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Using ArcGIS Spatial Analyst

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1. 4 5 L 0 66 E 6 Ms Mo E 10 Reclassified Landuse 3 E 3 0 34 m4 E gt Landuse E 6 m7 8 Reclassified Slope 10 High cell values are the more costly cells through which to route the road PERFORMING SPATIAL ANALYSIS 127 Combining the datasets The final cost raster is the result of adding the weighted datasets together ee 27 1 98 1 66 Taking this example the following diagram shows the final cost raster the result of reclassifying the datasets of slope and landuse weighting each by 0 66 and 0 34 respectively then combining the weighted datasets The cells shaded dark blue are the most suitable cells through which to route the road as they are the least costly 128 The Cost Weighted Distance function Using the cost raster and the source the Cost Weighted Distance function produces an output raster in which each cell is assigned a value that is the least accumulative cost of getting back to the source Using our example the function takes the cost raster and calculates a value for each cell in the output cost weighted distance raster that is the accumulated least cost of getting from that cell to the nearest source Every cell in the cost weighted distance raster is assigned a value that represents the sum of the minimum travel costs that would be incurred by traveling back along the least cost path to its nearest source In the example below the acc
2. Annulus Cells that fall within the annulus will be included in the processing of the neighborhood The inner radius specifies the radius of the inner circle of the annulus from the center of the processing cell Any cell falling within the radius will not be Usinc ArcGIS Spatiat ANALYST included in the processing of the neighborhood The outer radius specifies the radius of the outer circle of the annulus from the center of the processing cell The outer circle defines the extent of the neighborhood Any cell center falling within the radius of the outer circle but outside the radius of the inner circle will be included in the processing of the neighborhood The radius is identified in cells or map units measured perpendicular to the x or y axis LS Wedge Cells that fall within the wedge will be included in the processing of the neighborhood The wedge is created by specifying a radius and an angle The radius is specified in either cell or map units from the center of the processing cell measured perpendicular to the x or y axis The start angle for the wedge can be an integer or floating point value from 0 to 360 Values for the wedge begin at 0 on the positive x axis and increase counterclockwise until they return full circle to 0 The end angle for the wedge can be an integer or floating point value from 0 to 360 The angle defined by the start and end values is used to create the wedge All cells that fal
3. ArcGIS 9 Spatial Analyst ArcGIS ing Us Copyright 2001 2002 ESRI All rights reserved Printed in the United States of America The information contained in this document is the exclusive property of ESRI This work is protected under United States copyright law and other international copyright treaties and conventions No part of this work may be reproduced or transmitted in any form or by any means electronic or mechanical including photocopying and recording or by any information storage or retrieval system except as expressly permitted in writing by ESRI All requests should be sent to Attention Contracts Manager ESRI 380 New York Street Redlands CA 92373 8100 USA The information contained in this document is subject to change without notice DATA CREDITS Yellowstone National Park data National Park Service Yellowstone National Park Wyoming Joshua Tree National Park data National Park Service Department of the Interior U S Government Haul Cost Analysis map Boise Cascade Corporation Boise Idaho Quick start tutorial data courtesy of the State of Vermont CONTRIBUTING WRITERS Jill McCoy Kevin Johnston Steve Kopp Brett Borup Jason Willison Bruce Payne U S GOVERNMENT RESTRICTED LIMITED RIGHTS Any software documentation and or data delivered hereunder is subject to the terms of the License Agreement In no event shall the U S Government acquire greater than RESTRICTED LIMITED RIGHTS At
4. Layer Predictive Model Results 7 ip iih i Drug Trafficking Spatial Ani Illegal Drug Deaths 16th Street Line 16th Street Line Mask Drug Arrests 2 5 Months al gl E HNO District o K Major Streets Streets Railroads Rivers Lakes Canals Bays Local Parks National Parks Predictive Model Results VALUE fmo 35 Gi 35 42 833 GB 42 833 50 667 WB 50 667 58 5 58 5 66 333 WB 66 333 74 167 Me 4 167 82 x6 Plus Bars VALUE C 12 4 167 E 4 167 3 667 P 3 667 11 5 P 11 5 19 333 OR WARE K KKK K KKOO K Display Source anja B gt Arial Drawing 241 78 85 66 Miles Model results aid in visual analysis The darker red areas show locations predicting the highest level of drug traffic while the yellow dots represent the drug arrest locations for a three month period There is a high correlation between the two There is also a marked difference in the number of arrests when you go west of 16 Street INTRODUCING ARCGIS SpatiAL ANALYST Finding suitable locations Use the Spatial Analyst to query your data to identify locations that meet your set of objectives or produce a suitability map combining datasets to analyze suitability 1 JoshuaTreeNP_mxd ArcMap ArcView File Edit View Insert Selection Tools Window Help be amp a ex gt a 1 39 397 sf h Spatial Analyst Lay
