set of codes They are useful in situations in which two or more of the codes apply to the same feature In the Federal Lands coverage for example the set of prioritized attributes TYPE1 TYPE2 and TYPE 3 utilize nine codes representing the administrative status of the feature The codes are ordered by restrictions on use If a feature is both a national park and a military reservation the TYPE attribute is assigned to t
60. counties the FIPS code for the Primary Metropolitan Statistical Area PMSA 1 L_ST_FIPS The FIPS codes for the states on the left and right sides of a R_ST_FIPS boundary ST_NAMES The names for the states or state on either side of a boundary Notes 1 A complete listing of state county and metropolitan area FIPS codes can be found in Appendix C 2 U S subregions are shown on the map in Chapter 1 Naming conventions To ensure consistency naming conventions were adopted for ArcUSA coverages and attributes The names are intended to reflect the topic of the two database components features and map scale while complying with DOS restrictions on file name length Tables 3 and 4 present the conventions used for coverage and attribute names Attributes common to several different layers such as state name were assigned the same attribute name in all layers STATE_NAME Conversely unique attributes were given names that are always unique within a layer and generally unique across different layers One exception is attributes in the database that are generically named even though they refer to different features For example both the water body and railroad classification code attributes are April 1992 3 13 Chapter 3 Database concepts and organization Table 3 Coverage naming conventions Database scale RDS2M Cartographic coverages in 2M 1 2 000 000 RDS25M ArcUSA 1 2M and 1 25M 25M 1 25 000 000 Level of geo
61. county land area disturbed by surface mining activities coal sand gravel and other as of 1975 Land area in hectares and percentage of county land area disturbed by activities related to surface mining for coal as of 1975 ArcUSA User s Guide and Data Reference SAND_EXT P_SAND_EXT OTH_MINE P_OTH_MINE ALFISOL P_ALFISOL ARIDISOL P_ARIDISOL ENTISOL P_ENTISOL HISTOSOL P_HISTOSOL INCEPTSL P_INCEPTSL MOLLISOL P_MOLLISOL April 1992 Chapter 4 ArcUSA state and county statistical attribute layers Environmental Attributes Land area in hectares and percentage of county land area disturbed by activities related to extraction of sand and gravel as of 1975 Land area in hectares and percentage of county land area disturbed by activities related to surface mining for materials other than coal sand or gravel as of 1975 Soil order classification Land area in hectares and percentage of the county area in certain soil orders Percentages are calculated by dividing the soil area by CNTY_AREA Soil order alfisol Alfisols are fertile soils that develop in humid regions They are typically highly productive for agriculture Soil order aridisol Aridisols develop in desert environments They are poor in organic matter and have a high salt content Soil order entisol These soils are fertile and are found in many different climates Entisols are characterized by a lack of horizons layers
62. dollars per capita Direct payment of federal funds for individuals e g retirement and disability benefits summarized to the county or state level Figures are for 1986 in dollars per capita Federal procurement contract awards to organizations within a county summarized to the county or state level Figures are for 1986 in dollars per capita Federal funds for salaries and wages summarized to the county or state level Figures are for 1986 in dollars per capita Federal grants awarded to local governments or other organizations within a county summarized to the county or state level Figures are for 1986 in dollars per capita 4 111 Chapter 4 ArcUSA state and county statistical attribute layers Government and Financial Attributes LOC_GEN_RV INTER_GVT P_STATEREV LOC_TAXES TAX_CAP PROPTAX_CP GEN_EXP P_CHG_EXP GEN_EXP_CP P_EDUC P_HEALTH P_POLICE 4 112 Local government finance All quantities are for 1981 1982 Local government general revenue in millions of dollars summarized to the state and county levels Local government intergovernmental revenue in millions of dollars summarized to the state and county levels Percentage of local government intergovernmental revenue that came from the state summarized to the state and county levels Local government taxes within a state or county in millions of dollars and in dollars per capita Local govern
63. exception applies to some of the attributes derived from the U S Census of Agriculture which were given the same name in the Agricultural Product Inventory layers and the Agricultural Product Market Value layers even though they are not identical WHEATFARMS for example indicates the number of farms that grew wheat during the census year in the Inventory layers and the number of farms that sold wheat that year in the Market Value layers Data sources This section reviews the sources for ArcUSA data discusses their currency and briefly indicates modifications or enhancements that were made to the source data for the ArcUSA database Appendix A describes the development of the ArcUSA database in detail and the data sources and currency are summarized in Table 5 The name of the reference document for each source is also noted where relevant complete bibliographic references are listed in Appendix D These documents should be consulted by the user for comprehensive definitions of the attributes included in this database The primary source for the ArcUSA geographic data was the USGS Digital Line Graphs DLGs at a scale of 1 2 000 000 Other geographic data were generated or compiled by ESRI particularly the data for the index layers U S Bureau of the Census digital data from the 1990 Census of Population the 1988 County and City Data Book and the 1987 Census of Agriculture were the sources for most of the statistical attributes The
64. in Sq Mi LAND_AREA 11 N 0 123 4 7 B Total Population 1986 POP1986 11 N 0 127 4 9 B Population Rank 1986 POP_RANK 11 N 0 131 2 4 B continued B 34 ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 2M state and county statistical attribute layers Demographic and Health Attributes continued Polygon Attribute Table County Level Coverage continued dBASE Columns Begin Column Column Definition INFO Items Begin Item Item Description Item Name Column Definition Population per Square Mile Population 1980 Corrected Population Change 1980 1986 Pop Change 1980 1986 Births 1980 1986 Deaths 1980 1986 Net Migration 1980 1986 Percent White Population 1984 Black amp Other Races 1984 Males per 100 Females 1984 Persons under 5 Years 1984 Percent Persons 5 to 14 Years Percent Persons 15 to 24 Years Percent Persons 25 to 34 Years Percent Persons 35 to 44 Years Percent Persons 45 to 54 Years Percent Persons 55 to 64 Years Percent Persons 65 to 74 Years Percent Persons Over 74 Years Total Population 1984 Percent American Indian 1980 Percent Asian 1980 Percent Hispanic 1980 Population 1980 Births 1984 Births to Mothers lt 20 Years Births per 1 000 Pop 1984 Deaths 1984 Infant Deaths 1984 Deaths per 1 000 Pop 1984 Infant Deaths per 1 000 Births Marriages 1984 Marriages per 1 000 Pop 1984 Divorces 1984 Divorces per 1 000 Pop 1984 Active Phy
65. interstate route numbers may be assigned to a highway segment If a segment of highway has multiple interstate route numbers the lowest number is stored in INTER_RTE1 A code of 0 in either INTER _RTE2 or 3 means that the segment belongs to fewer than three interstate routes A code of 0 for all three attributes indicates that the road segment is not part of the interstate highway system U S highway route numbers As many as four U S route numbers may be assigned to a road segment If a road segment has multiple U S route numbers the numbers are ordered from lowest to highest with the lowest number stored in US_RTEI1 A code of 0 in US_RTE2 3 or 4 means that the segment belongs to fewer than three U S routes A code of 0 for all four attributes indicates that the road segment is not a U S route State route numbers As many as four state route numbers may be assigned to a road segment If a road segment has multiple state route numbers the numbers are ordered from lowest to highest with the lowest number stored in STATE_RTEI A code of 0 in STATE_RTE2 3 or 4 means that the segment belongs to fewer than three state routes A code of 0 for all four attributes indicates that the road segment is not a state route Geographic reference attributes Roads can be selected by the state name state FIPS code or U S subregion in which they are located 4 33 Chapter 4 ArcUSA 1 2M cartographic layers State Boundarie
66. is used to experiment with bivariate mapping techniques For more information about bivariate mapping see Chapter 6 1 Open the view titled bivar2m av Patterns representing positive and negative net migration at the county level are drawn in the graphic display April 1992 Chapter 2 Exploring the ArcUSA database Tip To increase drawing speed use the ArcUSA 1 25M coverages to draw state or county boundaries The state and county boundaries in the ArcUSA 1 2M database are much more detailed than those in ArcUSA 1 25M although both versions contain the same number of states and counties so they take longer to draw on the screen When you draw a basemap as opposed to a thematic map you may want the greater detail present in the 1 2M data for example you may want to use the 1 2M data for the Storm exercise that follows 2 13 Chapter 2 Exploring the ArcUSA database 2 Click on the check box to the left of the theme for Income per Capita 1985 This variable is symbolized with colo and draws beneath the shade pattern l that represents net migration Use a pattern and a color to display two variables Examine the relationship between net together Note that the variable symbolized using a migration and income per capita The pattern must be placed above the second variable in general pattern shows that counties the Table of Contents so that the patterns draw over
67. made to the coding scheme included the consolidation of existing attributes the development of new attributes and the introduction of attributes from one layer to another USGS DLG major and minor attribute codes derived from DLG data were reviewed for each cartographic layer In order to optimize the use of the ArcUSA database in an ARC INFO environment in most cases the codes were simplified restructured into a nonhierarchical scheme and given sequentially numbered attribute codes Measurement and suppressed value flag attributes in Census Bureau tabular data were consolidated into one attribute In the Census of Agriculture layers suppressed values are indicated by negative numbers indicating either that no measurement was available or that data were suppressed for various reasons In the County and City Data Book layers suppressed values are indicated by zeros New attributes introduced into the database include standardized attributes flag attributes prioritized attributes and name attributes The introduction of attributes from one layer into others was most common for the geographic reference attributes Attributes for state names state FIPS codes and U S subregions were introduced into all cartographic layers In addition state FIPS codes and name attributes were entered into the index layers These attributes were coded through overlay processing U S subregion codes and state name attributes were entered into the statistical
68. patterns in the Northeastern region of the United States draws to the screen 1 Double click on the theme Net Migration 1980 86 by county The property sheet will appear below the Table of Contents Notice that the attribute stat_flag has been preset to equal 1 in order to identify the largest land area polygon for each county Quit from the property sheet prior to continuing 2 Pick the Table option from the theme specific menu for Net Migration 1980 86 by county A table pops up presenting all attributes available in the 1 25M stat_c coverage for each county in the coterminous United States 3 Click on the Query Builder icon within the Net Migration 1980 86 by county table April 1992 Chapter 2 Exploring the ArcUSA database 2 9 Chapter 2 Exploring the ArcUSA database 4 Click on net_migr in the scrolling list of attributes 5 Select lt from the operators and enter 50000 on the line below the Values Attributes box The logical expression within the box will now read net_migr lt 50000 6 Click Select The following nine counties are identified as having lost more than 50 000 people from 1980 to 1986 e Milwaukee County Wis e Cook County Ill Chicago e Lake County Ind Greater Chicago e Wayne County Mich Detroit e Cuyahoga County Ohio Cleveland e Allegheny County Pa Pittsburgh e Erie County N Y Bu
69. products distributed in ARC INFO compatible format It includes database products marketed by ESRI and those offered by premier data publishers under the auspices of the ArcData program To obtain a copy of this valuable data guide contact the ESRI Regional Office nearest you or call the ESRI Marketing Department in Redlands California at 714 793 2853 April 1992 E 1 Index 1 2M data See ArcUSA 1 2M data layers 1 25M data See ArcUSA 1 25M data layers 1990 U S Census Public Law 94 171 Data layer 1 2M 4 61 to 4 69 data sources for 3 16 3 17 3 18 4 61 item definitions B 16 to B 20 types of population counts 4 61 Access database xi Agricultural Product Inventory layer 1 2M 4 70 to 4 79 data sources for 3 16 3 17 3 18 item definitions B 20 to B 27 meaning of negative numbers in 4 73 Agricultural Product Market Value layer 1 2M 4 80 to 4 88 data sources for 3 16 3 17 item definitions B 27 to B 32 meaning of negative numbers in 4 80 Albers Conic Equal Area projection 1 3 3 20 4 17 see also Projection systems Alphabetic codes 3 10 Annotation drawing order for 6 6 of cities 5 3 of counties 4 5 5 6 of countries 4 14 5 10 of polygons that cross political boundaries 4 19 of states 4 34 5 20 of water bodies 4 14 5 10 suppression of redundant See Flag attribute ARC INFO generated attributes 3 4 to 3 5 B 1 Arc attribute table explanation of columns in B 2 to B 3 use of 3 4 ArcUSA 1 2M data layers 4
70. quadrangles in which the features of interest lie Data quality review No independent evaluation of the attribute or positional accuracy of the source data was undertaken However a series of coverage based global diagnostic tests were run on each ArcUSA coverage to ensure data quality and integrity Code attributes were reviewed by checking for invalid codes in the database using the ARC INFO CODEFIND command Invalid code combinations were checked using the ARC INFO CONSIST command codes were deemed invalid if they were undefined in the ArcUSA data dictionary Zero measurement values in the agricultural attribute layers were checked to see whether they were true zero values or indicators of missing or suppressed data This was accomplished by checking the Census statistical attributes against their companion flag attributes The zero entries with no corresponding flag were retained and those with flags were replaced with the appropriate missing data identifier State and county name attributes were checked for spelling against the National Bureau of Standards Guideline Codes for Named Populated Places FIPS Publication 55 2 Discrepancies in spelling between Publication 55 and the U S Census digital tabular files were resolved by adopting the spelling from Publication 55 Visual tests involved the review of check plots The check plots were matched against the source map book for the 1 2 000 000 DLG data The National Atlas of
71. stream segment is stored in TYPE its English equivalent is stored in RIVER_TYPE The codes are as follows Codes Equivalents River shoreline River centerline Perennial river or stream Intermittent river or stream Centerline of perennial stream through a water body Centerline of intermittent stream through a water body Braided river or stream Navigable canal Other canal Ditch nN ABWNR O O ooN Hou ue il Geographic reference attributes Rivers can be selected by the state name state FIPS code or U S subregion in which that part of the river or stream is located ArcUSA User s Guide and Data Reference April 1992 Chapter 4 ArcUSA 1 2M cartographic layers Roads Layer description The Roads layer contains roads and highways Two classifications of road type are available Interstates U S highways and state highways toll roads and improved roads are examples of road types Route numbers are also included Using the Roads coverage This coverage contains attributes with the original twenty seven DLG road classes DLG_CLASS as well as a simplified ten class coding scheme ESRI_CLASS The simplified classification scheme is particularly useful for small scale displays or for regional displays where only a few road types are required The more detailed road classes can be useful for more detailed displays of local areas especially for trans
72. the defined item names the in the INFO software generated item names is replaced with an underscore _ in the dBASE tables The remaining item names in the ArcUSA database have been limited to ten alphanumeric characters so that names are identical in both formats 6 Inthe dBASE columns the Begin Column entry defines the column in which the variable begins A dBASE record may be up to 4 000 bytes or 128 items wide whichever comes first 7 A dBASE column definition has four elements a Item name see note 5 b Item width the number of bytes needed to store the variable c Item type may be N for numeric or C for character d Number of displayed decimal places for item type N 8 In the INFO Items columns the Begin Column entry defines the column in which the variable begins An INFO record may be 4 096 columns bytes wide This limit applies also to related records so the combined length of selected and related records cannot exceed 4 096 There are no related items in the ArcUSA 1 2M and ArcUSA 1 25M databases as they are delivered 9 An INFO item definition has five elements Item name see note 5 Item width the number of bytes needed to store the variable Output width the number of columns needed to display the item value Item type may be B for binary C for character F for floating decimal I for integer or N for numeric e Number of displayed decimal places for item types F N and on some pl
73. the user to select counties according to census geography The metropolitan area terms are explained on page 4 88 The codes are as follows e County within a CMSA PMSA e County within an MSA e County within an NECMA e County not in a metro area Metropolitan Statistical Area MSA or Consolidated MSA CMSA FIPS code This attribute is blank for counties that are not included in an MSA or CMSA and for MSA counties in New England Primary Metropolitan Statistical Area PMSA FIPS code In general a PMSA is a county that contains a city of over 100 000 population ArcUSA User s Guide and Data Reference LAND_AREA FEDFUNDGRT P_CHG_FNGR FNDGRT_CAP DIRPAY_CAP AWARDS_CAP FWAGES_CAP GRANTS_CAP April 1992 Chapter 4 ArcUSA state and county statistical attribute layers Government and Financial Attributes County land area This attribute appears only in the county level coverages The land area of the county in 1980 Land area excludes the areas of water bodies The value in this item is measured in square miles Federal funds and grants Federal funds and grants to local governments within a state or county for 1986 in millions of dollars Percent change in federal funds and grants to local governments within a state or county from 1985 to 1986 Federal funds and grants to local governments or other organizations within a county summarized to the county or state level Figures are for 1986 in
74. tour in Chapter 2 This hands on tutorial will help you learn the basic techniques for creating displays and querying the data e We have included several precomposed ArcUSA views ArcView users can immediately call these up to display and begin working with the data These displays are not accessible through ARC INFO or ArcCAD software however What is in this manual Each chapter in this manual addresses a particular aspect of the database or its use The order in which you read the chapters is up to you and you may wish to defer reading a chapter until the information it contains is relevant to what you are doing The chapters are as follows What is ArcUSA Presents the geographic extent of the database and an overview of its contents Exploring the ArcUSA database Provides an ArcView tutorial that introduces you to the basic database organization and illustrates fundamental techniques for selecting displaying querying and analyzing the data Explores cartographic index and statistical attribute data by leading you through sample applications ArcUSA User s Guide and Data Reference Chapter 3 Chapter 4 Chapter 5 Chapter 6 Appendixes AtoE Index April 1992 Getting started with ArcUSA Database concepts and organization Discusses such data elements as coverages and attributes and explains how they have been organized in the ArcUSA database Presents basic database concepts like projection and scale Lis
75. used to represent cities and satellite scene centers e Lines represent the shapes of geographic objects that are too narrow to depict as areas such as highways and streams e Areas are closed figures that represent the shapes and locations of homogeneous features such as states counties parcels and water bodies The characteristics or attributes of map features may also be conveyed by using labels or graphic symbols For example streams and water bodies are April 1992 3 1 Chapter 3 Database concepts and organization 3 2 drawn in blue to indicate water city streets are labeled with their names roads are drawn with various line widths patterns and colors to represent different road classes and so on In addition to displaying feature locations and attributes maps are typically characterized by the following e Scale the relationship between distance on the map and distance on the Earth e Projection the system used to transform the curved surface of the Earth to a plane e Coordinate system the method used to relate feature locations by distance and direction from other features Until recently maps were only available in paper or analog form The development of computerized geographic information systems has enabled analog map features relationships and characteristics to be translated into digital form for automated display query and analysis The ArcUSA database is just such a digital geographic dat
76. with Sugar Beets Acres of Sugar Beets Tons of Sugar Beets Harvested Farms with Sugar Cane Acres of Sugar Cane Tons of Sugar Cane Harvested Farms with Pineapples Acres of Pineapples Tons of Pineapples Harvested Farms with Peanuts for Nuts Acres of Peanuts Pounds of Peanuts Harvested Farms with Hay Acres of Hay Tons of Hay Harvested Farms with Vegetables Acres of Vegetables Farms with Orchards Acres of Orchards ltem Name dBASE Columns Begin Column Column Definition INFO Items Begin Column Item Definition SUGBEETFAR SUGBEETACR SUGBEETTON SUGCANEFAR SUGCANEACR SUGCANETON PINEAPLFAR PINEAPLACR PINEAPLTON PEANUTFARM PEANUTACRE PEANUT_LB HAYFARMS HAYACRES HAYTONS VEGFARMS VEGACRES ORCHRDFARM ORCHRDACRE 1508 1525 1542 1559 1576 1593 1610 1627 1644 1661 1678 1695 1712 1729 1746 1763 1780 1797 1814 Polygon Attribute Table County Level Coverage Item Description State FIPS Code County FIPS Code Combine FIPS Code State Name County Name U S Subregion Code Statistical Flag Number of Farms Acres of Farmland April 1992 ltem Name STATE_FIPS CNTY_FIPS FIPS STATE_NAME CNTY_NAME SUB_REGION STAT_FLAG NO_FARMS FARM_ACRES 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 dBASE Columns Begin Column 49 52 55 61 81 113 120 121 138 Column Definition 3 N 0 3 N 0 6 C 0 20 C 0 32 C 0 7 C 0 1 N 0 17 N 6 17 N 6
77. 0 Federal Funds and Grants 1986 FEDFUNDGRT 13 N 6 Change Funds Grants 85 86 P_CHG_FNGR 13 N 6 continued B 40 ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 2M state and county statistical attribute layers Government and Financial Attributes continued Polygon Attribute Table County Level Coverage continued dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Federal Funds amp Grants Capita FNDGRT_CAP 192 11 N 0 135 4 5 B Direct Payments of Fed Funds DIRPAY_CAP 203 11 N 0 139 4 5 B Procurement Awards per Capita AWARDS_CAP 214 11 N 0 143 4 5 B Fed Salaries Wages per Capita FWAGES_CAP 225 11 N 0 147 4 5 B Fed Grant Awards Capita 86 GRANTS_CAP 236 11 N 0 151 4 5 B Local Gen Revenue million LOC_GEN_RV 247 13 N 6 155 4 10 F Local Intergovernmental Rev INTER_GVT 260 13 N 6 159 4 10 F Local Gov t Revenue fr State P_STATEREV 273 13 N 6 163 4 6 F Local Taxes 1981 82 LOC_TAXES 286 13 N 6 167 4 10 F Local Taxes Capita 1981 82 TAX_CAP 11 N 0 171 2 4 B Property Taxes Capita 81 82 PROPTAX_CP 11 N 0 173 2 4 B Loc Gov t General Expenditures GEN_EXP 13 N 6 175 4 10 F Change Expend 1977 82 P_CHG_EXP 13 N 6 179 4 7 F General Expenditure per Capita GEN_EXP_CP 11 N 0 183 2 4 B Expenditure for Education P_EDUC 13 N 6 4 6 F Percent Expenditure for Health P_HEALTH 13 N 6 4 6 F Percent Expenditure for Police P_POLI
78. 04 0 06 Source and currency ESRI algorithm generated 1992 Thematic attribute groups Classification attributes Feature Number of Lines Latitude and longitude Represented by 134 lines lines 10 by 10 degree grid Line attributes Classification attributes LATITUDE The latitude of the grid line This attribute contains a blank for lines of longitude LONGITUDE The longitude of the grid line All longitude values in ArcUSA begin with a minus sign that indicates West longitude This attribute contains a blank for lines of latitude US NONUS Classification code for the line segment The codes are as follows Codes Definitions O Line segment lies outside the United States Over oceans and the Great Lakes the United States is defined by shorelines rather than by political boundaries 1 Line segment lies inside the United States 4 44 ArcUSA User s Guide and Data Reference USGS 1 24 000 Topographic Quadrangle Series Index Polygons April 1992 Chapter 4 ArcUSA 1 2M index layers USGS 1 24 000 Topographic Quadrangle Series Layer description The polygons in the USGS 1 24 000 Topographic Quadrangle Series Index layer contain the outlines of the U S Geological Survey 1 24 000 scale topographic maps 7 5 minute quadrangles Quadrangle name USGS map reference code publication data and map coverage by state are given
79. 1277 17 N 6 1294 17 N 6 1311 17 N 6 1328 17 N 6 1345 1362 1379 SICCOTTON SICTOBACCO SICOTHFLD SICVEG SICFRTNUT SICHORTSP SICGENCROP SICLVSTOCK SICBEEF SICDAIRY 1396 1413 1430 1447 1464 1481 1498 1515 1532 1549 SICPOULTRY SICANIMLSP SICGENLVST 1566 1583 1600 dBASE Columns Begin Column Item Name Column Definition 609 8 11 F 0 617 625 633 641 649 657 665 673 p p _ ee n HI t t t ti H Reo Hg g oooooocoo ph ph pb p ph pb ph pd pah fd p 90 00 90 00 00 00 O9 DO ODO gal INFO Items Begin Item Column Definition L_ST_FIPS 80 3 N 0 R_ST_FIPS 83 3 N 0 ST_NAMES 86 41 C 0 BNDY_TYPE 127 11 N 0 Note The state level and county level AATs are identical 29 3 3 32 76 B 32 ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 2M state and county statistical attribute layers Demographic and Health Attributes POP88S POP88C Polygon and Line Coverage Names Layer Type Polygon Attribute Table State Level Coverage dBASE Columns INFO Items Begin Column Begin Item Item Description State FIPS Code State Name U S Subregion Code Statistical Flag Total Population 1986 Population Rank 1986 Population per Square Mile Population 1980 Corrected Population Change 1980 1986 Pop Change 1980 1986 Births 1980 1986 Deaths 1980 1986 Net Migration 1980 1986 Percent White Populat
80. 143 Washington 145 White 147 Woodruff 149 Yell California 1 Alameda 3 Alpine 5 Amador 7 Butte 9 Calaveras 11 Colusa 13 Contra Costa 15 Del Norte 17 El Dorado 19 Fresno 21 Glenn 23 Humboldt 25 Imperial 27 Inyo 29 Kern 31 Kings 33 Lake 35 Lassen 37 Los Angeles 39 Madera 41 Marin 43 Mariposa 45 Mendocino 47 Merced 49 Modoc 51 Mono 53 Monterey 55 Napa 57 Nevada 59 Orange 61 Placer 63 Plumas 65 Riverside 67 Sacramento 69 San Benito 71 San Bernardino 73 San Diego 715 San Francisco 77 San Joaquin 79 San Luis Obispo 81 San Mateo 83 Santa Barbara 85 Santa Clara 87 Santa Cruz 89 Shasta 91 Sierra 93 Siskiyou 95 Solano 97 Sonoma 99 Stanislaus 101 Sutter 103 Tehama 105 Trinity 107 Tulare 109 Tuolumne 111 Ventura 113 Yolo 115 Yuba Colorado 1 Adams 3 Alamosa 5 Arapahoe F Archuleta 9 Baca 11 Bent 13 Boulder 15 Chaffee 17 Cheyenne 19 Clear Creek 21 Conejos 23 Costilla 25 Crowley 27 Custer 29 Delta 31 Denver 33 Dolores 35 Douglas 37 Eagle 39 Elbert 41 El Paso 43 Fremont 45 Garfield 47 Gilpin 49 Grand 51 Gunnison 53 Hinsdale 55 Huerfano 57 Jackson 59 Jefferson 61 Kiowa 63 Kit Carson 65 Lake 67 La Plata 69 Larimer 71 Las Animas 73 Lincoln 75 Logan 77 Mesa 79 Mineral 8 amp 1 Moffat 83 Montezuma 85 Montrose 87 Morgan 89 Otero 91 Ouray 93 Park 95 Phill
81. 27966208 000 21981236640 000 06842690240 000 99931396096 000 53300604928 000 Ja gt 1958429 875 F 2099593500 2052559 000 2019025 750 2027577 375 Note to user The database includes one record for every polygon included in a particular state or county Ifa state includes offshore islands the database includes a separate record for each individual island The geographic information for that state is repeated in each polygon record for each island To identify the largest land area polygon in each state use the Query Builder in the theme s property sheet or table to create a logical expression with the stat_flag attribute set equal to 1 This will ensure that values for each state are counted only once during tabular queries 2 4 ArcUSA User s Guide and Data Reference Chapter 2 Exploring the ArcUSA database 5 Click on the attribute net_migr in the scrolling list of attributes 6 Choose gt from the operators then enter the number 500000 on the line below the Values Attributes box The logical expression now reads net_migr gt 500000 7 Click Select Your map will now show California Texas and Florida highlighted within the graphic display and the table as states that gained more than 500 000 people because of net migration from 1980 to 1986 Use a logical expression to create a more focused selection set in this case to id
82. 3 N 0 29 Right State FIPS Code R_ST_FIPS 83 3 N 0 Adjacent States ST_NAMES 86 41 C 0 Boundary Type Code BNDY_TYPE 127 11 N 0 Statistical Attributes Coverage Names STATS_S STATS_C Layer Type Polygon and Line Polygon Attribute Table State Level Coverage dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition State FIPS Code STATE_FIPS 49 3 N 0 3 3 1 State Name STATE_NAME 52 20 L 0 20 20 C U S Subregion Code SUB_REGION 7 L 0 7 1 C Statistical Flag STAT_FLAG 1 N 0 1 1 1 Births 1984 BIRTHS_84 11 N 0 4 7 B Net Migration 1980 86 NET_MIGR 11 N 0 4 7 B Persons Under 5 Years 1984 P_UNDER_5 13 N 6 4 6 F 1 Persons 5 to 14 Years 1984 P_5_14 13 N 6 4 6 F 1 Persons 15 to 24 Years 84 P_15_24 13 N 6 4 6 F 1 Persons 25 to 34 Years 84 P_25_34 13 N 6 4 6 F 1 Persons 35 to 44 Years 84 P_35_44 13 N 6 4 6 F 1 Persons 45 to 54 Years 84 P_45_54 13 N 6 4 6 F 1 Persons 55 to 64 Years 84 P_55_64 13 N 6 4 6 F 1 Persons 65 to 74 Years 84 P_65_74 13 N 6 4 6 F 1 Persons 75 Yrs 1984 P_OVER_74 13 N 6 4 6 F 1 Total Population 1984 POP1984 11 N 0 4 9 B Persons per Household 1985 PERS_HHLD 13 N 6 4 7 F 2 Marriages 1984 MARRIAG_IK 13 N 6 4 7 F 1 continued B 50 ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 25M layers Statistical Attributes continued Polygon Attribute Table State Level Coverage continued dBASE Columns INF
83. 4 N 0 84 38 C 0 122 3 N 0 125 20 C 0 145 7 C 0 ArcUSA User s Guide and Data Reference 4 4 Appendix B ArcUSA 1 25M layers Roads Coverage Name RDS_25M Layer Type Line Arc Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Federal Interstate Route 1 INTER_RTE1 3 N 0 3 3 1 Federal Interstate Route 2 INTER_RTE2 3 N 0 3 3 1 Federal Interstate Route 3 INTER_RTE3 3 N 0 3 3 1 U S Route Number 1 US_RTE1 3 N 0 3 3 1 U S Route Number 2 US_RTE2 3 N 0 3 3 1 U S Route Number 3 US_RTE3 3 N 0 3 3 1 State Route Number One STATE_RTEI1 3 N 0 3 3 1 State Route Number Two STATE_RTE2 3 N 0 State FIPS Code STATE_FIPS 3 N 0 State Name STATE_NAME U S Subregion Code SUB_REGION State Boundaries Coverage Name ST_25M Layer Type Polygon and Line Polygon Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition State FIPS Code STATE_FIPS 3 N 0 3 3 State Name STATE_NAME 52 20 C 0 20 20 C U S Subregion Code SUB_REGION 72 7 C 0 7 7 C Statistical Flag STAT_FLAG 79 1 N 0 1 1 I April 1992 B 49 Appendix B ArcUSA 1 25M layers State Boundaries continued Arc Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Left State FIPS Code L_ST_FIPS
84. 52 254 318 Appendix B ArcUSA 1 2M cartographic layers State Boundaries Coverage Name ST2M Layer Type Polygon and Line Polygon Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition State FIPS Code STATE_FIPS 3 N 0 17 3 3 1 State Name STATE_NAME 20 C 0 20 20 C U S Subregion Code SUB_REGION 7 C 0 40 7 7 C Statistical Flag STAT_FLAG 1 N 0 47 1 1 1 Arc Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Left State FIPS Code L_ST_FIPS 3 N 0 29 3 3 1 Right State FIPS Code R_ST_FIPS 3 N 0 32 3 3 1 Adjacent States ST_NAMES 41 C 0 35 41 41 C Boundary Type Code BNDY_TYPE 11 N 0 76 4 5 B B 10 ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 2M index layers Landsat Nominal Scene Center Points SAT_PT Point Coverage Name Layer Type Point Attribute Table dBASE Columns Begin Column INFO Items Begin Item Column Definition 4 4 C 4 4 C 21 21 C Column Definition 4 C 0 4 C 0 Item Description Path Number Row Number Scene Center ltem Name PATH ROW SCN_CENTER State FIPS Code One State Name One State FIPS Code Two State Name Two State FIPS Code Three State Name Three State FIPS Code Four State Name Four State FIPS Code Five State Name Five State FIPS Code Six State Name Six ST_FIPS1
85. 55 Houston C 8 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 Hubbard Isanti Itasca Jackson Kanabec Kandiyohi Kittson Koochiching Lac Qui Parle Lake Lake of the Woods Le Sueur Lincoln Lyon McLeod Mahnomen Marshall Martin Meeker Mille Lacs Morrison Mower Murray Nicollet Nobles Norman Olmsted Otter Tail Pennington Pine Pipestone Polk Pope Ramsey Red Lake Redwood Renville Rice Rock Roseau St Louis Scott Sherburne Sibley Stearns Steele Stevens Swift Todd Traverse Wabasha Wadena Waseca Washington Watonwan Wilkin Winona 171 Wright 173 Yellow Medicine Mississippi 1 Adams 3 Alcorn 5 Amite 7 Attala 9 Benton 11 Bolivar 13 Calhoun 15 Carroll 17 Chickasaw 19 Choctaw 21 Claiborne 23 Clarke 25 Clay 27 Coahoma 29 Copiah 31 Covington 33 De Soto 35 Forrest 37 Franklin 39 George 41 Greene 43 Grenada 45 Hancock 47 Harrison 49 Hinds 51 Holmes 53 Humphreys 55 Issaquena 57 Itawamba 59 Jackson 61 Jasper 63 Jefferson 65 Jefferson Davis 67 Jones 69 Kemper 71 Lafayette 73 Lamar 75 Lauderdale 77 Lawrence 79 Leake 81 Lee 83 Leflore 85 Lincoln 87 Lowndes 89 Madison 91 Marion 93 Marshall 95 Monroe 97 Montgomery 99 Neshoba 101 Newton 103 Noxubee 105 Oktibbeha ArcUSA User s Guide and Data Reference 107 Panola 109 Pea
86. 6460 6480 6482 6483 6520 6560 6600 6640 6660 6680 6690 6720 6740 6760 6780 6800 6820 6840 6880 6920 6960 6980 7000 7040 7080 7090 7120 7160 7200 7240 7320 7360 Panama City FL MSA Parkersburg Marietta WV OH MSA Pascagoula MS MSA Pawtucket Woonsocket Attleboro RI MI PMSA Pensacola FL MSA Peoria IL MSA Philadelphia PA NJ PMSA Philadelphia Wilmington Trenton PA NJ DE MD CMSA Phoenix AZ MSA Pine Bluff AR MSA Pittsburgh PA PMSA Pittsburgh Beaver Valley PA CMSA Pittsfield MA MSA Pittsfield MA NECMA Portland ME MSA Portland ME NECMA Portland OR PMSA Portland Vancouver OR WA CMSA Portsmouth Dover Rochester NH ME MSA Portsmouth Dover Rochester NH NECMA Poughkeepsie NY MSA Providence RI RMSA Providence Pawtucket Fall River RI MA CMSA Providence Pawtucket Woonsocket RI NECMA Provo Orem UT MSA Pueblo CO MSA Racine WI PMSA Raleigh Durham NC MSA Rapid City SD MSA Reading PA MSA Redding CA MSA Reno NV MSA Richland Kennewick Pasco WA MSA Richmond Petersburg VA MSA Riverside San Bernardino CA PMSA Roanoke VA MSA Rochester MN MSA Rochester NY MSA Rockford IL MSA Sacramento CA MSA Saginaw Bay City Midland MI MSA St Cloud MN MSA St Joseph MO MSA St Louis MO IL MSA Salem OR MSA Salem Gloucester MA PMSA Salinas Seaside Monterey
87. 7 Chicago Rand McNally amp Company The Times Atlas of the World Eighth Comprehensive Edition 1990 New York Random House 1 2 000 000 Scale National Atlas Sectional Maps 1972 73 Reston Va U S Geological Survey Further reading All materials listed below are available from ESRI Book Sales 380 New York Street Redlands California 92373 Telephone 714 793 2853 Aronoff S ed 1989 Geographic Information Systems A Management Perspective Ottawa WDL Publications Burrough P A 1986 Principles of Geographical Information Systems for Land Resources Assessment New York Oxford University Press Butterfield B and R McMaster 1991 Map Generalization Making Rules for Knowledge Representation New York John Wiley amp Sons ESRI 1992 ArcView User s Guide Redlands Calif Environmental Systems Research Institute Inc D 2 ArcUSA User s Guide and Data Reference Appendix D Bibliography ESRI 1991 ARC INFO User s Guide Map Projections amp Coordinate Management 1991 Redlands Calif Environmental Systems Research Institute Inc ESRI 1991 ARC INFO 6 0 User s Guide ARC INFO Data Model Concepts amp Key Terms Redlands Calif Environmental Systems Research Institute Inc ESRI 1990 Understanding GIS The ARC INFO Method Redlands Calif Environmental Systems Research Institute Inc Goodchild M and S Gopal eds 1989 Accuracy of Spatial Databases New York Taylor amp Fr
88. 78 CLASS3 9 The codes are as follows Codes Equivalents 0 No class applies 1 Interstate highway 2 Major U S route limited access divided 3 Major state route limited access divided 4 Major other route limited access divided 5 Toll road 6 Interstate connector 7 Limited access divided connector 8 Toll connector 9 Interstate under construction 10 Interstate proposed 11 Minor U S route limited access 310 km 500 mi and longer 12 U S nonlimited access 310 km 500 mi and longer 13 Minor U S limited access less than 310 km 500 mi 14 USS nonlimited access less than 310 km 500 mi 15 Other minor U S limited access 16 Other U S route 17 Other minor state primary route limited access 18 Other state primary route 19 Minor U S parallel within 10 km 6 mi 20 USS parallel within 10 km 6 mi 21 Minor state parallel within 10 km 6 mi 22 State parallel within 10 km 6 mi 23 State secondary route all weather hard surface 24 Light duty all weather improved 25 Unimproved fair or dry weather 26 Road tunnel 27 Auto ferry 4 32 ArcUSA User s Guide and Data Reference INTER_RTE1 INTER_RTE2 INTER_RTE3 US_RTE1 US_RTE2 US_RTE3 US_RTE4 STATE_RTE1 STATE_RTE2 STATE_RTE3 STATE_RTE4 STATE_FIPS STATE_NAME SUB_REGION April 1992 Chapter 4 ArcUSA 1 2M cartographic layers Roads Interstate highway route numbers As many as three
89. 82 P_CHG_EXP 248 13 N 6 100 4 7 F 1 General Expenditure per Capita GEN_EXP_CP 261 11 N 0 104 2 4 B Expenditure for Education P_EDUC 272 13 N 6 106 4 6 F 1 Percent Expenditure for Health P_HEALTH 285 13 N 6 110 4 6 F 1 Percent Expenditure for Police P_POLICE 298 13 N 6 114 4 6 F 1 Expend for Public Welfare P_WELFARE 311 13 N 6 118 4 6 F 1 Expenditure for Highways P_HIGHWAY 324 122 4 6 F 1 Local Gov t Debt Outstanding DEBT 337 126 4 10 F 1 Local Gov t Debt per Capita DEBT_CAP 350 130 2 4 B Local Gov t Employment 1982 LOCGVT_EMP 361 132 4 7 B Local Gov t Empl 10K Pop LG_EMP_10K 372 136 4 8 F 1 Fed Civilian Employment 84 FEDCIV_EMP 385 140 4 7 B Fed Civ Emp Earnings 84 FEDCV_EARN 396 144 4 8 B Votes Cast for President 1984 PRESVOTE84 407 148 4 8 B Vote for Leading Party 1984 P_VTE_LEAD 418 152 4 6 F 1 Votes for Pres Leading Party LEAD_PARTY 431 156 1 1 1 Polygon Attribute Table County Level Coverage dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition State FIPS Code STATE_FIPS 3 N 0 3 3 1 County FIPS Code CNTY_FIPS 3 N 0 Combined FIPS Code FIPS 6 C 0 State Name STATE_NAME 20 C 0 County Name CNTY_NAME 32 C 0 U S Subregion Code SUB_REGION 7 C 0 Statistical Flag STAT_FLAG 1 N 0 County Type Code CNTY_TYPE 26 C 0 Metro Statistical Area Code MET_ST_AR 4 C 0 Consolidated MSA Code PR_MT_ST_A 4 C 0 County Land Area in Hectares LAND_AREA 11 N
90. 91 Arc Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Left State FIPS Code L_ST_FIPS 80 3 N 0 29 3 3 Right State FIPS Code R_ST_FIPS 83 3 N 0 3 3 Adjacent States ST_NAMES 86 41 C 0 41 41 C Boundary Type Code BNDY_TYPE 127 11 N 0 4 5 B Note The state level and county level AATs are identical B 36 ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 2M state and county statistical attribute layers Environmental Attributes Coverage Name ENVIR Layer Type Polygon and Line Polygon Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition State FIPS Code STATE_FIPS 49 3 N 0 3 3 1 County FIPS Code CNTY_FIPS 52 3 N 0 3 3 1 Combined FIPS Code FIPS 55 6 C 0 State Name STATE_NAME 61 20 C 0 County Name CNTY_NAME 81 32 C 0 U S Subregion Code SUB_REGION 113 7 C 0 Statistical Flag STAT_FLAG 120 1 N 0 Total Surface Area of County CNTY_AREA 121 11 N 0 Federal Land Area in County CNTY_FED 132 11 N 0 County Area in Federal Land P_CNTY_FED 143 13 N 6 County Land Area CNTY_LND 156 11 N 0 Rural Federal Land Area 1977 FED _R_LD 167 11 N 0 Percent Rural Federal Land Area P_FED_R_LD 178 13 N 6 Rural Non Federal Area 1977 NFD_R_LD 191 11 N 0 Rural Non Federal Land Area P_NFD_R_LD 202 13 N 6 Total Rural Land Area 1977 RUR_LND 215 11 N 0 Perc
91. 92 CITIES CTY_25M LAND25M SC_25M RIV_25M RDS_25M ST_25M STATS_S STATS_C 5 1 Cities Nashville Little Rock Points April 1992 Chapter 5 The ArcUSA 1 25M layers Cities Layer description The Cities layer contains point features representing populated places that are major U S cities state capitals and county seats Attributes include separate codes for the different kinds of cities so that they may be selected independently for display The city name elevation for some cities and geographic reference attributes are included as well Using the Cities coverage The 108 cities identified in this coverage are useful as general geographic identifiers for small scale maps The location of the points in this coverage was taken from latitude longitude coordinates listed in the digital version of the USGS s Concise Digital Database As is common for gazetteers the geographic coordinates were rounded so their positions may reflect some error 5 3 Chapter 5 The ArcUSA 1 25M layers Cities Summary of the Cities coverage Coverage name dBASE UNIX and size MB CITIES 0 03 0 04 Source and currency USGS Concise Digital Database approximately 1973 Thematic attribute Classification attributes groups Geographic reference attributes Feature Number of Points Represented by 108 points Point attributes Classification attributes NAME The name of the city is stored in this attribute
92. AD_NAME MAP_EDIT ST_FIPS1 ST_FIPS2 ST_FIPS3 ST_FIPS4 ST_NAME1 ST_NAME2 ST_NAME3 ST_NAME4 DATE_REV The quadrangle name The names of theoretical quadrangles indicate the quadrangle s relationship to the published map on which the land area appears Charleston OE W for example The word digital in a quadrangle name also indicates that the quadrangle is theoretical It is usually used for quadrangles that show islands that are distant from the map sheets on which they are inserted A single letter code for the type of map If several types of maps exist for the same quadrangle the lowest code value is listed The codes are as follows Codes Definitions Topographic contour Planimetric Orthophoto map with contours Shaded relief Other Satellite imagery Topography bathymetry line map Kaona me Hou ou ub th esl Quadrangle coverage attributes These attributes contain the FIPS codes for the states the quadrangle covers up to four The FIPS codes are always stored beginning with ST_FIPS1 but the states are not listed in any particular order For a complete listing of state FIPS codes see Appendix C If a quadrangle covers fewer than four states one or more attributes are blank The names of the states the quadrangle covers are stored in these attributes The state names are always stored beginning with ST_NAME1 but they are not listed in any particular order Publication data Most recent date of
93. AR 8 8 8 8 11 F 11 F 11 F 0 Value of Poultry Sold 1 000 POULTRYSAL 11 F 0 Farms Selling Dairy Products DAIRYFARMS 11 F 11 F Value Dairy Products 1K DAIRYSALES 0 0 gt gt continued April 1992 B 31 Appendix B ArcUSA 1 2M state and county statistical attribute layers Agricultural Product Market Value continued Polygon Attribute Table County Level Coverage continued Item Description Farms Selling Cattle Value of Cattle Sold 1 000 Farms Selling Hogs and Pigs Value of Hogs Sold 1 000 Farms Selling Sheep etc Value of Sheep Sold 1 000 Farms Selling Other Livestock Value of Other Livestock Sold Farms by SIC Cash Grain Farms in SIC Field Crops Farms in SIC Cotton Farms in SIC Tobacco Farms in SIC Other Field Crops Farms in SIC Vegetables Farms in SIC Fruits Nuts Farms in SIC Horticulture Farms in SIC General Crops Farms in SIC Livestock Farms in SIC Beef Cattle Farms in SIC Dairy Farms in SIC Poultry Farms in SIC Animal Spec Farms in SIC General Livestock Arc Attribute Table Item Description Left State FIPS Code Right State FIPS Code Adjacent States Boundary Type Code dBASE Columns Begin Column ltem Name Column Definition INFO Items Begin Item Column Definition CATTLEFARM CATTLESALE HOGFARMS HOGSALES SHEEPFARMS SHPWOOLSAL OTHLVSTFAR OTHLVSTSAL SICCASHGRN SICFLDCROP 1226 17 N 6 1243 17 N 6 1260 17 N 6
94. ARC INFO every time topology is established in a coverage Items for state name STATE_NAME FIPS code STATE_FIPS and U S subregion SUB_REGION were added to enhance display flexibility Data quality review After code restructuring the water bodies were plotted by class and DLG miscodes were corrected Nested cartography such as marsh on an island within a lake was carefully verified A 9 Appendix A Data quality information A 10 Place Names layer Topological edits The Place Names layer was derived from the U S Geographic Names Information System GNIS Concise Digital Database The names of national parks national forests lakes reservoirs and populated places were extracted from this file The populated places included in the coverage were county seats state capitals and major cities For the remaining four types of place names only the names of features present in ArcUSA layers were retained Location points were generated for each place name using the geographic coordinates listed in the Concise Digital Database file As is the case with most Gazetteer files these coordinates were subject to some rounding Attribution Items for county name CNTY_NAMEB state name STATE_NAMB FIPS code STATE_FIPS and U S subregion SUB_REGION were added to enhance display flexibility Data quality review No special reviews were performed for this coverage Railroads layer Topological edits After the APPENDing
95. ARMS CORNACRES CORN_BU 284 301 318 335 352 369 386 403 420 437 454 471 488 505 522 539 556 573 590 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 144 152 160 168 176 184 192 200 208 8 11 F 0 PO DOO POO 00 08 DO E DO continued B 21 Appendix B ArcUSA 1 2M state and county statistical attribute layers Agricultural Product Inventory continued Polygon Attribute Table State Level Coverage continued dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Farms with Corn for Silage SILAGEFARM 896 17 N 6 432 8 11 F 0 Acres of Corn for Silage SILAGEACRE 913 17 N 6 440 Tons of Corn Silage Produced SILAGE_TON 930 17 N 6 448 Farms with Sorghum SORGHMFARM 947 17 N 6 456 Acres of Sorghum SORGHMACRE 964 17 N 6 464 Bushels of Sorghum Harvested SORGHM_BU 981 17 N 6 472 Number of Farms with Wheat WHEATFARMS 998 17 N 6 480 Acres of Wheat WHEATACRES 1015 17 N 6 488 Bushels of Wheat Harvested WHEAT_BU 1032 17 N 6 496 Farms with Barley BARLEYFARM 1049 17 N 6 504 Acres of Barley BARLEYACRE 1066 17 N 6 512 Bushels of Barley Harvested BARLEY_BU 1083 17 N 6 Farms with Oat
96. Areas MSAs Primary Metropolitan Statistical Areas PMSAs Consolidated Metropolitan Statistical Areas PMSAs and New England County Metropolitan Areas NECMA To allow for the addition of new entries e g the names of new counties or states intervals were left between the FIPS codes For that reason the code list is not sequential even though it is complete C 1 Appendix C FIPS codes State FIPS codes 1 Alabama 4 Arizona 5 Arkansas 6 California 8 Colorado 9 Connecticut 10 Delaware 11 District of Columbia 12 Florida 13 Georgia 16 Idaho 17 Illinois County FIPS codes Alabama 1 Autauga 3 Baldwin 5 Barbour 7 Bibb 9 Blount 11 Bullock 13 Butler 15 Calhoun 17 Chambers 19 Cherokee 21 Chilton 23 Choctaw 25 Clarke 27 Clay 29 Cleburne 31 Coffee 33 Colbert 35 Conecuh 37 Coosa 39 Covington 41 Crenshaw 43 Cullman 45 Dale 47 Dallas 49 De Kalb 51 Elmore 53 Escambia 55 Etowah 57 Fayette 59 Franklin 61 Geneva 63 Greene 65 Hale 111 113 115 117 119 121 123 125 127 129 131 133 Indiana Jowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Henry Houston Jackson Jefferson Lamar Lauderdale Lawrence Lee Limestone Lowndes Macon Madison Marengo Marion Marshall Mobile Monroe Montgomery Morgan Perry Pickens Pike Randolph
97. BLACK P_NHBLACK NHAMIND P_NHAMIND Number of people and percentage of population in the state or county identified as belonging to a race other than white black American Indian or Asian and being 18 years of age or older Percentage is computed by dividing OTHER18 by TOTALI8 Total Hispanic population Number of people of all races identified as being of Hispanic origin and percentage of population identified as being of Hispanic origin Percentage is computed by dividing HISPANIC by POP1990 Non Hispanic population by race Number of people in the state or county identified as not being of Hispanic origin computed by adding NHWHITE NHBLACK NHAMIND NHASIAN and NHOTHER and percentage of population identified as not being of Hispanic origin computed by dividing NHISPAN by POP1990 Number of people and percentage of population in the state or county identified as being white and not of Hispanic origin Percentage is computed by dividing NHWHITE by NHISPAN Number of people and percentage of population in the state or county identified as being black and not of Hispanic origin Percentage is computed by dividing NHBLACK by NHISPAN Number of people and percentage of population in the state or county identified as being American Indian and not of Hispanic origin Percentage is computed by dividing NHAMIND by NHISPAN ArcUSA User s Guide and Data Reference April 1992 NHASIAN P_NHASIAN NHOTHER P_NHOTHER
98. Baca 13 Dona Ana 15 Eddy 17 Grant 19 Guadalupe 21 Harding 23 Hidalgo 25 Lea 27 Lincoln 28 Los Alamos 29 Luna 31 McKinley 33 Mora 35 Otero 37 Quay 39 Rio Arriba 41 Roosevelt 43 Sandoval 45 San Juan 47 San Miguel 49 Santa Fe 51 Sierra 53 Socorro 55 Taos 57 Torrance 59 Union 61 Valencia New York 1 Albany 3 Allegany 5 Bronx 7 Broome 9 Cattaraugus 11 Cayuga 13 Chautauqua 15 Chemung 17 Chenango 19 Clinton 21 Columbia 23 Cortland 25 Delaware 105 107 109 111 113 115 117 119 121 123 Dutchess Erie Essex Franklin Fulton Genesee Greene Hamilton Herkimer Jefferson Kings Lewis Livingston Madison Monroe Montgomery Nassau New York Niagara Oneida Onondaga Ontario Orange Orleans Oswego Otsego Putnam Queens Rensselaer Richmond Rockland St Lawrence Saratoga Schenectady Schoharie Schuyler Seneca Steuben Suffolk Sullivan Tioga Tompkins Ulster Warren Washington Wayne Westchester Wyoming Yates North Carolina 1 3 5 7 9 1 3 1 1 Alamance Alexander Alleghany Anson Ashe Avery Beaufort 113 115 117 119 121 123 125 127 129 Bertie Bladen Brunswick Buncombe Burke Cabarrus Caldwell Camden Carteret Caswell Catawba Chatham Cherokee Chowan Clay Cleveland Columbus Craven Cumberland Currituck Dare Davidson Davie Duplin Durham Edgecom
99. Because the scale bar is in a predetermined location that cannot be changed it can only be used for maps that display the full extent of the database 5 13 Chapter 5 The ArcUSA 1 25M layers Map Elements Summary of the Map Elements coverage Coverage name dBASE UNIX and size MB SC_25M 0 02 0 03 Source and currency ESRI 1992 Thematic attribute groups Classification attributes polygons Annotation text Map title scale and North arrow characters Feature Number of class Number of features attributes Polygons All polygon features Represented by 15 polygons Lines All line features Represented by 43 lines gt or 72 Polygon attributes Classification attribute FILL The scale bar is designed so that it can be filled with alternating colors The arrowhead on the North arrow can also be filled The codes are as follows Codes Definitions 1 First color scale bar 2 Second color scale bar and North arrow 5 14 ArcUSA User s Guide and Data Reference Rivers Lines April 1992 Chapter 5 The ArcUSA 1 25M layers Rivers Layer description The Rivers layer is a subset and a generalized version of the ArcUSA 1 2M Rivers and Streams layer Using the Rivers coverage The process of selecting rivers for this layer from the detailed ArcUSA 1 2M Rivers and Streams layer involved a two step process First the longest rivers and river branches were selected including segments coded as River cente
100. CE 13 N 6 193 4 6 F Expenditure Public Welfare P_WELFARE 13 N 6 197 4 6 F Expenditure for Highways P_HIGHWAY 13 N 6 201 4 6 F Local Gov t Debt Outstanding DEBT 13 N 6 4 10 F Local Gov t Debt per Capita DEBT_CAP 11 N 0 4 6 B Local Gov t Employment 1982 LOCGVT_EMP 11 N 0 4 7 B Local Gov t Empl 10K Pop LG_EMP_10K 13 N 6 4 8 F Fed Civilian Employment 84 FEDCIV_EMP 11 N 0 4 7 B Fed Civ Emp Earnings 84 FEDCV_EARN 11 N 0 4 8 B Votes Cast for President 1984 PRESVOTE84 11 N 0 4 8 B Vote for Leading Party 1984 P_VTE_LEAD 13 N 6 4 6 F 1 Vote for Pres Leading Party LEAD_PARTY 1 N 0 1 1 1 April 1992 B 41 Appendix B ArcUSA 1 2M state and county statistical attribute layers Government and Financial Attributes continued Arc Attribute Table Item Description Left State FIPS Code Right State FIPS Code Adjacent States Boundary Type Code ltem Name Begin Column dBASE Columns Column Definition INFO Items Begin Item Column Definition L_ST_FIPS R_ST_FIPS ST_NAMES BNDY_TYPE 3 N 0 3 N 0 41 C 0 11 N 0 29 3 3 35 35 76 Note The state level and county level AATs are identical Socioeconomic Attributes SOC88S SOC88C Polygon and Line Coverage Names Layer Type Polygon Attribute Table State Level Coverage Item Description State FIPS Code State Name U S Subregion Code Statistical Flag Total Households 1985 Change Households 1980 85 Persons per Househ
101. CITIES USGS Digital Line Graphs 1988 ESRI ArcWorld 1992 USGS DLG 1973 USGS DLG 1988 USGS DLG 1973 LAND25M RIV_25M RDS_25M Coverage Names 13 0 50 0 03 0 46 0 75 0 35 Wi 3 20 0 40 0 02 0 52 0 93 34 1 8 ArcUSA User s Guide and Data Reference Chapter 1 What is ArcUSA Table 4 ArcUSA 1 25M layers continued Layer Features Source Coverage _ Size MB curreney Names Statistical Polygons 336 Polygon attributes 41 USGS STATS_S 0 49 0 40 Attributes states population by race DLG 1973 by State and age income F crime farmland and Various oes farm sales Lines 472 Line attributes 4 state and international boundary type boundaries shorelines geogr reference Polygons 3 444 Polygon attributes 50 USGS DLG STATS _C 5 00 3 37 counties population by race 1988 and age income crime farmland and ee farm sales soils Lines 9 496 Line attributes 4 county boundaries boundary types shorelines geogr reference April 1992 1 9 Chapter 2 Exploring the ArcUSA database This guided tour introduces ArcView users to the ArcUSA database by exploring the precomposed views included with the data The tour does not cover all aspects of the database but it does illustrate some of the ways in which the data at both the 1 2 000 000 and 1 25 000 000 scales can be used By following the exercises in this chapter you will be better able to explo
102. CMSA as well ArcUSA User s Guide and Data Reference April 1992 Chapter 4 ArcUSA state and county statistical attribute layers Demographic and Health Attributes e Consolidated Metropolitan Statistical Areas are composed of one or more counties that are considered to be metropolitan in nature and that include at least one city of 100 000 population New England County Metropolitan Areas apply to the six New England States Maine New Hampshire Vermont Massachusetts Connecticut and Rhode Island Because MSAs in New England may be composed of partial county units NECMAs were created in order to define the same metropolitan areas based on entire counties When you use ArcUSA data to compare New England metropolitan areas with metropolitan areas in other states it is recommended that you select NECMA counties for the New England states and MSA counties elsewhere This is because in CNTY_TYPE a New England county that is part of a NECMA is classified as a NECMA county even if it also is part of an MSA If all or part of a New England county belongs to an MSA but not to a NECMA it is classified as an MSA county As a result a selection of MSA counties in New England will result in a set of seven fringe counties rather than complete MSAs The attribute MET_ST_AR contains the FIPS code for the MSA or CMSA to which a metropolitan county belongs This attribute is blank for counties that are not included in an MSA or CMSA and
103. CNTY_FIPS 3 N 0 20 3 3 County FIPS Code FIPS 6 L 0 23 6 6 C State Name STATE_NAME 20 L 0 29 20 20 C County Name CNTY_NAME 32 L 0 49 32 32 C U S Subregion Code SUB_REGION 113 7 L 0 81 7 7 C continued April 1992 B 51 Appendix B ArcUSA 1 25M layers Statistical Attributes continued Polygon Attribute Table County Level Coverage continued dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Statistical Flag STAT_FLAG 120 1 N 0 88 1 1 1 County Type Code CNTY_TYPE 121 26 C 0 89 26 26 C Metro Statistical Area Code MET_ST_AR 147 4 L 0 115 4 4 C Consolidated MSA Code PR_MT_ST_A 151 4 L 0 119 County Land Area LAND_AREA 155 11 N 0 123 Births 1984 BIRTHS _84 166 11 N 0 127 Net Migration 1980 86 NET_MIGR 177 11 N 0 131 Persons Under 5 Years 84 P_UNDER_5 188 13 N 6 135 Persons 5 to 14 Years 84 ve 201 13 N 6 139 Persons 15 to 24 Years 84 1S 214 13 N 6 143 Persons 25 to 34 Years 84 25 227 13 N 6 147 Persons 35 to 44 Years 84 240 13 N 6 151 Persons 45 to 54 Years 84 45 253 13 N 6 Persons 55 to 64 Years 84 A 266 13 N 6 Persons 65 to 74 Years 84 13 N 6 Persons 75 Yrs 84 S 13 N 6 Total Population 1984 305 11 N 0 Persons per Household 1985 PERS_HHLD 13 N 6 Marriages per 1 000 Pop MARRIAG_IK 329 13 N 6 Hospital Beds per 1 000 Pop HBEDS_1000 11 N 0 Soc Sec Recips 1 000 Pop SSRECIP_1IK 13 N 6 S
104. COSALE HAYSILGFAR 318 335 352 369 386 403 420 437 454 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 160 168 176 184 192 200 208 216 224 8 11 F 0 8 11 F 0 COW 0O OO OO OO OO OO OO OO eee m 00 00 00 OO OO OO O0 OO HC OO e eee e m gt gt gt gt ary 8 11 8 11 8 11 8 11 8 11 8 11 gy ty F F 0 F 0 F 0 F 0 F 0 continued ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 2M state and county statistical attribute layers Agricultural Product Market Value continued Polygon Attribute Table State Level Coverage continued dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Value of Hay etc Sold 1K HAYSILGSAL 930 17 N 6 448 8 11 F 0 Farms Selling Vegetables VEGFARMS 947 17 N 6 456 Value of Vegetables Sold 1K WEGSALES 964 17 N 6 464 Farms Selling Fruits or Nuts FRUITNUTFA 981 17 N 6 472 Value Fruits Nuts Sold 1K FRUITNUTSA 998 17 N 6 480 Farms Selling Nursery Crops NURSRYFARM 1015 17 N 6 488 Nursery Crops Sold 1 000 NURSRYSALE 1032 17 N 6 496 Farms Selling Other Crops OTHCROPFAR 1049 17 N 6 504 Value Other Crops Sold 1K OTHCROPSAL 1066 17 N 6 512 Farms Selling Livestock etc LVSTPOUL_F 1083 17 N 6 520
105. Contents Chapter 1 Chapter 2 Chapter 3 Preface Getting started with ArcUSA What is ArcUSA A flexible U S database at two scales U S regions and subregions ArcUSA database layer summary tables Exploring the ArcUSA database Getting started Exploring U S migration trends 1980 to 1986 by state Exploring U S migration trends 1980 to 1986 by county Bivariate mapping using ArcUSA 1 2M attributes Landfall of a large oceanic storm Data documentation views Ideas for other ways to use ArcUSA Database concepts and organization Concepts and terms Coverages The ArcUSA database Attributes ArcUSA attributes Naming conventions Data sources Coordinate systems Contents Chapter 4 In greater detail The ArcUSA 1 2M layers 4 ArcUSA 1 2M cartographic layers 4 County Boundaries 4 Federal Lands 4 Lakes and Other Water Bodies 4 Land Ocean Display 4 Map Elements 4 4 4 4 4 4 4 4 1 QW Ww WNNNRK RR RK ONW e Place Names Railroads Rivers and Streams Roads State Boundaries ArcUSA 1 2M index layers Landsat Nominal Scene Index Latitude Longitude Grids 4 42 USGS 1 24 000 Topographic Quadrangle Series Index 4 45 USGS 1 100 000 Topographic Quadrangle Series Index 4 5 USGS 1 250 000 Topographic Quadrangle Series Index 4 54 ArcUSA 1 2M state and county statistical attribute layers4 59 1990 U S Census Public Law 94 171 Data 4 61 Agricultural Product Inventory 4 70 Agricultural Pro
106. D Note Only the attributes marked with appear in ArcView tables The other ARC INFO generated attributes are physically present in the ArcUSA coverage tables but are not visible on the screen in ArcView Note that other ArcUSA attributes contain information similar to the ARC INFO generated data In such cases the two sets of values will be different from each other because they have been derived from a different source not calculated from the coordinate representation of the feature For example in the county level Demographic and Health Attributes layer both AREA and LAND_AREA give a value for county land area Yet the values are different because AREA is given in square meters in the Albers projection and is derived from a digitized map while LAND_AREA is given in square miles and is derived from a Census Bureau database Furthermore in counties and states made up of more than one polygon AREA contains the value for an individual polygon while LAND_AREA contains the value for the county or state as a whole Coverages in the user s guide In this user s guide a group of coverages like the four USGS 1 24 000 Quadrangle Series Index coverages mentioned above is called a layer To avoid repetition the layer is described rather than the individual coverages Furthermore ArcUSA county coverages that contain statistical attributes like AGINC usually have a counterpart coverage that contains identical statistics for states in thi
107. EANFAR SOYBEANACR SOYBEAN_BU DRYBEANFAR DRYBEANACR DRYBEANCWT POTATOFARM POTATOACRE POTATO_CWT SUGBEETFAR SUGBEETACR SUGBEETTON SUGCANEFAR SUGCANEACR SUGCANETON PINEAPLFAR PINEAPLACR PINEAPLTON PEANUTFARM PEANUTACRE PEANUT_LB HAYFARMS HAYACRES HAYTONS VEGFARMS VEGACRES ORCHRDFARM ORCHRDACRE 1379 1396 1413 1430 1447 1464 1481 1498 1515 1532 1549 1566 1583 1600 1617 1634 1651 1668 1685 1702 1719 1736 1753 1770 1787 1804 1821 1838 1855 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 ArcUSA User s Guide and Data Reference 681 689 697 705 713 721 729 737 745 453 761 769 777 785 793 801 809 817 825 8 11 F 0 HI t t ti H eo Hg g oooooocoo OO OO OO O0 O0 O0 00 O0 00 OC ph ph pb p ph pb ph pb pad fd OO O0 O0 O0 O0 O0 O0 O0 O0 Appendix B ArcUSA 1 2M state and county statistical attribute layers Agricultural Product Inventory continued Arc Attribute Table dBASE Columns Item Description Left State FIPS Code Right State FIPS Code Adjacent States Boundary Type Code ltem Name Begin Column Column Definition Column INFO Items Begin Item Definition L_ST_FIPS R_ST_FIPS ST_NAMES BNDY_TYPE
108. ED_DOL_CAP INC_CAP_85 RNK_INCCAP INC_CAP_79 INC_CNST79 MED_INC_79 49 52 55 61 81 113 120 121 147 151 155 166 177 190 203 214 227 240 251 3 N 0 3 N 0 6 C 0 20 C 0 32 C 0 7 C 0 1 N 0 26 C 0 4 C 0 4 C 0 11 N 0 11 N 0 13 N 6 13 N 6 11 N 0 13 N 6 13 N 6 11 N 0 13 N 6 11 N 0 11 N 0 11 N 0 11 N 0 11 N 0 11 N 0 11 N 0 13 N 6 13 N 6 11 N 0 13 N 6 11 N 0 11 N 0 11 N 0 11 N 0 11 N 0 11 N 0 ArcUSA User s Guide and Data Reference 3 3 3 3 6 6 C 20 20 C 32 32 C TIC 1 1 1 26 26 C 4 4 C 4 4 C 4 7 B 4 8 B 4 7 F 1 4 7 F 2 4 8 B 4 6 F 1 4 6 F 1 4 8 B 4 7 F 1 4 8 B 4 7 B 4 8 B 4 7 B 4 5 B 4 8 B 4 8 B 4 6 F 1 4 6 F 1 4 9 B 4 10 F 1 2 4 B 4 5 B 2 4 B 4 5 B 4 5 B 4 5 B continued Appendix B ArcUSA 1 2M state and county statistical attribute layers Socioeconomic Attributes continued Polygon Attribute Table County Level Coverage continued Item Description Persons Below Poverty 79 Persons of Poverty Status 79 Families Below Poverty 79 Family Households 1980 Housing Units 1980 Chg Housing Units 70 80 Occupied Housing Units 1980 Owner Occupied Housing Housing Units 2 Cars Occupied Housing Units Est Median Housing Unit Value Authorized New Units 1986 Authorized New Units 1980 86 1980 Units w Permits 80 86 Civilian Labor Force 1985 86 Chg Labor Force 1985 86 Unemployed Civ Labor Force Unemploym
109. Earth Observation Satellite Company 3 17 to 3 18 4 39 E 1 see also Landsat Nominal Scene Index coverage Feature attribute tables 3 4 Feature classes 3 2 Features that cross political boundaries See Polygons that cross political boundaries Federal Lands layer 1 2M 4 8 to 4 10 data sources for 3 15 3 16 3 17 item definitions B 5 production procedures for A 5 to A 6 A 9 Flag attribute 2 3 2 4 2 6 3 11 4 5 4 34 5 6 5 20 6 3 Index GeoEcology Database characteristics of and layers employed in 3 19 Geographic coordinates See Projection systems Geographic reference attributes defined 3 12 introduction into index and statistical layers A 6 listed 3 13 Government and Financial Attributes layer 1 2M 4 107 to 4 114 data sources for 3 16 3 19 3 18 to 3 19 item definitions B 39 to B 42 Graphics 6 6 to 6 8 see also Color optimizing through data selection 6 6 through drawing order 6 6 through suppression of redundant annotation See Flag attribute through use of data ranges 6 7 suppression of background polygons 4 11 use of latitude longitude grids 4 42 Hardware requirements x Index data layers 1 2M 4 37 to 4 57 characteristics 3 7 4 37 generation of A 12 to A 13 lists of 1 5 4 37 source and currency 3 16 Inserts use of in USGS topographic map sheets 4 46 4 47 Item definitions B 1 to B 53 Lakes and Other Water Bodies layer 1 2M 4 11 to 4 13 data quality review procedures for A 9
110. HISPAN18 P_HISPAN18 NHISPN18 P_NHISPN18 NHWHIT18 P_NHWHIT18 NHBLK18 P_NHBLK18 Chapter 4 ArcUSA state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data Number of people and percentage of population in the state or county identified as being Asian and not of Hispanic origin Percentage is computed by dividing NHASIAN by NHISPAN Number of people and percentage of population in the state or county identified as being of a race other than white black American Indian or Asian and not being of Hispanic origin Percentage is computed by dividing NHOTHER by NHISPAN Total adult Hispanic population Number of people in the state or county identified as being 18 years of age or older and of Hispanic origin percentage of population identified as such Percentage is computed by dividing HISPAN18 by POP1990 Adult non Hispanic population by race Number of people in the state or county identified as being 18 years of age and older and not of Hispanic origin computed by adding NHWHIT18 NHBLACK18 NHAMIN18 NHASIA18 and NHOTHE18 and percentage of population identified as being 18 years of age and older and not of Hispanic origin computed by dividing NHISPN18 by POP1990 Number of people and percentage of population in the state or county identified as being white not of Hispanic origin and 18 years of age or older Percentage is computed by dividing NHWHIT18 by TOTAL18 Number of people
111. Indexes 1 24K 1 100K 1 250K EOSAT algorithm 1992 EOSAT algorithm 1992 ESRI 1992 ESRI algorithm 1992 ESRI 1992 USGS Topographic Names Database Published Map Sheet Data File T 70 various published indexes 1986 Statistical Layers U S Census P L 94 171 Agricultural Product Inventory Agricultural Product Market Value Demographic amp Health Attributes Environmental Attributes Government amp Financial Attributes Socioeconomic Attributes USGS DLG 1988 USGS DLG 1988 USGS DLG 1988 USGS DLG 1988 USGS DLG 1988 USGS DLG 1988 USGS DLG 1988 U S Census 1990 U S Census of Agriculture 1987 U S Census of Agriculture 1987 County and City Data Book 1988 GeoEcology 1967 1979 County and City Data Book 1988 County and City Data Book 1988 3 16 ArcUSA User s Guide and Data Reference April 1992 Chapter 3 Database concepts and organization ArcUSA database The reference work for the DLG data source is Digital Line Graphs from 1 2 000 000 Scale Maps Data Users Guide 3 U S Geological Survey Reston Va 1990 The DLG data are the basis for features and attributes in the following ArcUSA 1 2M cartographic coverages County Boundaries Federal Lands Lakes and Other Water Bodies Railroads Rivers and Streams Roads and State Boundaries The DLG data are also the basis for the state and county features in all the statistical coverages The DLG data employed in the A
112. It complements the larger data set by allowing a quick overview of the ArcUSA database contents The ArcUSA database contains a broad range of data including cartographic features state and county boundaries roads railroads rivers lakes federal land areas county seats indexes latitude longitude grids USGS topographic maps Landsat scenes and statistical attributes for states and counties population by age and race income hospitals and doctors local government spending major soil types agricultural products raised and sold The user may also add layers either to tailor the database to a specific application or to provide a more exhaustive treatment of any of the data types already present ArcUSA data are formatted in both UNIX ARC INFO and PC ARC INFO coverages and can be used with the following e ArcView for UNIX and Windows e PC ARC INFO Rev 3 4D and higher e ARC INFO Rev 6 0 and higher on UNIX workstations e ArcCAD Version 11 and higher PC ARC INFO coverages store attributes in dBASE format Thus other MS DOS application software tools can be used with the ArcUSA database April 1992 1 1 Chapter 1 What is ArcUSA 1 2 U S regions and subregions U S regions and subregions Some ArcUSA 1 2M data layers are divided into three major regions encompassing states in the north south and west Most ArcUSA features are also assigned to a subregion e g Pacific Middle Atlantic so you have an easy m
113. Item Description State FIPS Code State Name U S Subregion Code Statistical Flag Federal Funds and Grants 1986 Change in Funds etc 85 86 Federal Funds Grants per Capita Direct Payments of Fed Funds Procurement Awards per Capita Fed Salaries Wages per Capita Fed Grant Awards Capita 86 Local Gen Revenue million Local Intergovernmental Rev Local Gov t Revenue fr State Local Taxes 1981 82 Local Taxes Capita 1981 82 Prop Taxes Capita 1981 82 ltem Name STATE_FIPS STATE_NAME SUB_REGION STAT_FLAG FEDFUNDGRT P_CHG_FNGR FNDGRT_CAP DIRPAY_CAP AWARDS_CAP FWAGES_CAP GRANTS_CAP LOC_GEN_RV INTER_GVT P_STATEREV LOC_TAXES TAX_CAP PROPTAX_CP dBASE Columns Begin Column Column 49 3 N 0 52 20 C 0 72 7 C 0 79 1 N 0 80 13 N 6 93 13 N 6 106 11 N 0 117 11 N 0 128 11 N 0 139 11 N 0 150 11 N 0 161 13 N 6 174 13 N 6 187 13 N 6 200 13 N 6 213 11 N 0 224 11 N 0 Definition Column 3 3 1 3 3 1 41 41 C 4 5 B INFO Items Begin Item 3 3 20 20 C continued Definition April 1992 B 39 Appendix B ArcUSA 1 2M state and county statistical attribute layers Government and Financial Attributes continued Polygon Attribute Table State Level Coverage continued dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Loc Gov t General Expenditures GEN_EXP 235 13 N 6 96 4 10 F 1 Change Expend 1977
114. MSA part of a Metropolitan Statistical Area MSA part of a New England County Metropolitan Area NECMA or none of the above The other two attributes MET ST AR and PR_MT_ST_A contain the four digit FIPS codes for metropolitan areas April 1992 4 91 Chapter 4 ArcUSA state and county statistical attribute layers Demographic and Health Attributes 4 92 Relationship between MSAs PMSAs and CMSAs Metropolitan Statistical Area MSA This MSA is composed of counties 1 2 and 3 MSA Primary Metropolitan Statistical Area PMSA County 5 contains a Central City of more than 100 000 population so is considered a PMSA Consolidated Metropolitan Statistica Area CMSA This CMSA is composed of counties 4 5 and 6 A CMSA always includes at least one PMSA U S Bureau of the Census publications should be consulted for complete information on how these areas are defined In general though these areas can be defined as follows e Metropolitan Statistical Areas are composed of one or more counties that are considered to be metropolitan in nature by the U S Bureau of the Census All cities in MSA counties have populations smaller than 100 000 In New England MSAs may be composed of partial county units where counties are divided along city and town lines e Primary Metropolitan Statistical Areas are counties that contain at least one city of 100 000 or more people A PMSA is always considered to be part of a
115. NAME STAT_FLAG POP1990 POP90_SQMI WHITE P_WHITE BLACK P_BLACK AMERIND P_AMERIND These geographic reference attributes appear only in the county level coverages The county polygon coverages contain the county FIPS code the combined state and county FIPS code and the county name Statistical flag Flag to identify a unique polygon for each state or county The codes are as follows Codes Definitions 0 Other polygon 1 Largest polygon Total population Total population of the state or county Average number of people per square mile Computed by dividing TOTAL by the land area of the state or county Population by race Number of people and percentage of population in the state or county identified as white Percentage is computed by dividing WHITE by POP1990 Number of people and percentage of population in the state or county identified as black Percentage is computed by dividing BLACK by POP1990 Number of people and percentage of population in the state or county identified as American Indian Percentage is computed by dividing AMERIND by POP1990 ArcUSA User s Guide and Data Reference ASIAN P_ASIAN OTHER P_OTHER TOTAL18 P_TOTAL18 WHITE18 P_WHITE18 BLACK18 P_BLACK18 AMERIN18 P_AMERIN18 ASIAN18 P_ASIAN18 April 1992 Chapter 4 ArcUSA state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data Number of people and percentage of population in
116. NAME 49 51 C 0 51 51 C Major City Code MAJ_CITY 100 1 N 0 Capital Code CAPITAL 101 1 N 0 County Seat Code CTY_SEAT 102 1 N 0 Elevation of Feature ELEVATION 103 6 N 0 County Name CNTY_NAME 109 31 C 0 State FIPS Code STATE_FIPS 140 3 N 0 State Name STATE_NAME 143 16 C 0 U S Subregion Code SUB_REGION 159 7 C 0 County Boundaries Coverage Name CTY_25M Layer Type Polygon and Line Polygon Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition State FIPS Code STATE_FIPS 49 3 N 0 17 3 3 1 County FIPS Code CNTY_FIPS 52 3 N 0 20 3 3 1 Combined FIPS Code FIPS 55 6 C 0 23 6 6 C State Name STATE_NAME 61 20 C 0 20 20 C County Name CNTY_NAME 81 32 C 0 32 32 C U S Subregion Code SUB_REGION 113 7 C 0 81 7 7 C STAT_FLAG 120 1 N 0 88 1 1 I B 46 ArcUSA User s Guide and Data Reference County Boundaries continued Arc Attribute Table Item Description Left State FIPS Code Right State FIPS Code Adjacent States Boundary Type Code ltem Name Appendix B ArcUSA 1 25M layers dBASE Columns Begin Column Column Definition INFO Items Begin Item Column Definition L_ST_FIPS R_ST_FIPS ST_NAMES BNDY_TYPE Land Ocean Display Coverage Name Layer Type LAND25M Polygon and Line Polygon Attribute Table Item Description Land Water Identifier ltem Name LND_WAT 3 N 0 83 3 N 0 86 41 C 0 127 11 N 0 dBASE Columns
117. O Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Hospital Beds per 1 000 Pop HBEDS_1000 256 11 N 0 104 2 4 B Soc Sec Recips 1 000 Pop SSRECIP_1K 267 13 N 6 106 4 7 F 1 Serious Crimes per 100K Pop SR_CR_100K 280 11 N 0 110 4 5 B Persons with 4 Yrs College P_COL_GRAD 291 13 N 6 114 4 6 F 1 Income per Capita 1985 INC_CAP_85 304 11 N 0 118 Median Housing Unit Value MEDIAN_DOL 315 11 N 0 122 Federal Funds and Grants 1986 FEDFUNDGRT 326 13 N 6 126 Local Taxes Capita 1981 82 TAX_CAP 339 11 N 0 130 Local Gov t Empl 10K Pop LG_EMP_10K K 350 13 N 6 134 Vote Cast for President 1984 PRESVOTE84 11 N 0 138 Total Population 1990 POP1990 11 N 0 142 Population Square Mile 1990 TOTAL_SQMI 13 N 6 146 Percent White 1990 P_WHITE 13 N 6 150 Percent Black 1990 P_BLACK 13 N 6 154 Percent American Indian 1990 P_AMERIND 13 N 6 158 Percent Asian 1990 P_ASIAN 13 N 6 162 Percent Other Race 1990 P_OTHER 13 N 6 166 Acres of Farmland FARM_ACRES 11 N 0 170 Average Size of Farm in Acres AVG_SIZE 11 N 0 174 Cropland in Acres CROP_ACRES 11 N 0 Irrigated Land in Acres IRRIGATE_A 11 N 0 Ag Products Sold 1 000 SALES_1K 11 N 0 Average Sales per Farm AVG_SALES 11 N 0 Polygon Attribute Table County Level Coverage dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition State FIPS Code STATE_FIPS 3 N 0 17 3 3 1 State Name
118. Oak Ridge National Laboratory s GeoEcology database was the source for the Environmental Attributes layer Digital Line Graphs The DLG is a digital map standard developed by the U S Geological Survey The data are offered at six scales ranging from 1 24 000 to 1 2 000 000 The source for the 1 2 000 000 scale data employed in the ArcUSA database is the 1970 National Atlas of the United States of America The data files contain planimetric information about boundaries hydrography and transportation The DLG uses a system of major and minor codes to classify geographic features These cumbersome codes were revised and simplified for the 3 15 Chapter 3 Database concepts and organization Table 5 Sources and currency of ArcUSA 1 2M data Graphic Data Layers Source Attribute Data Source Cartographic Layers County Boundaries Federal Lands Lakes and Other Water Bodies Land Ocean Display Place Names Railroads Rivers and Streams Roads State Boundaries USGS DLG 1988 USGS DLG 1980 USGS DLG 1980 USGS DLG 1988 USGS DLG 1980 USGS DLG 1988 ESRI ArcWorld 1992 ESRI ArcWorld 1992 USGS Concise Digital USGS Concise Digital Database Database 1973 USGS DLG 1979 USGS DLG 1973 USGS DLG 1980 USGS DLG 1973 1973 USGS DLG 1979 USGS DLG 1973 USGS DLG 1980 USGS DLG 1973 Index Layers Landsat Nominal Scene Index Latitude Longitude Grids USGS Topographic Map
119. PS The county polygon coverages contain the county FIPS code FIPS the combined state and county FIPS code and the county name CNTY_NAME Statistical flag STAT FLAG Flag to identify a unique polygon for each state or county The codes are as follows Codes Definitions 0 Other polygon 1 Largest polygon 4 94 ArcUSA User s Guide and Data Reference April 1992 CNTY_TYPE MET_ST_AR PR_MT_ST_A LAND_AREA POP1986 POP_RANK POP_SQMILE POP1980CR Chapter 4 ArcUSA state and county statistical attribute layers Demographic and Health Attributes Metropolitan area attributes These attributes appear only in the county level coverages This attribute allows the user to select counties according to census geography The metropolitan area terms are explained on page 4 91 The codes are as follows e County within a CMSA PMSA e County within an MSA e County within an NECMA e County not in a metro area Metropolitan Statistical Area MSA or Consolidated MSA CMSA FIPS code This attribute is blank for counties that are not included in an MSA or CMSA and for MSA counties in New England Primary Metropolitan Statistical Area PMSA FIPS code In general a PMSA is a county that contains a city of over 100 000 population County land area This attribute appears only in the county level coverages The land area of the county in 1980 Land area excludes the areas of water bodies The value in this item is
120. S 682 17 N 6 353 Value of Wheat Sold 1 000 WHEATSALES 699 17 N 6 361 Farms Selling Soybeans SOYBEANFAR 716 17 N 6 369 Value of Soybeans Sold 1 000 SOYBEANSAL 733 17 N 6 377 Farms Selling Sorghum SORGHMFARM 750 17 N 6 385 Value of Sorghum Sold 1 000 SORGHMSAL 767 17 N 6 393 Farms Selling Barley BARLEYFARM 784 17 N 6 401 Value of Barley Sold 1 000 BARLEYSALE 801 17 N 6 409 Farms Selling Oats OATSFARMS 818 17 N 6 417 Value of Oats Sold 1 000 OATSSALES 835 17 N 6 425 Farms Selling Other Grains OTHGRNFARM 17 N 6 433 Value of Other Grains 1K OTHGRNSALE 17 N 6 441 Farms Selling Cotton COTTONFARM 17 N 6 449 Value of Cotton Sold 1 000 COTTONSALE 17 N 6 457 Farms Selling Tobacco TOBACOFARM 17 N 6 465 Value of Tobacco Sold 1 000 TOBACOSALE 17 N 6 COW 0O OO OO OO OO 0O OO OO eee m Farms Selling Hay or Silage HAYSILGFAR 17 N 6 Value of Hay etc Sold 1K HAYSILGSAL 17 N 6 Farms Selling Vegetables VEGFARMS Value of Vegetables Sold 1K VEGSALES Farms Selling Fruits or Nuts FRUITNUTFA Value Fruits Nuts Sold 1K FRUITNUTSA Farms Selling Nursery Stock NURSRYFARM Value Nursery Crops 1K NURSRYSALE Farms Selling Other Crops OTHCROPFAR Value of Other Crops 1K OTHCROPSAL ary COW 0O 0O OO OO O0 HW 00 OO e eee e m m e meme TO a ead a T gt Farms Selling Livestock etc LVSTPOUL_F Value Livestock Poultry 1K LVSTPOUL_S 8 8 0 Farms Selling Poultry POULTRYF
121. Some types of federal land areas are nested within others For example a scenic waterway may be located within a wilderness area that is also part of a national forest These nested land areas may be administered by different government agencies Each land area classification has been prioritized according to restrictions on use The areas with the most stringent restrictions on use like scenic waterways were assigned the highest priority the areas with the fewest restrictions on use like national forests were assigned the lowest priority The names of national parks and forests are included in the Place Names layer 4 8 ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA 1 2M cartographic layers Federal Lands Summary of the Federal Lands coverage Coverage name dBASE UNIX and size MB FED2M 2 24 2 33 Source and currency USGS DLG 1980 Thematic attribute Classification attributes polygons groups Geographic reference attributes polygons Feature Number of Polygons National parks etc Represented by 630 polygons National wildlife Represented by 640 polygons refuges etc National scenic Represented by 139 polygons waterways etc Indian reservations Represented by 381 polygons Military reservations Represented by 168 polygons National forests and Represented by 619 polygons grasslands Not a federal land area Represented by 174 polygons All polygon features Represented by 2 741 polygons Po
122. State Level Coverage dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition State FIPS Code State Name U S Subregion Code Statistical Flag Total 1990 Population 1990 Pop per Square Mile Total White Percent White Total Black Percent Black Total American Indian Percent American Indian Total Asian Percent Asian Total Other Percent Other Total 18 Years and Older Percent 18 of Total Pop White 18 Percent White 18 Black 18 Percent Black 18 American Ind 18 Percent Amer Ind 18 Asian 18 Percent Asian 18 Other 18 Percent Other 18 Total Hispanic Percent Hispanic of Total Pop Total Non Hispanic Percent Non Hispanic Non Hispanic White B 16 STATE_FIPS STATE_NAME SUB_REGION STAT_FLAG POP1990 POP90_SQMI WHITE P_WHITE BLACK P_BLACK AMERIND P_AMERIND ASIAN P ASIAN OTHER P_OTHER TOTALI18 P_TOTAL18 WHITE18 P_WHITE18 BLACK18 P_BLACK18 AMERIN18 P_AMERIN18 ASIAN18 P_ASIAN18 OTHER18 P_OTHER18 HISPANIC P_HISPANIC NHISPAN P_NHISPAN NHWHITE 49 52 712 79 80 91 104 115 128 139 152 163 176 187 200 211 3 N 0 20 C 0 7 C 0 1 N 0 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 ArcUSA User s Gu
123. TATE_NAME CNTY_NAME SUB_REGION STAT_FLAG POP1990 POP90_SQMI WHITE P_WHITE BLACK P_BLACK AMERIND P_AMERIND ASIAN P_ASIAN OTHER P_OTHER TOTALI8 P_TOTAL18 WHITE18 P_WHITE18 BLACK18 P_BLACK18 AMERIN18 P_AMERIN18 ASIAN18 P_ASIAN18 OTHER18 P_OTHER18 HISPANIC P_HISPANIC NHISPAN P_NHISPAN 49 52 55 61 81 113 120 121 132 145 156 169 180 193 228 241 3 N 0 3 N 0 6 C 0 20 C 0 32 C 0 7 C 0 1 N 0 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 ArcUSA User s Guide and Data Reference 3 3 3 3 6 6 C 20 20 C 32 32 C 7 7 C 1 1 1 4 9 B 4 9 F 2 4 9 B 4 6 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 6 F 2 continued Appendix B ArcUSA 1 2M state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data continued Polygon Attribute Table County Level Coverage continued dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Non Hispanic White NHWHITE 457 11 N 0 201 4 9 B Percent Non Hispanic White P_NHWHITE 468 13 N 6 205 4 5 F 2 Non Hispanic Black NHBLACK 481 11 N 0 209 4 9 B
124. Upson Walker Walton Ware Warren Washington Wayne Webster Wheeler White Whitfield Wilcox Wilkes Wilkinson Worth Ada Adams Bannock Bear Lake Benewah 11 Bingham 13 Blaine 15 Boise 17 Bonner 19 Bonneville 21 Boundary 23 Butte 25 Camas 27 Canyon 29 Caribou 31 Cassia 33 Clark 35 Clearwater 37 Custer 39 Elmore 41 Franklin 43 Fremont 45 Gem 47 Gooding 49 Idaho 51 Jefferson 53 Jerome 55 Kootenai 57 Latah 59 Lemhi 61 Lewis 63 Lincoln 65 Madison 67 Minidoka 69 Nez Perce 71 Oneida 73 Owyhee 75 Payette 77 Power 79 Shoshone 81 Teton 83 Twin Falls 85 Valley 87 Washington Illinois 1 Adams 3 Alexander 5 Bond 7 Boone 9 Brown 11 Bureau 13 Calhoun 15 Carroll 17 Cass 19 Champaign 21 Christian 23 Clark 25 Clay 27 Clinton 29 Coles 31 Cook 33 Crawford ArcUSA User s Guide and Data Reference Appendix C FIPS codes 35 Cumberland 151 Pope 59 Hancock 175 Washington 37 De Kalb 153 Pulaski 61 Harrison 177 Wayne 39 De Witt 155 Putnam 63 Hendricks 179 Wells 41 Douglas 157 Randolph 65 Henry 181 White 43 Du Page 159 Richland 67 Howard 183 Whitley 45 Edgar 161 Rock Island 69 Huntington 47 Edwards 163 St Clair 71 Jackson lowa 49 Effingham 165 Saline 13 Jasper 1 Adair 51 Fayette 167 Sangamon 75 Jay 3 Adams 53 Ford 169 Schuyler 77 Jeffer
125. Waller Ward Washington Webb Wharton Wheeler Wichita Wilbarger Willacy Williamson Wilson Winkler Wise Wood Yoakum Young Zapata Zavala Beaver Box Elder Cache Carbon Daggett Davis Duchesne Emery Garfield Grand Iron Juab Kane Millard Morgan Piute Rich Salt Lake San Juan Sanpete Sevier Summit Tooele Uintah 49 Utah 51 Wasatch 53 Washington 55 Wayne 57 Weber Vermont 1 Addison 3 Bennington 5 Caledonia 7 Chittenden 9 Essex 11 Franklin 13 Grand Isle 15 Lamoille 17 Orange 19 Orleans 21 Rutland 23 Washington 25 Windham 27 Windsor Virginia 1 Accomack 3 Albemarle 5 Alleghany 7 Amelia 9 Amherst 11 Appomattox 13 Arlington 15 Augusta 17 Bath 19 Bedford 21 Bland 23 Botetourt 25 Brunswick 27 Buchanan 29 Buckingham 31 Campbell 33 Caroline 35 Carroll 36 Charles City 37 Charlotte 41 Chesterfield 43 Clarke 45 Craig 47 Culpeper 49 Cumberland 51 Dickenson 53 Dinwiddie 57 Essex 59 Fairfax 61 Fauquier 63 Floyd 65 Fluvanna 67 Franklin 69 Frederick 71 Giles C 14 ArcUSA User s Guide and Data Reference Appendix C FIPS codes 141 143 145 147 149 153 155 157 159 161 163 165 167 169 171 173 175 177 179 181 183 185 187 191 193 195 Gloucester Goochland Grayson Greene Greensville Halifax Hanover Henr
126. a Only one state is identified for international boundaries and shorelines Classification attribute Each line is classified according to boundary type This attribute allows you to choose different symbols for political boundaries and coastlines Wherever boundaries are coincident rank is assigned beginning with coastlines in the reverse order of the list below Thus a state boundary that is also a coastline will be coded as 4 for coastline The codes are as follows Codes Equivalents 2 State boundary 3 International boundary 4 Coastline ArcUSA User s Guide and Data Reference ArcUSA 1 2M index layers The coverages in the 1 2M index layers provide reference to Landsat satellite data latitude longitude and to USGS topographic maps Users can quickly determine the location of geographic features by using one of the latitude longitude grids The map and satellite indexes provide information needed for ordering those products they can also provide a handy way to zoom in on a particular study area The ArcUSA 1 2M index layers are listed in the table below Landsat Nominal Scene Index SAT_PT SAT_BND Latitude Longitude Grids LTLG2 LTLG5 LTLG10 USGS 1 24 000 Topographic Q_24K Q_24KN Q_24KS Q_24KW Quadrangle Series Index USGS 1 100 000 Topographic Q_100K Quadrangle Series Index USGS 1 250 000 Topographic Q_250K Quadrangle Series Index April 1992 4 37 Landsat Nominal Scene Index Points
127. a map and the extent to which the grid will be used for reference will determine the most suitable grid interval The 10 degree grid is appropriate for small scale displays such as maps showing the full extent of the United States The 5 degree grid is excellent for regional displays while the 2 degree grid is best for large scale maps showing a state or local area To create grid resolutions that are finer than 2 degrees the latitude longitude grids can be supplemented with the USGS topographic map sheet grids ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA 1 2M index layers Latitude Longitude Grids Summary of Latitude Longitude Grids coverages Two degree interval coverage Coverage name dBASE UNIX and size MB LTLG2 2 63 0 23 Source and currency ESRI algorithm generated 1992 Thematic attribute groups Classification attributes Feature Number of Lines Latitude and longitude Represented by 1 225 lines lines 2 by 2 degree grid Five degree interval coverage Coverage name dBASE UNIX and size MB LTLG5 0 08 0 08 Source and currency ESRI algorithm generated 1992 Thematic attribute groups Classification attributes Feature Number of Lines Latitude and longitude Represented by 314 lines lines 5 by 5 degree grid April 1992 4 43 Chapter 4 ArcUSA 1 2M index layers Latitude Longitude Grids Ten degree interval coverage Coverage name dBASE UNIX and size MB LTLG10 0