5. Spatial Analyst S Layer elevation 7 j Distance gt Density Interpolate to Raster gt Surface Analysis Cell Statistics Neighborhood Statistics Zonal Statistics Raster Calculator Convert gt Options 2 Click the Input raster dropdown arrow and click landuse 3 Click the Reclass field dropdown arrow and click Landuse 4 Type the following values in the New values column Agriculture 10 Built up 3 Barren land 6 Forest 4 Brush Transitional 5 34 You will now remove the Water and Wetland attributes and change their values to NoData Click the row for Water press the Shift key click Wetlands then click Delete Entries Check Change missing values to NoData All values for Water and Wetlands will be changed to NoData Click OK 4 2 Reclassify HES E Input raster landuse S Reclass field Landuse 3 Set values to reclassify Add Entry Delete Entries Olutput raster lt Temporary gt Usinea ArcGIS Spatiat ANALYST The output reclassified landuse dataset will be added to your ArcMap session as a new layer It shows locations that have landuse types that are considered to be better than others for locating the school higher values indicate more suitable locations 8 Right click Reclass of landuse in the table of contents and click Properties 9 Click the Symbology tab 10 Click the Display NoData as dropd
6. Reclassify Raster Calculator Convert b Options Cost Weighted Distance to Cost raster Maximum distance Output cell size O aien fia 5 QF Create allocation Temporary Output raster Temporary a Cancel Us nG ArcGIS Spatiat ANALYST Shortest path What is the Shortest Path function The Shortest Path function determines the path from a destination point to a source Once you have performed the Cost Weighted Distance function creating distance and direction rasters you can then compute the least cost or shortest path from a chosen destination to your source point which in our original example was the starting point for the new road Why find the shortest path The shortest path travels from the destination to the source and is guaranteed to be the cheapest route relative to the cost units defined by the original cost raster Use it to find the best route for a new road in terms of construction costs or to identify the path to take from several suburban locations shopping mall destinations sources to the closest You can see two potential paths for the new road in the diagram above in purple and red to illustrate an important point The PERFORMING SPATIAL ANALYSIS purple line represents the path created using a cost raster where each input raster landuse and slope had the same influence The red line represents the path created using a cost raster whe
7. This chapter contains e Conceptual information about each function e Step by step details of how to use each function Use this chapter as a reference guide looking up a particular function when you need more information 119 Mapping distance What are distance mapping functions The distance mapping functions are global functions They compute an output raster dataset where the output value at each location is potentially a function of all the cells in the input raster datasets There are several distance mapping tools for measuring both straight line Euclidean distance and distance measured in terms of other factors such as the cost to travel over the landscape The outputs from the Straight Line Distance functions are normally used directly while the outputs from the Cost Weighted Distance functions are most commonly used to compute shortest or least cost paths Straight Line Distance functions The Straight Line Distance function measures the straight line distance from each cell to the closest source the source identifies the objects of interest such as wells roads or a school The distance is measured from cell center to cell center The Straight Line Allocation function assigns each cell the value of the source to which it is closest The nearest source is determined by the Straight Line Distance The Straight Line Direction function computes the direction to the nearest source measured in degrees
8. Understanding raster data Usinc ArcGIS Spatiat ANALYST Performing analysis Section 3 Setting up your analysis environment IN THIS CHAPTER e Creating temporary or permanent results Specifying a location on disk for the results e Using an analysis mask Setting the coordinate system for results Setting the extent for results Specifying the cell size for results Specifying a certain extent cell size and working directory for your analysis results is a prerequisite to performing analysis For instance you may only be interested in analyzing a small piece of a geographic area or you may want to write the results to a specific location Setting the options for your analysis results enables you to control the output directory for your results the analysis extent and the cell size It also enables you to specify an analysis mask and a snapping extent if appropriate It is recommended that you set up your analysis options before you perform analysis on your data or you can accept the defaults By default the directory for your analysis results is set to that of your system s temporary directory usually c temp the cell size is set to that of the largest cell size of your inputs and the extent is set to the intersection of your input data This chapter will explain the following e Understanding and creating temporary and permanent results e How to specify a location on disk for your analysis result