128. a summary of the data for municipal county town and township government figures In other words the value for local government taxes per capita TAX_CAP in the county coverage represents the county taxes plus taxes levied by towns and cities within the county In the state coverage TAX_CAP represents the summary of the county and municipal government data for the whole state It does not represent the taxes levied by the state government Agricultural attributes The agricultural attributes in this layer come from the U S Census of Agriculture The agricultural census does not recognize or summarize statistics for independent cities Such places may have a blank or zero value for some of these attributes Additional general information about agricultural attributes begins on page 4 70 5 24 ArcUSA User s Guide and Data Reference Chapter 5 The ArcUSA 1 25M layers Statistical Attributes Summary of the Statistical Attributes coverages State coverage Coverage name dBASE UNIX and size MB STATS_S 0 49 0 40 Source and currency Cartography from Digital Line Graphs current to 1973 Attribute data selected from various sources which are U S Census Bureau 1990 Census and Digital County and City Data Book 1988 U S Census of Agriculture Tables 1 and 2 1987 Thematic attribute Geographic reference attributes polygons and lines groups Demographic attributes polygons Socioeconomic attributes polygons Governmen
129. abase one that can be used by either ArcView or ARC INFO Coverages The ArcUSA database is organized by coverage Coverages represent the main method for vector data storage in ARC INFO format A coverage is a digital version of a single map sheet layer and generally describes one type of map feature such as roads counties or lines of latitude and longitude A coverage contains both the locational data and thematic attributes associated with map features Coverage feature classes In a coverage map features are stored as points lines also known as arcs or polygons The three feature classes can be employed in a coverage either separately or in combination depending on the requirements of the captured geographic data For example in the ArcUSA database counties are stored in one coverage as both polygon features areas and line features boundaries A fourth feature class annotation is used in ArcUSA as a special way to store the title and other characters in the Map Elements and Land Ocean Display coverages ArcUSA User s Guide and Data Reference Chapter 3 Database concepts and organization Coverage feature classes and attribute tables T z sub_region T J SSR BY Points represent features like named places Points have no length or area A point is defined as a single x y coordinate pair Lines represent linear features like roads Lines have length but no area A line is defi
130. able dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Left State FIPS Code L_ST_FIPS 80 3 N 0 29 3 3 Right State FIPS Code R_ST_FIPS 83 3 N 0 32 3 3 Adjacent States ST_NAMES 86 41 L 0 35 41 41 C Boundary Type Code BNDY_TYPE 127 11 N 0 76 4 5 B Note The state level and county level AATs are identical April 1992 B 53 Appendix C April 1992 Federal Information Processing Standards FIPS codes Federal Information Processing Standards FIPS codes are standard international codes that have been developed to facilitate the transfer of information between systems to reduce data coding error and to reduce waste in data storage by eliminating duplication The codes were developed by the National Computer Systems Laboratory at the National Institute of Standards and Technology There are FIPS codes for place names throughout the world for the United States the codes include the place names for incorporated places Indian reservations airports and U S Post Offices The ArcUSA database uses the U S state and county FIPS codes Each state has a unique two digit numeric code and each county has a three digit numeric code that is unique within the state In combination these codes give each county a unique five digit code The ArcUSA database also uses the four digit FIPS codes for census metropolitan areas These areas are Metropolitan Statistical
131. ach polygon is classified as either land or water ocean and the Great Lakes as follows e Land e Water April 1992 4 15 Chapter 4 ArcUSA 1 2M cartographic layers Land Ocean Display Line attributes Classification attribute BND GRID Each line segment is classified as either a feature boundary shorelines and international boundaries or an artificial grid line a data processing line that divides the data into geographic sections The codes are as follows Codes Definitions O Artificial grid line 1 Feature boundary or outer coverage extent line 4 16 ArcUSA User s Guide and Data Reference Map Elements Polygons and Lines April 1992 Chapter 4 ArcUSA 1 2M cartographic layers Map Elements Layer description The Map Elements layer contains a scale bar North arrow and a title that can be used to make your display look like a finished map Using the Map Elements coverage Polygon attributes include codes for the scale bar and the head of the North arrow so that they may be filled with color Annotation features provide the title and characters associated with the other map elements The scale is given in kilometers since the Albers Conic Equal Area projection uses meters Because the scale bar is in a predetermined location that cannot be changed it is best suited to maps that display the full extent of the database Chapter 4 ArcUSA 1 2M cartographic layers Map Elements Summary
132. alue of Crops Sold 1 000 VAL_CROPS 427 17 N 6 233 Value of Livestock etc Sold VAL_ANIMAL 444 17 N 6 241 Farmer as Principal Occupation FARMERS 17 N 6 Farmer as Other Occupation OTH_OPERS 17 N 6 Farmers with Days Off Farm OTHJOB_ANY 17 N 6 Farmers w 200 Days Off OTHJOB_200 17 N 6 Average Age of Farmers AVG_AGE 17 N 6 Production Expenses 1 000 PROD_EXP 17 N 6 Avg Expenses per Farm AVG_EXP 17 N 6 Farms with Cattle and Calves CATTLEFARM 17 N 6 Number of Cattle and Calves CATTLE 17 N 6 Farms with Beef Cows BEEFFARMS 17 N 6 Number of Beef Cows BEEFCOWS 17 N 6 Farms with Dairy Cows MILKFARMS 17 N 6 Number of Dairy Cows MILKCOWS 17 N 6 Farms Selling Cattle amp Calves COWSOLDFAR 17 N 6 No of Cattle and Calves Sold CATTLESOLD 17 N 6 Farms with Hogs and Pigs HOGFARMS 17 N 6 Number of Hogs and Pigs HOGS 17 N 6 Farms Selling Hogs and Pigs HOGSOLDFAR 17 N 6 continued B 24 ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 2M state and county statistical attribute layers Agricultural Product Inventory continued Polygon Attribute Table County Level Coverage continued dBASE Columns Begin Column Begin Item Item Name Column Definition Column Definition HOGS_SOLD 767 17 N 6 393 8 11 F 0 INFO Items Item Description No of Hogs and Pigs Sold Farms with Sheep and Lambs Number of Sheep and Lambs Farms with Chickens Number of Chickens Farms Selling Broilers Number of Broilers Sold
133. an a single complex statement Use the 1 25M database whenever possible As noted in Chapter 2 another way to decrease drawing time is to use the 1 25 000 000 scale data whenever possible For small scale representations of the attribute information present in the 1 2 000 000 scale data the cartographic level of detail may be served better by the 1 25M layers Be aware however that even though you can zoom in to display data at any scale desired the cartographic level of detail remains consistent with the scale at which the database was constructed For use with ARC INFO normalize the database ARC INFO users may want to create a series of smaller more compact tables for tabular information in order to take advantage of the relate capability in ARC INFO The process of creating compact related tables is called normalization explanations can be found in standard database design textbooks The present design of the ArcUSA database allows the Arc View user to access tables that are not normalized ArcUSA User s Guide and Data Reference April 1992 Chapter 6 Using the database Working with attributes Flag attributes Some of the states and counties in the database are represented by multiple polygons The state of Michigan with its upper peninsula and many islands is a good example In these cases the polygons in the layer have been coded with a Statistical flag named STAT_FLAG that can be used to select the largest polygon o
134. ancis Detailed treatment of error and accuracy particularly of modeling uncertainty and reliability testing accuracy and the practical implications for use of spatial data Huxhold W E 1991 Introduction to Urban Geographic Information Systems New York Oxford University Press Basic concepts and applications of GIS in local government Useful for students and practitioners Intelligent Infrastructure The Movie A Management Level Overview of GIS 1990 Englewood Colo UGC Corporation 15 min video Intelligent Infrastructure Workbook A Management Level Primer on GIS 1990 Englewood Colo UGC Corporation Maguire D J M F Goodchild and D W Rhind 1991 Geographical Information Systems Principles and Applications New York John Wiley amp Sons Marx R W ed The Census Bureau s TIGER System Jan 1990 Cartography and Geographic Information Systems 17 no 1 17 113 Bethesda Md American Congress on Surveying and Mapping Monmonier M and G A Schnell 1988 Map Appreciation Englewood Cliffs N J Prentice Hall Mounsey H ed 1988 Building Databases for Global Science New York Taylor amp Francis Proceedings of the first meeting of the International Geophysical Union Global Database Planning Project Roger Tomlinson gen ed Onsrud H J and D W Cook 1990 Geographic and Land Information Systems for Practicing Surveyors A Compendium Bethesda Md American Congress on
135. aphic features The bulk of the data in these coverages is locational attributes are few and usually they identify the location and class of the features The ArcUSA 1 2M database includes ten cartographic layers County Boundaries Federal Lands Lakes and Other Water Bodies Land Ocean Display Map Elements title and scale bar Place Names Railroads Rivers and Streams Roads and State Boundaries Index layers Coverages in the five ArcUSA 1 2M index layers contain several geographic reference grids and data indexes The index layers are Landsat Nominal Scene Index for Landsat 4 and 5 satellite data Latitude Longitude Grids 2 5 and 10 degree intervals and USGS Topographic Quadrangle Series Indexes for maps at scales of 1 24 000 1 100 000 and 1 250 000 State and county statistical attribute layers Coverages in the ArcUSA 1 2M state and county statistical layers contain both geographic features which are identical to the geographic data in the state and county cartographic coverages and a large number of attributes for state or county statistics There are both state and county layers called the following 1990 Census Public Law 94 171 Data demographic data used for redistricting Agricultural Product Inventory Agricultural Product Market Value Demographic and Health Attributes Government and Financial Attributes and Socioeconomic Attributes There is also an Environmental Attributes coverage for counties 3 7 Ch
136. aphs from 1 2 000 000 Scale Maps Data Users Guide 3 Special processing techniques applicable to a single database layer are described separately under the heading appropriate for the layer The 1 2 000 000 scale DLG optional files of the coterminous United States fifteen panels were converted into single precision ARC INFO coverages using the DLGARC command in ARC INFO Rev 5 0 1 The coverages were then projected to a common coordinate space Albers Conic Equal Area projection see technical specifications for projection parameters Following projection the coverages were appended using the ARC INFO APPEND command After all topological edits were completed for each layer topology was established in the APPENDed coverage using the ARC INFO command CLEAN with a fuzzy tolerance of 50 8 m This resulted in a single 1 2M coverage of the coterminous United States for each database layer All linework and attribute processing and all data quality reviews occurred on the APPENDed coverage Once attribute processing and all data reviews were complete the APPENDed coverages for the USGS 1 24 000 Topographic Quadrangle Series Index layer and the Lakes and Other Water Bodies layer were split into three tiles regions corresponding to the northern southern and western portions of the coterminous United States using the ARC INFO command SPLIT with a fuzzy tolerance of 50 8 m A 5 Appendix A Data quality information Attribution Modifications
137. appropriate for cultivation ArcUSA User s Guide and Data Reference April 1992 P_DIST_UND L_ST_FIPS R_ST_FIPS ST_NAMES BNDY_TYPE Chapter 5 The ArcUSA 1 25M layers Statistical Attributes Percentage of the county land area that has been disturbed by surface mining activities Line attributes Geographic reference attributes The FIPS code of the states on either the left or right side of a boundary segment are contained in these attributes The states on either side of a boundary are identified by name in this attribute Classification attribute Each line is classified according to boundary type The codes are as follows Codes Definitions 1 County boundary 2 State boundary 3 International boundary 4 Coastline 5 31 Chapter 6 Using the database This chapter contains information that will help you use the ArcUSA database successfully The information covers three general areas techniques for selecting data in order to improve software performance information about working with attributes in order to analyze data and suggestions for creating attractive functional graphic displays Optimizing performance Reduce the number of features To improve performance when you use a large database like ArcUSA reduce the amount of data you are dealing with as soon as possible This will improve performance for subsequent search operations logical operations as well as reduce drawing times Ma
138. apter 3 Database concepts and organization 3 8 Characteristics of ArcUSA 1 25M coverages The ArcUSA 1 25M layers contain data that are generalized from the 1 2M coverages Map features are less detailed and there are fewer feature attributes The 1 25M coverages complement the more detailed coverages by providing a quick overview of ArcUSA data Because both are stored in the same coordinate system features from 1 25M coverages and features from 1 2M coverages can be displayed together For example you might display 1 25M roads as a basic interstate highway map and simultaneously display a latitude longitude grid from a 1 2M coverage ArcUSA 1 25M has seven cartographic layers Cities County Boundaries Land Ocean Display Map Elements Rivers and Streams Roads and State Boundaries There are two 1 25M statistical attribute layers one for states and one for counties There are no index layers at this scale Attributes The attributes or items in the ArcUSA feature attribute tables contain different types of values specifically measurements codes flags and names The values contained in an attribute determine the kinds of statistical operations that can be performed on the data and influence the display of the data The four kinds of attribute values are discussed below Measurement attributes Measurement attributes have numeric values that indicate a measurement such as a number of people cows miles bushels or crimes
139. are housing characteristics These attributes are reported for both states and counties Using the Socioeconomic Attributes coverages Information about using these coverages and the other coverages containing attributes from the County and City Data Book is explained on pages 4 89 through 4 93 The Socioeconomic Attributes coverages can be used to compare U S counties or regions according to broad socioeconomic indicators such as percentage of households with female family householders Social Security recipients per 1 000 population violent crime college graduates and median household income Limited time series analysis can be done using some attributes such as percent change in number of households between 1980 and 1985 Other attributes provide statistics for a single year April 1992 4 115 Chapter 4 ArcUSA state and county statistical attribute layers Socioeconomic Attributes Summary of Socioeconomic Attributes coverages State coverage Coverage name dBASE UNIX and size MB SOC88S 1 00 1 82 Source and currency Cartography from Digital Line Graphs current to 1973 Attribute data from U S Census Bureau County and City Data Book 1988 Thematic attribute Geographic reference attributes polygons and lines groups County land area polygons Households polygons Social Security polygons Education polygons Income polygons Housing and construction polygons Labor force attributes polygons Cl
140. aries see also State Boundaries layers and County Boundaries layers and coastlines priority of coding for 4 7 4 36 and rivers 4 26 5 15 6 6 outside U S display of 4 14 4 34 5 10 Polygon attribute table explanation of columns in B 1 use of 3 4 Polygons that cross political boundaries annotation of 4 19 coding of federal land areas 4 10 coding of water bodies 4 13 Positional accuracy of database A 13 to A 14 A 19 to A 20 Processing grid suppression of 4 14 5 10 Projection systems Albers Conic Equal Area projection 1 3 3 20 4 17 conversion capability 3 21 definition of 3 2 used for ArcUSA database 1 3 3 20 Published Map Sheet Data File 3 17 Railroads layer 1 2M 4 23 to 4 26 criterion for classification 4 23 data sources for 3 15 3 16 3 17 Railroads layer 1 2M cont item definitions B 8 production procedures for A 5 to A 6 A 10 Regions and subregions defined 1 2 Regions and subregions ArcUSA data map of 1 2 Index Resolution database A 3 A 16 Restrictions on use as coding criterion 3 11 4 8 4 9 to 4 10 Rivers and political boundaries 4 26 5 15 6 6 Rivers and Streams layer 1 2M 4 26 to 4 28 see also Rivers and political boundaries drainage network how to generate using 4 26 generation of 3 15 3 17 item definitions B 8 production procedures for A 5 to A 6 A 10 to A 11 relationship to Lakes and Water Bodies layer 4 26 to 4 27 Rivers layer 1 25M 5 15 to 5 17 gene
141. arion 29 Dearborn 145 Shelby 73 Greene 123 Marshall 31 Decatur 147 Spencer 75 Grundy 125 Mason 33 De Kalb 149 Starke 77 Guthrie 127 Massac 35 Delaware 151 Steuben 79 Hamilton 129 Menard 37 Dubois 153 Sullivan 81 Hancock 131 Mercer 39 Elkhart 155 Switzerland 83 Hardin 133 Monroe 41 Fayette 157 Tippecanoe 85 Harrison 135 Montgomery 43 Floyd 159 Tipton 87 Henry 137 Morgan 45 Fountain 161 Union 89 Howard 139 Moultrie 47 Franklin 163 Vanderburgh 91 Humboldt 141 Ogle 49 Fulton 165 Vermillion 93 Ida 143 Peoria 51 Gibson 167 Vigo 95 Iowa 145 Perry 53 Grant 169 Wabash 97 Jackson 147 Piatt 55 Greene 171 Warren 99 Jasper 149 Pike 57 Hamilton 173 Warrick 101 Jefferson April 1992 C 5 Appendix C FIPS codes 103 Johnson 105 Jones 107 Keokuk 109 Kossuth 111 Lee 113 Linn 115 Louisa 117 Lucas 119 Lyon 121 Madison 123 Mahaska 125 Marion 127 Marshall 129 Mills 131 Mitchell 133 Monona 135 Monroe 137 Montgomery 139 Muscatine 141 O Brien 143 Osceola 145 Page 147 Palo Alto 149 Plymouth 151 Pocahontas 153 Polk 155 Pottawattamie 157 Poweshiek 159 Ringgold 161 Sac 163 Scott 165 Shelby 167 Sioux 169 Story 171 Tama 173 Taylor 175 Union 177 Van Buren 179 Wapello 181 Warren 183 Washington 185 Wayne 187 Webster 189 Winnebago 191 Winneshiek 193 Woodbury 195 Worth 197 Wright Kansas 1 Allen 3 Anderson 5 Atchison 7 Barber 9 Bar
142. arlottesville VA MSA Chattanooga TN GA MSA Cheyenne WY MSA Chicago IL PMSA Chicago Gary Lake County IL IL IN WI CMSA Chico CA MSA Cincinnati OH K Y IN PMSA Cincinnati Hamilton OH K Y IN CMSA Clarksville Hopkinsville TN KY MSA Cleveland OH PMSA Cleveland Akron Lorain OH CMSA Colorado Springs CO MSA Columbia MO MSA Columbia SC MSA Columbus GA AL MSA Columbus OH MSA Corpus Christi TX MSA Cumberland MD WV MSA Dallas TX PMSA Dallas Fort Worth TX CMSA Danbury CT PMSA Danville VA MSA Davenport Rock Island Moline IA IL MSA Dayton Springfield OH MSA Daytona Beach FL MSA Decatur IL MSA Denver CO PMSA Denver Boulder CO CMSA Des Moines IA MSA Detroit MI PMSA Detroit Ann Arbor MI CMSA Dothan AL MSA Dubuque IA MSA Duluth MN WI MSA Eau Claire WI MSA El Paso TX MSA Elkhart Goshen IN MSA Elmira NY MSA Enid OK MSA Erie PA MSA Eugene Springfield OR MSA Evansville IN KY MSA 2480 2520 2560 2580 2600 2640 2650 2655 2670 2680 2700 2710 2720 2750 2760 2800 2840 2880 2900 2920 2960 2975 2985 3000 3040 3060 3080 3120 3160 3180 3200 3240 3280 3282 3283 3290 3320 3350 3360 3362 3400 3440 3480 3500 Fall River MA RI PMSA Fargo Moorhead ND MN MSA Fayetteville NC MSA Fayetteville Springdale AR MSA Fitchburg Leominster MA MSA Flint MI MSA Florence AL MSA
143. as follows Codes Definitions 1 County boundary 2 State boundary 3 International boundary 4 Coastline ArcUSA User s Guide and Data Reference Government and Financial Attributes Pol ygons and lines for states Gov ec ou et wealth p_police p_welfare p_highway 7 Polygons and lines for counties Chapter 4 ArcUSA state and county statistical attribute layers Government and Financial Attributes Layer descriptions These layers contain attributes pertaining to local government financing and employment Local governments include county municipal town and township governments data for these entities are summarized to the county and state levels Some national election data are also included in these layers Using the Government and Financial Attributes coverages Information about using these coverages and the other coverages that contain attributes from the County and City Data Book is explained on pages 4 88 through 4 90 State and county information in these coverages represents a summary of the data for municipal county town and township government figures In other words the value for local government general revenue LOC_GEN_RV in a county coverage represents the county revenue plus revenue of towns and cities within the county In a state coverage LOC_GEN_RV represents the summary of the county and municipal government data for the whole state It d
144. as follows Codes Equivalents 0 No class applies Interstate highway Limited access divided highway Other U S highway Other state primary highway State secondary highway Improved road Unimproved road Parallel highway Toll road Tunnel Auto ferry OODANANMNBRWNFR p Note In this classification system the parallel highway class code 8 includes those U S minor U S and state highways that are through roads and generally within ten kilometers six miles of an interstate or other type of divided limited access highway The CLASSI 2 and 3 attributes contain the detailed road segment classification codes used in the DLG source and the DLG_CLASS1 2 and 3 attributes contain their English word equivalents CLASS1 2 or 3 priority is assigned based on the degree of multilane limited access and then by decreasing jurisdictional control interstate U S state The highest priority code is stored in CLASS1 If a road segment has no lower priority class CLASS2 and or CLASS3 contains a code of 0 As an example if a highway is an Interstate highway code 1 and an Other U S route code 16 then CLASS1 contains 1 CLASS2 contains 16 and CLASS3 contains 0 4 31 Chapter 4 ArcUSA 1 2M cartographic layers Roads A relatively small number of lines are assigned CLASS2 and CLASS3 codes Attribute Number of lines assigned codes gt 0 CLASS1 27 710 all line features in the layer CLASS2 9
145. assification attributes lines Feature Number of Polygons Coterminous states 49 features represented by 1 295 polygons plus District of Columbia Lines State and international Represented by 1 607 lines 4 boundaries shorelines 4 116 ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA state and county statistical attribute layers Socioeconomic Attributes County coverage Coverage name dBASE UNIX and size MB SOC88C 7 80 5 67 Source and currency Cartography from Digital Line Graphs current to 1988 Attribute data from U S Census Bureau County and City Data Book 1988 Thematic attribute Metropolitan area attributes polygons groups County land area polygons Plus the attribute groups listed for states above Feature Number of feat r Number of class UMDEr OF ieanures attributes Polygons Counties and 3 111 features represented by 4 409 54 independent cities of polygons coterminous United States Lines County state and Represented by 10 485 lines international boundaries shorelines The polygon and line attributes described below are present in both the state and the county coverages except where specifically noted Polygon attributes Geographic reference attributes STATE_FIPS The state FIPS code state name and U S subregion can be STATE_NAME used to select particular state or county polygons for display SUB_REGION or study The U S subregions are shown on the map in Chapter 1
146. ate Level Coverage continued Item Description Sales by Farms w 20K 25K Farms Selling 25 000 40 000 Sales by Farms w 25K 40K Farms Selling 40 000 50 000 Sales by Farms w 40K 50K Farms w 50 000 100 000 Sales by Farms w 50K 100K Farms w 100 000 250 000 Sales by Farms w 100K 250K Farms Selling 250K 500K Sales by Farms w 250K 500K Farms Selling 500 000 Sales by Farms w 500K No of Farms Selling Crops Total Value Crops Sold 1K No of Farms Selling Grain Total Value Grain Sold 1K Farms Selling Corn Value of Corn Sold 1 000 Farms Selling Wheat Value of Wheat Sold 1 000 Farms Selling Soybeans Value of Soybeans Sold 1 000 Farms Selling Sorghum Value of Sorghum Sold 1 000 Farms Selling Barley Value of Barley Sold 1 000 Farms Selling Oats Value of Oats Sold 1 000 Farms Selling Other Grains Value Other Grains Sold 1K Farms Selling Cotton Value of Cotton Sold 1 000 Farms Selling Tobacco Value of Tobacco Sold 1 000 Farms Selling Hay or Silage B 28 ltem Name dBASE Columns Begin Column Column Definition INFO Items Item Definition Begin Column S_250_500K F_OVR_500K S_OVR_500K CROPFARMS CROPSALES GRAINFARMS GRAINSALES CORNFARMS CORNSALES WHEATFARMS WHEATSALES SOYBEANFAR SOYBEANSAL SORGHMFARM SORGHMSAL BARLEYFARM BARLEYSALE OATSFARMS OATSSALES OTHGRNFARM OTHGRNSALE COTTONFARM COTTONSALE TOBACOFARM TOBA
147. atforms B aoe April 1992 B 3 Appendix B ArcUSA 1 2M cartographic layers County Boundaries CTY2M Polygon and Line Coverage Name Layer Type Polygon Attribute Table Item Description State FIPS Code County FIPS Code Combined FIPS Code State Name County Name U S Subregion Code Statistical Flag Arc Attribute Table Item Description Left State FIPS Code Right State FIPS Code Adjacent States Boundary Type Code B 4 ltem Name dBASE Columns Begin Column Column Definition INFO Items Begin Item Column Definition STATE_FIPS CNTY_FIPS FIPS STATE_NAME CNTY_NAME SUB_REGION STAT_FLAG ltem Name 3 N 0 3 N 0 6 C 0 20 C 0 32 C 0 7 C 0 1 N 0 dBASE Columns Begin Column Column Definition 3 3 INFO Items Begin Item Column Definition L_ST_FIPS R_ST_FIPS ST_NAMES BNDY_TYPE 3 N 0 3 N 0 41 C 0 11 N 0 ArcUSA User s Guide and Data Reference 3 3 3 3 41 41 C 4 5 B Appendix B ArcUSA 1 2M cartographic layers Federal Lands Coverage Name FED2M Layer Type Polygon Polygon Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Federal Land Type Code One TYPE1 1 N 0 1 1 1 Type Code One Name ADMN_TYPE1 28 C 0 Federal Land Type Code Two TYPE2 1 N 0 Type Code Two Name ADMN_TYPE2 28 C 0 Federal Land Type Code Three TYPE3 1 N 0 Type Code Three Name ADMN_TYPE3 28 C 0 Stat
148. ators in the state or county who have worked one or more days off the farm number of farm operators who have worked 200 or more days off the farm The average age of farm operators in years for the state or county Farm production expenses Total farm production expenses for the state or county in thousands of dollars Average farm production expenses per farm for the state or county in dollars 4 75 Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Inventory CATTLEFARM CATTLE BEEFFARMS BEEFCOWS MILKFARMS MILKCOWS COWSOLDFAR CATTLESOLD HOGFARMS HOGS HOGSOLDFAR HOGS_SOLD SHEEPFARMS SHEEP CHICKENFAR CHICKENS BROILSLD_F BROIL_SOLD CORNFARMS CORNACRES CORN_BU SILAGEFARM SILAGEACRE SILAGE_TON SORGHMFARM SORGHMACRE SORGHM_BU 4 76 Farm inventory attributes Number of farms in the state or county with an inventory of cattle and calves and number of cattle and calves Number of farms in the state or county with beef cows and number of beef cows Number of farms in the state or county with dairy cows and number of dairy cows Number of farms in the state or county that sold cattle and calves and number of cattle and calves sold Number of farms in the state or county with hogs and pigs number of hogs and pigs number of farms that sold hogs and pigs and number of hogs and pigs sold Number of farms in the state or county with sheep and
149. ays Harbor Island Jefferson King Kitsap Kittitas Klickitat Lewis Lincoln Mason Okanogan Pacific Pend Oreille Pierce San Juan Skagit Skamania Snohomish Spokane Stevens Thurston Wahkiakum Walla Walla Whatcom Whitman Yakima West Virginia 1 3 5 7 Barbour Berkeley Boone Braxton Brooke Cabell Calhoun Clay Doddridge Fayette Gilmer Grant Greenbrier Hampshire Hancock Hardy Harrison Jackson Jefferson Kanawha Lewis Lincoln Logan McDowell Marion Marshall Mason Mercer Mineral 59 Mingo 61 Monongalia 63 Monroe 65 Morgan 67 Nicholas 69 Ohio 71 Pendleton 73 Pleasants 75 Pocahontas 71 Preston 79 Putnam 81 Raleigh 83 Randolph 85 Ritchie 87 Roane 89 Summers 91 Taylor 93 Tucker 95 Tyler 97 Upshur 99 Wayne 101 Webster 103 Wetzel 105 Wirt 107 Wood 109 Wyoming Wisconsin 1 Adams 3 Ashland 5 Barron 7 Bayfield 9 Brown 11 Buffalo 13 Burnett 15 Calumet 17 Chippewa 19 Clark 21 Columbia 23 Crawford 25 Dane 27 Dodge 29 Door 31 Douglas 33 Dunn 35 Eau Claire 37 Florence 39 Fond Du Lac 41 Forest 43 Grant 45 Green 47 Green Lake 49 Jowa 51 Iron 53 Jackson 55 Jefferson 57 Juneau 59 Kenosha April 1992 C 15 Appendix C FIPS codes 61 Kewaunee 93 Pierce 127 Walworth 15 Goshen 63 La Crosse 95 Polk 129 Washburn 17 Hot Springs 65 La
150. be Forsyth Franklin Gaston Gates Graham Granville Greene Guilford Halifax Harnett Haywood Henderson Hertford Hoke Hyde Iredell Jackson Johnston Jones Lee Lenoir Lincoln McDowell Macon Madison Martin Mecklenburg Mitchell Montgomery Moore Nash New Hanover C 10 ArcUSA User s Guide and Data Reference Appendix C FIPS codes 131 Northampton 41 Hettinger 47 Fayette 161 Van Wert 133 Onslow 43 Kidder 49 Franklin 163 Vinton 135 Orange 45 La Moure 51 Fulton 165 Warren 137 Pamlico 47 Logan 53 Gallia 167 Washington 139 Pasquotank 49 McHenry 55 Geauga 169 Wayne 141 Pender 51 McIntosh 57 Greene 171 Williams 143 Perquimans 53 McKenzie 59 Guernsey 173 Wood 145 Person 55 McLean 61 Hamilton 175 Wyandot 147 Pitt 57 Mercer 63 Hancock 149 Polk 59 Morton 65 Hardin Oklahoma 151 Randolph 61 Mountrail 67 Harrison 1 Adair 153 Richmond 63 Nelson 69 Henry 3 Alfalfa 155 Robeson 65 Oliver 71 Highland 5 Atoka 157 Rockingham 67 Pembina 73 Hocking 7 Beaver 159 Rowan 69 Pierce 75 Holmes 9 Beckham 161 Rutherford 71 Ramsey 77 Huron 11 Blaine 163 Sampson 73 Ransom 79 Jackson 13 Bryan 165 Scotland 75 Renville 81 Jefferson 15 Caddo 167 Stanly 77 Richland 83 Knox 17 Canadian 169 Stokes 79 Rolette 85 Lake 19 Carter 171 Surry 81 Sargent 87 Lawrence 21 Cherokee 173 Swain 83 Sheridan 89 Licking 23 Choctaw 175 Transylvania 85 Sioux 91 Logan 25 Cimarron 177 Tyrrell 87 Slope 93 Lorain 27 Cleve
151. bia Cook Coweta Crawford Crisp Dade Dawson Decatur De Kalb Dodge Dooly Dougherty Douglas Early Echols 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 171 173 175 177 179 181 183 185 187 189 191 193 195 197 199 201 205 207 209 211 213 215 217 219 Effingham Elbert Emanuel Evans Fannin Fayette Floyd Forsyth Franklin Fulton Gilmer Glascock Glynn Gordon Grady Greene Gwinnett Habersham Hall Hancock Haralson Harris Hart Heard Henry Houston Irwin Jackson Jasper Jeff Davis Jefferson Jenkins Johnson Jones Lamar Lanier Laurens Lee Liberty Lincoln Long Lowndes Lumpkin McDuffie McIntosh Macon Madison Marion Meriwether Miller Mitchell Monroe Montgomery Morgan Murray Muscogee Newton Oconee 221 223 225 227 229 231 233 235 237 239 241 243 245 247 249 251 253 255 257 259 261 263 265 267 269 271 273 275 277 279 281 283 285 287 289 291 293 295 297 299 301 303 305 307 309 311 313 315 317 319 321 Idaho OANNWe Oglethorpe Paulding Peach Pickens Pierce Pike Polk Pulaski Putnam Quitman Rabun Randolph Richmond Rockdale Schley Screven Seminole Spalding Stephens Stewart Sumter Talbot Taliaferro Tattnall Taylor Telfair Terrell Thomas Tift Toombs Towns Treutlen Troup Turner Twiggs Union
152. bute layers have been standardized and are expressed as percentages Suppressed measurement values Sometimes the measurement for a particular geographic area is missing or suppressed in the database such as when low response to a survey makes it unreliable or the privacy of individuals must be protected In the four coverages containing Census of Agriculture data missing data in any of the measurement attributes are represented by negative codes such as 1 or 2 To perform statistical analyses with these attributes first select only those records that contain values greater than or equal to zero The codes follow the census designations for missing data except for the negative sign In the six coverages containing data from the County and City Data Book suppressed measurements appear as zero values This type of zero value is explained in more detail in Demographic and Health Attributes in Chapter 4 April 1992 3 9 Chapter 3 Database concepts and organization ARC INFO generated attribute Code attribute Name attribute zJ All Selected Federal Lands admn_type1 Indian reservation fed2m id typel type2 admn_type2 admn_type3 Prioritized code attributes Code attributes Code attributes have either numeric or alphabetic codes The codes are a short form for text descriptions of groups or categories In the ArcUSA database code attributes are most
153. by the DLG was retained because some federal land areas may belong to more than one category Unlike the DLG source data however ArcUSA prioritized the assignment of type codes TYPE1 TYPE2 TYPE3 The category with the most stringent restrictions on use such as scenic waterway is listed first and the category with the fewest restrictions on use such as national forest is listed last Items for state name STATE_NAMEB FIPS code STATE_FIPS and U S subregion SUB_REGION were added to enhance cartographic flexibility Items containing the name of the land type ADMN_TYPE1 ADMN_TYPE2 ADMN_TYPE3 were added as an online aid to the user Data quality review No special reviews were performed for this coverage Lakes and Other Water Bodies layer Topological edits In cases where inland water shorelines e g marshes abutted coastlines or international boundaries inland water polygons were edited to have coordinate coincidence with the boundary or coastline Attribution The complex coding structure for lakes and other water bodies in the DLG source database permitted a feature to be coded with multiple codes This coding scheme was replaced with a simpler scheme for the ArcUSA database In the new system an inland water body could only be assigned one code according to a set priority rank The DLG source data contained attributes for area and length These were eliminated because both these attributes are software generated in
154. by the direction in which that line segment was digitized so both attributes must be checked when querying for the boundaries of a particular state This attribute contains the names of states adjacent to a boundary Two states are listed for state boundaries e g Wisconsin Minnesota Only one state is identified for county and international boundaries and shorelines Classification attribute Each line is classified according to boundary type This attribute allows you to choose different symbols for political boundaries and coastlines Wherever boundaries are coincident rank is assigned beginning with coastlines in the reverse order of the list below Thus a county boundary that is also a state and international boundary will only be coded as 3 for international boundary The codes are as follows Codes Definitions 1 County boundary 2 State boundary 3 International boundary 4 Coastline Chapter 4 ArcUSA 1 2M cartographic layers Federal Lands Layer description The Federal Lands layer delimits those land areas that are administered by the federal government These include national parks monuments and recreation areas national wildlife refuges scenic waterways and wilderness areas national forests and grasslands Indian reservations and military reservations Each area contains three different attributes to describe its administrative relationships Polygons Using the Federal Lands coverage
155. by value of sales polygons Farm operators polygons Farm production expenses polygons Farm inventory attributes polygons Classification attributes lines Feature Number of Polygons Coterminous states 49 features represented by 1 295 plus District of polygons Columbia Lines State and international Represented by 1 607 lines 4 boundaries shorelines Acres harvested If two or more crops were harvested from the same land during the year the acres were counted for each crop Therefore the total number of acres of all crops harvested generally exceeds the number of acres of cropland harvested An exception is land used for hay when more than one cutting of hay was taken from the same acres the acres were counted only once but the quantity harvested includes all cuttings If a crop was planted but not harvested the acres were not reported as harvested However acres of land in fruit orchards including citrus and other groves are counted as harvested whether the crop was harvested or failed April 1992 4 71 Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Inventory County coverage Coverage name dBASE UNIX and size MB AGINC 13 11 8 33 Source and currency Cartography from Digital Line Graphs current to 1988 Attribute data from 1987 U S Census of Agriculture Table 1 Thematic attribute Same as for state level coverage above groups Feature Number of Polygo
156. ce Chapter 1 What is ArcUSA Table 3 Environ mental Attributes Government amp Financial Attributes by State Socio economic Attributes by State Features Polygons 4 409 counties Lines 10 485 county boundaries Polygons 1 295 states Lines 1 607 state boundaries Polygons 4 409 counties Lines 10 485 county boundaries Polygons 1 295 states Lines 1 607 state boundaries Polygons 4 409 counties Lines 10 485 county boundaries Polygon attributes 63 land capability land use soil orders surface mining Line attributes 4 boundary types Polygon attributes 34 Federal grants to local gov ts local gov t spending on police education highways Line attributes 4 boundary types geogr reference Polygon attributes 41 Line attributes 4 Polygon attributes 47 Social Security crime education income and poverty housing Line attributes 4 boundary types geogr reference Polygon attributes 54 Line attributes 4 ArcUSA 1 2M state and county statistical attribute layers continued Source Coverage Size MB Currency Names dBASE UNIX USGS DLG ENVIR 8 33 5 74 1988 Oak Ridge National Lab GeoEcology database 1967 1979 USGS DLG GOV88S 1973 U S Census County amp City Data Book 1988 USGS DLG SOC88S 1973 U S Census County amp City Data Book 1988 USGS DLG GOV88C 7 12 5 43 1988 U S Ce
157. ck 18 NHBLK18 11 N 0 224 4 9 B Non Hispanic Black 18 P_NHBLK18 13 N 6 228 4 5 F 2 Non Hispanic Am Ind 18 NHAMIN18 11 N 0 232 4 9 B Non Hisp Am Ind 18 P_NHAMIN18 13 N 6 236 4 5 F 2 Non Hispanic Asian 18 NHASIA18 11 N 0 4 9 B Non Hispanic Asian 18 P_NHASIA18 13 N 6 244 4 5 F 2 Non Hispanic Other 18 NHOTHE18 11 N 0 248 4 9 B Non Hispanic Other 18 P_NHOTHE18 13 N 6 252 4 5 F 2 Housing Units 1990 HSE_UNITS 11 N 0 4 9 B April 1992 B 17 Appendix B ArcUSA 1 2M state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data continued Polygon Attribute Table County Level Coverage dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition State FIPS Code County FIPS Code Combined FIPS Code State Name County Name U S Subregion Code Statistical Flag Total 1990 Population 1990 Pop per Square Mile Total White Percent White Total Black Percent Black Total American Indian Percent American Indian Total Asian Percent Asian Total Other Percent Other Total 18 Years and Older Percent 18 of Total Pop White 18 Percent White 18 Black 18 Percent Black 18 American Ind 18 Percent Amer Ind 18 Asian 18 Percent Asian 18 Other 18 Percent Other 18 Total Hispanic Percent Hispanic of Total Pop Total Non Hispanic Percent Non Hispanic B 18 STATE_FIPS CNTY_FIPS FIPS S
158. columns in a feature attribute table represent the attributes imagine the attribute names listed across the top of the table and each contains information about a row or feature imagine the features listed down the side of the table Each entry in the table contains an attribute value for a particular record feature ARC INFO generated attributes ARC INFO generated attributes are automatically created by ARC INFO and are different for each coverage type The ARC INFO generated attributes are listed in Table 1 Since the ArcUSA database was developed using ARC INFO software these attributes exist in the feature attribute tables even though they are not apparent with ArcView software Several of the ARC INFO generated attributes such as length area and perimeter provide useful information about coverage features They are all calculated in the units used for the coverage coordinate system in the ArcUSA database the Albers projection uses meters ArcUSA User s Guide and Data Reference Chapter 3 Database concepts and organization Table 1 ARC INFO generated attributes Attribute Tables Attribute Tables Attribute Tables AREA set to 0 FNODE AREA PERIMETER set to 0 TNODE PERIMETER lt coverage name gt LPOLY set to 0 if no polygons lt coverage name gt lt coverage name gt ID RPOLY setto 0 if no polygons lt coverage name gt ID LENGTH lt coverage name gt lt coverage name gt I
159. coverages are generally derived from a combination of these sources Data derived from USGS Digital Line Graphs State boundaries county boundaries rivers and roads layers were all derived from USGS 1 2 000 000 scale DLG The original data were dated 1973 although ESRI has updated the county data to 1988 DLG data are distributed in distinct thematic coverages whose extent corresponds to the National Atlas Sectional Maps a 1 2 000 000 scale hard copy map series produced by the USGS Production processes for creating the ArcUSA 1 2M data set are described in detail in the lineage section for the 1 2M data Following processing of the 1 2M coverages the data were subjected to a generalization process to create the 1 25M coverages All polygonal features less than 5 1 sq km in area were eliminated from the database No elimination of line features based on minimum length criteria was performed Lines were subjected to a coordinate generalization process using the ARC GENERALIZE command with a tolerance of 500 m Thematic simplification rules were also applied to the Roads and Rivers coverages by eliminating certain codes For example all road features were eliminated with the exception of interstate highways and interstate highway connectors After the 1 25M data were reviewed some additional features were eliminated from the most dense regions particularly in and around major metropolitan areas This last step was performed to support the effe
160. ctive cartographic display of the data River features were originally limited to the centerlines of double line features present in the original DLG data This criterion however did not result in a consistent river network As a result cartographic judgment was used to eliminate and to add features to create a more pleasing appearance and to provide a more even distribution of features across the database ArcUSA User s Guide and Data Reference April 1992 Appendix A Data quality information Data derived from ArcWorld 1 3M data The Land Ocean Display coverage is the only 1 25M coverage derived from ESRI s ArcWorld database The initial creation of this coverage was identical to the creation of the 1 2M Land Ocean Display coverage see the explanation on p A 12 These have been further generalized using the ARC GENERALIZE command with a tolerance of 500 m Additionally extraneous attribute items have been dropped to conform to the ArcUSA 1 25M database specification Data derived from U S Government tabular files The Statistical Attributes layer is a combination of the same cartography as that presented in the State and County Boundaries layers and an additional set of statistical attributes The attributes were derived from the 1 2M state and county statistical attribute layers see p A 13 The ArcUSA 1 25M version has significantly fewer attributes than the fully detailed 1 2M version Positional accuracy The positional ac
161. curacy of the ArcUSA 1 25M database is affected by the accuracy of the two primary sources of cartographic data the USGS DLGs and the ArcWorld data The accuracy of the database components that originated in the USGS DLGs can be inferred to have the same accuracy as the original plus the cumulative effects of the data processing performed by ESRI The original DLG data met the criteria for inclusion in the National Digital Cartographic Database 90 percent of a minimum of 20 tested points must be within plus or minus 005 inch 127 mm from the true correct position of the map feature as indicated on the stable base copy of the USGS source graphic The original USGS source conformed to the requirement that 90 of the well defined points tested be in error by no more than 1 30 in 0 85 mm A root sum square calculation indicates that the expected positional error of the 1 2M DLGs is 0 034 in 0 86 mm or a ground distance of 1720 m Additional ESRI processes that could introduce error include two applications of fuzzy tolerances at 50 8 m Fuzzy tolerances have the potential of offsetting lines from their original positions by the amount specified although the effects are extremely localized A 19 Appendix A Data quality information A more significant effect on positional accuracy is the use of the ARC GENERALIZE command which uses a Douglas Peuker algorithm to remove vertices along arcs The tolerance used in this command 500 m repre
162. d Number of farms in the state or county raising rice acres in rice and rice harvested in hundreds of pounds Number of farms in the state or county raising sunflowers for seed acres in sunflowers for seed and pounds of sunflower seed harvested Number of farms in the state or county raising cotton or cottonseed acres of cotton and bales of cotton harvested Number of farms in the state or county raising tobacco acres of tobacco and pounds of tobacco harvested Number of farms in the state or county raising soybeans for beans acres of soybeans for beans bushels of soybeans harvested Number of farms in the state or county raising dry edible beans excluding dry lima beans acres of dry edible beans excluding dry lima beans and dry edible beans harvested excluding dry lima beans in hundreds of pounds Number of farms in the state or county raising Irish potatoes acres of Irish potatoes and Irish potatoes harvested in hundreds of pounds 4 77 Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Inventory 4 78 SUGBEETFAR SUGBEETACR SUGBEETTON SUGCANEFAR SUGCANEACR SUGCANETON PINEAPLFAR PINEAPLACR PINEAPLTON PEANUTFARM PEANUTACRE PEANUT_LB HAYFARMS HAYACRES HAYTONS VEGFARMS VEGACRES ORCHRDFARM ORCHRDACRE m T_FIPS T_FIPS D nn ST_NAMES In the state or county number of farms raising sugar beets for sugar acres of sugar beets for s
163. d 3 111 features represented by 4 409 95 independent cities of polygons coterminous United States Lines County state and Represented by 10 485 lines international boundaries shorelines The polygon and line attributes described below are present in both the state and county coverages except where specifically noted Polygon attributes Geographic reference attributes STATE FIPS The state FIPS code state name and U S subregion can be STATE_NAME used to select particular state or county polygons for display SUB_REGION or study The U S subregions are shown on the map in Chapter 1 4 82 ArcUSA User s Guide and Data Reference CNTY_FIPS FIPS CNTY_NAME STAT_FLAG SALESFARMS SALES_1K AVG_SALES FARM_UND1K SALE_UND1K F_1K_2500 S_1K_2500 F_2500_5K S_2500_5K FARM_5_10K SALE_5_10K F_10_20K S_10_20K F_20_ 25K S_20_25K Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Market Value These geographic reference attributes appear only in the county level coverages The county polygon coverages contain the county FIPS code the combined state and county FIPS code and the county name Statistical flag Flag to identify a unique polygon for each state or county The codes are as follows Codes Definitions O Other polygon 1 Largest polygon General agricultural product sales The total number of farms in the state or county that sold agricultural produc
164. d MSA CMSA FIPS code This attribute is blank for counties that are not included in an MSA or CMSA and for MSA counties in New England Primary Metropolitan Statistical Area PMSA FIPS code In general a PMSA is a county that contains a city of over 100 000 population County land area This attribute appears only in the county level coverage The land area of the county in 1980 Land area excludes the areas of water bodies The value in this item is measured in square miles 5 27 Chapter 5 The ArcUSA 1 25M layers Statistical Attributes BIRTHS_84 NET_MIGR P_UNDER_5 P_5 14 P_15_24 P_25 34 P_35_ 44 P_45 54 P_55_ 64 P_65_74 P_OVER_74 POP1984 PERS_HHLD MARRIAG_1K HBBDS_1000 SSRECIP_1K SR_CR_100K 5 28 Demographic attributes Number of births in the state or county during 1984 Net migration in or out of the state or county from 1980 to 1986 This value represents the difference between the number of persons moving into an area and the number of persons moving away from the area A negative value indicates net outmigration from the area Percentage of the state or county population between a given age range in 1984 For example P_5_14 is the percentage of population between 5 and 14 years of age Total state or county population in 1984 This value was used to compute 1984 race and age population percentages Average number of persons per household in the state or count
165. d code Polygon attributes 1 area fill code Line attributes 0 Point attributes 10 feature name type elevation geogr reference Line attributes 5 railroad line class state name FIPS subregion Line attributes 5 river type name state name FIPS subregion Line attributes 22 road classes route numbers geogr reference Polygon attributes 4 state name Line attributes 4 boundary type geogr reference Source Currency USGS Digital Line Graphs DLG 1988 Coverage Names LAK2M LAK2M_N LAK2M_S LAK2M_W ESRI ArcWorld 1992 ESRI 1992 USGS Concise Digital Database 1973 LAND2M USGS DLG 1979 USGS DLG 1973 USGS DLG 1980 USGS DLG 1973 1 4 ArcUSA User s Guide and Data Reference Chapter 1 What is ArcUSA Table 2 ArcUSA 1 2M index layers Landsat Nominal Scene Index Latitude Longitude Grids USGS 1 24 000 Topographic Quadrangle Series Index USGS 1 100 000 Topographic Quadrangle Series Index USGS 1 250 000 Topographic Quadrangle Series Index Features Point attributes 15 path row states covered lat long of point Points 702 scene center points Line attributes 15 path row states covered lat long of footprint Lines 702 scene coverages Line attributes 3 latitude longitude U S or non U S code Lines 1 225 2 by 2 degree grid Lines 314 5 by 5 degree grid Lines 134 10 by 10 de
166. data sources for 3 15 3 16 3 17 item definitions B 6 production procedures for A 5 to A 6 A 9 relationship to Rivers and Streams layer 4 26 to 4 27 Land Ocean Display layer 1 2M 4 14 to 4 16 generation of 3 16 3 19 A 12 item definitions B 6 April 1992 Index 3 Index Land Ocean Display layer 1 25M 5 10 to 5 12 generation of 3 16 3 19 item definitions B 47 Land use classification coding for 4 8 4 10 Landsat Nominal Scene Index layer 1 2M 4 39 to 4 4 generation of 3 17 to 3 18 item definitions B 11 to B 12 relationship to Thematic Mapper and Multispectral Scanner data 4 39 Latitude longitude grids See also Latitude Longitude Grids layer display in foreground and background polygons 4 42 relationship of grid interval to map scale 4 42 use with USGS topographic map sheet grids 4 42 Latitude Longitude Grids layer 1 2M 4 42 to 4 44 generation of 3 19 item definitions B 12 Layer see also ArcUSA 1 2M data layers ArcUSA 1 25M data layers definition of 3 5 Layer summary tables 1 3 to 1 9 Line definition of 3 1 3 3 Line feature table B 2 Logical consistency See Data quality review procedures Logical expression 2 8 2 10 MSA Metropolitan Statistical Area defined 4 91 4 92 4 93 Map Elements layer 1 2M 4 17 to 4 18 generation of 3 19 item definitions B 7 Map Elements layer 1 25M 5 13 to 5 14 generation of 3 19 item definitions B 48 Measurement attributes 3 8 to 3 9 I
167. deral tobacco subsidies 1987 Areas affected by potential Total Disturbed Land Environmental reclamation of mines Disturbed Land Attributes Planning access to Land in Sand Gravel Extraction Environmental materials for massive Land in Sand Gravel Extract Attributes highway construction Potential sites for mining Land Area in Histosol Soils Environmental peat Land Area in Histosol Soils Attributes 2 21 Chapter 3 Database concepts and organization This chapter defines several basic database terms and explains how the ArcUSA database is organized The standards and procedures employed during the development of the database are discussed and the sources for the ArcUSA data are described The information in this chapter applies to all components of the database so it may be helpful to read this chapter before reading Chapters 4 and 5 which contain a detailed descriptions of each data layer Concepts and terms A map is a graphic display of spatially distributed elements called map features which correspond to real world geographic entities These real world entities are located spatially on maps by means of points lines and areas e Points define discrete locations on a map for geographic phenomena that are too small to be depicted as lines or areas such as well locations telephone poles and buildings Points can also represent locations that have no area such as mountain peaks In the ArcUSA database points are
168. des are as follows Codes Definitions 1 County boundary 2 State boundary 3 International boundary 4 Coastline 4 79 Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Market Value farm une Polygons and lines for states Polygons and lines for counties Layer descriptions The state and county Agricultural Product Market Value layers contain statistical data about the market value of various agricultural products including the number of farms reporting sales of given products and the sales value of those products Products range from grains to cash crops from poultry to mutton The previous layer Agricultural Product Inventory focuses on the amount of crops or the number of animals raised but not necessarily sold Using the Agricultural Product Market Value coverages Some of the attributes in these layers have the same name as attributes in the Agricultural Product Inventory layer but contain a slightly different statistic For example in this layer COTTONFARM contains the number of farms that sold cotton in 1987 in the Agricultural Product Inventory layers COTTONFARM contains the number of farms that raised cotton An attribute containing a negative number indicates that no data exist or that data were suppressed for that particular geographic unit Lack of data may result from a number of situations such as the sup
169. duct Market Value 4 80 Demographic and Health Attributes 4 89 Environmental Attributes 4 100 Government and Financial Attributes 4 107 Socioeconomic Attributes 4 115 Chapter 5 The ArcUSA 1 25M layers 5 1 Cities 5 3 County Boundaries 5 6 Land Ocean Display 5 10 Map Elements 5 13 Rivers 5 15 Roads 5 18 State Boundaries 5 20 Statistical Attributes 5 23 vi ArcUSA User s Guide and Data Reference April 1992 Chapter 6 Appendix A Appendix B Appendix C Appendix D Appendix E Index Using the database Optimizing performance Working with attributes Drawing with ArcUSA Database quality information ArcUSA 1 2M data Summary of ArcUSA 1 2M characteristics Lineage Data derived from USGS Digital Line Graphs Data derived from ESRI ArcWorld 1 3M data Index coverages Data derived from U S Government tabular files Positional accuracy Attribute accuracy Logical consistency Completeness ArcUSA 1 25M data Summary of ArcUSA 1 25M characteristics Lineage Data derived from USGS Digital Line Graphs Data derived from ArcWorld 1 3M data Data derived from U S Government tabular files Positional accuracy Attribute accuracy Logical consistency Completeness ArcUSA item definitions Federal Information Processing Standards FIPS codes Bibliography Other data sources Contents I I ere MANWN e E I I p pb p ph ph OOOoO OWMONADN Mn BBW YW NN PPP PPRPP PPPE Pry P NON w an C 1 E 1
170. e 105 Potter 107 Schuylkill 109 Snyder 111 Somerset 113 Sullivan 115 Susquehanna 117 Tioga 119 Union 121 Venango 123 Warren 125 Washington 127 Wayne 129 Westmoreland 131 Wyoming 133 York Rhode Island 1 Bristol 3 Kent 5 Newport 7 Providence 9 Washington South Carolina 1 Abbeville 3 Aiken 5 Allendale 7 Anderson 9 Bamberg 11 Barnwell 13 Beaufort 15 Berkeley 17 Calhoun 19 Charleston 21 Cherokee 23 Chester 25 Chesterfield 27 Clarendon 29 Colleton 31 Darlington 33 Dillon 35 Dorchester 37 Edgefield 39 Fairfield 41 Florence 43 Georgetown 45 Greenville 47 Greenwood 49 Hampton 51 Horry 53 Jasper 55 Kershaw 57 Lancaster Laurens Lee Lexington McCormick Marion Marlboro Newberry Oconee Orangeburg Pickens Richland Saluda Spartanburg Sumter Union Williamsburg York South Dakota Aurora Beadle Bennett Bon Homme Brookings Brown Brule Buffalo Butte Campbell Charles Mix Clark Clay Codington Corson Custer Davison Day Deuel Dewey Douglas Edmunds Fall River Faulk Grant Gregory Haakon Hamlin Hand Hanson Harding Hughes Hutchinson Hyde Jackson Jerauld Jones Kingsbury Lake C 12 ArcUSA User s Guide and Data Reference Appendix C FIPS codes 81 Lawrence 83 Lincoln 85 Lyman 87 McCook 89 McPherson 91 Marshall 93 Meade 95 Mellette 97 Miner 99 Minnehaha 101 Moody 103 Pennington 105 Perkins 107 Potter 109 Roberts 111 Sanborn 113
171. e FIPS Code STATE_FIPS 3 N 0 State Name STATE_NAME 20 C 0 U S Subregion Code SUB_REGION 7 C 0 April 1992 B 5 Appendix B ArcUSA 1 2M cartographic layers Lakes and Other Water Bodies Coverage Names LAK2M LAK2M_N LAK2M_S LAK2M_W Layer Type Polygon Polygon Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Waterbody Classification Code TYPE 1 N 0 1 1 1 Waterbody Code Name WATER_TYPE 25 C 0 State FIPS Code STATE_FIPS 3 N 0 State Name STATE_NAME 20 C 0 U S Subregion Code SUB_REGION 7 C 0 Land Ocean Display Coverage Name LAND2M Layer Type Polygon and Line Polygon Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Land Water Identifier LND_WAT 49 5 C 0 17 5 5 C Annotation Includes country water body and other major place names Arc Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Feature Grid Identifier BND_GRID 80 1 N 0 29 1 1 B 6 ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 2M cartographic layers Map Elements Coverage Name SC_2M Layer Type Polygon and Line Polygon Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definit
172. e Soto East Baton Rouge East Carroll East Feliciana Evangeline Franklin Grant Iberia Iberville Jackson Jefferson Jefferson Davis Lafayette LaFourche La Salle Lincoln Livingston Madison Morehouse Natchitoches Orleans Ouachita Plaquemines Pointe Coupee Rapides Red River Richland Sabine St Bernard St Bernard St Charles St Helena St James St John the Baptist St Landry St Martin St Mary St Tammany Tangipahoa Tensas Terrebonne Union Vermilion Vernon Washington Webster West Baton Rouge West Carroll West Feliciana Winn Maine 1 Androscoggin 3 Aroostook 5 Cumberland 7 Franklin 9 Hancock 11 Kennebec 13 Knox 15 Lincoln 17 Oxford 19 Penobscot 21 Piscataquis 23 Sagadahoc 25 Somerset 27 Waldo 29 Washington 31 York Maryland 1 Allegany 3 Anne Arundel 5 Baltimore 9 Calvert 11 Caroline 13 Carroll 15 Cecil 17 Charles 19 Dorchester 21 Frederick 23 Garrett 25 Harford 27 Howard 29 Kent 31 Montgomery 33 Prince George s 35 Queen Anne s 37 St Mary s 39 Somerset 41 Talbot 43 Washington 45 Wicomico 47 Worcester 510 Baltimore City Massachusetts 1 Barnstable 3 Berkshire 5 Bristol 7 Dukes 9 Essex 11 Franklin 13 Hampden 15 Hampshire 17 Middlesex 19 Nantucket 21 Norfolk 23 Plymouth 25 Suffolk 27 Worcester Michigan 1 Alcona 3 Alger 5 Allegan 7 Alpena 9
173. e attributes contain the FIPS codes for the states the quadrangle covers up to four The FIPS codes are always stored beginning with ST_FIPS1 but the states are not listed in any particular order For a complete listing of state FIPS codes see Appendix C If a quadrangle covers fewer than four states one or more attributes contain a blank The names of the states the quadrangle covers are stored in these attributes The state names are always stored beginning with ST_NAME1 but they are not listed in any particular order If a quadrangle covers fewer than four states one or more attributes contain a blank Note that the information in the ST_NAME attributes is derived from the published map sheets and not from the quadrangle boundaries in this index Therefore if there is any discrepancy between the information conveyed by the ST_NAME attributes and by a display of the quadrangle 4 49 Chapter 4 ArcUSA 1 2M index layers USGS 1 24 000 Topographic Quadrangle Series 4 50 ST1_SQ_MI ST2_SQ_MI ST3_SQ_MI ST4_SQ_MI TOT_Q_SQMI DATE_REV DATE_PUB PHOTO_R_DT index as to which states are covered by a given map sheet the information conveyed by the ST_NAME attributes should be considered more accurate The area of the states represented by the quadrangle expressed in square miles If a quadrangle covers fewer than four states one or more attributes are blank The total area represented by the quadrangle expressed
174. e names of many coastal parks and recreation areas draw to the screen Notice that there are several large coastal parks that might require evacuation if a large storm came in off the ocean 4 Click off the check boxes to the left of Parks and County Seats 5 Click on the check box to the left of 1990 Population A thematic map representing 1990 population draws in the graphic display You might want to select the Show Legend option from the theme specific menu for the themes as they are drawn 2 16 ArcUSA User s Guide and Data Reference Chapter 2 Exploring the ArcUSA database 6 Click on the check box to the left of the theme for Doctors per 100K People The symbol for this variable is a pattern that draws over the shades l that represent 1990 population The relationship between population and number of Notice that there are five counties doctors per 100 000 people can be compared by in the highest population range using the bivariate mapping technique with a high number of doctors per 100 000 people 7 Click off the check box to the left of Doctors per 100K People 8 Click on the check box to the left of the theme for Hospital Beds per 1000 People The symbol for this variable is also a pattern that draws over the population variable Notice that On your own there are three counties in the You may use the Identify tool from the Palette to gain high
175. eans of selecting a small multistate area for display or study These state groups are the same as the Census Bureau s except that the Census Bureau considers New England to be a fourth major region instead of a subregion The ArcUSA 1 25M data set is for the full extent of the coterminous United States only It can function as a stand alone database or as a complement of the ArcUSA 1 2M database ArcUSA User s Guide and Data Reference April 1992 Chapter 1 What is ArcUSA The ArcUSA database you have licensed may contain either of the following data sets e ArcUSA 1 2M Full Extent plus ArcUSA 1 25M e ArcUSA 1 25M The ArcUSA 1 2M data are delivered in two coordinate systems the Albers Conic Equal Area projection in meters and geographic coordinates latitude longitude in decimal degrees The ArcUSA 1 25M data are delivered only in the Albers Conic Equal Area projection ArcUSA database layer summary tables The four tables that begin on the next page summarize the ArcUSA database Tables 1 through 3 describe the 1 2M cartographic index and statistical attribute layers coverage names are listed for the entire United States as well as for the three regions Regional coverage names end in N for north S for south and W for west Table 4 describes the 1 25M layers The coverage sizes in the tables are approximate In UNIX format some information is stored in a separate directory so the overall database sizes listed
176. ent Rate 1986 Arc Attribute Table Item Description Left State FIPS Code Right State FIPS Code Adjacent States Boundary Type Code Note The state level and county level AATs are identical ltem Name dBASE Columns Column Definition Begin Column INFO Items Begin Column Item Definition P_POVERTY POV_STATUS P_FAM_POV FAMILYHHLD HSE_UNITS P_CHG_HSE OCCUP_HSE P_OWN_OCC P_2CAR_OCC OCC_SAMPLE MEDIAN_DOL PERMIT_86 PRMT_80_86 P_PERMITS CIVLABOR86 P_CHG_CIV CIV_UNEMP UNEMP_RATE ltem Name 457 470 481 494 505 516 529 540 13 N 6 11 N 0 13 N 6 11 N 0 11 N 0 13 N 6 11 N 0 13 N 6 13 N 6 11 N 0 11 N 0 11 N 0 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 dBASE Columns Begin Column Column Definition 223 227 231 235 239 243 247 251 255 259 263 267 271 275 279 283 287 291 4 6 F 1 4 9 B 4 6 F 1 4 9 B 4 8 B 4 6 F 1 4 8 B 4 6 F 1 4 6 F 1 4 8 B 4 6 B 4 7 B 4 7 B 4 6 F 1 INFO Items Begin Column Item Definition L_ST_FIPS R_ST_FIPS ST_NAMES BNDY_TYPE 80 83 86 127 3 N 0 3 N 0 41 C 0 11 N 0 29 32 35 76 3 3 3 3 41 41 C 4 5 B April 1992 B 45 Appendix B ArcUSA 1 25M layers Cities Coverage Name CITIES Layer Type Point Point Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Name of Feature
177. ent Rural Land Area P_RUR_LND 226 13 N 6 Total Urban Land Area 1977 URB_LND 11 N 0 Percent Urban Land Area P_URB_LND 13 N 6 Census Water Area 1977 WATER 11 N 0 Percent Water Area P_WATER 13 N 6 Soils with No Limitations SOILS_OK 11 N 0 Soils with No Limitations P_SOILS_OK 13 N 6 Soils with Some Limitations SL_SMLTS 11 N 0 Soils with Some Limitations P_SL_SMLTS 13 N 6 Soils with Severe Limitations SL_SVLTS 11 N 0 Soils with Severe Lmts P_SL_SVLTS 13 N 6 Soils with Very Severe Lmts SL_VSLTS 11 N 0 Soils w Very Severe Lmts P_SL_VSLTS 13 N 6 Soils Level but Wet Stoney SL_WET 11 N 0 Soils Level but Wet Stony P_SL_WET 13 N 6 Soil for Range Forest etc SL_RANGE 11 N 0 Soil for Range Forest etc P_SL_RANGE 13 N 6 continued April 1992 B 37 Appendix B ArcUSA 1 2M state and county statistical attribute layers Environmental Attributes continued Polygon Attribute Table continued Item Description Soil for Forest Wildlife Soil for Forest Wildlife Soil Not Good for Cultivation Soil Not Good for Cult Total Disturbed Land Percent Disturbed Land Land in Coal Mines Percent Land in Coal Mines Land in Sand Gravel Extraction Land in Sand Gravel Extr Land in Other Mines Percent Land in Other Mines Alfisol Percent Alfisol Aridisol Percent Aridisol Entisol Percent Entisol Histosol Percent Histosol Inceptisol Percent Inceptisol Mollisol Percent Mollisol Spodosol Percent S
178. entify the states that gained the most people April 1992 2 5 Chapter 2 Exploring the ArcUSA database 8 Click on the net_migr attribute 10 in the table and select Statistics Use the scroll bar to scroll right to the appropriate section of the table After Statistics for net_migr is selected a window pops up that displays the count sum minimum maximum and mean values for the specified attribute both for all records contained in the layer and records specific to the selected set The sum is not equal to zero because this attribute reflects not only migration from other states but also migration from other countries Within this statistics window you ll see that the maximum net migration from 1980 to 1986 was 1 778 000 Click Dismiss Enlarge the table window so that the state_name and net_migr attributes are contained within the window area California gained 1 778 000 as a result of net migration from 1980 to 1986 Move the table down below the graphic display prior to continuing EG Net Migration 1980 86 by state net_migr gt 500000 TEN EJ Ai stat_flay births_ net_migr _under_5 p_5_14 p_15_24 Statistics When you set the stat_flag attribute equal to 1 the proper total values display in the Statistics window 7 Net Migration 1980 86 by state Al Al ry ad ATOKA etmy sow stats_s id state_fips state_name
179. er 4 In greater detail The ArcUSA 1 2M layers This chapter describes the individual coverages in the ArcUSA 1 2M database To avoid repetition all coverages that belong to the same layer are described together since coverages in the same layer have the same feature and attribute definitions As outlined in Chapter 3 the layer descriptions are presented in three major groups cartographic index and statistical attribute Within each group the layers are listed in alphabetical order The description of each layer begins with a discussion of the map features and attributes in that layer The discussion continues with information about the use of the coverages in that layer Then a tabular summary of the layer is given The table lists the individual coverage names coverage feature classes map feature counts for the full U S coverage and the number of database attributes associated with each feature class The last part of the layer description usually the longest defines the individual attributes that appear in the coverage feature attribute tables and the coding schemes associated with the attributes The summary tables for ArcUSA 1 2M layers may list four coverage names for each layer These coverage names correspond to the full U S coverage and each of the three U S regional coverages The standard ARC INFO generated attributes described in Chapter 3 do not appear nor are they included in the attribute count in the layer s
180. erious Crimes 100 000 Pop SR_CR_100K 11 N 0 Persons with 4 Yrs College P_COL_GRAD 13 N 6 Income per Capita 1985 INC_CAP_85 11 N 0 Median Housing Unit Value MEDIAN_DOL 11 N 0 Federal Funds and Grants 1986 FEDFUNDGRT 13 N 6 Local Taxes Capita 1981 82 TAX _CAP 11 N 0 Local Gov t Empl 10K Pop LG_EMP_10K 13 N 6 Votes Cast for President 1984 PRESVOTE84 11 N 0 Total Population 1990 POP1990 11 N 0 Population Square Mile 1990 TOTAL_SQMI 13 N 6 Percent White 1990 P_WHITE 13 N 6 4 6 F 2 Percent Black 1990 P_BLACK 13 N 6 4 5 F 2 Percent American Indian 1990 P_AMERIND 13 N 6 4 5 F 2 Percent Asian 1990 P_ASIAN 13 N 6 4 5 F 2 Percent Other Race 1990 P_OTHER 13 N 6 4 5 F 2 continued B 52 ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 25M layers Statistical Attributes continued Polygon Attribute Table County Level Coverage continued dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Acres of Farmland FARM_ACRES 549 11 N 0 249 4 11 B Average Size of Farm in Acres AVG_SIZE 560 11 N 0 253 4 11 B Cropland in Acres CROP_ACRES 571 11 N 0 257 4 11 B Irrigated Land in Acres IRRIGATE_A 582 11 N 0 261 4 11 B Ag Products Sold 1 000 SALES_1K 593 11 N 0 265 4 11 B Average Sales per Farm AVG_SALES 604 11 N 0 269 Soil Not Good for Cult P_SL_NO_AG 615 13 N 6 273 Disturbed Land P_DIST_LND 628 13 N 6 277 Arc Attribute T
181. erosion potential shallowness salinity low fertility or excess water 4 103 Chapter 4 ArcUSA state and county statistical attribute layers Environmental Attributes 4 104 SL_VSLTS P_SL_VSLTS SL_WET P_SL_WET SL_RANGE P_SL_RANGE SL_WILD P_SL_WILD SL_NO_AG P_SL_NO_AG DIST_LND P_DIST_LND COAL_MNS P_COAL_MNS Soils with very severe limitations restricting land use These soils are generally capable of producing cultivated crops Limitations may include dryness high erosion potential shallowness salinity low fertility or excess water Soils that are generally level but wet or stony These soils are generally capable of sustaining managed natural vegetation Other limitations may include dryness for stony soils high erosion potential shallowness salinity or low fertility Soils that are suitable for rangeland forest or other managed natural vegetation These soils are generally capable of sustaining managed natural vegetation Limitations may include dryness wetness high erosion potential shallowness salinity or low fertility Soils most suitable for forest or wildlife habitat Generally these soils are not appropriate for cultivated crops or managed natural vegetation Limitations may include dryness high erosion potential shallowness salinity low fertility or excess water Soils where cultivation is precluded Land surface mining Total land area in hectares and percentage of
182. es continued Polygon Attribute Table County Level Coverage dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition State FIPS Code County FIPS Code Combined FIPS Code State Name County Name U S Subregion Code Statistical Flag County Type Code Metro Statistical Area Code Consolidated MSA Code Land Area of the County Total Households 1985 Change Households 80 85 Persons per Household 1985 Total Households 1980 Households w Female Head One Person Households Soc Security Recipients 1985 Soc Sec Recips 1 000 Pop Soc Sec Payments 1985 1K Supplemental Sec Recip 86 Serious Crimes 1985 Violent Crimes 1985 Serious Crimes per 100K Pop Public School Enrollment 86 Public School Enrollment 80 Pop with High School Educ Pop with 4 Yrs College Persons 25 Years of Age Local Gov t Educ Spending Per Capita Education Spending Income per Capita 1985 County Rank Income Capita Income per Capita 1979 Income Capita 79 Constant Median Household Income 79 B 44 STATE_FIPS CNTY_FIPS FIPS STATE_NAME CNTY_NAME SUB_REGION STAT_FLAG CNTY_TYPE MET_ST_AR PR_MT_ST_A LAND_AREA HSEHOLD_85 P_CHG_HHLD PERS _HHLD HSEHOLD_80 P_FEM_HHLD P_1PER_ HH SSEC_RECIP SSRECIP_1K SSPAYMT_IK SUPP_RECIP SERIOUS_CR VIOLENT_CR SR_CR_100K PUPILS86 PUPILS80 P_HS_GRADS P_COL_GRAD AGE_25_UP ED_DOL_1M
183. es ST2M and CTY2M The state and county statistical attribute layers are listed on the next page April 1992 4 59 Chapter 4 ArcUSA state and county statistical attribute layers State and county statistical attribute layers ayer 1990 U S Census Public Law POP90S 94 171 Data by State 1990 U S Census Public Law POP90C 94 171 Data by County Agricultural Product Inventory AGIN_S by State Agricultural Product Inventory AGIN_C by County Agricultural Product Market AGVL_S Value by State Agricultural Product Market AGVL_C Value by County Demographic and Health POP88S Attributes by State Demographic and Health POP99C Attributes by County Environmental Attributes ENVIR by County Government and Financial GOV88S Attributes by State Government and Financial GOV88C Attributes by County Socioeconomic Attributes SOC88S by State Socioeconomic Attributes SOC88C by County 4 60 ArcUSA User s Guide and Data Reference 1990 U S Census Public Law 94 171 Data Polygons and lines for states pop1990 _ pop30 56464 0195 Al 64175 38341 Polygons and lines for counties Chapter 4 ArcUSA state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data Layer descriptions The coverages in the state and county 1990 U S Census Public Law 94 171 Data layers contain state or county population statistics from the 1990 Cen
184. est population range with a more information about a county or feature high number of hospital beds per Remember to highlight the theme you would like to 1 000 people query by clicking on the theme name once within the Table of Contents 9 Click off the check box to the left of the themes for Hospital Beds per 1000 People and 1990 Population April 1992 2 17 Chapter 2 Exploring the ArcUSA database 10 11 12 13 Click on the check box to the left of the Roads and Railroads themes Evaluate the transportation network for routes out of the coastal area should an evacuation become necessary Click off the check box for the Roads and Railroads themes Click on the check box to the left of the Rivers theme This information is useful for determining which areas might be prone to flooding in the event of a large oceanic storm Click off the check box to the left of the Rivers theme The coastal transportation network is symbolized using the simplified road classes for more information on the road_class attribute see Chapter 4 The Digital Line Graph classifications carried in the dig_class attributes offer alternatives for symbolizing the roads network A map of coastal rivers and estuaries You may draw the Rivers theme with the two transportation themes to evaluate the probability of flooding on or near transp
185. f a boundary are defined by the direction in which that line segment was digitized so both attributes must be checked when querying for boundaries of a particular state This attribute contains the names of states on both sides of a boundary Two states are listed for state boundaries e g Wisconsin Minnesota Only one state is identified for county and international boundaries and shorelines ArcUSA User s Guide and Data Reference April 1992 BNDY_TYPE Chapter 5 The ArcUSA 1 25M layers County Boundaries Classification attribute Each line is classified according to boundary type This attribute allows you to choose unique symbols for different political boundaries and coastlines Wherever boundaries are coincident rank is assigned in the reverse order of the list below beginning with coastlines Thus a county boundary that is also a state and international boundary will only be coded as 3 for international boundary The codes are as follows Codes Definitions 1 County boundary 2 State boundary 3 International boundary 4 Coastline 5 9 Chapter 5 The ArcUSA 1 25M layers Land Ocean Display Polygons Layer description Land and water areas beyond the extent of the other ArcUSA cartographic layers are contained in the Land Ocean Display layer Canada Mexico the Atlantic and Pacific oceans and each of the Great Lakes can be displayed and labeled to create a finished looking map Using t
186. f the group The flag allows a single polygon to be selected so that the state or county name will appear only once in a display The flag also allows attribute values to be added correctly The same attribute values are stored for every polygon that composes the political entity Ifa state is represented by four polygons the same attribute record is coded for each of the four polygons Unless data are selected using STAT_FLAG statistical operations in the software will return a total population for example for that state four times the true population figure First selecting only the flagged polygons will result in the correct statistic Data export Attribute data from ArcUSA may be downloaded into other software programs like spreadsheets or database management systems where charts graphs and other graphic displays can be generated ArcView users can save a selected tabular data set to a file by clicking on the save the table as a file icon at the top of a Theme Table A dialog box appears that you can use for navigating to a directory into which you can write the file By default ArcView saves a tab separated ASCII file You can change this setting by choosing Preferences in the File menu See Chapter 3 in the ArcView User s Guide for more information on saving tabular data A list of Windows software for use with ArcUSA appears in Table 1 This list of software is included to illustrate the types of packages with which ArcView for W
187. fayette 97 Portage 131 Washington 19 Johnson 67 Langlade 99 Price 133 Waukesha 21 Laramie 69 Lincoln 101 Racine 135 Waupaca 23 Lincoln 71 Manitowoc 103 Richland 137 Waushara 25 Natrona 73 Marathon 105 Rock 139 Winnebago 27 Niobrara 75 Marinette 107 Rusk 141 Wood 29 Park 77 Marquette 109 St Croix 31 Platte 78 Menominee 111 Sauk Wyoming 33 Sheridan 79 Milwaukee 113 Sawyer 1 Albany 35 Sublette 81 Monroe 115 Shawano 3 Big Horn 37 Sweetwater 83 Oconto 117 Sheboygan 5 Campbell 39 Teton 85 Oneida 119 Taylor 7 Carbon 41 Uinta 87 Outagamie 121 Trempealeau 9 Converse 43 Washakie 89 Ozaukee 123 Vernon 11 Crook 45 Weston 91 Pepin 125 Vilas 13 Fremont Metropolitan area FIPS codes A 0845 Beaver County PA PMSA 0040 Abilene TX MSA 0860 Bellingham WA MSA 0080 Akron OH PMSA 0870 Benton Harbor MI MSA 0120 Albany GA MSA 0875 Bergen Passaic NJ PMSA 0160 Albany Schenectady Troy NY MSA 0880 Billings MT MSA 0200 Albuquerque NM MSA 0920 Biloxi Gulfport MS MSA 0220 Alexandria LA MSA 0960 Binghamton NY MSA 0240 Allentown Bethlehem PA NJ MSA 1009 Birmingham AL MSA Easton PA 1010 Bismarck ND MSA 0280 Altoona PA MSA 1020 Bloomington IN MSA 0320 Amarillo TX MSA 1040 Bloomington Normal IL MSA 0360 Anaheim Santa Ana CA PMSA 1080 Boise City ID MSA 0380 Anchorage AK MSA 1120 Boston MA PMSA 0400 Anderson IN MSA 1122 Boston Lawrence Salem MA NH CMSA 0405 Anderson SC MSA 1123 Bosto
188. ffalo e Baltimore City County Md e Philadelphia County Pa Note that the nine counties that lost the highest number of people because of net migration from 1980 to 1986 were all metropolitan counties within the Rust Belt In the following steps you will examine the attributes for loser and gainer counties that represent potential factors in the negative growth of urban counties and the positive growth of suburban counties 2 10 ArcUSA User s Guide and Data Reference Chapter 2 Exploring the ArcUSA database 7 Use the Zoom to Box tool from the palette to zoom in on the area around Philadelphia Pennsylvania ME 7 L R2E RE ead Philadelphia 8 Click once on Net Migration 1980 86 by County within the Table of Contents to highlight the theme 9 Using the Identify tool from the palette click once on Philadelphia Pennsylvania A pop up window containing various attributes contained within the stats_c coverage appears for this loser county 10 Using the Identify tool again click once on Montgomery County Pennsylvania This county which borders Philadelphia to the west is a gainer county 11 Scroll down to the attribute net_migr in both pop up windows Notice that Philadelphia lost 78 400 people due to net migration during 1980 86 Montgomery County gained 13
189. fication attributes lines Feature Number of Polygons Coterminous states 49 features represented by 1 295 57 plus District of polygons Columbia Lines State and international Represented by 1 607 lines 4 boundaries shorelines 4 62 ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data County coverage Coverage name dBASE UNIX and size MB POP90C 8 17 5 69 Source and currency Cartography from Digital Line Graphs current to 1988 Attribute data from 1990 U S Census Thematic attribute Same as for state level coverage above groups Feature Number of Polygons Counties and 3 111 features represented by 4 409 independent cities of polygons coterminous United States Lines County state and Represented by 10 485 lines international boundaries shorelines The polygon and line attributes described below are present in both the state and the county coverages except where specifically noted Polygon attributes Geographic reference attributes STATE FIPS The state FIPS code state name and U S subregion can be STATE_NAME used to select particular state or county polygons for display SUB_REGION or study The U S subregions are shown on the map in Chapter 1 April 1992 4 63 Chapter 4 ArcUSA state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data 4 64 CNTY_FIPS FIPS CNTY_
190. for MSA counties in New England If a county is also considered a Primary Metropolitan Statistical Area the attribute PR_MT_ST_A contains the PMSA FIPS code A complete listing of metropolitan areas and their FIPS codes is given in Appendix C Using the Demographic and Health Attributes coverages These coverages can be used to explore recent population changes at the county and state levels Information about migration births deaths and other vital statistics is 4 93 Chapter 4 ArcUSA state and county statistical attribute layers Demographic and Health Attributes contained here Also broad health indicators such as the number of doctors and health care facilities by state and county can be found in these coverages In conjunction with the Socioeconomic Attributes coverages relationships between population change components and social and economic indicators such as crime occurrence or percentage of unemployment can be analyzed The polygon and line attributes described below are present in both the state and county coverages except where specifically noted Polygon attributes Geographic reference attributes STATE FIPS The state FIPS code state name and U S subregion can be STATE_NAME used to select particular state or county polygons for display SUB_REGION or study The U S subregions are shown on the map in Chapter 1 These geographic reference attributes appear only in the county level coverages CNTY FI
191. for each quadrangle Using the USGS Topographic Quadrangle Series Index layers The USGS 1 24 000 Topographic Quadrangle Series Index layer is one of three quadrangle index layers in the 1 2M ArcUSA database Indexes to maps at scales of 1 100 000 30 by 60 minutes and 1 250 000 1 by 2 degrees are also included The relationship between these map scales and the graticule are illustrated in the diagram below 1 24 000 quadrangk 1 100 000 quacrangle Te ao re A 200 000 quadange a 4 45 Chapter 4 ArcUSA 1 2M index layers USGS 1 24 000 Topographic Quadrangle Series Summary of USGS 1 24 000 Topographic Quadrangle Series Index coverages Coverage names dBASE UNIX and sizes MB Q_ 24K 26 41 26 01 Q_24KN 8 82 8 82 Q_24KS 7 47 7 49 Q_24KW 10 52 10 47 Source and currency Attributes and origin from USGS Topographic Names Database Published Map Sheet Data File also known as the T 70 file and various published indexes Grid from an ESRI algorithm Current for map sheet information to 1986 Thematic attribute groups Classification attributes Feature Number of Polygons Areas covered by Represented by 53 911 polygons USGS 1 24 000 quadrangles In general these map series systematically divide the United States into units of regular space and size However in order to minimize the number of maps that would contain mostly open water the USGS deviated from the regular system in four different ways rotation
192. formation A 12 State Boundaries layer Topological edits Where state and coastline arcs were coincident duplicate arcs were eliminated leaving only one arc In the DLG source data boundaries extended into the Great Lakes For the ArcUSA database these boundaries were edited so that they terminated at the shoreline Attribution County names CNTY_NAME and U S subregions SUB_REGION were added as new items to the database Data quality review County and combined state and county FIPS codes were reviewed visually and corrected when found to be invalid or missing Data derived from ESRI ArcWorld 1 3M data The only data in the ArcUSA 1 2M database derived from ESRI s ArcWorld 1 3M database appear in the Land Ocean Display layer The ArcWorld database was originally derived from the 1973 World Data Bank II WDBII database which was produced by the U S Central Intelligence Agency CIA Little formal documentation exists on the lineage of WDBII although it is known that it was automated from a wide variety of sources ESRI received the data as ASCII flat files of coordinates and related tables The data were converted into ARC INFO format using a simple conversion routine at ESRI The ArcWorld database includes significant revisions to the original WDBII source mainly in the areas of topology correction spurious polygon removal and coordinate density reduction of line primitives The Land Ocean Display coverage consists of those
193. g 2 13 to 2 14 6 8 Cartographic data layers 1 2M 4 3 to 4 36 characteristics 3 7 source and currency 3 16 lists of 1 4 4 3 Choroplethic mapping 6 7 to 6 8 Cities layer 1 25M 5 3 to 5 5 data source for 3 16 3 17 5 3 elevations 4 21 item definitions B 46 Classification attribute defined 3 12 CMSA Consolidated Metropolitan Statistical Area defined 4 91 4 92 4 93 Coastlines and political boundaries extending beyond U S borders 5 10 priority of coding 4 7 4 36 Code attribute 3 10 Color drawing order for when used with patterns lines points and text 6 6 use for background display 5 10 use to distinguish countries 2 15 use to distinguish variables 2 14 4 11 6 8 use with North arrow and scale bar 4 17 4 18 5 13 5 14 County and City Data Book Index 2 characteristics of and layers employed in 3 18 to 3 19 currency of data derived from 4 89 meaning of zero values in data derived from 4 89 to 4 91 metropolitan area attributes used in data from 4 91 to 4 93 Concise Digital Database characteristics of and layers employed in 3 17 Coordinate precision 3 21 A 4 A 17 Coordinate system 3 19 to 3 21 see also Projection systems defined 3 2 used for ArcUSA 1 2M data 1 3 County Boundaries layer 1 2M 4 5 to 4 8 data quality review procedures for A 8 data source for 3 15 3 16 3 17 item definitions B 4 production procedures for A 5 to A 6 A 8 County Boundaries layer 1 25M 5 6 to 5 9