9. the percentage slope approaches infinity The Slope function is most frequently run on an elevation dataset as the following diagrams show Steeper slopes are shaded red on the output slope dataset It can also be used with other types of continuous data such as population to identify sharp changes in value PERFORMING SPATIAL ANALYSIS Elevation dataset Output slope dataset in degrees 153 Calculating slope The Slope function enables you to create a slope raster for an entire area enabling you to get an impression of the steepness of the terrain and to use the output for further analysis The Z factor is the number of ground x y units in one surface z unit The Input surface values are multiplied by the specified Z factor to adjust the Input surface z units to another unit of measure Tip Degree and percent slope Slope can be measured in degrees from horizontal 0 90 or percent slope which is the rise divided by the run times 100 Tip Why use a Z factor To get accurate slope results the z units must be the same as the x y units If they are not the same use a Z factor to convert z units to x y units For example if your x y units are in meters and your z units are in feet you could use a Z factor of 0 3048 to convert feet to meters 154 Creating a slope dataset 1 Click the Spatial Analyst dropdown arrow point to Surface Analysis and click Slope 2 Click the
10. Cost Weighted Distance functions The Cost Weighted Distance function modifies the Straight Line Distance by some other factor which is a cost to travel through any given cell For example it may be shorter to climb over the mountain to the destination but it is faster to walk around it The Cost Weighted Allocation function identifies the nearest source cell based on accumulated travel cost 120 The Cost Weighted Direction function provides a road map identifying the route to take from any cell along the least cost path back to the nearest source The Distance and Direction raster datasets are normally created to serve as inputs to the pathfinding function the shortest or least cost path Why is it useful to map distance By mapping distance you can find out information such as the distance to the nearest hospital from certain areas for an emergency helicopter or find all fire hydrants within 500 meters of a burning building Alternatively you could find the shortest or least cost path from one location to another based on some cost factor The pages that follow explain Straight Line Distance Allocation Cost Weighted Distance and Shortest Path in more detail Usinc ArcGIS Spatiat ANALYST Straight line distance What are the Straight Line Distance functions The Straight Line Distance functions describe each cell s relationship to a source or a set of sources There are three potential outputs fro
11. Distance be Density Interpolate to Faster b Surface Analysis Cell Statistics Slope Neighborhood Statistics Aspect Zonal Statistics Hillshade Viewshed Reclassify CutFill Raster Calculator Convert b Options Input surface Contour definition Input height range Contour interval Base contour Z factor Output information based on input contour definition Minimum contour 500 Maximum contour Total number of contour intervals fe data ctourl shp 1s 1 cancet_ Output features Usinc ArcGIS Spatiat ANALYST Slope What is slope The Slope function calculates the maximum rate of change between each cell and its neighbors the maximum change in elevation over distance between the cell and its eight neighbors for example the steepest downhill descent for the cell Every cell in the output raster has a slope value The lower the slope value the flatter the terrain the higher the slope value the steeper the terrain The output slope dataset can be calculated as percent slope or degree of slope rise Degree of slope 9 Percent of slope 100 run rise tan 8 run rise run Degree of slope 30 45 76 Percent of slope 58 100 375 When the slope angle equals 45 degrees the rise is equal to the run Expressed as a percentage the slope of this angle is 100 percent Note that as the slope approaches vertical 90
12. Name Each raster dataset must have a name to distinguish it from the other raster datasets in a database All access to a raster dataset is performed through its name which must be used consistently in all expressions v EG ETATIO N WAT ee owe reee emery aus E NO DATA 77 Coordinate space and the raster dataset Coordinate space defines the spatial relationship between the locations in a raster dataset All raster datasets are in some coordinate space This coordinate space may be a real world coordinate system or image space Since almost all raster datasets represent some real world location it is best to have that dataset in the real world coordinate system that best represents it Converting a raster dataset from a nonreal world coordinate system image space to a real world coordinate system is called georeferencing For a raster dataset the orientation of the cells is determined by the x and y axes of the coordinate system Cell boundaries are parallel to the x and y axis and the cells are square in map coordinates Cells are always referenced by an x y location in map coordinate space and never by specifying a row column location Y axis rT Number of columns W Number of rows Cell size lt __ Xmin Ymin Column X axis Center of lower left cell 78 The x y Cartesian coordinate system associated with a raster dataset that is in a real world coordinate space