194. g the Environmental Attributes coverages Since these data are organized by county and usually by percentage of county area only general patterns about individual attributes are discernible For example selecting the attribute for percent aridisols and displaying the data on a choroplethic map will show a general distribution area in the western United States but will not indicate exact soil boundaries ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA state and county statistical attribute layers Environmental Attributes Summary of the Environmental Attributes coverage County coverage Coverage name dBASE UNIX and size MB ENVIR 8 33 5 74 Source and currency Cartography from Digital Line Graphs current to 1988 Attribute data from Oak Ridge National Laboratory GeoEcology Database Most of the statistics included here were derived from the Conservation Needs Inventory CNI compiled in 1967 Data on surface mining date from 1975 Thematic attribute Geographic reference attributes polygons and lines groups Statistical flag polygons Land area and land use polygons Land capability polygons Land surface mining polygons Soil order classification polygons Classification attributes lines Feature Number of Polygons Counties and 3 111 features represented by 4 409 63 independent cities of polygons coterminous United States Lines County state and Represented by 10 485 lines 4 international bou
195. graphy POP90S State and county statistical S States AGIN_C attribute coverages in ArcUSA C Counties 1 2M and 1 25M U S region ArcUSA 1 2M Lakes and Other N Northern Region Water Bodies and USGS S Southern Region 1 24 000 Quadrangle Series W Western Region Index coverages Content or source RIV_25M Rivers All coverages LTLGS5 Latitude longitude grid 5 degree intervals GOV88CW Government statistics from the 1988 County amp City Data Book Note The coverage files which contain feature attribute tables are assigned the coverage name plus an extension for the table type PAT for polygons and points AAT for arcs For example the file RDS2M AAT contains the arc attribute table for the RDS2M coverage Table 4 Attribute naming conventions P_ percentage P_HS_GRADS All percentages especially in Percentage of people state and county statistical with 12 years of attribute coverages education K thousand MARRIAG_1K Number of Wherever applicable marriages per 1 000 especially in state and county people statistical attribute coverages Abbreviation HOSP_BEDS Number All attributes of hospital beds SICBEEF Number of farms falling under the Standard Industrial Code for beef farms TOT_Q_SQMI Total square miles of land area represented by a quadrangle map 3 14 ArcUSA User s Guide and Data Reference April 1992 Chapter 3 Database concepts and organization named TYPE Another
196. gree grid Polygons 53 911 1 24 000 scale map areas Polygon attributes 19 quad name and ID states covered map date edition Polygons 1 809 1 100 000 scale map areas Polygon attributes 12 quad name and ID states covered map date edition Polygon attributes 13 quad name and ID states covered map date edition Polygons 488 1 250 000 scale map series Source Currency EOSAT algorithm generated 1992 Coverage Names EOSAT algorithm generated 1992 SAT_BND ESRI algorithm generated 1992 LTLG10 USGS various ESRI algorithm generated 1986 USGS various ESRI algorithm generated 1986 USGS various ESRI algorithm generated 1986 April 1992 1 5 Chapter 1 What is ArcUSA Table 3 ArcUSA 1 2M state and county statistical attribute layers 1990 U S Census P L 94 171 Data by State By County Agricultural Product Inventory by State Agricultural Product Market Value by State By County Demographic and Health Attributes by State Features Polygons 1 295 states Lines 1 607 state boundaries Polygons 4 409 counties Lines 10 485 county boundaries Polygons 1 295 states Lines 1 607 state boundaries Polygons 4 409 counties Lines 10 485 county boundaries Polygons 1 295 states Lines 1 607 state boundaries Polygons 4 409 counties Lines 10 485 county boundaries Polygons 1
197. harles 185 St Clair 187 St Francois 189 St Louis 193 Ste Genevieve 195 Saline 197 Schuyler 199 Scotland 201 Scott 203 Shannon 205 Shelby 207 Stoddard 209 Stone 211 Sullivan 213 Taney 215 Texas 217 Vernon 219 Warren 221 Washington 223 Wayne 225 Webster 227 Worth 229 Wright 510 St Louis City Montana 1 Beaverhead 3 Big Horn 5 Blaine 7 Broadwater 9 Carbon 11 Carter 13 Cascade 15 Chouteau 17 Custer 19 Daniels 21 Dawson 23 Deer Lodge 25 Fallon 27 Fergus 29 Flathead 31 Gallatin 33 Garfield 35 Glacier 37 Golden Valley 39 Granite 41 Hill 43 Jefferson 45 Judith Basin 47 Lake 49 Lewis and Clark 51 Liberty Lincoln McCone 57 Madison 59 Meagher 61 Mineral 63 Missoula 65 Musselshell 67 Park 69 Petroleum 71 Phillips 73 Pondera 75 Powder River 77 Powell 79 Prairie 81 Ravalli 83 Richland 85 Roosevelt 87 Rosebud 89 Sanders 91 Sheridan 93 Silver Bow 95 Stillwater 97 Sweet Grass 99 Teton 101 Toole 103 Treasure 105 Valley 107 Wheatland 109 Wibaux 111 Yellowstone 113 Yellowstone National Park Part Nebraska 1 Adams 3 Antelope 5 Arthur 7 Banner 9 Blaine 11 Boone 13 Box Butte 15 Boyd 17 Brown 19 Buffalo 21 Burt 23 Butler 25 Cass 27 Cedar 29 Chase 31 Cherry 33 Cheyenne 35 Clay 37 Colfax 39 Cuming 41 Custer 43 Dakota 45 Dawes 127 129 131 133 135 137 139 141 143 145 147 149 151 153 155 157 159 161 Dawson Deuel Dixon Dodge Douglas Dundy Fillmore Franklin Fron
198. he Land Ocean Display coverage The primary purpose of this layer is to provide an attractive cartographic treatment between the data content area and the edge of the display window For example a continuous background can be displayed by symbolizing the polygons in this layer with solid colors such as blue for water and beige for land A U S coastline display using the State Boundaries or County Boundaries layer can be continued into Canada and Mexico with the line theme in this layer The processing grid can be omitted from display if you select only the feature lines The annotation theme associated with this layer contains labels for the major country and water features Annotation is best for displays showing the full extent of the database so that names will be entirely visible The annotation is suited for a detailed display of the Great Lakes region however because the annotation text for those features is relatively small ArcUSA User s Guide and Data Reference Chapter 5 The ArcUSA 1 25M layers Land Ocean Display Summary of the Land Ocean Display coverage Coverage name dBASE UNIX and size MB LAND25M 0 40 0 50 Source and currency ESRI ArcWorld 1992 Thematic attribute groups Classification attributes polygons and lines Annotation Mexico Canada Atlantic Ocean Lake Superior Lake Michigan Gulf of Mexico Gulf of California and so on Feature Number of class Feature Number of features att
199. he entries County level crime occurrence related items have the third highest percentage VIOLENT_CR SERIOUS_CR with 4 of the data represented by zero entries indicating that data were unavailable 4 90 ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA state and county statistical attribute layers Demographic and Health Attributes County coverage Coverage name dBASE UNIX and size MB POP88C 7 91 5 67 Source and currency Cartography from Digital Line Graphs current to 1988 Attribute data from U S Census Bureau County and City Data Book 1988 Thematic attribute Metropolitan area attributes polygons groups County land area polygons Plus the attribute groups listed for states above Feature Number of Polygons Counties and 3 111 features represented by 4 409 55 independent cities of polygons coterminous United States Lines County state and Represented by 10 485 lines international boundaries shorelines Those sixty attributes for which zero indicates something other than a measurement of zero are marked with an asterisk in the attribute listings Attributes for metropolitan areas The county level coverages from the County and City Data Book contain three attributes that identify metropolitan counties The first attribute county type CNTY_TYPE identifies whether a county is considered a Primary Metropolitan Statistical Area PMSA part of a Consolidated Metropolitan Statistical Area C
200. he more restrictive designation 1 for National park and TYPE to the less restrictive one 5 for Military reservation Rankings were established by ESRI In this example TYPE3 is blank Flag attributes Flag attributes contain a code that identifies certain records or features in a coverage Flags are needed in ArcUSA coverages that contain counties or states in order to generate accurate summary statistical data This is because some counties and states such as those that include offshore islands are represented by multiple polygons For measurement attributes each separate polygon is assigned the total value for the political unit resulting in repeated values A summation across all records would yield inflated results The flag value has been assigned to the largest polygon in each county and state enabling a single record per political unit to be selected for statistical analysis or display of the county or state name Name attributes Name attributes may contain either alphabetic or alphanumeric names They serve two functions in the ArcUSA database First they may contain the English language equivalents of codes If so the user has the option of generating an online display of attribute classes either by name or by code For example in the Lakes and Other Water Bodies layer TYPE contains the codes for the different classes of water bodies and WATER TYPE contains the names for the different classes of water bodies A
201. heme for the ArcUSA database In the new system a river segment can only be assigned one code according to a set priority rank The code for intercoastal waterways was dropped entirely because of its low frequency of use Also dropped were any codes that are ordinarily software generated such as the length of a river segment Items for state name STATE_NAMEB FIPS code STATE_FIPS and U S subregion SUB_REGION were added to enhance display flexibility Data quality review No special reviews were performed on this coverage Roads layer Topological edits No special topological edits were performed Attribution The twenty seven DLG road classes were restructured into a simplified ten class coding scheme ESRI_CLASS suitable for small scale or regional displays requiring less detail New items DLG_CLASS1 to 3 were added they contained class descriptions rather than just road class code numbers Also added were items for state name STATE_NAME FIPS code STATE_FIPS and U S subregion SUB_REGION These geographic identifiers were added to enhance display flexibility Data quality review Automated diagnostic checks were performed on the database for invalid and missing codes The coverage was also reviewed for roads that crossed water bodies Roads and interstates were plotted and a general visual review of road classes and route numbers was performed Inconsistent or invalid codes were corrected Appendix A Data quality in
202. ia TX MSA Vineland Millville Bridgeton NJ PMSA Visalia Tulare Porterville CA MSA April 1992 C 19 Appendix C FIPS codes WwW 9140 Williamsport PA MSA 8800 Waco TX MSA 9160 Wilmington DE NJ MD PMSA 8840 Washington DC MD VA MSA 9200 Wilmington NC MSA 8880 Waterbury CT MSA 9240 Worcester MA MSA 8920 Waterloo Cedar Falls IA MSA 9243 Worcester Fitchburg Leominster MA NECMA 8940 Wausau WI MSA 8960 West Palm Beach Boca Raton Delray Beach Y FL MSA 9260 Yakima WA MSA 9000 Wheeling WV OH MSA 9280 York PA MSA 9040 Wichita KS MSA 9320 Youngstown Warren OH MSA 9080 Wichita Falls TX MSA 9340 Yuba City CA MSA C 20 ArcUSA User s Guide and Data Reference Appendix D Bibliography Source data The following publications contain further information about the data sources for this database Data Access and Use Staff Data User Services Division 1990 Census of Agriculture 1987 on CD ROM Washington D C U S Bureau of the Census Data Access and Use Staff Data User Services Division 1989 County and City Data Book 1988 Files on CD ROM Technical Documentation Washington D C U S Bureau of the Census National Bureau of Standards 1987 Guideline Codes for Named Populated Places Primary County Divisions and Other Locational Entities of the United States and Outlying Areas Gaithersburg Md U S Department of Commerce FIPS Publication 55 2 Olson R J
203. ico Henry Highland Isle of Wight James City King and Queen King George King William Lancaster Lee Loudoun Louisa Lunenburg Madison Mathews Mecklenburg Middlesex Montgomery Nelson New Kent Northampton Northumberland Nottoway Orange Page Patrick Pittsylvania Powhatan Prince Edward Prince George Prince William Pulaski Rappahannock Richmond Roanoke Rockbridge Rockingham Russell Scott Shenandoah Smyth Southampton Spotsylvania Stafford Surry Sussex Tazewell Warren Washington Westmoreland Wise 197 Wythe 199 York 510 Alexandria 515 Bedford 520 Bristol 530 Buena Vista 540 Charlottesville 550 Chesapeake 560 Clifton Forge 570 Colonial Heights 580 Covington 590 Danville 595 Emporia 600 Fairfax 610 Falls Chruch 620 Franklin 630 Fredericksburg 640 Galax 650 Hampton 660 Harrisonburg 670 Hopewell 678 Lexington 680 Lynchburg 683 Manassas 685 Manassas Park 690 Martinsville 700 Newport News 710 Norfolk 720 Norton 730 Petersburg 735 Poquoson 740 Portsmouth 750 Radford 760 Richmond 770 Roanoke 7715 Salem 780 South Boston 790 Staunton 800 Suffolk 810 Virginia Beach 820 Waynesboro 830 Williamsburg 840 Winchester Washington 1 Adams 3 Asotin 5 Benton 7 Chelan 9 Clallam 11 Clark 13 Columbia 15 Cowlitz 17 Douglas 19 Ferry 21 Franklin 23 Garfield Grant Gr
204. ide and Data Reference 3 3 1 20 20 C 7 7 C 1 1 4 9 B 4 9 F 2 4 9 B 4 6 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 5 F 2 4 9 B 4 6 F 2 4 9 B continued Appendix B ArcUSA 1 2M state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data continued Polygon Attribute Table State Level Coverage continued dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Percent Non Hispanic White P_NHWHITE 427 13 N 6 164 4 6 F 2 Non Hispanic Black NHBLACK 440 11 N 0 168 4 9 B Percent Non Hispanic Black P_NHBLACK 451 13 N 6 172 4 5 F 2 Non Hispanic Amer Ind NHAMIND 464 11 N 0 176 4 9 B Percent Non Hispanic Am Ind P_NHAMIND 475 13 N 6 180 4 5 F 2 Non Hispanic Asian NHASIAN 488 11 N 0 184 4 9 B Percent Non Hispanic Asian P_NHASIAN 499 13 N 6 188 4 5 F 2 Non Hispanic Other NHOTHER 512 11 N 0 192 4 9 B Percent Non Hispanic Other P_NHOTHER 523 13 N 6 196 4 5 F 2 Total Hispanic 18 and older HISPAN18 536 11 N 0 200 4 9 B Percent Hispanic 18 P_HISPAN18 547 13 N 6 204 4 5 F 2 Total Non Hispanic 18 NHISPN18 560 11 N 0 208 4 9 B Percent Non Hispanic 18 P_NHISPN18 13 N 6 212 4 5 F 2 Non Hispanic White 18 NHWHIT18 11 N 0 216 4 9 B Non Hispanic White 18 P_NHWHIT18 13 N 6 220 4 6 F 2 Non Hispanic Bla
205. ies Land Ocean Display Map Elements Place Names Rivers and Streams Roads Railroads State Boundaries Landsat Nominal Scene Index Latitude Longitude Grids USGS 1 24 000 Topographic Quadrangle Series Index USGS 1 100 000 Topographic Quadrangle Series Index USGS 1 250 000 Topographic Quadrangle Series Index State and County 1990 Census Public Law 94 171 Data State and County Agricultural Product Inventory State and County Agricultural Product Market Value State and County Demographic and Health Attributes County Environmental Attributes State and County Government and Financial Attributes State and County Socioeconomic Attributes The ArcUSA 1 2M coverages have the following characteristics Characteristic ArcUSA coverage characteristics Input scale 1 2 000 000 Resolution Lines 50 8 m Polygons 2 3 sq km Spurious polygons of smaller size may exist because of the overlay processing used to attribute state names and FIPS codes to features in cartographic layers Resolution of statistical data To county level Generalization tolerance Not applicable April 1992 A 3 Appendix A Data quality information Unnormalized repeating records exist Number of layers Cartographic Index Statistical attribute Attribute types Naming conventions Coverages Tables Attributes Projection system 10 13 coverages 5 11 coverages 13 13 coverages Measurement interval or ordinal values Suppressed value
206. iew please see the ArcView installation instructions Next load your ArcUSA data set see the ArcUSA 1 2M Installation Instructions The views directory includes a series of precomposed ArcView displays to guide you through the tour ArcUSA User s Guide and Data Reference Exploring U S migration trends 1980 to 1986 by state In this exercise you ll explore migration trends at the state level Begin by opening the view mig25mst av that displays the ArcUSA 1 25M state boundaries layer for the coterminous United States 1 Click on the check box for the theme named Net Migration 1980 86 by state You will see a thematic map showing states that lost or gained population due to migration from 1980 to 1986 Net migration net_migr is one of the variables in the ArcUSA 1 25M stats_s coverage that contains selected statistical attribute data at the state level 2 Double click on the theme Net Migration 1980 86 by state The Theme Property Sheet will appear below the Table of Contents Notice that the attribute stat_flag has been preset to equal 1 Quit from the property sheet to continue Chapter 2 Exploring the ArcUSA database The upper peninsula of Michigan is not shaded because it is not the largest polygon for the state See Note to user on page 2 4 for more information about the stat_flag attribute F Properties Net Migration 1980 86 by state
207. in square miles Publication data Most recent date of revision expressed as the last two digits of the year This information was not available for some quadrangles Most recent date of publication expressed as the last two digits of the year This information was not available for some quadrangles Most recent date of photo revision if applicable expressed as the last two digits of the year This information was not available for some quadrangles ArcUSA User s Guide and Data Reference USGS 1 100 000 Topographic Quadrangle Series Index Polygons April 1992 Chapter 4 ArcUSA 1 2M index layers USGS 1 100 000 Topographic Quadrangle Series Layer description The USGS 1 100 000 Topographic Quadrangle Series Index layer contains polygons that represent the geographic extent of USGS 1 100 000 topographic maps 30 by 60 minute quadrangles Quadrangle names publication data and map coverage by state are given for each quadrangle Using the USGS 1 100 000 Topographic Quadrangle Series Index coverages The quadrangle index contained in this layer is a systematic grid based on the graticule One 1 100 000 scale map sheet covers the same area as thirty two 1 24 000 quadrangles The relationship between this quadrangle index the graticule and the other two quadrangle series in the ArcUSA database are further explained in Using the USGS Topographic Quadrangle Index Layers page 4 45
208. indow or by using the ARCPLOT CLASS command in ARC INFO 6 7 Chapter 6 Using the database Bivariate mapping A variation of choroplethic mapping which was referred to in Chapter 2 as bivariate mapping is simultaneously displaying two variables using different symbols over the same geographic area In ArcView bivariate mapping can be accomplished by displaying one variable in a color and the other variable in a pattern This technique is commonly used to investigate relationships or correlations between two different attributes For example net migration out of an area may be related to a high rate of crime high unemployment or a high local tax rate In statistical terms the variable being explained net migration is called the dependent variable and the others are called independent variables Because ArcView makes it so easy to generate color ramps colors of gradually changing hue or of gradually increasing intensity which can be made to correspond to gradual increases in a variable it is recommended that you use colors to display the independent variables and a pattern to display the dependent variable using color and pattern in this way makes it easy to create a series of bivariate maps 6 8 ArcUSA User s Guide and Data Reference Appendix A Data quality information This appendix summarizes quality information and technical details about the ArcUSA database The informat
209. indows can be used It is not an endorsement of any particular software product nor is it inclusive many other products will work as effectively These are merely the products that we have tried at ESRI and have found to be effective for use with ArcUSA 6 3 Chapter 6 Using the database Table 1 Windows software Software Program dBASE Used to manage and manipulate feature attribute and related tables Excel Spreadsheet tools for manipulating selected attribute records business graphics summaries and other spreadsheet functions Joins dBASE attribute tables CorelDRAW Graphics editor for Windows Paintbrush Graphics editor for Windows and delivered as part of Windows ObjectVision Used to build front ends to dBASE files Publisher A word processing and publishing package that is integrated with Windows Elementary Student Population Counties of Northern G ia 1986 Sargia E Towns E Union E Fannin O Murray E Whitfield E Catoosa Walker E Habersham ArcUSA data can be imported into other software applications like Excel for further statistical analysis 6 4 ArcUSA User s Guide and Data Reference Chapter 6 Using the database Units of measure A number of different units are used for the various measurement attributes The units used for area length volume and weight are listed in Table 2 Other units used in the database include decimal degrees used for all geographic coordinate layers and in
210. ing the USGS 1 24 000 Topographic Quadrangle Series coverages The 1 24 000 map series index coverage for the full coterminous United States Q_24K is made up of nearly 54 000 polygons representing the locations of the 1 24 000 scale quadrangles The grid does not replicate offset over edge and insert sheet layouts that occur near the shorelines but correct map sheet information is included for all land areas To optimize software performance query this large layer using the regional coverages instead of the full U S coverage and whenever possible break logical expressions for selecting quadrangles into several simple statements instead of using a single complex expression For example to select the quadrangles that cover Ohio first select the records where ST_NAME contains Ohio then select 4 47 Chapter 4 ArcUSA 1 2M index layers USGS 1 24 000 Topographic Quadrangle Series 4 48 USGS_QD_ID QUAD_NAME records where ST_NAME2 contains Ohio and so on Using a single expression that searches all four state name attributes at once reduces performance The detail in this layer makes it especially appropriate for display at more detailed scales such as creating a topographic map index for a study area If the 2 degree latitude longitude grid and this index are overlaid a 2 degree by 2 degree area will be 16 quadrangles wide by 16 quadrangles high Polygon attributes Quadrangle identification attributes The
211. inst source lithographs for consistency in attribute coding Logical consistency All data were found to be topologically correct using ARC INFO Rev 5 0 1 No duplicate features are present All polygons are closed and all lines intersect where intended No undershoots or overshoots are present ArcUSA User s Guide and Data Reference Appendix A Data quality information Completeness The ArcUSA data were closely reviewed to ensure completeness of shorelines and of state and county boundaries River and road layer completeness is less well defined since cartographic judgment has been used to create a visually pleasing product Statistical data are incomplete in the sense that selected records in the database may not have data for some attributes April 1992 A 15 Appendix A Data quality information ArcUSA 1 25M data Summary of ArcUSA 1 25M characteristics The 1 25M data set is intended to serve as a basemap for display and analysis at very small scales Its smaller file size and coordinate density also allow for more rapid drawing when viewed graphically ArcUSA data at the scale of 1 25 000 000 consist of the following layers e Cities e County Boundaries e Rivers e Roads e Land Ocean Display e Map Elements e State Boundaries State and County Statistical Attributes The ArcUSA 1 25M coverages have the characteristics shown in the following tables Characteristic ArcUSA coverage characteristics Input scale 1
212. ion Fill Area Code FILL 49 2 N 0 17 2 2 1 Annotation Includes labels for scale bar North arrow and display title Arc Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition All items are ARC INFO generated Place Names Coverage Name NAM2M Layer Type Point Point Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Name of Feature NAME 49 51 C 0 51 51 C Feature Type FEAT_TYPE 100 11 C 0 11 11 C Major City Code MAJ_CITY 111 1 N 0 1 1 1 Capital Code CAPITAL 112 1 N 0 1 1 1 County Seat Code CTY_SEAT 113 1 N 0 1 1 1 Elevation of Feature ELEVATION 114 6 N 0 6 6 1 County Name CNTY_NAME 120 31 C 0 31 31 C State FIPS Code STATE_FIPS 151 3 N 0 3 3 1 State Name STATE_NAME 154 16 C 0 16 16 C U S Subregion Code SUB_REGION 170 7 C 0 ERE April 1992 B 7 Appendix B ArcUSA 1 2M cartographic layers Railroads Coverage Name RR2M Layer Type Line Arc Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Rail Line Classification TYPE 80 1 N 0 29 1 1 1 Rail Line Class Name RAIL_TYPE 81 72 C 0 30 State FIPS Code STATE_FIPS 153 3 N 0 102 State Name STATE_NAME 156 20 C 0 105 U S Subregion Code SUB_REGION 176 7 C 0 125 Rivers and Streams Coverage Name RIV2M Laye
213. ion 1984 Black amp Other Races 1984 Males per 100 Females 1984 Persons Under 5 Years 1984 Percent Persons 5 to 14 Years Percent Persons 15 to 24 Years Percent Persons 25 to 34 Years Percent Persons 35 to 44 Years Percent Persons 45 to 54 Years Percent Persons 55 to 64 Years Percent Persons 65 to 74 Years Percent Persons 65 to 74 Years Total Population 1984 Percent American Indian 1980 Percent Asian 1980 Percent Hispanic 1980 Population 1980 Births 1984 Births to Mothers lt 20 Years Births per 1000 Pop 1984 April 1992 ltem Name Column Definition Column Definition STATE_FIPS 49 STATE_NAME 52 SUB_REGION STAT_FLAG POP1986 POP_RANK POP_SQMILE POP1980CR POP_CHG P_POP_CHG BIRTHS DEATHS NET_MIGR P_WHITE_84 P_BLK_OTH MALE_100F P_UNDER_5 P_5_14 P_AMERIND P_ASIAN P_HISPANIC POP1980 BIRTHS_84 P_BIR_TEEN BIR_1KPOP 3 N 0 20 C 0 7 C 0 1 N 0 11 N 0 11 N 0 13 N 6 11 N 0 11 N 0 13 N 6 11 N 0 11 N 0 11 N 0 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 11 N 0 13 N 6 13 N 6 13 N 6 11 N 0 11 N 0 13 N 6 13 N 6 3 3 20 20 C 7 7 C 1 1 979 4 7 B 4 6 F 1 4 6 F 1 continued B 33 Appendix B ArcUSA 1 2M state and county statistical attribute layers Demographic and Health Attributes continued Polygon Attribute Table State Level Coverage continued dBASE Columns INFO Ite
214. ion attributes Each polygon is classified according to the following list of categories TYPE contains the code number and WATER_TYPE contains the English description Codes Equivalents Perennial lake or pond Marsh Intermittent lake or pond Dry lake or pond Reservoir Intermittent reservoir Glacier or snowfield Island Not a water body background polygon OMANDMNBRWNFR Hou We a we wb ab tt Geographic reference attributes These attributes which can be used for feature selection store the state FIPS code state name and U S subregion in which the water body is located A water body located in more than one state is represented by multiple polygons each of which is assigned the appropriate state and subregional geographic reference information 4 13 Chapter 4 ArcUSA 1 2M cartographic layers Land Ocean Display Layer description Land and water areas beyond the extent of the other ArcUSA cartographic layers are contained in the Land Ocean Display layer Canada Mexico the Atlantic and Pacific oceans and each of the Great Lakes can be displayed and labeled to create a finished looking map Polygons Using the Land Ocean Display coverage The purpose of this coverage is to provide an attractive cartographic treatment between the data content area and the edge of the display window For example a continuous background can be displayed by using solid colors for the polygons in this layer such as
215. ion attributes lines Feature Number of Polygons Counties and 3 111 features represented by 4 409 independent cities polygons Lines County and Represented by 7 504 lines 4 independent city boundaries State boundaries Represented by 1 204 lines International Represented by 68 lines boundaries Shorelines Represented by 1 709 lines All line features Represented by 10 485 lines Polygon attributes Geographic reference attributes STATE FIPS The state county and combined state county FIPS codes as CNTY_FIPS well as the state name and U S subregion can be used to FIPS select particular county polygons for display or study The STATE_NAME porns y PO pray y CNTY NAME _ U S subregions are shown on the map on page 1 2 SUB_REGION 4 6 ArcUSA User s Guide and Data Reference April 1992 STAT_FLAG m T_FIPS T_FIPS D nn ST_NAMES BNDY_TYPE Chapter 4 ArcUSA 1 2M cartographic layers County Boundaries Statistical flag Flag to identify a unique polygon for each county The codes are as follows Codes Definitions 0 Other polygon if Largest polygon Line attributes Geographic reference attributes The FIPS codes of the states on either the left or right side of a boundary are contained in these attributes For county boundaries inside a state the left and right FIPS codes are the same For state boundaries the left and right FIPS codes are different The left and right sides of a boundary are defined
216. ion is presented to assist users in determining the suitability of ArcUSA data for their applications The information about ArcUSA data characteristics is generally presented in the format recommended by the Digital Cartographic Data Standards Task Force as part of the development of the Spatial Data Transfer Standard SDTS ESRI is providing data quality related information in this format to facilitate communication between providers and users of digital geographic data April 1992 A 1 Appendix A Data quality information A 2 ArcUSA 1 2M data During ArcUSA development several modifications were made to the source data in order to generate a database in which the data had the following characteristics Common scale Uniform level of resolution e Consistent coding scheme e Comparable standardized measurement data Production of the ArcUSA database involved e Joining multiple panel data into a single panel covering the coterminous United States e Modifying source cartographic information and attribution schemes e Associating tabular data with a cartographic base In addition a second smaller scale 1 25 000 000 data set was produced from the larger 1 2 000 000 one ArcUSA User s Guide and Data Reference Appendix A Data quality information Summary of ArcUSA 1 2M characteristics ArcUSA data at the scale of 1 2 000 000 consist of the following layers County Boundaries Federal Lands Lakes and Other Water Bod
217. ips 97 Pitkin 99 Prowers 101 Pueblo 103 Rio Blanco 105 Rio Grande 107 Routt 109 Saguache 111 San Juan 113 San Miguel 115 Sedgwick 117 Summit 119 Teller 121 Washington 123 Weld 125 Yuma Connecticut 1 Fairfield 3 Hartford 5 Litchfield 7 Middlesex 9 New Haven 11 New London 13 Tolland 15 Windham Delaware 1 Kent 3 New Castle 5 Sussex District of Columbia 1 Washington Florida 1 Alachua 3 Baker 5 Bay Bradford Brevard Broward Calhoun Charlotte Citrus Clay Collier Columbia Dade De Soto Dixie Duval Escambia Flagler Franklin Gadsden Gilchrist Glades Gulf Hamilton Hardee Hendry Hernando Highlands Hillsborough Holmes Indian River Jackson Jefferson Lafayette Lake Lee Leon Levy Liberty Madison Manatee Marion Martin Monroe Nassau Okaloosa Okeechobee Orange Osceola Palm Beach Pasco Pinellas Polk Putnam St Johns St Lucie Santa Rosa Sarasota Seminole Sumter Suwannee April 1992 Appendix C FIPS codes 123 125 127 129 131 133 Taylor Union Volusia Wakulla Walton Washington ia Appling Atkinson Bacon Baker Baldwin Banks Barrow Bartow Ben Hill Berrien Bibb Bleckley Brantley Brooks Bryan Bulloch Burke Butts Calhoun Camden Candler Carroll Catoosa Charlton Chatham Chattahoochee Chattooga Cherokee Clarke Clay Clayton Clinch Cobb Coffee Colquitt Colum
218. istics layers The attributes in the Agricultural Product Inventory and Agricultural Product Market Value layers come from the U S Census of Agriculture The agricultural census does not recognize or summarize statistics for independent cities Such places may have a blank or zero value for some agricultural attributes Complete information about how agricultural census data are collected is available in Census Bureau publications For your convenience a few general definitions of some important Census Bureau terms are included below A farmis defined as any place from which 1 000 or more of agricultural products were produced and sold or normally would have been sold during the census year Farm size is calculated by including land owned and operated as well as land rented from others Land rented to a tenant was considered the tenant s farm and not the owner s 4 70 ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Inventory Summary of Agricultural Product Inventory coverages State coverage Coverage name dBASE UNIX and size MB AGIN_S 3 94 2 64 Source and currency Cartography from Digital Line Graphs current to 1973 Attribute data from 1987 U S Census of Agriculture Table 1 Thematic attribute Geographic reference attributes polygons and lines groups Statistical flag polygons General farm description attributes polygons Farms
219. ited States The cartographic representation of boundaries and shorelines has been generalized from the ArcUSA 1 2M State Boundaries layer The polygon and line attributes and attribute values are identical to those in the ArcUSA 1 2M layer Using the State Boundaries coverage The more generalized cartography in this layer makes it particularly useful for the fast display of small scale thematic maps with ArcUSA 1 2M statistical attribute data Some states such as Michigan and New York are represented by multiple polygons Each of these polygons is assigned the statistics for the entire state The statistical flag attribute STAT_FLAG which identifies only one polygon per state can be used to prevent state totals from being added repeatedly during statistical analyses and to prevent text like the state name from being drawn repeatedly in a display The statistical flag attribute value has been assigned to the largest polygon in each state To create a base map with state names you can use the state name attribute as text to label the polygons Again you can use the flag attribute to select only one polygon per state for text labeling ArcUSA User s Guide and Data Reference Chapter 5 The ArcUSA 1 25M layers State Boundaries Summary of the State Boundaries coverage Coverage name dBASE UNIX and size MB ST_25M 0 34 0 35 Source and currency DLG 1973 Thematic attribute Geographic reference attributes polygons and lines
220. its in the state or county in 1980 Percentage change in the number of housing units in the state or county from 1970 to 1980 Number of housing units in the state or county that were occupied in 1980 Percentage of housing units in the state or county that were occupied by the owner in 1980 Percentage of occupied housing units in the state or county that included two or more automobiles in 1980 Estimated total number of occupied housing units in the state or county in 1980 This figure is based on a sample It was used to compute PLOWN_OCC and P_2CAR_OCC The median value of occupied housing units in the state or county in 1980 in dollars New private housing units in the state or county that were authorized by permit in 1986 Approximately 17 000 places require permits for new construction constituting about 95 of all new construction New private housing units in the state or county that were authorized by permit for the years 1980 through 1986 New private housing units in the state or county that were authorized by permit from 1980 to 1986 as a percentage of housing units in 1980 Computed by dividing PRMT_80_86 by HSE_UNITS ArcUSA User s Guide and Data Reference CIVLABOR86 P_CHG_CIV CIV_UNEMP UNEMP_RATE L_ST_FIPS R_ST_FIPS ST_NAMES BNDY_TYPE April 1992 Chapter 4 ArcUSA state and county statistical attribute layers Socioeconomic Attributes Labor force attributes Civilian labor force i
221. lambs and number of sheep and lambs Number of farms in the state or county with chickens number of chickens number of farms that sold broilers and number of broilers sold Number of farms in the state or county raising corn for grain or seed acres in corn for grain or seed and bushels of corn harvested Number of farms in the state or county raising corn for silage acres in corn for silage and tons of silage produced Number of farms in the state or county raising sorghum for grain or seed acres in sorghum for grain or seed and bushels of sorghum harvested ArcUSA User s Guide and Data Reference April 1992 WHEATFARMS WHEATACRES WHEAT_BU BARLEYFARM BARLEYACRE BARLEY_BU OATSFARMS OATSACRES OATS_BU RICEFARMS RICEACRES RICE_CWT SUNFLWFARM SUNFLWACRE SUNFLW_LB COTTONFARM COTTONACRE COTTONBALE TOBACOFARM TOBACOACRE TOBACO_LB SOYBEANFAR SOYBEANACR SOYBEAN_BU DRYBEANFAR DRYBEANACR DRYBEANCWT POTATOFARM POTATOACRE POTATO_CWT Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Inventory Number of farms in the state or county raising wheat for grain acres in wheat for grain and bushels of wheat harvested Number of farms in the state or county raising barley for grain acres in barley for grain and bushels of barley harvested Number of farms in the state or county raising oats for grain acres in oats for grain and bushels of oat grain harveste
222. land 177 Tyrrell 89 Stark 95 Lucas 29 Coal 179 Union 91 Steele 95 Lucas 31 Comanche 181 Vance 93 Stutsman 97 Madison 33 Cotton 183 Wake 95 Towner 99 Mahoning 35 Craig 185 Warren 97 Traill 101 Marion 37 Creek 187 Washington 99 Walsh 103 Medina 39 Custer 189 Watauga 101 Ward 105 Meigs 41 Delaware 191 Wayne 103 Wells 107 Mercer 43 Dewey 193 Wilkes 105 Williams 109 Miami 45 Ellis 195 Wilson 111 Monroe 47 Garfield 197 Yadkin Ohio 113 Montgomery 49 Garvin 199 Yancey 1 Adams 115 Morgan 51 Grady 3 Allen 117 Morrow 53 Grant North Dakota 5 Ashland 119 Muskingum 55 Greer 1 Adams 7 Ashtabula 121 Noble 57 Harmon 3 Barnes 9 Athens 123 Ottawa 59 Harper 5 Benson 1 Auglaize 125 Paulding 61 Haskell 7 Billings 13 Belmont 127 Perry 63 Hughes 9 Bottineau 15 Brown 129 Pickaway 65 Jackson 11 Bowman 17 Butler 131 Pike 67 Jefferson 13 Burke 19 Carroll 133 Portage 69 Johnston 15 Burleigh 21 Champaign 135 Preble 71 Kay 17 Cass 23 Clark 137 Putnam 73 Kingfisher 19 Cavalier 25 Clermont 139 Richland 75 Kiowa 21 Dickey 27 Clinton 141 Ross 77 Latimer 23 Divide 29 Columbiana 143 Sandusky 79 Le Flore 25 Dunn 31 Coshocton 145 Scioto 81 Lincoln 27 Eddy 33 Crawford 147 Seneca 83 Logan 29 Emmons 35 Cuyahoga 149 Shelby 85 Love 31 Foster 37 Darke 151 Stark 87 McClain 33 Golden Valley 39 Defiance 153 Summit 89 McCurtain 35 Grand Forks 41 Delaware 155 Trumbull 91 McIntosh 37 Grant 43 Erie 157 Tuscarawas 93 Major 39 Grigg
223. layers The restructured data were subjected to a limited review in order to assess the completeness and logical consistency of the data For the most part these reviews focused on verifying the correctness of the restructuring process and not the correctness of the source data As described under Data quality review selected attribute codes for individual layers were reviewed more extensively Indexing Display and query times for the ArcUSA database were reduced by introducing two types of indexes into the database One index is for the individual items in the database a tabular index and the other index is for the coverages a spatial index A 6 ArcUSA User s Guide and Data Reference April 1992 Appendix A Data quality information In the tabular index which applies to data in UNIX format only all attributes are sorted by value Such sorting facilitates user operations like logical reselections It permits fast binary searches of item values in place of slower sequential ones values of interest are identified and then matched with the corresponding record numbers In the spatial index all coverages are spatially subdivided into quadrangles using a modified quadtree approach The size and number of the quadrangles vary across the different coverages according to feature density Spatial indexing supports subsequent user operations like spatial reselections and drawing efforts It permits the speedy identification of the
224. le ID Number USGS_QD_ID 49 8 C 0 8 8 C Quadrangle Name QUAD_NAME 57 32 C 0 32 32 C Map Edition Number MAP_EDIT 89 1 C 0 State FIPS Code One ST_FIPS1 90 3 N 0 State Name One ST_NAME1 93 20 C 0 State FIPS Code Two ST_FIPS2 113 3 N 0 State Name Two ST_NAME2 116 20 C 0 State FIPS Code Three ST_FIPS3 State Name Three ST_NAME3 State FIPS Code Four ST_FIPS4 159 State Name Four ST_NAME4 Date of Publication DATE_PUB B 14 ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 2M index layers USGS 1 250 000 Topographic Quadrangle Series Coverage Name Q_250K Layer Type Polygon Polygon Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition USGS Quadrangle ID Number USGS_QD_ID 8 C 0 8 8 C Quadrangle Name QUAD_NAME 20 C 0 20 20 C Map Edition Number MAP_EDIT 1 C 0 State FIPS Code One ST_FIPS1 3 N 0 State Name One ST_NAME1 20 C 0 State FIPS Code Two ST_FIPS2 3 N 0 State Name Two ST_NAME2 20 C 0 State FIPS Code Three ST_FIPS3 3 N 0 State Name Three ST_NAME3 20 C 0 State FIPS Code Four ST_FIPS4 3 N 0 State Name Four ST_NAME4 20 C 0 Date of Revision DATE_REV 2 C 0 Date of Publication DATE_PUB 2 C 0 April 1992 B 15 Appendix B ArcUSA 1 2M state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data POP90S POP90C Polygon and Line Coverage Names Layer Type Polygon Attribute Table
225. lygon attributes Classification attributes TYPE1 These three attributes contain codes representing the TYPE2 administrative type of the land area Every land area is TYPES assigned at least a TYPE code Ifa land area is nested within the limits of one or two other federal land areas the April 1992 4 9 Chapter 4 ArcUSA 1 2M cartographic layers Federal Lands 4 10 ADMN_TYPE1 ADMN_TYPE2 ADMN_TYPE3 STATE_FIPS STATE_NAME SUB_REGION additional codes are stored in TYPE2 and TYPE3 Codes are prioritized from most restrictions on use beginning with TYPE1 to fewest restrictions on use Thus if an area is both a national park and an Indian reservation TYPE1 contains 1 TYPE2 contains 4 and TYPE3 contains a blank The classification order is given below Codes Definitions 1 National park monument lakeshore parkway battlefield or recreation area National wildlife refuge game preserve or fish hatchery National scenic waterway or wilderness area Indian reservation Military reservation National forest or grassland Not a federal land area ONNBL N These three attributes contain the abbreviated English equivalents of the classifications defined above They are as follows e Parks monuments etc e Wildlife refuges etc e Waterways and wilderness areas e Indian reservation e Military reservation e National forest or grassland e Not a federal land area Geographic reference attributes These a
226. m Description Item Name Column Definition Column Definition Area AREA 13 N 6 4 12 F 3 Perimeter PERIMETER 13 N 6 4 12 F 3 Arc Internal Number coverage name 11 N 0 4 5 B User Assignable ID coverage name ID 11 N 0 4 5 B April 1992 B 1 Appendix B ArcUSA item definitions Line feature tables Coverage Names FTA2M FTA2M_N FTA2M_S FTA2M_W Layer Type 2 Line Arc Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition From Node Number FNODE 1 11 N 0 4 5 B To Node Number TNODE 12 11 N 0 4 5 B Left Polygon Number LPOLY 23 11 N 0 4 5 B Right Polygon Number RPOLY 34 11 N 0 4 5 B Arc Length LENGTH 45 13 N 6 4 12 F 3 Arc Internal Number coverage name 58 11 N 0 4 5 B User Assignable ID coverage name ID 69 11 N 0 4 5 B Notes 1 The coverage directory names For the ArcUSA 1 2M database the first coverage listed is for the full U S coverage The next three coverages listed represent the north south and west regions respectively The final letter of the regional coverages designates the region Where both state and county level coverages exist for a particular layer the letter S designates state and C designates county 2 The type of coverage Coverages that contain only polygons lines arcs or points require only one feature attribute table Many of the ArcUSA coverages contain both polygon
227. m Name Column Definition Column Definition STATE_FIPS CNTY_FIPS FIPS STATE_NAME CNTY_NAME SUB_REGION STAT_FLAG SALESFARMS SALES_1K AVG_SALES FARM_UNDIK SALE UNDIK F_1K_2500 S_1K_2500 F_2500_5K S_2500_5K FARM_5_10K SALE _5_10K F_10_20K S_10_20K _100_250K F_250_500K S_250_500K F_OVR_500K S_OVR_500K CROPFARMS CROPSALES 49 52 55 61 81 113 120 121 138 155 172 189 206 223 240 257 274 291 3 N 0 3 N 0 6 C 0 20 C 0 32 C 0 3 3 1 3 3 1 6 6 C 20 20 C 32 32 C 7 7 C 1 1 1 8 11 F 0 8 11 F 0 8 11 F 0 00 00 0O OO OO OO O0 HW OO OO eee m 00 00 0O OO OO OO O0 HW KH OO e eee e m gt gt gt ary ph ph pb ph pah p pnh 8 11 8 11 8 11 8 11 8 11 8 11 Hi H H t H a a a F F 0 F 0 F 0 F 0 F 0 continued ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 2M state and county statistical attribute layers Agricultural Product Market Value continued Polygon Attribute Table County Level Coverage continued dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Number of Farms Selling Grain GRAINFARMS 614 17 N 6 321 8 11 F 0 Total Value of Grain 1 000 GRAINSALES 631 17 N 6 329 8 11 F 0 Farms Selling Corn CORNFARMS 648 17 N 6 337 Value of Corn Sold 1 000 CORNSALES 665 17 N 6 345 Farms Selling Wheat WHEATFARM
228. make the river network look more familiar display the Boundaries layer with the Rivers and Streams layer ArcView 1 r ArcView 1 RA x Key a Oy Will le we Ka x Kemp y W ie we Feature drawing order The order in which features are drawn on the screen affects the final display For example if polygon features are shaded last the shades will cover any previously drawn shades line work and text You will need to experiment with the drawing order of the features you select in order to achieve the best display In general the following drawing order from bottom to top in the ArcView Table of Contents can help you achieve the desired display Color filled polygon shades Pattern filled polygons Lines or polygon borders Point features and text Py SS ArcUSA User s Guide and Data Reference April 1992 Chapter 6 Using the database A logical order can also often be identified for line features For example contour lines represent the ground drainage lines represent the flow of water over the ground and transportation lines represent bridges over the water By drawing these features in that order lines will be displayed by their logical hierarchy Choroplethic mapping Choroplethic mapping is the use of area shades or patterns to show the areal distribution of statistical information Many of the statistical attribute data are ideally represented by this type of mapping However to develop
229. meaningful comparisons you will often need to standardize the data by area or population For example the 1986 population of Arizona and Connecticut is 3 279 000 and 3 189 000 respectively If the area of the states is not taken into account a choropleth map would show the populations as approximately equal But Connecticut has less than 5 the area of Arizona so population density is 654 people per square mile as compared with twenty nine people per square mile for Arizona the population situations are very different In this instance the population density for both states is listed in an attribute named POP_SQMILE For other population variables however such as the number of people belonging to one race or another in the 1990 U S Census layer the data are absolute numbers and have not been standardized by area To simplify a display use the same patterns for the same ranges in all areas If the value of each state s density were given a unique value the resulting map would show forty eight unique shades which would be difficult to interpret Instead divide the data into a few classes which are easier to understand when they are mapped Cartographers generally recommend using from four to ten different classes some cartographers recommend using an odd number of classes so that there is one class that can be further categorized as high medium and low You can form classes by using the class values option in the ArcView legend w
230. measured in square miles Demographic attributes Total population for the state or county estimated for 1986 Rank of state or county by 1986 population State or county population per square mile for 1986 Corrected state or county population for 1980 4 95 Chapter 4 ArcUSA state and county statistical attribute layers Demographic and Health Attributes POP_CHG P_POP_CHG BIRTHS DEATHS NET_MIGR P_WHITE_84 P_BLK_OTH MALE_100F P_UNDER_5 P_5 14 P_15_24 P_25_34 P_35_44 P_45_54 P_55_64 P_65_74 P_OVER_74 4 96 Net population change from 1980 to 1986 for the state or county A negative value means that the population was smaller in 1986 than in 1980 Percentage population change from 1980 to 1986 for the state or county A negative value means that the population was smaller in 1986 than in 1980 Number of births in the state or county during the years 1980 through 1986 Number of deaths in the state or county during the years 1980 through 1986 Net migration from 1980 to 1986 for the state or county This value represents the difference between the number of persons moving into an area and the number of persons moving away from the area A negative value indicates net outmigration from the area Percentage of the total population for the state or county identified as white in 1984 Percentage of the total population for the state or county identified as being black or of a race
231. ment property taxes within a state or county in dollars per capita Local government direct general expenditures in millions of dollars summarized to the state and county levels Percentage of change in local government direct general expenditures from 1977 to 1982 for local governments within a state or county Local government direct general expenditures in dollars per capita summarized to the state and county levels Percentage of 1981 1982 local government expenditures averaged to the state and county levels for the following Education Health and hospitals Police protection ArcUSA User s Guide and Data Reference P_WELFARE P_HIGHWAY DEBT DEBT_CAP LOCGVT_EMP LG_EMP_10K FEDCIV_EMP FEDCV_EARN PRESVOTE84 P_VTE_LEAD LEAD_PARTY April 1992 Chapter 4 ArcUSA state and county statistical attribute layers Government and Financial Attributes Public welfare Highways Outstanding local government debt for 1981 82 for local governments within a state or county in millions of dollars and in dollars per capita Local government employment Local government employment and local government employment per 10 000 population as of October 1982 Federal government civilian employment and federal government civilian employee earnings in thousands of dollars 1984 Elections For the 1984 presidential election Total vote cast for President in the state or cou
232. ms Begin Column Begin Item Item Description Item Name Column Definition Column Definition Deaths 1984 DEATHS_ 84 437 11 N 0 162 4 7 B Infant Deaths 1984 INFANT_DTH 448 11 N 0 166 4 5 B Deaths per 1 000 Pop 1984 DEATH1KPOP 459 13 N 6 170 4 6 F 1 Infant Deaths per 1 000 Births INF_DTH_1K 472 13 N 6 174 4 6 F 1 Marriages 1984 MARRIAGES 485 11 N 0 178 4 7 B Marriages per 1 000 Pop 1984 MARRIAG_ 1K 496 13 N 6 182 4 7 F 1 Divorces 1984 DIVORCES 186 4 7 B Divorces per 1 000 Pop 1984 DIVORC_1K 190 4 7 F 1 Active Physicians 1985 DOCTORS 194 4 6 B Physicians per 1 000 Pop 1985 DOCT_100K 198 2 4 B Hospitals 1985 HOSPITALS 200 2 4 B Hospital Beds 1985 HOSP_BEDS 4 7 B Hospital Beds per 1 000 Pop HBEDS_1000 2 4 B Nursing Homes 1986 NURSEHOMES 4 5 B Nursing Home Beds 1986 NURSHM_BED 11 N 0 4 7 B Polygon Attribute Table County Level Coverage dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition State FIPS Code STATE_FIPS 49 3 N 0 17 3 3 1 County FIPS Code CNTY_FIPS 52 3 N 0 20 3 3 1 Combined FIPS Code FIPS 55 6 C 0 23 6 6 C State Name STATE_NAME 61 20 C 0 29 20 20 C County Name CNTY_NAME 81 32 C 0 49 32 32 C U S Subregion Code SUB_REGION 113 7 C 0 81 LAE Statistical Flag STAT_FLAG 120 1 N 0 88 1 1 1 County Type Code CNTY_TYPE 121 26 C 0 89 26 26 C Metro Statistical Area Code MET_ST_AR 4 C 0 115 4 4 C Consolidated MSA Code PR_MT_ST_A 4 C 0 119 4 4 C County Land Area
233. n Lawrence Salem Lowell Brockton 0440 Amn Arbor MI PMSA MA NECMA 0450 Anniston AL MSA 1200 Brockton MA PMSA 0460 Appleton Oshkosh Neenah WI MSA 1125 Boulder Longmont CO PMSA 0480 Asheville NC MSA 1140 Bradenton FL MSA 0500 Athens GA MSA 1145 Brazoria TX PMSA 0620 Atlanta GA MSA 1150 Bremerton WA MSA 0560 Atlantic City NJ NSA 1160 Bridgeport Milford CT PMSA 0600 Augusta GA SC MSA 1163 Bridgeport Stamford Norwalk Danbury 0620 Aurora Elgin IL PMSA CT NECMA 0640 Austin TX MSA 1170 Bristol CT PMSA 1200 Brockton MA PMSA B 1240 Brownsville Harlingen TX MSA 0680 Bakersfield CA MSA io RNY T 0720 Baltimore MD MSA 1282 Buffalo Niagara Falls NY CMSA 0730 Bangor ME MSA 1300 Burlington NC MSA 0760 Baton Rouge LA MSA 1303 Burlington VT NECMA 0780 Battle Creek MI MSA 1305 Burlington VT MSA 0840 Beaumont Port Arthur TX MSA p gt Vig C 16 ArcUSA User s Guide and Data Reference Appendix C FIPS codes 1320 1350 1360 1400 1440 1480 1520 1540 1560 1580 1600 1602 1620 1640 1642 1660 1680 1692 1720 1740 1760 1800 1840 1880 1900 1920 1922 1930 1950 1960 2000 2020 2040 2080 2082 2120 2160 2162 2180 2200 2240 2290 2320 2330 2335 2340 2360 2400 2440 Canton OH MSA Casper WY MSA Cedar Rapids IA MSA Champaign Urbana Rantoul IL MSA Charleston SC MSA Charleston WV MSA Charlotte Gastonia Rock Hill NC SC MSA Ch
234. n Jasper Jeff Davis Jefferson Jim Hogg Jim Wells Johnson Jones Karnes Kaufman Kendall Kenedy Kent Kerr Kimble King Kinney Kleberg Knox Lamar Lamb Lampasas La Salle Lavaca Lee Leon Liberty Limestone Lipscomb Live Oak Llano Loving Lubbock Lynn McCulloch McLennan McMullen Madison Marion Martin Mason Matagorda Maverick Medina Menard 329 331 333 335 337 339 341 343 345 347 349 351 353 355 357 359 361 363 365 367 369 371 373 375 377 379 381 383 385 387 389 391 393 395 397 399 401 403 405 407 409 411 413 415 417 419 421 423 425 427 429 431 433 435 437 439 441 443 Midland Milam Mills Mitchell Montague Montgomery Moore Morris Motley Nacogdoches Navarro Newton Nolan Nueces Ochiltree Oldham Orange Palo Pinto Panola Parker Parmer Pecos Polk Potter Presidio Rains Randall Reagan Real Red River Reeves Refugio Roberts Robertson Rockwall Runnels Rusk Sabine San Augustine San Jacinto San Patricio San Saba Schleicher Scurry Shackelford Shelby Sherman Smith Somervell Starr Stephens Sterling Stonewall Sutton Swisher Tarrant Taylor Terrell 445 447 449 451 453 455 457 459 461 463 465 467 469 471 473 475 477 479 481 483 485 487 489 491 493 495 497 499 501 503 505 507 Terry Throckmorton Titus Tom Green Travis Trinity Tyler Upshur Upton Uvalde Val Verde Van Zandt Victoria Walker
235. n the state or county in 1986 Percentage change in the civilian labor force from 1985 to 1986 in the state or county Unemployed civilian labor force in the state or county in 1986 Unemployment rate of the civilian labor force in the state or county in 1986 Line attributes Thorough definitions of these attributes are given on page 4 7 Geographic reference attributes The FIPS code of the states on either the left or right side of a boundary segment is contained in these attributes The states on either side of a boundary are identified by name in this attribute Classification attribute Each line is classified according to boundary type The codes are as follows Codes Definitions 1 County boundary 2 State boundary 3 International boundary 4 Coastline 4 123 Chapter 5 The ArcUSA 1 25M layers The ArcUSA 1 25M coverages represent generalized versions of some of the larger scale USA 1 2M coverages The ArcUSA 1 25M coverages have fewer attributes than the 1 2M coverages and are designed for people interested in either national level analysis or a quick exploratory reconnaissance before delving into the ArcUSA 1 2M layers for more detailed state or region level analysis The ArcUSA 1 25M layers are listed in the table below Cities County Boundaries Land Ocean Display Map Elements Rivers Roads State Boundaries Statistical Attributes by State Statistical Attributes by County April 19
236. nce attributes polygons and lines groups Statistical flag polygons Classification attributes lines Feature Numberot featur Number of class UMDerOLIEaAtUTES attributes Polygons Counties and 3 111 features represented by 3 444 independent cities polygons Lines County and Represented by 7 491 lines 4 independent city boundaries State boundaries Represented by 1 203 lines International Represented by 68 lines boundaries Shorelines Represented by 734 lines Polygon attributes Geographic reference attributes STATE_FIPS The state county and combined state county FIPS codes as CNTY_FIPS well as the state name and U S subregion can be used to FIPS select icul i particular county polygons for display or study The STATE_NAME CNTY NAME U S subregions are shown on the map on page 1 2 SUB_REGION April 1992 5 7 Chapter 5 The ArcUSA 1 25M layers County Boundaries STAT_FLAG m T_FIPS T_FIPS D nn ST_NAMES 5 8 Statistical flag Flag used to identify a single polygon for each county The codes are as follows Codes Definitions 0 Additional polygon 1 Largest polygon Line attributes Geographic reference attributes The FIPS codes of the states on the left and right sides of a boundary are contained in these attributes For county boundaries inside a state the left and right FIPS codes are the same For state boundaries the left and right FIPS codes are different The left and right sides o
237. ndaries shorelines April 1992 4 101 Chapter 4 ArcUSA state and county statistical attribute layers Environmental Attributes STATE_FIPS STATE_NAME SUB_REGION CNTY_FIPS FIPS CNTY_NAME STAT_FLAG CNTY_AREA CNTY_FED P_CNTY_FED CNTY_LND FED_R_LD P_FED_R_LD 4 102 Polygon attributes Geographic reference attributes The state and county FIPS codes state and county names and U S subregion can be used to select particular state or county polygons for display or study The U S subregions are shown on a map in Chapter 1 Statistical flag Flag to identify a unique polygon for each county or county equivalent The codes are as follows Codes Definitions O Other polygon 1 Largest polygon Land area and land use Total surface area of the county 1977 measured in hectares Total federal land area in the county in hectares and percentage of county area in federal land in 1977 Percentage is computed by dividing CNTY_FED by CNTY_AREA Land area of the county water area excluded 1977 in hectares Federal land area considered rural in hectares and percentage of the county land area in rural federal land in 1977 Percentage is computed by dividing FED_R_LD by CNTY_AREA ArcUSA User s Guide and Data Reference April 1992 NFD_R_LD P_NFD_R_LD RUR_LND P_RUR_LND URB_LND P_URB_LND WATER P_WATER SOILS_OK P_SOILS_OK SL_SMLTS P_SL_SMLTS SL_SVLTS P_SL_SVLTS Chapter 4
238. ndex 4 Metropolitan area attributes See Attribute Multispectral Scanner data See Landsat Nominal Scene Index layer NECMA New England County Metropolitan Area defined 4 91 4 93 Name attribute 3 11 Naming conventions 3 13 to 3 15 Negative numbers meaning of 3 9 4 73 4 80 see also Data suppressed Nested land areas classification of 3 11 4 8 Nominal scene center points see also Landsat Nominal Scene Index layer defined 4 39 query using 4 40 Nominal scene footprints defined 4 39 4 40 see also Landsat Nominal Scene Index layer Nominal scene index See Landsat Nominal Scene Index layer Normalization 6 2 North arrow 4 17 5 13 Numeric codes use of 3 10 Offsets use of in USGS topographic map sheets 4 46 4 47 Over edge extension use of in USGS topographic map sheets 4 46 4 47 PMSA Primary Metropolitan Statistical Area defined 4 91 4 92 4 93 Package components ix 1 3 Performance optimizing 6 1 to 6 2 by normalizing the database 6 2 by reducing number of attributes 6 1 by reducing number of features 6 1 by using the ArcUSA 1 25M layers 6 2 by using simple selection statements 6 2 ArcUSA User s Guide and Data Reference Place Names layer 1 2M 4 19 to 4 22 elevations for features in 4 21 generation of 3 17 4 19 item definitions B 7 production procedures for A 5 to A 6 A 10 Point defined 3 1 3 3 Point attribute table use of 3 4 explanation of columns in B 1 Political bound
239. ned as a string of x y coordinate pairs with beginning and ending points a ArcView 1 iG BSR Ko wy d Soc8 c 2 ao owas Polygons represent area features like counties Polygons have area and a perimeter A polygon is defined as a string of x y coordinate pairs with the same beginning and ending points April 1992 Chapter 3 Database concepts and organization 3 4 In the ArcUSA database coverages are given names that reflect their content such as CTY2M county boundary data at the 1 2 000 000 scale and AGINC agricultural product inventory data by county Two coverages for the USGS1 24 000 Quadrangle Series Index layer and the Lake and Other Water Bodies layer contain a very large number of features For these layers three regional coverages are provided in addition to the coverage that contains the full extent of the database The smaller coverages improve software performance during some operations The extents of the northern southern and western regional coverages are shown on the map in Chapter 1 Feature attribute tables The attributes of the polygons lines and points in a coverage are stored in feature attribute tables Each feature class in a coverage has its own table polygon attributes are stored in Polygon Attribute Tables PATS line attributes are stored in Arc Attribute Tables AATs and point attributes are stored in Point Attribute Tables PATs The
240. nition Latitude LATITUDE 80 4 C 0 29 4 4 C Longitude LONGITUDE 84 4 C 0 33 4 4 C U S Non U S Area Code US_NONUS 88 1 N 0 37 1 1 B 12 ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 2M index layers USGS 1 24 000 Topographic Quadrangle Series Coverage Names Q_ 24K Q_24KN Q_24KS Q_24KW Layer Type Polygon Polygon Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition USGS Quadrangle ID Number USGS_QD_ID 8 C 0 8 8 C Quadrangle Name QUAD_NAME 41 C 0 41 41 C Map Edition Number MAP_EDIT 1 C 0 1 1 C State FIPS Code One ST_FIPS1 3 N 0 3 3 1 State Name One ST_NAME1 20 C 0 20 20 C Area in State One ST1_SQ_MI 2 N 0 State FIPS Code Two ST_FIPS2 3 N 0 State Name Two ST_NAME2 20 C 0 Area in State Two ST2_SQ_MI 3 N 0 State FIPS Code Three ST_FIPS3 State Name Three ST_NAME3 Area in State Three ST3_SQ_MI State FIPS Code Four ST_FIPS4 State Name Four ST_NAME4 Area in State Four ST4_SQ_MI Total Quadrangle Area TOT_Q_SQMI Date of Revision DATE_REV Date of Publication DATE_PUB Date of Photo Revision PHOTO_R_DT April 1992 B 13 Appendix B ArcUSA 1 2M index layers USGS 1 100 000 Topographic Quadrangle Series Coverage Name Q_100K Layer Type Polygon Polygon Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition USGS Quadrang
241. ns Counties and 3 111 features represented by 4 409 110 independent cities of polygons coterminous United States Lines County state and Represented by 10 485 lines 4 international boundaries shorelines Market value of agricultural products Values given for agricultural products represent the gross market value before taxes and production expenses of all agricultural products sold or removed from the place in 1987 regardless of who received the payment They do not include payments received for participation in federal farm programs The value of crops sold in 1987 does not necessarily represent the sales from crops harvested in 1987 due to sale of stored crops or storage of new crops Sales figures are reported in current 1987 dollars and have not been adjusted for inflation 4 72 ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Inventory Using the Agricultural Product Inventory coverages Some attributes in these layers have the same names as attributes in the Agricultural Product Market Value layers but they contain a slightly different statistic For example in these layers COTTONFARM contains the number of farms that raised cotton during 1987 in the Agricultural Product Market Value layers COTTONFARM contains the number of farms that sold cotton An attribute containing a negative number indicates that no data exist or that data were sup
242. nsus County amp City Data Book 1988 USGS DLG SOC88C 7 80 5 67 1988 U S Census County amp City Data Book 1988 April 1992 1 7 Chapter 1 What is ArcUSA Table 4 ArcUSA 1 25M layers Features Points 108 major cities state capitals County Boundaries Polygons 3 444 counties independent cities Lines 9 496 county and state boundaries shorelines Land Ocean Display Polygons 510 land water Lines 749 features grid Annotation Canada Mexico Map Elements Polygons scale bar North arrow Lines scale bar North arrow Annotation map title scale Lines 2 162 perennial amp intermittent rivers braided streams canals Roads Lines 4 658 Interstates U S and state highways State Polygons 336 Boundaries states Lines 472 state and international boundaries shorelines Point attributes 9 city name type Polygon attributes 7 county and state names FIPS codes U S subregion Line attributes 4 boundary type geogr reference Polygon attributes 1 land water code Line attributes 1 feature grid code Polygon attributes area fill code Line attributes O Line attributes 5 river types geogr reference Line attributes 11 road types route numbers geogr reference Polygon attributes 4 states geogr reference Line attributes 4 boundary types geogr reference Source Currency USGS Concise Digital Database 1973
243. nty percentage of the total vote cast that was for the party that had a majority or plurality The leading party the party for which the percentage is given in P_VTE_LEAD The codes are as follows Codes Definitions 1 Democratic 2 Republican 4 113 Chapter 4 ArcUSA state and county statistical attribute layers Government and Financial Attributes Line attributes Thorough definitions of these attributes are given on page 4 7 Geographic reference attributes L ST FIPS The FIPS code of the states on either the left or right side of R_ST_FIPS a boundary segment are contained in these attributes ST NAMES The states on either side of a boundary are identified by name in this attribute Classification attribute BNDY TYPE Each line is classified according to boundary type The codes are as follows Codes Definitions 1 County boundary 2 State boundary 3 International boundary 4 Coastline 4 114 ArcUSA User s Guide and Data Reference Socio economic Attributes Polygons and lines for states Polygons and lines for counties Chapter 4 ArcUSA state and county statistical attribute layers Socioeconomic Attributes Layer descriptions These layers contain attributes describing households family structure education and income Other population attributes include the incidence of certain crimes and labor force participation Also included in these layers
244. ny layers in the database have been coded by geographic region and by state Thus if you know that your need for cartographic or attribute information is limited to one state or region selecting first by the appropriate values will speed up subsequent operations Any of the geographic reference attributes such as state and county names can be used for this selection The use of FIPS codes eliminates the need to spell out long state names like Massachusetts In ArcView use the Definition tool in the Theme Property Sheet to select the states or counties with which to work Reduce the number of attributes You can also reduce the number of attributes you work with If you are an ARC INFO user you can use commands like DROPITEM or PULLITEMS to eliminate unnecessary attributes If you use ArcView for Windows you can April 1992 6 1 Chapter 6 Using the database use commercially available PC software like Q E dBASE or FoxPro for this purpose Use simple selection statements Break complex selection logic statements into simpler statements For example to select all counties in Ohio in which the percentage of population between the ages of 5 and 14 is greater than 10 you could use the following complex statement STATE_NAME Ohio and P_5_14 gt 10 However the same selection logic can be expressed in the following two statements STATE_NAME Ohio P_5_14 gt 10 and these statements will search the database in less time th
245. oes not represent the general revenue of the state government April 1992 4 107 Chapter 4 ArcUSA state and county statistical attribute layers Government and Financial Attributes Summary of Government and Financial Attributes coverages State coverage Coverage name dBASE UNIX and size MB GOV88S 2 13 1 74 Source and currency Cartography from Digital Line Graphs current to 1973 Attribute data from U S Census Bureau County and City Data Book 1988 Thematic attribute Geographic reference attributes polygons and lines groups Statistical flag polygons County land area polygons Federal funds and grants polygons Local government finance polygons Local government employment polygons Elections polygons Classification attributes lines Feature Number of Polygons Coterminous states 49 features represented by 1 295 polygons plus District of Columbia Lines State and international Represented by 1 607 lines 4 boundaries shorelines 4 108 ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA state and county statistical attribute layers Government and Financial Attributes County coverage Coverage name dBASE UNIX and size MB GOV88C 7 12 5 43 Source and currency Cartography from Digital Line Graphs current to 1988 Attribute data from U S Census Bureau County and City Data Book 1988 Thematic attribute Metropolitan area attributes polygons groups County land area polygon
246. of 1 6 to 1 7 source and currency 3 16 Statistical flag attribute See Flag attribute Suppressed data See Data suppressed T 70 file 3 17 Thematic Mapper See Landsat Nominal Scene Index layer Title map 4 17 5 13 Topographic Names Database 3 17 Topographic quadrangle indexes see alsoUSGS 1 24 000 Topographic Quadrangle Series layer USGS 1 100 000 Topographic Quadrangle Series layer and USGS 1 250 000 Topographic Quadrangle Series layer deviations from USGS map sheets 4 46 to 4 47 generation of 3 16 3 19 relationship to latitude and longitude 4 45 Index 6 Units of measure used in data layers 6 5 U S Census of Agriculture characteristics of and layers employed in 3 18 U S Census of Population and Housing characteristics of and layers employed in 3 18 USGS 1 24 000 Topographic Quadrangle Series layer 1 2M 4 45 to 4 50 generation of 3 16 3 19 A 12 to A 13 item definitions B 13 recommended methods for query 4 47 to 4 48 relationship to USGS map sheets 4 47 4 48 4 49 to 4 50 and ST_NAME attributes 4 49 USGS 1 100 000 Topographic Quadrangle Series layer 1 2M 4 51 to 4 53 generation of 3 16 3 19 A 12 to A 13 item definitions B 14 relationship to USGS map sheets 4 52 4 53 USGS 1 250 000 Topographic Quadrangle Series layer 1 2M 4 54 to 4 57 generation of 3 16 3 19 A 12 to A 13 item definitions B 15 relationship to USGS map sheets 4 55 4 56 Zero values meaning of in Demographic and Health Att
247. of DLG coverages imprecise matching of line segments along source edges was corrected through manual edits Attribution The DLG minor major code structure was dropped in favor of a simplified coding scheme in which railroads were classified into six classes according to volume of traffic Items in the simplified coding scheme are TYPE classification code and RAIL_TYPE English equivalent of numerical code Items for state name STATE_NAMEB FIPS code STATE_FIPS and U S subregion SUB_REGION were added to enhance display flexibility Data quality review No special reviews were performed on this coverage Rivers and Streams layer Topological edits After the APPENDing of DLG coverages imprecise matching of line segments along source edges was corrected through manual edits Centerlines were digitized for all rivers that were wide enough to be ArcUSA User s Guide and Data Reference April 1992 Appendix A Data quality information represented as two inland shorelines in the DLG source data Where gaps existed in the rivers and streams coverage because of inland water bodies centerlines were added to achieve connectivity in the coverage Display of centerlines is therefore necessary in order to view a complete hydrological network Attribution River codes in the DLG source database consisted of a complex coding structure permitting a feature to be coded with multiple codes This coding scheme was replaced with a simpler sc
248. of the Map Elements coverage Coverage name dBASE UNIX and size MB SC_2M 0 02 0 03 Source and currency ESRI 1992 Thematic attribute groups Classification attributes polygons Annotation text Map title scale and North arrow Feature Number of class Number of features attributes Polygons All polygon features Represented by 15 polygons Lines All line features Represented by 43 lines ooe Polygon attributes Classification attribute FILL The scale bar is designed so it can be filled with alternating colors The arrowhead on the North arrow also can be filled The codes are as follows Codes Definitions 1 First color scale bar 2 Second color scale bar and North arrow 4 18 ArcUSA User s Guide and Data Reference Wapantpca National Wife Retoge C Marion Mempis April 1992 Chapter 4 ArcUSA 1 2M cartographic layers Place Names Layer description Point features representing major cities state capitals county seats national forests national parks lakes and reservoirs are contained in the Place Names layer The point attributes include the type and name of each feature The elevation of some features is also given Using the Place Names coverage The locations of the points in this coverage were taken from latitude longitude coordinates listed in the digital version of the National Atlas Gazetteer As is common for gazetteers the geographic coordinates were rounded so
249. old 1985 Total Households 1980 Households w Female Head One person Households Soc Security Recipients 1985 Soc Sec Recips 1 000 Pop Soc Sec Payments 1985 1K Supplemental Sec Recip 86 Serious Crimes 1985 B 42 ltem Name dBASE Columns Begin Column Column Definition INFO Items Begin Item Column Definition STATE_FIPS STATE_NAME SUB_REGION STAT_FLAG HSEHOLD_85 P_CHG_HHLD PERS_HHLD HSEHOLD_80 P_FEM_HHLD P_1PER_HH SSEC_RECIP SSRECIP_1K SSPAYMT_1K SUPP_RECIP SERIOUS_CR 3 N 0 20 C 0 7 C 0 1 N 0 11 N 0 13 N 6 13 N 6 11 N 0 13 N 6 13 N 6 11 N 0 13 N 6 11 N 0 11 N 0 11 N 0 ArcUSA User s Guide and Data Reference 3 3 1 20 20 C 7 7 C 4 7 F 1 4 8 B 4 1 B 4 8 B continued Appendix B ArcUSA 1 2M state and county statistical attribute layers Socioeconomic Attributes continued Polygon Attribute Table State Level Coverage continued Item Description Violent Crimes 1985 Serious Crimes per 100K Pop Public School Enrollment 86 Public School Enrollment 80 Pop with High School Educ Pop with 4 Yrs College Persons 25 Years of Age Loc Gov t Education Spending Per Capita Education Spending Income per Capita 1985 State Rank Income Capita 85 Income per Capita 1979 Income Capita 79 Constant Median Household Income 79 Persons Below Poverty 79 Persons of Poverty Status 79 Families Below Poverty 79 Family H
250. ons 1990 Census attributes polygons Farm and agricultural attributes polygons County land capability polygons Classification attribute lines Feature Number of featur Number of class AMOET ON eee attributes Polygons Counties and 3 111 features represented by 3 444 50 independent cities of polygons coterminous United States Lines County state and Represented by 9 496 lines 4 international boundaries shorelines These geographic reference attributes appear only in the county level coverages CNTY FIPS The county polygon coverages also contain the county FIPS FIPS codes the combined state and county FIPS codes and the CNTY_NAME county name 5 26 ArcUSA User s Guide and Data Reference April 1992 STAT_FLAG CNTY_TYPE MET_ST_AR PR_MT_ST_A LAND_AREA Chapter 5 The ArcUSA 1 25M layers Statistical Attributes Statistical flag Flag to identify a unique polygon for each county and county equivalent The codes are as follows Codes Definitions 0 Additional polygon 1 Largest polygon Metropolitan area attributes These attributes appear only in the county level coverage This attribute allows the user to select counties according to census geography The metropolitan area terms are explained on page 4 91 The codes are as follows e County within a CMSA PMSA e County within an MSA e County within an NECMA e County not in a metro area Metropolitan Statistical Area MSA or Consolidate
251. ortation lines 2 18 ArcUSA User s Guide and Data Reference 14 Click on the check box to the left of the 100K Topo Quad Areas This theme displays areas covered by USGS topographic quadrangles If you decide that you need a more detailed source determine which quadrangle covers your area of interest by using the Identify tool from the palette April 1992 Chapter 2 Exploring the ArcUSA database Locate the USGS 1 100 000 scale quadrangle that covers your area of interest 2 19 Chapter 2 Exploring the ArcUSA database Data documentation views Accompanying the ArcUSA database are two views arcusa2M av and arcusa25M av that provide summary information about the data When you enter one of these views you will first see a display of state boundaries for the full extent of the database as well as a title scale bar and North arrow 1 Click on the check box for any theme to display a sample of the indicated data Displays of certain cartographic coverages such as roads are limited to a single state or region because of feature density 2 Double click on any theme within arcusa2m av or arcusa25m av Within the comments box in the Theme Property Sheet you can access basic information about the content of any of the ArcUSA coverages Note that when you enter the Theme Property Sheet the bottom portion of the comments text block will
252. other than white in 1984 Number of males per 100 females in the state or county in 1984 Percentage of the state or county population between a given age range in 1984 For example P_5_14 is the percentage of population between 5 and 14 years of age ArcUSA User s Guide and Data Reference POP1984 P_AMERIND P_ASIAN P_HISPANIC POP1980 BIRTHS_84 P_BIR_TEEN BIR_1KPOP DEATHS_84 INFANT_DTH DEATH1KPOP INF_DTH_1K April 1992 Chapter 4 ArcUSA state and county statistical attribute layers Demographic and Health Attributes Total state or county population in 1984 This value was used to compute 1984 race and age population percentages Percentage of state or county population identified as American Indian Eskimo and Aleut in 1980 Percentage of state or county population of Asian and Pacific Island origin in 1980 Percentage of state or county population of Hispanic origin in 1980 Total state or county population in 1980 This value was used to compute 1980 population percentages for race and Hispanic origin Vital statistics Number of births in the state or county during 1984 Percentage of total births to mothers under 20 years old in the state or county in 1984 Number of births per 1 000 persons in the state or county in 1984 Number of deaths in 1984 in the state or county Number of infant deaths in the state or county in 1984 Figures for infant deaths include deaths of
253. ouseholds 1980 Housing Units 1980 Chg Housing Units 70 80 Occupied Housing Units 80 Owner Occupied Housing Housing Units 2 Cars Occupied Housing Units Est Median Housing Unit Value Authorized New Units 1986 Authorized New Units 1980 86 1980 Units w Permits 80 86 Civilian Labor Force 1986 Chg Labor Force 1985 86 Unemployed Civ Labor Force Unemployment Rate 1986 ltem Name dBASE Columns Begin Column Column Definition INFO Items Begin Column Definition Item VIOLENT_CR SR_CR_100K PUPILS86 PUPILS80 P_HS_GRADS P_COL_GRAD AGE_25_UP ED_DOL_1M ED_DOL_CAP INC_CAP_85 RNK_INCCAP INC_CAP_79 INC_CNST79 MED_INC_79 P_POVERTY POV_STATUS P_FAM_POV FAMILYHHLD HSE_UNITS P_CHG_HSE OCCUP_HSE P_OWN_OCC P_2CAR_OCC OCC_SAMPLE MEDIAN_DOL PERMIT_86 PRMT_80_86 P_PERMITS CIVLABOR86 P_CHG_CIV CIV_UNEMP UNEMP_RATE 211 222 233 244 255 268 281 292 305 316 327 338 349 360 371 384 395 408 419 443 454 467 480 491 502 513 524 537 11 N 0 92 11 N 0 96 100 104 108 112 116 120 124 126 130 132 136 140 144 148 152 156 160 13 N 6 4 7 B 4 5 B 4 8 B 4 8 B 4 6 F 1 4 6 F 1 4 9 B 4 10 F 2 4 B 4 5 B 2 4 B 4 5 B 4 5 B 4 5 B 4 6 F 1 4 9 B 4 6 F 1 4 9 B 4 8 B 4 6 F 1 4 8 B 4 6 F 1 4 6 F 1 4 8 B April 1992 B 43 Appendix B ArcUSA 1 2M state and county statistical attribute layers Socioeconomic Attribut
254. oute state route or other type of road Categories in classification attributes are generally mutually exclusive although in certain cases such as for prioritized attributes they may be used together Other attributes The remaining attributes in ArcUSA layers are grouped by topic to assist in locating the desired information Most of them are measurement attributes Some attribute groups in the county level Socioeconomic Attributes coverage are for example Households Social Security Crime Education Income and Labor Force Attributes Individual attributes in the Crime group include SERIOUS_CR number of serious crimes by county in 1985 VIOLENT_CR violent crimes and SR_CR_100K serious crimes per 100 000 population ArcUSA User s Guide and Data Reference Chapter 3 Database concepts and organization Table 2 Geographic reference attributes STATE_NAME The name of the state in which a feature is located and the FIPS STATE_FIPS code for the state CNTY_NAME The name of the county in which a feature is located and the CNTY_FIPS FIPS code for the county 1 FIPS The combined state county FIPS code SUB_REGION An abbreviation for the U S subregion in which a feature is located 2 MET_ST_AR For metropolitan counties the FIPS code for the Metropolitan Statistical Area MSA Consolidated Metropolitan Statistical Area CMSA or New England County Metropolitan Area NECMA PR_MT_ST_A For applicable metropolitan
255. over edge extensions offsets and inserts These irregularities in the map sheet boundaries are restricted to coastal areas and offshore islands More than one of these modifications may have been made to a single map sheet e In rotation the long east west axis of the map sheet is reoriented north south in order to parallel the direction of a long section of coastline This technique is restricted to the 1 250 000 and 1 100 000 map series 4 46 ArcUSA User s Guide and Data Reference April 1992 Chapter 4 ArcUSA 1 2M index layers USGS 1 24 000 Topographic Quadrangle Series e In an over edge extension one edge of a map sheet is extended in order to enlarge the coverage area for a single sheet e In an offset the location of a whole map sheet is shifted in order to create the best fit between the map sheet and the land area e The use of inserts refers to showing small isolated areas on unused portions of nearby map sheets The quadrangle boundaries in the ArcUSA database are entirely regular that is none of the modifications of map sheet size or location are reflected in the grids Therefore the quadrangles in the index do not necessarily correspond to the map sheets on which the land area is published Also note that because the index data were developed at a scale of 1 2 000 000 the location of the quadrangle boundaries on a zoomed in display may not correspond exactly to the boundary of the published map sheet Us
256. p a TA TT Reo igs Reo yy ooooooocoo ph ph pd p ph pd ph pb pd ph p PO DORO O OO 20 200 DO SUNFLW_LB 1277 COTTONFARM 1294 COTTONACRE 1311 COTTONBALE 1328 TOBACOFARM 1345 TOBACOACRE 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 17 N 6 Pounds of Sunflower Seed Farms with Cotton Acres of Cotton Bales of Cotton Harvested Farms with Tobacco Acres of Tobacco continued April 1992 B 25 Appendix B ArcUSA 1 2M state and county statistical attribute layers Agricultural Product Inventory continued Polygon Attribute Table County Level Coverage continued Item Description Pounds of Tobacco Harvested Farms with Soybeans for Beans Acres of Soybeans for Beans Bushels of Soybeans Farms with Dry Bean Acres of Dry Beans Dry Beans Harvested 100 Ibs Farms with Potatoes Acres of Potatoes Potatoes Harvested 100 Ibs Farms with Sugar Beets Acres of Sugar Beets Tons of Sugar Beets Harvested Farms with Sugar Cane Acres of Sugar Beets Tons of Sugar Beets Harvested Farms with Pineapples Acres of Pineapples Tons of Pineapples Harvested Farms with Peanuts for Nuts Acres of Peanuts Pounds of Peanuts Harvested Farms with Hay Acres of Hay Tons of Hay Harvested Farms with Vegetables Acres of Vegetables Farms with Orchards Acres of Orchards B 26 ltem Name dBASE Columns Begin Column Column Definition INFO Items Begin Column Item Definition TOBACO_LB SOYB
257. phic information systems If you ve never worked with a geographic information system you may want to get an introduction to basic GIS concepts before you read this guide in detail You should also be familiar with the basic tools of the software you ll be using ArcView ARC INFO or ArcCAD e To understand some basic concepts of GIS see What s GIS Chapter 5 of the ArcView User s Guide e The book Understanding GIS The ARC INFO Method is an excellent more extensive resource for novice ARC INFO users e The ARC INFO 6 0 handbook ARC INFO Data Model Concepts amp Key Terms will also be helpful e You can get excellent detailed information from the numerous published materials on geographic information systems See the bibliography for references to other materials that might prove useful April 1992 xi Getting started with ArcUSA Chapter 1 Chapter 2 xii Using ArcUSA data with ArcView This user s guide assumes that you are familiar with the basic tools and functionality of your ArcView software Although this manual concentrates on using the database with ArcView all of the applications discussed and more are possible using ARC INFO If you re new to ArcView and the ArcUSA database is the first database you ll be exploring begin by taking the ArcView guided tour see Chapter 2 of the ArcView User s Guide e Once you ve become familiar with ArcView explore the ArcUSA database by following the guided
258. podosol Ultisol Percent Ultisol Vertisol Percent Vertisol B 38 ltem Name dBASE Columns Begin Column Column Definition INFO Items Begin Column Item Definition SL_WILD P_SL_WILD SL_NO_AG P_SL_NO_AG DIST_LND P_DIST_LND COAL_MNS P_COAL_MNS SAND_EXT P_SAND_EXT OTH_MINE P_OTH_MINE ALFISOL P_ALFISOL ARIDISOL P_ARIDISOL ENTISOL P_ENTISOL HISTOSOL P_HISTOSOL INCEPTSL P_INCEPTSL MOLLISOL P_MOLLISOL SPODOSOL P_SPODOSOL ULTISOL P_ULTISOL VERTISOL P_VERTISOL 431 442 455 466 479 490 503 514 527 538 551 562 575 586 599 610 623 634 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 ArcUSA User s Guide and Data Reference 193 197 201 205 209 213 217 221 225 229 233 237 241 245 249 253 257 261 265 4 9 B 4 6 F 2 4 9 B 4 6 F 2 4 8 B 4 6 F 2 Appendix B ArcUSA 1 2M state and county statistical attribute layers Environmental Attributes continued Arc Attribute Table Item Description Left State FIPS Code Right State FIPS Code Adjacent States Boundary Type Code ltem Name dBASE Columns Begin Column Column Definition INFO Items Begin Item Column Definition L_ST_FIPS R_ST_FIPS ST_NAMES BNDY_TYPE Government and Financial Attributes Coverage Names Layer Type GOV88S GOV88C Polygon and Line 3 N 0 83 3 N 0 86 41 C 0 127 11 N 0 Polygon Attribute Table State Level Coverage
259. portation applications 4 29 Chapter 4 ArcUSA 1 2M cartographic layers Roads Summary of the Roads coverage Coverage name dBASE UNIX and size MB RDS2M 15 81 14 31 Source and currency USGS DLG 1980 Thematic attribute Classification attributes groups Geographic reference attributes Feature Number of Lines Interstate highways Represented by 5 406 lines 22 Limited access divided Represented by 1 153 lines highways Other U S highways Represented by 6 720 lines Other state primary Represented by 2 066 lines highways State secondary Represented by 4 960 lines highways Improved roads Represented by 911 lines Unimproved roads Represented by 27 lines Parallel highways Represented by 7 238 lines Toll roads Represented by 31 lines Tunnel Represented by 1 line Auto ferries Represented by 217 lines All line features Represented by 28 730 lines Note This table is for the ESRI Roads coding scheme 4 30 ArcUSA User s Guide and Data Reference April 1992 ESRI_CLASS ROAD_CLASS CLASS1 DLG_CLASS1 CLASS2 DLG_CLASS2 CLASS3 DLG_CLASS3 Chapter 4 ArcUSA 1 2M cartographic layers Roads Line attributes Classification attributes ESRI developed a simplified road classification system by condensing the more than twenty five road categories in the source database the DLG to only ten classes The code numbers are stored in ESRI_CLASS while the English equivalent is stored in ROAD_CLASS The codes are
260. pplemental Security Income program recipients in the state or county in June 1986 This program provides cash payments to persons with limited income and resources who are aged blind or disabled Crime Serious crimes known to police in 1985 for states and counties The seven serious crimes included in this figure are as follows e Murder and nonnegligent manslaughter includes deaths caused by negligence suicide or accident justifiable homicide and attempted murder Forcible rape excludes statutory rape Robbery Aggravated assault Burglary Larceny theft Motor vehicle theft Violent crimes known to police in 1985 for states and counties The first four serious crimes listed above are considered to be violent crimes Serious crimes known to police per 100 000 population by state and county in 1985 Education Public school enrollment for 1986 1987 by state and county Public school enrollment in 1980 by state and county Percentage of people in the state or county who were 25 years of age and older with 12 years or more education in 1980 ArcUSA User s Guide and Data Reference P_COL_GRAD AGE_25_UP ED_DOL_1M ED_DOL_CAP INC_CAP_85 RNK_INCCAP INC_CAP_79 INC_CNST79 MED_INC_79 P_POVERTY POV_STATUS P_FAM_POV FAMILYHHLD April 1992 Chapter 4 ArcUSA state and county statistical attribute layers Socioeconomic Attributes Percentage of people in the state or county who
261. pressed by the Census Bureau for that particular geographic unit Lack of data may result from a number of situations such as the suppression of information to maintain the privacy of individual farms The polygon and line attributes described below are present in both the state and county coverages except where specifically noted Polygon attributes Geographic reference attributes STATE FIPS The state FIPS code state name and U S subregion can be STATE NAME used to select particular state or county polygons for display SUB_REGION or study The U S subregions are shown on the map in Chapter 1 April 1992 4 73 Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Inventory CNTY_FIPS FIPS CNTY_NAME STAT_FLAG NO_FARMS FARM_ACRES AVG_SIZE LAND_BLD_F LAND_BLD_A MACHINE_F F_1_9ACRE F_10_49 F_50_179 F_180_499 F_500_999 F_OVER_999 CROP_FARMS CROP_ACRES HARVSTED_F HARVSTED_A 4 74 These geographic reference attributes appear only in the county level coverages The county polygon coverages contain the county FIPS code the combined state and county FIPS code and the county name Statistical flag Flag to identify a unique polygon for each state or county The codes are as follows Codes Definitions O Other polygon 1 Largest polygon General farm description attributes Number of farms amount of farmland in acres and average farm size in acres for the s
262. pression of information to maintain the privacy of individual farms 4 80 ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Market Value Summary of Agricultural Product Market Value coverages State coverage Coverage name dBASE UNIX and size MB AGVLS 3 61 2 49 Source and currency Cartography from Digital Line Graphs current to 1973 Attribute data from 1987 U S Census of Agriculture Table 2 Thematic attribute Geographic reference attributes polygons and lines groups Statistical flag polygons General agricultural product sales polygons Sales by commodity polygons Number of farms by Standard Industrial Code SIC polygons Classification attributes lines Feature Number of Polygons Coterminous states 49 features represented by 1 295 polygons plus District of Columbia Lines State and international Represented by 1 607 lines 4 boundaries shorelines April 1992 4 81 Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Market Value County coverage Coverage name dBASE UNIX and size MB AGVLC 11 97 7 81 Source and currency Cartography from Digital Line Graphs current to 1988 Attribute data from 1987 U S Census of Agriculture Table 2 Thematic attribute Same as for state level coverage above groups Feature Number of features Number of class attributes Polygons Counties an
263. products total market value of livestock poultry and related products sold in thousands of dollars Number of farms in the state or county selling poultry and poultry products total market value of poultry and poultry products sold in thousands of dollars Number of farms in the state or county selling dairy products total market value of dairy products sold in thousands of dollars Number of farms in the state or county selling cattle and calves total market value of cattle and calves sold in thousands of dollars Number of farms in the state or county selling hogs and pigs total market value of hogs and pigs sold in thousands of dollars Number of farms in the state or county selling sheep lambs and wool total market value of sheep lambs and wool sold in thousands of dollars Number of farms in the state or county selling other livestock and products total market value of other livestock and products sold in thousands of dollars ArcUSA User s Guide and Data Reference SICCASHGRN SICFLDCROP SICCOTTON SICTOBACCO SICOTHFLD SICVEG SICFRTNUT SICHORTSP SICGENCROP SICLVSTOCK SICBEEF April 1992 Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Market Value Number of farms by Standard Industrial Code SIC Farms in SIC for Cash grains SIC 011 Includes wheat rice corn soybeans barley buckwheat cowpeas dry field and seed beans and peas
264. quadrangle identification number As shown in the sketch below the ID number incorporates latitude longitude and an alphanumeric grid cell code ID numbers are included for theoretical quadrangles those that do not correspond exactly to published map sheets 37076 Fe 76 WSGs_OD0_ D 37076H1 Latude 37 Longtude 76 Index number H1 The quadrangle name The names of theoretical quadrangles indicate the quadrangle s relationship to the published map ArcUSA User s Guide and Data Reference April 1992 MAP_EDIT ST_FIPS1 ST_FIPS2 ST_FIPS3 ST_FIPS4 ST_NAME1 ST_NAME2 ST_NAME3 ST_NAME4 Chapter 4 ArcUSA 1 2M index layers USGS 1 24 000 Topographic Quadrangle Series on which the land area appears Charleston OE W for example The word digital in a quadrangle name also indicates that the quadrangle is theoretical It is usually used for quadrangles that show islands that are distant from the map sheets on which they are inserted A single number or letter code for the type of map If several types of maps exist for the same quadrangle the lowest code value is listed The codes are as follows Codes Definitions Surface minerals Bureau of Land Management Topography bathymetry line map Topography bathymetry orthophoto map 1 Topographic contour 3 Planimetric 9 Slope G Surface management status Bureau of Land Management H K L Quadrangle coverage attributes Thes
265. r Type Line Arc Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition River Classification Code TYPE 80 4 N 0 4 4 1 River Classification Code Name RIVER_TYPE 84 38 C 0 38 38 C State FIPS Code STATE_FIPS 122 3 N 0 3 3 1 State Name STATE_NAME 125 20 C 0 20 20 C U S Subregion Code SUB_REGION 145 7 C 0 TAS B 8 ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 2M cartographic layers Roads Coverage Name RDS2M Layer Type Line Arc Attribute Table dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Simplified Road Class ESRI_CLASS 80 2 2 1 Road Class Name Road Class One Road Class One Name Road Class Two Road Class Two Name Road Class Three Road Class Three Name Federal Interstate Route 1 Federal Interstate Route 2 Federal Interstate Route 3 U S Route Number One U S Route Number Two U S Route Number Three U S Route Number Four State Route Number One State Route Number Two State Route Number Three State Route Number Four State FIPS Code State Name U S Subregion Code April 1992 ROAD_CLASS CLASSI DLG_CLASS1 CLASS2 DLG_CLASS2 CLASS3 DLG_CLASS3 INTER RTE1 INTER RTE2 INTER RTE3 US_RTE1 US_RTE2 US_RTE3 US_RTE4 STATE_RTE1 STATE_RTE2 STATE_RTE3 STATE_RTE4 STATE_FIPS STATE_NAME SUB_REGION 82 120 122 186 188 2
266. r is drawn April 1992 Chapter 2 Exploring the ArcUSA database A coastal basemap with offshore water shaded The land2m or land25m layers can also be used to display Mexico and Canada in a different color than the United States To do this assign the land attribute a color other than white and then draw the U S state or county area polygons in a contrasting color Note to user The time required for accessing data once you open a view depends partly on the type of platform you are using Also a view that references large data sets like those in the ArcUSA 1 2M coverages requires more time for data access than views that reference smaller data sets like those in the ArcUSA 1 25M coverages 2 15 Chapter 2 Exploring the ArcUSA database 2 Click on the check box to the left TIP of the theme for Parks and To make room for new theme legends in the Table of Recreation Areas Contents use the Hide Legend option in the theme specific menu see page 2 9 in the ArcView User s Guide for more information on Hide Legend and Show Legend Or drag on the lower right hand corner of the Table of Contents box to enlarge the available legend display space National parks recreation areas and other federally administered areas are shaded green 3 Click on the check box to the left of the themes for Parks and County Seats The names and locations of all county seats as well as th
267. ration of 5 15 item definitions B 48 Roads layer 1 2M 4 29 to 4 33 data quality review procedures for A 11 data sources for 3 15 3 16 3 17 item definitions B 9 production procedures for A 5 to A 6 A 11 relationship of simplified and DLG classification systems 4 29 4 31 to 4 32 A 11 Roads layer 1 25M 5 18 to 5 19 generation of 5 18 item definitions B 49 Rotation use of in USGS topographic map sheets 4 46 Scale bar 4 17 5 13 Selection statements 6 2 6 6 Simplified road classes 4 29 4 31 Socioeconomic Attributes layer 1 2M 4 115 to 4 123 data sources for 3 16 3 17 3 18 to 3 19 item definitions B 42 to B 45 Software compatible with ArcUSA data 6 3 to 6 4 Software generated attributes 3 4 to 3 5 B 1 April 1992 Index 5 Index Software requirements x Source data See Data sources Standardizing data 3 8 to 3 9 stat_flag attribute See Flag attribute STAT_FLAG attribute See Flag attribute State Boundaries layer 1 2M 4 34 to 4 36 data quality review procedures for A 12 data sources for 3 15 3 16 3 17 item definitions B 10 production procedures for A 5 to A 6 A 12 State Boundaries layer 1 25M 5 20 to 5 22 generation of 3 8 item definitions B 49 to B 50 Statistical Attributes layer 1 25M 5 23 to 5 31 data sources and currency 5 23 generation of 5 23 A 19 item definitions B 50 to B 53 Statistical attribute layers 1 2M 4 59 to 4 123 characteristics 3 7 generation of A 13 list
268. rcUSA database range in currency the data for some of the coverages are as recent as 1988 but date back to 1980 Concise Digital Database The Concise Digital Database is a digital compendium of U S place names developed in 1973 in conjunction with the DLG The translation to digital form was made by the USGS s Geographic Names Information System GNIS The Concise Digital Database references each place name through latitude longitude coordinates The Concise Digital Database was the source for the Place Names and Cities cartographic layers The latitude longitude coordinates were used to generate the point feature coverage Some of the Concise Digital Database attributes such as the elevation attribute were also retained Other USGS data The USGS Topographic Names Database and the Published Map Sheet Data File also known as the T 70 file were the two primary digital sources for the attributes in the USGS Quadrangle Series index coverages Where these database were incomplete various published USGS map indexes were consulted to update the attributes Further explanatory information about USGS quadrangles can be found in the Catalog of Topographic and Other Published Maps and the Index to Topographic and Other Map Coverage U S Geological Survey Reston Va These USGS companion publications are available for every state Landsat nominal scene indexes The Landsat satellites are operated by the Earth Observation Satellite Company
269. rcUSA database uses a simpler coding scheme for rivers than the original DLG codes In the simpler system codes are prioritized and only one code is assigned to each river segment Elimination of river length in the DLG classifications also helped to simplify the scheme In these coverages river length is contained in the ARC INFO generated attribute LENGTH More information about ARC INFO generated attributes is given in Chapter 3 A number of spatial interactions are possible between rivers and political boundaries For example a political boundary may follow a river course precisely follow a historical river course or follow one shoreline For this reason if you are displaying a political unit such as a state the rivers along the political boundary may appear to lack continuity A more detailed discussion of coincident rivers and political boundaries is given in Chapter 5 The Rivers and Streams layer and the Lakes and Water Bodies layer can be displayed either individually or in combination When rivers are displayed alone the centerlines through the water bodies can be displayed to form a complete drainage network ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA 1 2M cartographic layers Rivers and Streams Summary of the Rivers and Streams coverage Coverage name and size MB RIV2M dBASE 16 48 UNIX 14 50 Source and currency USGS DLG 1973 Thematic attribute Classification groups class
270. re identified by name in this attribute 4 68 ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data Classification attribute BNDY TYPE Each line is classified according to boundary type The codes are as follows Codes Definitions 1 County boundary 2 State boundary 3 International boundary 4 Coastline April 1992 4 69 Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Inventory ArcView 1 4i xe 52 Xi 845491 0212 E te P yi 14160606013 Agin_s Boca Polygons and lines for states a E agi 367116 500 2602356 5342023 000 5815373 3 4550281728000 4194744381 15793 4681 3549 937 99059210 61941 260 1966762 750_ 8266 030 140845086 000 77378023 2303329 000 Polygons and lines for counties Layer descriptions Agricultural Product Inventory coverage attributes include general farm statistics for states and counties such as the total number of farms the number of farms of a given size and total acres of harvested crops Other attributes give more specific information about the number of farms acreage and yield for various agricultural products ranging from cattle to pineapples The next layer Agricultural Product Market Value focuses on the amount and value of products sold Using the agricultural stat
271. re the data on your own You will gain the most from these exercises if you are familiar with Arc View functions The emphasis of this tutorial is on exploring the database and not on how to use the software tools so it is recommended that you first do the exercises in Chapter 2 of the ArcView User s Guide This chapter will help you become familiar with the ArcUSA data such as the 1 25M Roads coverage shown in this ArcView display April 1992 2 1 Chapter 2 Exploring the ArcUSA database 2 2 In the first two exercises you will look at U S migration trends at the state and county levels from 1980 to 1986 and explore potential relationships between these migration trends and other statistical variables or attributes present in the ArcUSA database The third exercise teaches you how to create and analyze bivariate maps The fourth exercise involves preparing a coastal basemap and exploring the geographic factors involved in assessing the potential impact of a large oceanic storm on a coastal area The last exercise explores data documentation views The exercises are independent of each other and can be done in any order However because data display and query operations are described in more detail in the first exercise you are likely to gain more from the later exercises if you try the migration exercises first Getting started Begin by loading ArcView if you haven t already loaded and started ArcV
272. rest The 5 or 10 degree grids can be overlaid with this index to aid in geographic reference or to create displays of blocks of quadrangles ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA 1 2M index layers USGS 1 250 000 Topographic Quadrangle Series Summary of the USGS 1 250 000 Topographic Quadrangle Series Index coverage Coverage name dBASE UNIX and size MB Q_250K 0 42 0 44 Source and currency Attributes and origin from USGS Topographic Names Database Published Map Sheet Data File also known as the T 70 file and various published indexes Grid from an ESRI algorithm Current to 1986 Thematic attribute groups Classification attributes Feature Number of features Number of class attributes Polygons Areas covered by Represented by 488 polygons 13 USGS 1 250 000 quadrangles Polygon attributes Quadrangle identification attributes USGS QD ID The quadrangle identification number As shown in the sketch below the ID number incorporates latitude longitude and an alphanumeric grid cell code ID numbers are included for theoretical quadrangles those that do not correspond exactly to published map sheets me 37077 we 37076 75 2 USGS ODID 3707641 Lattude 37 Longtude 767 Index number 41 gt moo ma ea r Hr oo DF mn I are o mos 7 65432187 6 5 4 3 2 1 April 1992 4 55 Chapter 4 ArcUSA 1 2M index layers USGS 1 250 000 Topographic Quadrangle Series 4 56 QU
273. revision expressed as the last two digits of the year ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA 1 2M index layers USGS 1 250 000 Topographic Quadrangle Series DATE PUB Most recent date of publication expressed as the last two digits of the year April 1992 4 57 ArcUSA 1 2M state and county statistical attribute layers The coverages in the ArcUSA 1 2M statistical attribute layers provide a diverse set of statistics from a variety of sources for both the states and counties The sources are the U S Census the County and City Data Book the Census of Agriculture and the GeoEcology Database These diverse data permit the user to study the United States from a number of disciplinary viewpoints and to establish relationships between them All state and county rankings in ArcUSA 1 2M are based on data from all fifty states plus the District of Columbia even though information for only forty eight states plus the District of Columbia are included in the database For example the rank of states by population is based on fifty one political units but two ranks the ranks of Alaska and Hawaii will be missing from the list Each statistical attribute coverage contains either state or county boundaries so that the statistical attributes can be displayed on an appropriate cartographic base The state and county boundaries in the statistical attribute layers are identical to those provided in the cartographic layers coverag
274. ributes Polygons Land Represented by 471 polygons Water Represented by 39 polygons Lines Artificial grid lines Represented by 96 lines 1 Feature boundaries Represented by 653 lines Polygon attributes Classification attribute LND WAT Each polygon is classified as either land or water ocean and the Great Lakes as follows e Land e Water April 1992 5 11 Chapter 5 The ArcUSA 1 25M layers Land Ocean Display Line attributes Classification attribute BND GRID Each line segment is classified either as a feature boundary shorelines and international boundaries or an artificial grid line a data processing line that divides the data into geographic sections The codes are as follows Codes Definitions O Artificial grid line 1 Feature boundary or outer coverage extent line 5 12 ArcUSA User s Guide and Data Reference Map Elements Polygons and Lines April 1992 Chapter 5 The ArcUSA 1 25M layers Map Elements Layer description The Map Elements layer contains a scale bar North arrow and title that can be used to make your display look like a finished map Using the Map Elements coverage In the polygon theme the scale bar and the head of the North arrow are coded so that they may be filled with color An annotation theme provides the title and characters associated with the other map elements The scale is given in kilometers since the Albers Conic Equal Area Projection uses meters
275. ributes layer 1 2M 4 89 to 4 91 in Statistical Attributes layer 1 25M 5 24 ArcUSA User s Guide and Data Reference
276. rithm was spot checked visually to verify the validity of the scene footprints Data derived from U S Government tabular files The state and county statistical attribute layers are a combination of the cartography presented in the layers for State and County Boundaries and an additional set of statistical attributes The attributes were derived from the Census of Population and Housing 1990 the Digital County and City Data Book 1988 the U S Census of Agriculture Tables 1 and 2 1987 and the Oak Ridge National Laboratory GeoEcology Database 1967 1979 Each of these sources was acquired by ESRI as flat ASCII files which were loaded into INFO after empty INFO templates with the appropriate field widths were prepared Each of these tables was linked to the State and County Boundaries coverages through state and county FIPS codes Positional accuracy The positional accuracy of the ArcUSA 1 2M database is affected by the accuracy of sources of cartographic data the USGS DLGs and the ArcWorld data The accuracy of the database components that originated in the USGS DLGs can be inferred to have the same accuracy as the original plus the cumulative effects of the data processing performed at ESRI The original DLG data met the criteria for inclusion in the National Digital Cartographic Database A 13 Appendix A Data quality information A 14 90 percent of a minimum of 20 tested points must be within plus or minus 005 inch 127 mm
277. rl River 111 Perry 113 Pike 115 Pontotoc 117 Prentiss 119 Quitman 121 Rankin 123 Scott 125 Sharkey 127 Simpson 129 Smith 131 Stone 133 Sunflower 135 Tallahatchie 137 Tate 139 Tippah 141 Tishomingo 143 Tunica 145 Union 147 Walthall 149 Warren 151 Washington 153 Wayne 155 Webster 157 Wilkinson 159 Winston 161 Yalobusha 163 Yazoo Missouri 1 Adair 3 Andrew 5 Atchison 7 Audrain 9 Barry 11 Barton 13 Bates 15 Benton 17 Bollinger 19 Boone 21 Buchanan 23 Butler 25 Caldwell 27 Callaway 29 Camden 31 Cape Girardeau 33 Carroll 35 Carter 37 Cass 39 Cedar 41 Chariton 43 Christian 45 Clark 47 Clay 49 Clinton 51 Cole 53 Cooper Appendix C FIPS codes 137 139 141 143 145 147 149 151 153 155 157 159 161 163 165 167 169 Crawford Dade Dallas Daviess De Kalb Dent Douglas Dunklin Franklin Gasconade Gentry Greene Grundy Harrison Henry Hickory Holt Howard Howell Iron Jackson Jasper Jefferson Johnson Knox Laclede Lafayette Lawrence Lewis Lincoln Linn Livingston McDonald Macon Madison Maries Marion Mercer Miller Mississippi Moniteau Monroe Montgomery Morgan New Madrid Newton Nodaway Oregon Osage Ozark Pemiscot Perry Pettis Phelps Pike Platte Polk Pulaski 171 Putnam 173 Ralls 175 Randolph 177 Ray 179 Reynolds 181 Ripley 183 St C
278. rline and Centerline through a waterbody Next this result was checked visually and some rivers were reintegrated to provide an even cartographic appearance A number of spatial interactions between rivers and political boundaries are possible For example a political boundary may coincide with a river may follow a historical river course or may follow one shoreline For this reason if you are displaying a political unit such as a state a river along the political boundary may appear to lack continuity Illustrations of these situations and further discussion of coincident rivers and political boundaries are presented in Chapter 6 5 15 Chapter 5 The ArcUSA 1 25M layers Rivers Summary of the Rivers coverage Coverage name dBASE UNIX and size MB RIV_25M 0 52 0 46 Source and currency DLG 1973 Thematic attribute Classification attributes groups Geographic reference attributes an roe r Lines River shorelines Represented by 3 lines River centerlines Represented by 978 lines Perennial rivers Represented by 899 lines Intermittent rivers Represented by 12 lines Centerlines of Represented by 213 lines perennial streams through water bodies Centerlines of Represented by 2 lines intermittent streams through water bodies Braided rivers Represented by 50 lines Navigable canals Represented by 2 lines Other canals Represented by 3 lines All features Represented by 2 162 lines 5 16 ArcUSA User s G
279. rs Roads Summary of the Roads coverage Coverage name and size MB Source and currency DLG 1980 Thematic attribute groups Feature class Lines INTER_RTE1 INTER_RTE2 INTER_RTE3 US_RTE1 US_RTE2 US_RTE3 STATE_RTE1 STATE_RTE2 STATE_FIPS STATE_NAME SUB_REGION April 1992 RDS_25M dBASE 0 93 UNIX 0 75 Route numbers Geographic reference attributes Feature Number of features Number of attributes All roads Represented by 4 658 lines 11 Line attributes Route numbers Federal interstate route numbers If a road segment has multiple federal route numbers the lowest numeral will be present in INTER RTE1 A zero indicates that the interstate does not have additional route numbers or that the road segment is not part of the interstate highway system U S route numbers If a road segment has multiple U S route numbers the lowest numeral will be present in US_RTE1 A zero indicates that no U S route number applies State route numbers If a road segment has multiple state route numbers the lowest numeral will be present in STATE_RTEI A zero indicates that no state route number applies Geographic reference attributes Roads can be selected by the state name FIPS code or the subregion in which they are located 5 19 Chapter 5 The ArcUSA 1 25M layers State Boundaries 5 20 Layer description The State Boundaries layer serves as a basemap for the coterminous Un
280. rthern region coverages You can prevent them from appearing in a display if you wish by selecting only polygons with codes less than 9 9 is defined as not a water body Names for selected lakes and reservoirs are contained in the Place Names layer The Great Lakes which are outside the extent of ArcUSA can be displayed using the Land Ocean Display layer April 1992 4 11 Chapter 4 ArcUSA 1 2M cartographic layers Lakes and Other Waterbodies Summary of Lakes and Other Water Bodies coverages Coverage names dBASE UNIX and sizes MB LAK2M 3 97 3 93 LAK2M_N 1 78 1 81 LAK2M_S 1 30 1 35 LAK2M_W 0 92 0 95 Source and currency USGS DLG 1980 Thematic attribute Classification attributes groups Geographic reference attributes Feature Number of Polygons Perennial lakes Represented by 4 429 polygons Marshes Represented by 44 polygons Intermittent lakes Represented by 216 polygons Dry lakes Represented by 132 polygons Reservoirs Represented by 970 polygons Intermittent reservoirs Represented by 4 polygons Glaciers and snowfields Represented by 35 polygons Islands Represented by 527 polygons Background polygons Represented by 8 polygons All polygon features Represented by 6 365 polygons 4 12 ArcUSA User s Guide and Data Reference TYPE WATER_TYPE STATE_FIPS STATE_NAME SUB_REGION April 1992 Chapter 4 ArcUSA 1 2M cartographic layers Lakes and Other Water Bodies Polygon attributes Classificat
281. s Polygons Lines 4 34 Layer description The State Boundaries layer serves as a state base map for the coterminous United States The lower forty eight states plus the District of Columbia are represented as polygons and boundary lines Boundaries are classified as state or international boundaries or as shorelines Attributes for selecting geographic areas for display are contained in both the line and polygon attribute tables Using the State Boundaries coverage Some states like Michigan and New York are represented by multiple polygons Each of these polygons is assigned the statistics for the entire state The statistical flag attribute STAT_FLAG which identifies only one polygon per state can be used to prevent state totals from being added repeatedly during statistical analyses and to prevent text like the state name from being drawn repeatedly in a display The statistical attribute flag value has been assigned to the largest polygon in each state Political boundaries are terminated at the oceans and the Great Lakes In order to display the Great Lakes the oceans or adjacent portions of Mexico and Canada use the Land Ocean Display layer ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA 1 2M cartographic layers State Boundaries Summary of the State Boundaries coverage Coverage name dBASE UNIX and size MB ST2M 1 67 1 59 Source and currency USGS DLG 1973 Thematic attrib
282. s Plus the attribute groups listed for states above Feature Number of feat r Number of class UMDEr OF ieanures attributes Polygons Counties and 3 111 features represented by 4 409 41 independent cities of polygons coterminous United States Lines County state and Represented by 10 485 lines international boundaries shorelines The polygon and line attributes described below are present in both the state and county coverages except where specifically noted otherwise Polygon attributes Geographic reference attributes STATE_FIPS The state FIPS code state name and U S subregion can be STATE_NAME used to select particular state or county polygons for display SUB_REGION or study The U S subregions are shown on the map in Chapter 1 April 1992 4 109 Chapter 4 ArcUSA state and county statistical attribute layers Government and Financial Attributes CNTY_FIPS FIPS CNTY_NAME STAT_FLAG CNTY_TYPE MET_ST_AR PR_MT_ST_A 4 110 These geographic reference attributes appear only in the county level coverages The county polygon coverages contain the county FIPS code the combined state and county FIPS code and the county name Statistical flag Flag to identify a unique polygon for each state or county The codes are as follows Codes Definitions 0 Other polygon 1 Largest polygon Metropolitan area attributes These attributes appear only in the county level coverages This attribute allows
283. s 0 1 2 3 4 5 6 Missing values 0 Code numeric or alphabetic codes Null values numeric 9 99 999 9999 Not applicable values alphabetic blanks Name alphabetic or alphanumeric names Missing values blanks 10 alphanumeric characters only A Z 1 9 or allowed 10 primary and 3 extension alphanumeric characters xxxxxxxx PAT or AAT with A Z 1 9 or _ allowed 10 alphanumeric characters Tabular all attributes sorted by value Spatial all coverages spatially subdivided into quadrangles by feature density Albers Conic Equal Area Standard parallels 25 30 N 45 30 N Origin 96 00 W 23 00 N Data are also available in geographic coordinates expressed in decimal degrees Single coordinates rounded to the nearest meter A 4 ArcUSA User s Guide and Data Reference April 1992 Appendix A Data quality information Lineage The lineage of the ArcUSA 1 2M data includes four main sources e Data derived primarily from 1 2 000 000 scale USGS DLG e Data derived from ESRI s ArcWorld 1 3M database e Mathematically generated indexes e Data derived from tabular files published by the U S Bureau of the Census Data derived from USGS Digital Line Graphs Basic production process The following general processing methods are applicable to all layers derived from DLG data For a description of the characteristics of the DLG source data refer to the DLG user guide Digital Line Gr
284. s 45 Fairfield 159 Union 95 Marshall April 1992 C 11 Appendix C FIPS codes 97 99 101 103 105 107 109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 151 153 Oregon 1 Mayes Murray Muskogee Noble Nowata Okfuskee Oklahoma Okmulgee Osage Ottawa Pawnee Payne Pittsburg Pontotoc Pottawatomie Pushmataha Roger Mills Rogers Seminole Sequoyah Stephens Texas Tillman Tulsa Wagoner Washington Washita Woods Woodward Baker Benton Clackamas Clatsop Columbia Coos Crook Curry Deschutes Douglas Gilliam Grant Harney Hood River Jackson Jefferson Josephine Klamath Lake Lane Lincoln Linn Malheur Marion Morrow Multnomah Polk Sherman Tillamook Umatilla Union Wallowa Wasco Washington Wheeler Yamhill Pennsylvania 1 Adams Allegheny Armstrong Beaver Bedford Berks Blair Bradford Bucks Butler Cambria Cameron Carbon Centre Chester Clarion Clearfield Clinton Columbia Crawford Cumberland Dauphin Delaware Elk Erie Fayette Forest Franklin Fulton Greene Huntingdon Indiana Jefferson Juniata Lackawanna Lancaster Lawrence Lebanon Lehigh Luzerne Lycoming McKean Mercer Mifflin Monroe Montgomery Montour 95 Northampton 97 Northumberland 99 Perry 101 Philadelphia 103 Pik
285. s OATSFARMS 1100 17 N 6 Acres of Oats OATSACRES 1117 17 N 6 Bushels of Oats Harvested OATS_BU 17 N 6 Farms with Rice RICEFARMS 17 N 6 Acres of Rice RICEACRES 17 N 6 Rice Harvested 100 pounds RICE_CWT 17 N 6 Farms with Sunflowers for Seed SUNFLWFARM 17 N 6 Acres of Sunflowers for Seed SUNFLWACRE 17 N 6 HI t t ti H eo Hg g oooooocoo OO OO OO O0 O0 O0 00 00 00 OC ph ph pb p ph pb ph pb pad fd Pounds of Sunflower Seed SUNFLW_LB 17 N 6 Farms with Cotton COTTONFARM 17 N 6 Acres of Cotton COTTONACRE 17 N 6 Bales of Cotton Harvested COTTONBALE 17 N 6 Farms with Tobacco TOBACOFARM 17 N 6 Acres of Tobacco TOBACOACRE 17 N 6 Pounds of Tobacco Harvested TOBACO_LB 17 N 6 Farms with Soybeans for Beans SOYBEANFAR 17 N 6 Acres of Soybeans for Beans SOYBEANACR 17 N 6 Bushels of Soybeans SOYBEAN_BU 17 N 6 a TA TT Reo igs Reo yy ooooooocoo m ee ee m Farms with Dry Beans DRYBEANFAR 17 N 6 Acres of Dry Beans DRYBEANACR 17 N 6 Dry Beans Harvested 100 Ibs DRYBEANCWT 17 N 6 Farms with Potatoes POTATOFARM 17 N 6 Acres of Potatoes POTATOACRE 17 N 6 Potatoes Harvested 100 Ibs POTATO_CWT 17 N 6 continued B 22 ArcUSA User s Guide and Data Reference Appendix B ArcUSA 1 2M state and county statistical attribute layers Agricultural Product Inventory continued Polygon Attribute Table State Level Coverage continued Item Description Farms
286. s case AGINS agricultural product inventory data by state Such counterpart state and county level coverages are also described as a single layer in this manual April 1992 3 5 Chapter 3 Database concepts and organization ArcUSA database organization Do cum entaion Physical Organization Organizalon LAYERS COY ERAGES The ArcUSA database The ArcUSA database includes data at two scales 1 2 000 000 and 1 25 000 000 Data at both scales are presented in the Albers Conic Equal Area projection The 1 2 000 000 scale data are also presented in geographic coordinates expressed in decimal degrees in a second set of coverages The two sets of 1 2M coverages have identical names but they are delivered in different directories Any one coverage contains data at only one scale and in one projection coordinate system 3 6 ArcUSA User s Guide and Data Reference April 1992 Chapter 3 Database concepts and organization Characteristics of ArcUSA 1 2M coverages The ArcUSA 1 2M coverages contain more detail and a greater number of features and feature attributes than the 1 25M coverages This user s guide groups the coverages containing the 1 2 000 000 scale data into cartographic index and statistical state and county layers An overview of these three 1 2M layer groups follows Cartographic layers Coverages in the cartographic layers represent common basemap information made up of a variety of man made and natural geogr
287. s layers contain detailed total population counts and vital statistics data for states and counties Also important health indicators are provided These layers include some racial data but emphasize the total population dynamics for the geographic units represented Using the Census coverages from the County and City Data Book Attribute dates Coverages containing Demographic and Health Attributes Government and Financial Attributes and Socioeconomic Attributes contain U S Bureau of the Census data published in 1988 Note that even though these data were published in the same year they do not all apply to the same year For example some data are for 1986 some are for 1984 and still other data cover a range of years such as 1980 to 1986 This variety in dates should be considered when making data comparisons Zero values For some of the attributes in these County and City Data Book layers a zero value may represent something other than a measurement of zero It may represent an approximate value of zero measurements of greater than zero but less than half the measurement unit like less than half a hectare were rounded down to zero However a zero entry may also mean that data were unavailable that the actual value was suppressed by the Census Bureau for reasons of confidentiality or publication standards or that the measurement did not apply to that political unit April 1992 4 89 Chapter 4 ArcUSA state and coun
288. s three attributes that identify metropolitan counties The first attribute CNTY_TYPE identifies whether a county is considered a metropolitan county and if so which type The other two attributes MET_ST_AR and PR_MT_ST_A list the appropriate metropolitan area FIPS codes These attributes are more thoroughly defined in Using the Census coverages from the County and City Data Book beginning on page 4 89 A complete listing of metropolitan areas and their FIPS codes is given in Appendix C 5 23 Chapter 5 The ArcUSA 1 25M layers Statistical Attributes Zero values For some of the attributes in these coverages particularly the county level coverage a zero value may represent something other than a measurement of zero It may represent an approximate value of zero measurements of greater than zero but less than half the measurement unit like less than half a hectare were rounded down to zero However a zero entry may also mean that data were unavailable that the actual value was suppressed for reasons of confidentiality or publication standards or that the measurement did not apply to that political unit Additional information about attributes with zero values is given on pages 4 89 and 4 91 Those attributes for which zero indicates something other than a measurement of zero are marked with an asterisk in the attribute listings Definition of local government State and county information in these attributes represents
289. second function of the name attributes is to store place name information for the geographic features For example the attribute in the Place Names layer called NAME contains the names of cities national parks national forests and lakes April 1992 3 11 Chapter 3 Database concepts and organization 3 12 ArcUSA attributes In Chapters 4 and 5 the attributes within a coverage have been grouped by topic or theme regardless of the type of values they contain The thematic attribute groups provide logical organization to the sometimes long lists of coverage attributes and help the user locate data of interest in the online feature attribute tables The most common ArcUSA thematic attribute groups are described below Geographic reference attributes Geographic reference attributes allow the user to create displays that contain features located in a geographic area of interest such as one state Many ArcUSA layers include some geographic reference attributes although the specific attributes vary from one layer to another The geographic reference attributes used in the ArcUSA database are presented in Table 2 Classification attributes Classification attributes which occur primarily in the cartographic layers contain codes or names that give a typology to geographic features For example in the 1 2M Roads coverage the attribute ESRI_CLASS contains codes that specify whether a particular line represents an interstate U S r
290. sents a true offsetting of lines from their original positions Therefore a conservative estimate of the accuracy of the ArcUSA 1 2M data derived from the DLG 1 2M using a root sum square calculation is SQRT 1720 m 2 50 8 m 500 m 2 or 1792 m The positional accuracy of the ArcWorld 1 3M data is not known No detailed evaluation of the positional accuracy of this database has been made and knowledge of the source of the WDBII data is insufficient to make a determination in this regard Attribute accuracy The accuracy of most attributes in the ArcUSA 1 25M database has not been explicitly tested against independent sources However all of the data have been reviewed for anomalous visual patterns both on line and in hard copy Before generalization and attribute restructuring into the 1 25M design road rail and drainage features were plotted with various attribute combinations symbolized and reviewed against source lithographs for consistency in attribute coding After generalization and attribute restructuring the data were again subjected to the same process at the smaller scale Logical consistency All data were found to be topologically correct using ARC INFO Rev 6 0 1 No duplicate features are present All polygons are closed and all lines intersect where intended No undershoots or overshoots are present A 20 ArcUSA User s Guide and Data Reference Appendix A Data quality information Completeness The
291. sicians 1985 April 1992 POP_SQMILE POP1980CR POP_CHG P_POP_CHG BIRTHS DEATHS NET_MIGR P_WHITE_84 P_BLK_OTH MALE_100F P_UNDER_5 P_AMERIND P_ASIAN P_HISPANIC POP1980 BIRTHS_84 P_BIR_TEEN BIR_1KPOP DEATHS_84 INFANT_DTH DEATH1KPOP INF_DTH_IK MARRIAGES MARRIAG_IK DIVORCES DIVORC_1K DOCTORS 188 201 212 223 236 247 258 269 282 295 308 321 334 347 360 373 386 399 412 13 N 6 11 N 0 11 N 0 13 N 6 11 N 0 11 N 0 11 N 0 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 13 N 6 11 N 0 13 N 6 13 N 6 13 N 6 11 N 0 11 N 0 13 N 6 13 N 6 11 N 0 11 N 0 13 N 6 13 N 6 11 N 0 13 N 6 11 N 0 13 N 6 11 N 0 133 137 141 145 149 153 157 161 165 169 173 177 181 185 197 201 205 4 9 F 1 4 9 B 4 7 F 4 7 B 4 7 F 4 6 B continued B 35 Appendix B ArcUSA 1 2M state and county statistical attribute layers Demographic and Health Attributes continued Polygon Attribute Table County Level Coverage continued dBASE Columns INFO Items Begin Column Begin Item Item Description Item Name Column Definition Column Definition Physicians per 1 000 Pop 1985 DOCT_100K 630 11 N 0 277 2 4 B Hospitals 1985 HOSPITALS 641 11 N 0 279 Hospital Beds 1985 HOSP_BEDS 652 11 N 0 281 Hospital Beds per 1 000 Pop HBEDS_1000 663 11 N 0 285 Nursing Homes 1986 NURSEHOMES 674 11 N 0 287 Nursing Home Beds 1986 NURSHM_BED 685 11 N 0 2
292. son 5 Allamakee 55 Franklin 171 Scott 79 Jennings 7 Appanoose 57 Fulton 173 Shelby 81 Johnson 9 Audubon 59 Gallatin 175 Stark 83 Knox 11 Benton 61 Greene 177 Stephenson 85 Kosciusko 13 Black Hawk 63 Grundy 179 Tazewell 87 Lagrange 15 Boone 65 Hamilton 181 Union 89 Lake 17 Bremer 67 Hancock 183 Vermilion 91 La Porte 19 Buchanan 69 Hardin 185 Wabash 93 Lawrence 21 Buena Vista 71 Henderson 187 Warren 95 Madison 23 Butler 73 Henry 189 Washington 97 Marion 25 Calhoun 75 Iroquois 191 Wayne 99 Marshall 2T Carroll 77 Jackson 193 White 101 Martin 29 Cass 719 Jasper 195 Whiteside 103 Miami 31 Cedar 81 Jefferson 197 Will 105 Monroe 33 Cerro Gordo 83 Jersey 199 Williamson 107 Montgomery 35 Cherokee 85 Jo Daviess 201 Winnebago 109 Morgan 37 Chickasaw 87 Johnson 203 Woodford 111 Newton 39 Clarke 89 Kane 113 Noble 41 Clay 91 Kankakee Indiana 115 Ohio 43 Clayton 93 Kendall 1 Adams 117 Orange 45 Clinton 95 Knox 3 Allen 119 Owen 47 Crawford 97 Lake 5 Bartholomew 121 Parke 49 Dallas 99 La Salle 7 Benton 123 Perry 51 Davis 101 Lawrence 9 Blackford 125 Pike 53 Decatur 103 Lee 11 Boone 127 Porter 55 Delaware 105 Livingston 13 Brown 129 Posey 57 Des Moines 107 Logan 15 Carroll 131 Pulaski 59 Dickinson 109 McDonough 17 Cass 133 Putnam 61 Dubuque 111 McHenry 19 Clark 135 Randolph 63 Emmet 113 McLean 21 Clay 137 Ripley 65 Fayette 115 Macon 23 Clinton 139 Rush 67 Floyd 117 Macoupin 25 Crawford 141 St Joseph 69 Franklin 119 Madison 27 Daviess 143 Scott 71 Fremont 121 M
293. state or county selling grains total market value of grains sold in thousands of dollars Number of farms in the state or county selling corn for grain or seed total market value of corn sold for grain or seed in thousands of dollars Number of farms in the state or county selling wheat for grain total market value of wheat sold in thousands of dollars Number of farms in the state or county selling soybeans for beans total market value of soybeans sold in thousands of dollars ArcUSA User s Guide and Data Reference SORGHMFARM SORGHMSAL BARLEYFARM BARLEYSALE OATSFARMS OATSSALES OTHGRNFARM OTHGRNSALE COTTONFARM COTTONSALE TOBACOFARM TOBACOSALE HAYSILGFAR HAYSILGSAL VEGFARMS VEGSALES FRUITNUTFA FRUITNUTSA NURSRYFARM NURSRYSALE April 1992 Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Market Value Number of farms in the state or county selling sorghum for grain or seed total market value of sorghum sold in thousands of dollars Number of farms in the state or county selling barley for grain total market value of barley sold in thousands of dollars Number of farms in the state or county selling oats for grain total market value of oats sold in thousands of dollars Number of farms in the state or county selling other grain crops total market value of other grain crops sold in thousands of dollars Number of farms in the state or count
294. sub region stat flag births 84 Massachusetts N Eng 2 6 ArcUSA User s Guide and Data Reference Chapter 2 Exploring the ArcUSA database 11 Click once on Net Migration 1980 86 by State within the Table of Contents to highlight the theme 12 Select the Identify tool from the Tool Palette 13 Click once on the state of California with the Identify tool A window pops up that contains all attributes within the 1 25M stat_s coverage for the state of California 14 Scroll to the attribute tax_cap within the pop up window This attribute represents local government taxes for 1981 1982 in dollars per capita Californians paid an average of 429 per capita to local government during 1981 1982 Keep this window up for later comparison 15 Click on the Query Builder icon within the table 16 Click on the attribute net_migr within the scrolling list of attributes April 1992 2 7 Chapter 2 Exploring the ArcUSA database 17 18 19 20 Choose lt from the operators and enter 500000 on the line below the Values Attributes box The logical expression now reads net_migr lt 500000 Click Select Michigan will be highlighted as the only state that lost more than 500 000 people because of net migration from 1980 to 1986 Click once on the state of Michigan with the Identify tool from the palette
295. sus The coverages include population counts by race age and ethnicity which are known as Public Law 94 171 data because that law requires that these statistics be the first released from the new census and that they be utilized in the decennial process of congressional and legislative redistricting Using the 1990 U S Census Public Law 94 171 coverages The only category of population by age group included in this data set is people 18 years of age and older Hispanic origin is the only ethnic category and it is treated as an entirely separate variable from race In other words someone of Hispanic origin can belong to any one of the five race categories April 1992 4 61 Chapter 4 ArcUSA state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data Summary of 1990 U S Census Public Law 94 171 Data coverages State coverage Coverage name dBASE UNIX and size MB POP90S 2 49 1 87 Source and currency Cartography from Digital Line Graphs current to 1973 Attribute data from 1990 U S Census Thematic attribute Geographic reference attributes polygons and lines groups Statistical flag polygons Total population polygons Population by race polygons Adult population by race polygons Total Hispanic population polygons Non Hispanic population by race polygons Total adult Hispanic population polygons Adult non Hispanic population by race polygons Housing units polygons Classi
296. t and financial attributes polygons 1990 Census attributes polygons Farm and agricultural attributes polygons Classification attribute lines Feature Number of Polygons Coterminous states 49 features represented by 336 polygons plus District of Columbia All boundaries Represented by 472 lines The polygon and line attributes described below are present in both the state and county coverages except where specifically noted otherwise Polygon attributes Geographic reference attributes The state FIPS code state name and U S subregion can be STATE_FIPS i STATE NAME _ Used to select particular state or county polygons for display SUB_REGION or study The U S subregions are shown on the map in Chapter 1 April 1992 5 25 Chapter 5 The ArcUSA 1 25M layers Statistical Attributes County coverage Coverage name dBASE UNIX and sizes MB STATS_C 5 00 3 37 Source and currency Cartography from Digital Line Graphs current to 1988 Attribute data selected from various sources which are U S Census Bureau 1990 Census and Digital County and City Data Book 1988 U S Census of Agriculture Tables 1 and 2 1987 Oak Ridge National Laboratory GeoEcology Database various dates 1967 to 1979 Thematic attribute Geographic reference attributes polygons and lines groups County land area polygons Demographic attributes polygons Socioeconomic attributes polygons Government and financial attributes polyg
297. tate or county The average value in dollars of the land and buildings per farm and per acre for the state or county and the average estimated market value in dollars of machinery per farm for the state or county The number of farms between 1 acre and more than 999 acres in size in the state or county The number of farms in the state or county with cropland and total area of cropland in acres Number of farms in the state or county with harvested cropland area of harvested cropland in acres ArcUSA User s Guide and Data Reference IRRIGATE_F IRRIGATE_A VAL_CROPS VAL_ANIMAL FARMERS OTH_OPERS OTHJOB_ANY OTHJOB_200 AVG_AGE PROD_EXP AVG_EXP April 1992 Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Inventory Number of farms in the state or county with irrigated land area of irrigated land in acres Irrigated land includes all land watered by any artificial or controlled means such as sprinklers furrows or ditches and spreader dikes Value of crop and livestock sales Market value of crops sold for the state or county including nursery and greenhouse crops market value of livestock poultry and their products sold Both values in thousands of dollars Farm operators Number of farm operators in the state or county for whom farming is the principal occupation number of farm operators for whom farming is not the principal occupation Number of farm oper
298. te or county in 1985 Hospital beds comprise beds cribs and pediatric bassinets regularly set up and staffed for use of inpatients They exclude newborn infant bassinets Number of nursing homes in the state or county and number of nursing home beds in 1986 Homes with fewer than three beds are not counted ArcUSA User s Guide and Data Reference April 1992 L_ST_FIPS R_ST_FIPS ST_NAMES BNDY_TYPE Chapter 4 ArcUSA state and county statistical attribute layers Demographic and Health Attributes Line attributes Thorough definitions of these attributes are given on page 4 7 Geographic reference attributes The FIPS code of the states on either the left or right side of a boundary segment are contained in these attributes The states on either side of a boundary are identified by name in this attribute Classification attribute Each line is classified according to boundary type The codes are as follows Codes Definitions 1 County boundary 2 State boundary 3 International boundary 4 Coastline 4 99 Chapter 4 ArcUSA state and county statistical attribute layers Environmental Attributes Polygons and lines for counties 4 100 Layer description The Environmental Attributes layer contains a variety of attributes related to soils land capability and soil taxonomy as well as land use and surface mining attributes All of the environmental attributes are summarized by county Usin
299. tem Description No of Farms with Cropland Cropland in Acres Farms with Harvested Cropland Harvested Cropland in Acres Farms with Irrigated Land Irrigated Land in Acres Value of Crops Sold 1 000 Value of Livestock etc Sold Farmer as Principal Occupation Farmer as Other Occupation Farmers with Days Off Farm Farmers with 200 Days Off Average Age of Farmers Farm Expenses 1 000 Avg Expenses per Farm Farms with Cattle and Calves Number of Cattle and Calves Farms with Beef Cows Number of Beef Cows Farms with Dairy Cows Number of Dairy Cows Farms Selling Cattle amp Calves No of Cattle and Calves Sold Farms with Hogs and Pigs Number of Hogs and Pigs Farms Selling Hogs and Pigs Number of Hogs and Pigs Sold Farms with Sheep and Lambs Number of Sheep and Lambs Farms with Chickens Number of Chickens Farms Selling Broilers Number of Broilers Sold Farms with Corn for Grain etc Acres of Corn Bushels of Corn Harvested April 1992 ltem Name dBASE Columns Begin Column Column Definition INFO Items Begin Column Item Definition CROP_FARMS CROP_ACRES HARVSTED_F HARVSTED_A IRRIGATE_F IRRIGATE_A VAL_CROPS VAL_ANIMAL FARMERS OTH_OPERS OTHJOB_ANY OTHJOB_200 AVG_AGE PROD_EXP AVG_EXP CATTLEFARM CATTLE BEEFFARMS BEEFCOWS MILKFARMS MILKCOWS COWSOLDFAR CATTLESOLD HOGFARMS HOGS HOGSOLDFAR HOGS_SOLD SHEEPFARMS SHEEP CHICKENFAR CHICKENS BROILSLD_F BROIL_SOLD CORNF
300. the Landsat Nominal Scene Index coverages Point coverage Coverage name dBASE UNIX and size MB SAT_PT 0 18 0 18 Source and currency EOSAT nominal scene algorithm 1992 Thematic attribute groups Classification attributes Feature Number of Points Landsat 4 or 5 nominal 702 scene centers represented by 702 15 scene center points points A scene footprint resembles a polygon but is represented by a single self closing line The footprint boundary lines may be queried but because the footprints overlap somewhat we recommend that you query this layer by using the scene center points 4 40 ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA 1 2M index layers Landsat Nominal Scene Index Boundary coverage Coverage name dBASE UNIX and size MB SAT_BND 0 24 0 22 Source and currency EOSAT nominal scene algorithm 1992 Thematic attribute groups Classification attributes Feature Number of Lines Landsat 4 or 5 nominal 702 scenes represented by 702 lines 15 scene footprints Point attributes These attributes are also associated with the line coverage Classification attributes PATH Landsat 4 or 5 satellite path number and row number ROW SCN CENTER Latitude and longitude of the scene center expressed as z degrees minutes seconds North latitude and degrees minutes seconds West longitude Example 135 35 35N 135 35 35W ST FIPS1 These attributes contain the FIPS codes for the states the
301. the United States of America to verify the validity of particular codes Plots consisted of single attribute code plots Depending on the complexity of the codes either all codes or only a subset of valid codes was plotted to facilitate the review For example the Reservoir and Lake code classification might A 7 Appendix A Data quality information A 8 be plotted together to ensure that no reservoir feature had been coded as a lake or vice versa Cartographically nested codes for example an island enclosed by a lake that in turn was surrounded by a marsh were closely reviewed Codes found to be illegitimate were corrected State and county FIPS codes were very closely reviewed The reason for this close scrutiny was that these codes played a key role in the association of the statistical attribute data with the graphic data Both the state and county coverages were plotted out in full and each individual FIPS code state county combined was checked All FIPS codes found to be invalid or missing were corrected The FIPS codes were checked again after the graphic and the statistical attribute data were associated to ensure that the attribute data were assigned to the appropriate state and county This check represented a rigorous county by county review that entailed querying the FIPS codes associated with each county in each statistical attribute layer Layer specific processing County Boundaries layer Topological edits
302. the latitude longitude grids and dollars which may be expressed in different denominations like thousands of dollars Table 2 Units of measure in the ArcUSA database Layers in Which Used Common Equivalents Square miles USGS 1 24 000 Topographic Quadrangle 640 acres Series Index 259 hectares Demographic and Health Attributes 2 59 square km Government and Financial Attributes Socioeconomic Attributes Square meters All polygon layers 10 76 square feet Hectares Environmental Attributes 2 471 acres Acres Agricultural Product Inventory 0 405 hectares Length Meters All layers 3 281 feet Kilometers Map Elements scale bar 0 621 miles Volume Bushels Agricultural Product Inventory 35 238 liters 1 244 cubic feet Bales Agricultural Product Inventory Pounds Agricultural Product Inventory Hundredweight Agricultural Product Inventory 100 pounds CWT Agricultural Product Inventory 2 000 pounds April 1992 6 5 Chapter 6 Using the database 6 6 Drawing with ArcUSA Graphic results of selection operations The geographic features in most of the database layers are coded by state and region to facilitate selection operations Sometimes this type of coding can produce unexpected graphic results For example because rivers often meander in and out of a state a selection of features by state name will display only those river segments that are within the state and not those slightly outside the state boundary To
303. the state or county identified as Asian Percentage is computed by dividing ASIAN by POP1990 Number of people and percentage of population in the state or county identified as belonging to a race other than white black American Indian or Asian Percentage is computed by dividing OTHER by POP1990 Adult population by race Number of people 18 years of age and older in the state or county and percentage of population 18 years of age and older Percentage is computed by dividing TOTAL18 by POP1990 Number of people and percentage of population in the state or county identified as being white and 18 years of age or older Percentage is computed by dividing WHITE18 by TOTALI8 Number of people and percentage of population in the state or county identified as being black and 18 years of age or older Percentage is computed by dividing BLACK18 by TOTALI8 Number of people and percentage of population in the state or county identified as being American Indian and 18 years of age or older Percentage is computed by dividing AMERIN18 by TOTAL18 Number of people and percentage of population in the state or county identified as being Asian and 18 years of age or older Percentage is computed by dividing ASIAN18 by TOTALI8 4 65 Chapter 4 ArcUSA state and county statistical attribute layers 1990 U S Census Public Law 94 171 Data 4 66 OTHER18 P_OTHER18 HISPANIC P_HISPANIC NHISPAN P_NHISPAN NHWHITE P_NHWHITE NH
304. their positions may reflect some error Only one point has been coded for every unique place in this layer even though the feature itself may be an area that falls into more than one state For example Lake Tahoe is divided between California and Nevada and it is represented as two polygons in the Lakes layer In the Place Names layer however only a single point represents Lake Tahoe Since the point location lies in California California is given as the state of geographic reference Cities in this layer are coded as to whether they are major U S cities state capitals and or county seats Cities can be selectively displayed and symbolized for different purposes The point features and their place names are useful as general geographic identifiers especially for small scale maps They can also be used to label the equivalent area features in other layers The national parks and forests named in this layer correspond to the national parks and forests 4 19 Chapter 4 ArcUSA 1 2M cartographic layers Place Names Summary of the Place Names coverage Coverage name dBASE UNIX and size MB NAM2M 1 05 0 96 Source and currency USGS Concise Digital Database approximately 1973 Thematic attribute Classification attributes groups Geographic reference attributes Elevation Feature Number of Points Cities Represented by 3 096 points 10 National forests Represented by 174 points National parks Represented by 492 points
305. tier Furnas Gage Garden Garfield Gosper Grant Greeley Hall Hamilton Harlan Hayes Hitchcock Holt Hooker Howard Jefferson Johnson Kearney Keith Keya Paha Kimball Knox Lancaster Lincoln Logan Loup McPherson Madison Merrick Morrill Nance Nemaha Nuckolls Otoe Pawnee Perkins Phelps Pierce Platte Polk Red Willow Richardson Rock Saline Sarpy Saunders Scotts Bluff Seward Sheridan April 1992 C 9 Appendix C FIPS codes 163 Sherman 165 Sioux 167 Stanton 169 Thayer 171 Thomas 173 Thurston 175 Valley 177 Washington 179 Wayne 181 Webster 183 Wheeler 185 York Nevada 1 Churchill 3 Clark 5 Douglas 7 Elko 9 Esmeralda 11 Eureka 13 Humboldt 15 Lander 17 Lincoln 19 Lyon 21 Mineral 23 Nye 27 Pershing 29 Storey 31 Washoe 33 White Pine 510 Carson City New Hampshire 1 Belknap 3 Carroll 5 Cheshire 7 Coos 9 Grafton 11 Hillsborough 13 Merrimack 15 Rockingham 17 Strafford 19 Sullivan New Jersey 1 Atlantic 3 Bergen 5 Burlington 7 Camden 9 Cape May 11 Cumberland 13 Essex 15 Gloucester 17 Hudson 19 Hunterdon 21 Mercer 23 Middlesex 25 Monmouth 27 Morris 29 Ocean 31 Passaic 33 Salem 35 Somerset 37 Sussex 39 Union 41 Warren New Mexico 1 Bernalillo 3 Catron 5 Chaves 6 Cibola 7 Colfax 9 Curry 11 De
306. tional boundaries and shorelines Classification attribute Each line is classified according to boundary type The codes are as follows Codes Definitions 2 State boundary 3 International boundary 4 Coastline ArcUSA User s Guide and Data Reference Statistical Attributes Polygons and lines for states Stats_c 5 a F sa El OO mL ata area bi Polygons and lines for counties April 1992 Chapter 5 The ArcUSA 1 25M layers Statistical Attributes Layer descriptions The Statistical Attributes layers contain selected attributes from the ArcUSA 1 2M state and county statistical attribute layers These attributes include demographic socio economic local government financing and agricultural data for states and counties The county level layer also contains land capability attributes from the ArcUSA 1 2M Environmental Attributes layer Using the Statistical Attributes coverages Since the attributes in this layer come from several sources different types of considerations apply to different groups of attributes Note also that the data in these coverages are for various years For example some data are for 1980 others for 1984 while still other data cover a range of years such as 1980 to 1986 This variety in dates should be considered when making data comparisons Attributes for metropolitan areas The county level coverage contain
307. ton 11 Bourbon 13 Brown 15 Butler 115 117 119 121 123 125 127 129 131 Chase Chautauqua Cherokee Cheyenne Clark Clay Cloud Coffey Comanche Cowley Crawford Decatur Dickinson Doniphan Douglas Edwards Elk Ellis Ellsworth Finney Ford Franklin Geary Gove Graham Grant Gray Greeley Greenwood Hamilton Harper Harvey Haskell Hodgeman Jackson Jefferson Jewell Johnson Kearny Kingman Kiowa Labette Lane Leavenworth Lincoln Linn Logan Lyon McPherson Marion Marshall Meade Miami Mitchell Montgomery Morris Morton Nemaha 133 Neosho 135 Ness 137 Norton 139 Osage 141 Osborne 143 Ottawa 145 Pawnee 147 Phillips 149 Pottawatomie 151 Pratt 153 Rawlins 155 Reno 157 Republic 159 Rice 161 Riley 163 Rooks 165 Rush 167 Russell 169 Saline 171 Scott 173 Sedgwick 175 Seward 177 Shawnee 179 Sheridan 181 Sherman 183 Smith 185 Stafford 187 Stanton 189 Stevens 191 Sumner 193 Thomas 195 Trego 197 Wabaunsee 199 Wallace 201 Washington 203 Wichita 205 Wilson 207 Woodson 209 Wyandotte Kentucky 1 Adair 3 Allen 5 Anderson 7 Ballard 9 Barren 11 Bath 13 Bell 15 Boone 17 Bourbon 19 Boyd 21 Boyle 23 Bracken 25 Breathitt 27 Breckinridge 29 Bullitt 31 Butler 33 Caldwell 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143 145 147 149 Callowa
308. ts Total sales of agricultural products in the state or county and average sales of agricultural products per farm both in thousands of dollars The next twelve attribute pairs contain the number of farms in the state or county that sold products in a certain value range in 1987 and the total value of agricultural products sold by those farms in 1987 in thousands of dollars For example FARM_UND IK is the number of farms in the state or county that sold less than 1 000 worth of agricultural products and SALE_UND IK is the total value of agricultural products sold by farms that individually sold less than 1 000 worth of produce in thousands of dollars 4 83 Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Market Value 4 84 F_25 40K S_25_ 40K F_40_50K S_40_50K F_50_100K S_50_100K F_100_250K S_100_250K F_250_500K S_250_500K F_OVR_500K S_OVR_500K CROPFARMS CROPSALES GRAINFARMS GRAINSALES CORNFARMS CORNSALES WHEATFARMS WHEATSALES SOYBEANFAR SOYBEANSAL Number of farms in the state or county that sold products in a certain value range in 1987 and the total value of agricultural products sold by those farms in 1987 in thousands of dollars continued Sales by commodity Number of farms in the state or county selling crops including nursery crops total market value of crops and nursery crops sold in thousands of dollars Number of farms in the
309. ts data sources In greater detail The ArcUSA 1 2M layers Examines in detail the geographic features represented by each data layer Presents definitions and codes for all of the feature attributes This is the chapter you ll use most often during a work session The ArcUSA 1 25M layers Describes the features and attribute definitions for the ArcUSA 1 25M data set Using the database Suggests strategies for using the database to display and query and gives information about advanced applications like data export Strategies apply to both ArcView and ARC INFO users Describe enhancements made during database development Present attribute field definitions for both INFO and dBASE formats for use with advanced applications that use ARC INFO and ArcCAD List Federal Information Processing Standards FIPS codes and sources of additional information Provides information by a topic or key word xiii Chapter 1 What is ArcUSA A flexible U S database at two scales The ArcUSA database contains data for the coterminous United States at two scales The ArcUSA 1 2M data set is larger in both scale and content It was developed at a nominal scale of 1 2 000 000 the M in 1 2M stands for million and it contains representations of more than 100 000 features and more than 1 000 attributes The ArcUSA 1 25M data set represents a smaller scale map and contains a sample of the features and thematic attributes from the 1 2M database
310. ttributes which can be used for spatial selection store the state FIPS code state name and U S subregion in which the federal land area is located A federal land area that is located in more than one state is represented by multiple polygons each of which is assigned the appropriate state and subregional geographic reference information For example Yellowstone National Park is represented by three polygons one each in Wyoming Idaho and Montana ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA 1 2M cartographic layers Lakes and Other Water Bodies Lakes and Other Water Bodies Layer description The Lakes and Other Water Bodies layer contains more than 6 000 water body and island polygon features for the coterminous United States This number includes perennial lakes perennial reservoirs intermittent lakes intermittent reservoirs dry lakes marshes glaciers and snowfields Islands within any of these water bodies are also included Polygons Using the Lakes coverages In some complex hydrologic situations different types of water bodies may be located completely within others For example a perennial lake may be within a larger intermittent lake or a marsh may contain an island that in turn contains a perennial pond To clarify these displays use areas instead of lines to display water bodies and use different colors for different classes Background polygons are present in the full U S and no
311. turkeys duck geese pheasants pigeons and quail SICANIMLSP Animal specialties SIC 027 Includes fur bearing animals rabbits horses ponies bees fish in captivity except those in fish hatcheries worms and laboratory animals SICGENLVST General farms that primarily focus on special livestock SIC 029 Includes livestock farms where less than 50 of sales came from any single three digit industry group Line attributes Thorough definitions of these attributes are given on page 4 7 Geographic reference attributes L ST FIPS The FIPS code of the states on either the left or right side of R_ST_FIPS a boundary segment are contained in these attributes ST NAMES The states on either side of a boundary are identified by name in this attribute Classification attribute BNDY TYPE Each line is classified according to boundary type The codes are as follows Codes Definitions 1 County boundary 2 State boundary 3 International boundary 4 Coastline 4 88 ArcUSA User s Guide and Data Reference Demographic and Health Attributes 1988 State Pop Stats Hispanic at Oscar p pop_chg births deaths net_migr p_white 84 80 43000 2 92 09 97 Polygons and lines for states Polygons and lines for counties Chapter 4 ArcUSA state and county statistical attribute layers Demographic and Health Attributes Layer descriptions The Demographic and Health Attribute
312. ty statistical attribute layers Demographic and Health Attributes Summary of Demographic and Health Attributes coverages State coverage Coverage name dBASE UNIX and size MB POP88S 2 36 1 82 Source and currency Cartography from Digital Line Graphs current to 1973 Attribute data from U S Census Bureau County and City Data Book 1988 Thematic attribute Geographic reference attributes polygons and lines groups Statistical flag polygons Demographic attributes polygons Vital statistics polygons Health attributes polygons Classification attributes lines Feature Number of features Numberot class attributes Polygons Coterminous states 49 features represented by 1 295 polygons plus District of Columbia Lines State and international Represented by 1 607 lines 4 boundaries shorelines A zero in a group of closely related attributes often shares the same meaning For example in all nine population age group attributes in the county level data P_UNDER_5 etc a zero indicates that the actual value has been suppressed because the data did not meet publication standards Zeros representing suppressed data constitute 35 of each of the nine population age group attributes the largest percentage of this type of data in the database The second highest instance again for county level data is for the attributes for new private housing units authorized by permit PERMITS_ 86 etc where zeros occur in 19 of t
313. ugar tons of sugar beets for sugar harvested Number of farms in the state or county raising sugar cane for sugar acres of sugar cane for sugar tons of sugar cane for sugar harvested Number of farms in the state or county raising pineapples acres of pineapples tons of pineapples harvested Number of farms in the state or county raising peanuts for nuts acres of peanuts for nuts pounds of peanuts for nuts harvested Number of farms in the state or county raising hay acres of hay tons of hay harvested Hay includes grass silage haylage and green hay alfalfa other tame grasses small grain and wild grass silage Number of farms in the state or county harvesting vegetables sweet corn and melons for sale acres of vegetables harvested for sale Number of farms in the state or county with orchards acres of orchards with produce harvested for sale Line attributes Thorough definitions of these attributes are given on page 4 7 Geographic reference attributes The FIPS code of the states on either the left or right side of a boundary segment are contained in these attributes The states on either side of a boundary are identified by name in this attribute ArcUSA User s Guide and Data Reference April 1992 BNDY_TYPE Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Inventory Classification attribute Each line is classified according to boundary type The co
314. uide and Data Reference April 1992 Chapter 5 The ArcUSA 1 25M layers Rivers Line attributes Classification attributes TYPE The class number of the river or stream segment is stored in RIVER_TYPE TYPE its English equivalent is stored in RIVER_TYPE The codes are as follows Codes 1 NnBWN O on Equivalents River shorelines River centerlines Perennial river or stream Intermittent river or stream Centerline of perennial stream through a waterbody Centerline of intermittent stream through a waterbody Braided river or stream Navigable canal Other canal Geographic reference attributes STATE FIPS Rivers can be selected by the state name FIPS code or the STATE_NAME subregion in which they are located SUB_REGION 5 17 Chapter 5 The ArcUSA 1 25M layers Layer description The Roads layer contains selected roads particularly interstate highways from the ArcUSA 1 2M Roads layer Interstate U S and state route numbers have been retained Geographic reference attributes for the selection and display of a certain geographic area are given also Using the Roads coverage Lines This simplified Roads layer is especially useful for small scale U S or regional maps where a basic road network is needed for visual orientation It can be used with other ArcUSA 1 25M layers or in conjunction with ArcUSA 1 2M data 5 18 ArcUSA User s Guide and Data Reference Chapter 5 The ArcUSA 1 25M laye
315. umber of Lines Main lines heavy use Represented by 3 445 lines Main lines light use Represented by 3 931 lines Branch lines heavy Represented by 2 149 lines use Branch lines light use Represented by 2 763 lines Other railroad Represented by 883 lines Railroad ferry Represented by 11 lines All line features Represented by 12 182 lines 4 24 ArcUSA User s Guide and Data Reference Chapter 4 ArcUSA 1 2M cartographic layers Railroads Line attributes Classification attributes TYPE The railroad lines are classified according to volume of RAIL_TYPE traffic measured in tons The code number is stored in TYPE and the English equivalent is stored in RAIL_TYPE The codes are as follows Codes Equivalents 1 Main line bearing more than 20 tons annually 2 Main line bearing less than 20 tons annually 3 Branch line bearing more than 1 but less than 5 tons annually 4 Branch line bearing less than 1 ton annually 5 Other railroad 6 Railroad ferry Geographic reference attributes STATE FIPS Railroads can be selected by the state name state FIPS code STATE_NAME and U S subregion in which they are located SUB_REGION April 1992 4 25 Chapter 4 ArcUSA 1 2M cartographic layers Rivers and Streams 4 26 Layer description The Rivers and Streams layer contains perennial and intermittent rivers braided rivers canals ditches and stream centerlines Using the Rivers and Streams coverage The A
316. ummary tables April 1992 4 1 Chapter 4 In greater detail The ArcUSA 1 2M layers The layer descriptions do include geographic reference attributes because the list of those attributes differs slightly from one layer to the next the geographic reference attributes are described more thoroughly in Chapter 3 Detailed attribute field definitions for both dBASE and INFO formats are given for each layer in Appendix B 4 2 ArcUSA User s Guide and Data Reference ArcUSA 1 2M cartographic layers The coverages in the cartographic layers contain geographic features like roads rivers boundaries and place names which provide a general location context for the data in other layers The features in these coverages represent those that are often placed on maps to orient the user The cartographic coverages have few attributes other than those used for classification and geographic reference The county and state boundary coverages described in this section are identical to those used as the cartographic foundation for the state and county statistical attribute coverages described later The ArcUSA 1 2M cartographic layers and coverages are listed in the table below Layer County Boundaries CTY2M Lakes and Other Water Bodies Land Ocean Display Generalized versions of these layers are provided with ArcUSA 1 25M If you do not need the detail of the 1 2M coverage substituting a generalized coverage will minimize display time
317. ute Geographic reference attributes polygons and lines groups Statistical flag polygons Classification attributes lines Feature Number of Polygons Coterminous states 49 features Lae by 1 295 polygons plus District of Columbia Lines State boundaries Represented by 151 lines International Represented by 24 lines boundaries Shorelines Represented by 1 432 lines Polygon attributes Geographic reference attributes STATE FIPS The state FIPS code state name or U S subregion can be STATE_NAME used to select one or more state polygons for display or SUB_REGION study The U S subregions are shown on the map on page 1 2 April 1992 4 35 Chapter 4 ArcUSA 1 2M cartographic layers State Boundaries 4 36 STAT_FLAG m T_FIPS T_FIPS D nn ST_NAMES BNDY_TYPE Statistical flag This attribute is used to select a single polygon for each state The codes are as follows Codes Definitions O Other polygon 1 Largest polygon Line attributes Geographic reference attributes These attributes contain the FIPS codes of the states on either side of a state boundary The left and right sides of the boundary are defined by the direction in which the line segment was digitized so both attributes must be checked when querying for the boundaries of a particular state This attribute contains the names of states on both sides of a boundary Two states are listed for state boundaries e g Wisconsin Minnesot
318. ve was added Geographic and attribute data for the Latitude Longitude Grids coverages were also developed by ESRI The Land Ocean Display coverages which extend the U S ocean shorelines into Canada and Mexico were created from another ESRI product the ArcWorld database Special ArcUSA map titles and scale bars were created for the Map Elements coverages Coordinate systems The ArcUSA database is available in projections that promote usability as both stand alone data and in conjunction with other data sets ARC INFO users will 3 19 Chapter 3 Database concepts and organization be able to convert the database to other projections The ArcUSA 1 2M and 1 25M databases also feature a specified coordinate precision Projection systems The ArcUSA database employs the Albers Conic Equal Area projection at both the 1 2M and 1 25M scales This conic projection is implemented with standard parallels at 29 5 and 45 5 North latitude With this projection equal area is preserved but shape is somewhat distorted In general the shape of the regions between the two standard parallels becomes expanded and the shape of those beyond becomes compressed The coordinate units employed in conjunction with the Albers Conic Equal Area projection are meters The point of origin is 96 00 W and 23 00 N The ArcUSA 1 2M database is also delivered in decimal degrees Storage in geographic coordinates facilitates use with other data which are commonl
319. verages Demographic and Health Attributes Government and Financial Attributes and Socioeconomic Attributes The reference work for this data source is the County and City Data Book 1988 Files on CD ROM Technical Documentation U S Bureau of the Census Data Access and Use Staff Data User Services Division Washington D C 1989 GeoEcology Database The GeoEcology Database is a tabular digital database developed by the Oak Ridge National Laboratory for the U S Department of Energy The database contains environmental data for the counties of the coterminous United States The GeoEcology database included research efforts spanning extended geographic areas and addressing the long term impact of human activity on ecosystems in general The currency of the data varies the most recent entries range from 1979 The ArcUSA Environmental Attributes coverage employs a small subset of the GeoEcology data The reference work for this data source is GeoEcology A County Level Environmental Data Base for the Conterminous United States R J Olson C J Emerson and M K Nungesser Oak Ridge National Laboratory Oak Ridge Tenn 1980 ESRI in house development Several ArcUSA coverages do not have a specific source but were developed for the database by ESRI For example the 1 2 000 000 scale grids for the three USGS topographic quadrangle indexes were mathematically generated by ESRI then the attribute information from USGS sources mentioned abo
320. ville NC MSA Janesville Beloit WI MSA Jersey City NJ PMSA Johnson City Kingsport Bristol TN TN VA MSA Johnstown PA MSA Joliet IL PMSA Joplin MD MSA Kalamazoo MI MSA Kankakee IL MSA Kansas City MO KS MSA Kenosha WI PMSA Killeen Temple TX MSA Knoxville TN MSA Kokomo IN MSA La Crosse WI MSA Lafayette LA MSA Lafayette West Lafayette IN MSA Lake Charles LA MSA Lake County IL PMSA Lakeland Winter Haven FL MSA Lancaster PA MSA Lansing East Lansing MI MSA Laradeo TX MSA Las Cruces NM MSA Las Vegas NV MSA Lawrence KS MSA Lawrence Haverhill MA NH PMSA Lawton OK MSA Lewiston Auburn ME MSA Lewiston Auburn ME NECMA Lexington Fayette KY MSA Lima OH MSA Lincoln NE MSA Little Rock North Little Rock AR MSA Longview Marshall TX MSA Lorain Elyria OH PMSA Los Angeles Anaheim Riverside CA CMSA Los Angeles Long Beach CA PMSA Louisville KY IN MSA Lowell MA NH PMSA Lubbock TX MSA Lynchburg VA MSA Macon Warner Robins GA MSA Madison WI MSA Manchester NH MSA 4363 4800 4880 4890 4900 4920 4940 4992 5000 5015 5020 5040 5080 5082 5120 5160 5170 5190 5200 5240 5280 5320 5345 5350 5360 5380 5400 5403 5440 5480 5483 5520 5623 5560 5600 5602 5640 5700 5720 5760 5775 5790 5800 5880 5910 5920 5950 5960 5990 6000 Manchester Nasua NH NECMA Mansfield OH
321. were 25 years of age and older with 16 years or more education in 1980 Number of people in the state or county who were aged 25 years and older in 1980 This figure was used to compute P_HS_GRADS and P_COL_GRAD Local government expenditures for education in 1982 summarized for states and counties in millions of dollars and in dollars per capita Income Money income per capita in 1985 by state and county State or county rank by money income per capita in 1985 Money income per capita in 1979 in current dollars i e 1979 dollars by state and county Money income per capita in 1979 in constant dollars 1 e 1967 dollars by state and county This figure is computed using the Consumer Price Index The index for the base year 1967 equals 100 the index for 1979 equals 217 4 Median household income by state and county for 1979 Percentage of people below poverty level and number of people assigned poverty status for 1979 Percentage is computed using POV_STATUS Percentage of families below poverty level in the state or county in 1979 Family households in the state or county in 1980 This figure was used to compute P_FAM_POV 4 121 Chapter 4 ArcUSA state and county statistical attribute layers Socioeconomic Attributes 4 122 HSE_UNITS P_CHG_HSE OCCUP_HSE P_OWN_OCC P_2CAR_OCC OCC_SAMPLE MEDIAN_DOL PERMIT_86 PRMT_80_86 P_PERMITS Housing and construction Housing un
322. y Computed by dividing TOTAL by the land area of the state or county Percentage of the state or county population identified as white Computed by dividing WHITE by TOTAL Percentage of the state or county population identified as black Computed by dividing BLACK by TOTAL 5 29 Chapter 5 The ArcUSA 1 25M layers Statistical Attributes P_AMERIND P_ASIAN P_OTHER FARM_ACRES AVG_SIZE CROP_ACRES IRRIGATE_A SALES_1K AVG_SALES P_SL_NO_AG 5 30 Percentage of the state or county population identified as American Indian Computed by dividing AMERIND by TOTAL Percentage of the state or county population identified as Asian Computed by dividing ASIAN by TOTAL Percentage of the state or county population identified as belonging to a race other than white black American Indian or Asian Computed by dividing OTHER by TOTAL Farm and agricultural attributes The amount of farmland in the state or county in acres Average farm size in the state or county in acres Total area of cropland in the state or county in acres Area of irrigated land in the state or county in acres Market value of agricultural products sold from the state or county in thousands of dollars Average sales of agricultural products per farm in the state or county in dollars County land capability These attributes appear only in the county level coverage Percentage of the county land area with soils that are in
323. y Campbell Carlisle Carroll Carter Casey Christian Clark Clay Clinton Crittenden Cumberland Daviess Edmonson Elliott Estill Fayette Fleming Floyd Franklin Fulton Gallatin Garrard Grant Graves Grayson Green Greenup Hancock Hardin Harlan Harrison Hart Henderson Henry Hickman Hopkins Jackson Jefferson Jessamine Johnson Kenton Knott Knox Larue Laurel Lawrence Lee Leslie Letcher Lewis Lincoln Livingston Logan Lyon McCracken McCreary McLean C 6 ArcUSA User s Guide and Data Reference Appendix C FIPS codes 151 Madison 153 Magoffin 155 Marion 157 Marshall 159 Martin 161 Mason 163 Meade 165 Menifee 167 Mercer 169 Metcalfe 171 Monroe 173 Montgomery 175 Morgan 177 Muhlenberg 179 Nelson 181 Nicholas 183 Ohio 185 Oldham 187 Owen 189 Owsley 191 Pendleton 193 Perry 195 Pike 197 Powell 199 Pulaski 201 Robertson 203 Rockcastle 205 Rowan 207 Russell 209 Scott 211 Shelby 213 Simpson 215 Spencer 217 Taylor 219 Todd 221 Trigg 223 Trimble 225 Union 227 Warren 229 Washington 231 Wayne 233 Webster 235 Whitley 237 Wolfe 239 Woodford Louisiana 1 Acadia 3 Allen 5 Ascension 7 Assumption 9 Avoyelles 11 Beauregard 13 Bienville 15 Bossier 17 Caddo 19 Calcasieu 21 Caldwell 115 117 119 121 123 125 127 Cameron Catahoula Claiborne Concordia D
324. y in 1985 Number of marriages per 1 000 people in the state or county in 1984 Number of hospital beds per 1 000 persons in the state or county in 1985 Socioeconomic attributes The number of Social Security beneficiaries per 1 000 population in the state or county in 1985 Serious crimes known to police per 100 000 population in the state or county in 1985 ArcUSA User s Guide and Data Reference P_COL_GRAD INC_CAP_85 MEDIAN_DOL FEDFUNDGRT TAX_CAP LG_EMP_10K PRESVOTE84 POP1990 TOTAL_SQMI P_WHITE P_BLACK April 1992 Chapter 5 The ArcUSA 1 25M layers Statistical Attributes Percentage of state or county population 25 years of age and older with 16 years or more education in 1980 Money income per capita in the state or county in 1985 The median value of occupied housing units in the state or county 1980 in dollars Government and financial attributes Federal funds and grants to local governments in 1986 summarized to the state or county level in millions of dollars Local government taxes in 1981 1982 in dollars per capita summarized to the state or county level Local government employment per 10 000 population as of October 1982 summarized to the state or county level Votes cast for President in the 1984 presidential election 1990 Census attributes Total population of the state or county in 1990 Average population per square mile in the state or count
325. y supplied in decimal degrees and enables conversion into the projection of choice for update or analysis The units of measure used with the decimal degrees are spherical latitude longitude coordinates For example the latitude longitude coordinate of 37 30 15 is expressed as 37 50417 Albers Conic Equal Area projection with two standard parallels 3 20 ArcUSA User s Guide and Data Reference April 1992 Chapter 3 Database concepts and organization Datums The horizontal datum used is the North American Datum of 1927 NAD1927 and the vertical datum used is the National Geodetic Vertical Datum of 1929 NGVD 1929 The vertical datum applies only to the Place Names layer that contains elevation information Coordinate precision Coordinate precision refers to the maximum number of digits allocated within a data file for the storage of an x y or z coordinate value Single precision maps store as many as seven significant digits for each coordinate All ArcUSA data are in single precision This means that any x y coordinate in the ArcUSA database has a locational accuracy at least to the nearest meter Projection conversion capability ARC INFO users can employ the PROJECT command to convert the ArcUSA data into other projections A coordinate system definition file PRJ is included for each ArcUSA coverage and can be used in ARC INFO for map projection conversions This option is not available to ArcView users 3 21 Chapt
326. y selling cotton and cottonseed total market value of cotton and cottonseed sold in thousands of dollars Number of farms in the state or county selling tobacco total market value of tobacco sold in thousands of dollars Number of farms in the state or county selling hay total market value of hay sold in thousands of dollars Hay includes grass silage haylage and green hay alfalfa other tame grasses small grain and wild grass silage Number of farms in the state or county selling vegetables sweet corn and melons total market value of vegetables sweet corn and melons sold in thousands of dollars Number of farms in the state or county selling fruits nuts and berries total market value of fruits nuts and berries sold in thousands of dollars Number of farms in the state or county selling nursery and greenhouse crops total market value of nursery and greenhouse crops sold in thousands of dollars 4 85 Chapter 4 ArcUSA state and county statistical attribute layers Agricultural Product Market Value OTHCROPFAR OTHCROPSAL LVSTPOUL_F LVSTPOUL_S POULTRYFAR POULTRYSAL DAIRYFARMS DAIRYSALES CATTLEFARM CATTLESALE HOGFARMS HOGSALES SHEEPFARMS SHPWOOLSAL OTHLVSTFAR OTHLVSTSAL 4 86 Number of farms in the state or county selling other crops total market value of other crops sold in thousands of dollars Number of farms in the state or county selling livestock poultry and related

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