13. Reclass of slope 2 Double click Reclass of landuse to add it to the expression box gt Click the Add button About building expressions Cancel Ea 4 Double click Reclass of slope to add it to the expression box 5 Click Evaluate QUICK START TUTORIAL 47 The result is added to your ArcMap session Locations Step 2 Performing cost weighted distance with low values identify the areas that will be the least costly to build a road through They are displayed in dark blue in the graphic below You will now perform cost weighted distance using the Cost dataset you just created and the School site layer the source Using this function you will create a Distance dataset where each cell contains a value representing the accumulated least cost of traveling from that cell to the school site and a Direction dataset that gives the direction of the least cost path from each cell back to the source This conceptual process is explained in more detail in Chapter 7 Performing spatial analysis 1 Click the Spatial Analyst dropdown arrow point to Distance and click Cost Weighted Spatial Analyst x Spatial Analyst Layer cot HI a L Distance Straight Line Density Allocation 6 Click the output layer in the table of contents to highlight wtnye gt ileal i P y 8 8 Surface Analysis gt Shortest Path it click again and rename it Cost Cell Statistics You will now r
14. When used in conjunction with ArcMap Spatial Analyst provides a compre hensive set of tools for exploring and analyzing your spatial data enabling you to find solutions to your spatial problems Tutorial scenario The town of Stowe Vermont USA has experienced a substantial increase in population Demographic data suggests this increase has occurred due to families with children moving to the region taking advantage of the many recreational facilities located nearby It has been decided that a new school must be built to take the strain off the existing schools and as a town planner you have been assigned the task of finding the potential sites Spatial Analyst provides the tools to find an answer to such spatial prob lems This tutorial will show you how to use some of these tools and will give you a solid basis from which you can start to think about how to solve your own specific spatial problems 11 It is assumed that you have installed the Spatial Analyst extension before you begin this tutorial The data required is included on the Spatial Analyst installation disk the default installation path is ArcGIS ArcTutor Spatial on the drive where the tutorial data is installed The datasets were provided courtesy of the State of Vermont for use in this tutorial The tutorial scenario is fictitious and the original data has been adapted for the purpose of the tutorial The datasets are Dataset Description Elevation Raster
15. as a guide to learn the concepts and the steps to perform a certain task Finding answers to questions Like most people your goal is to complete your tasks while investing a minimum amount of time and effort on learning how to use software You want intuitive easy to use software that gives you immediate results without having to read pages of documentation However when you do have a question you want the answer quickly so you can complete your task That s what this book is all about getting the answers you need when you need them This book describes spatial analysis tasks from basic to advanced that you ll perform using Spatial Analyst Although you can read this book from start to finish you ll likely use it more as a reference When you want to know how to perform a particular task such as finding the shortest path just look it up in the table of contents or the index What you ll find is a concise step by step description of how to complete the task Some chapters also include detailed information that you can read if you want to learn more about the concepts behind the tasks You may also refer to the glossary in this book if you come across any unfamiliar GIS terms or need to refresh your memory About this book This book is designed to help you perform spatial analysis by giving you conceptual information and teaching you how to perform tasks to solve your spatial problems Topics covered in Chapter 2 Quic
16. e For focal functions if any cell location in a neighborhood of a processing cell is assigned NoData the function will ignore the NoData value and compute with the remaining values The keyword NoData can be used to override this default behavior to return NoData as the output for the processing cell location when any cell within the neighborhood contains NoData e For zonal functions if any cell location on the input value grid dataset or raster layer in a zone defined by the input zone grid dataset or raster layer is assigned NoData by default the function will ignore the NoData value and compute with the remaining values The keyword NoData can be used to override this behavior and return NoData to the cell location when any cell within the zone contains NoData If NoData exists for any cell location on the input zone grid dataset or raster layer the output value for the location is NoData e For straight line Euclidean distance functions the NoData value is ignored for computations since the distance and 195 direction are true Straight Line distance and direction The input source grid dataset or raster layer must contain valid values for source cells and NoData for nonsource cells e For cost distance functions any cell assigned NoData in the cost grid dataset or raster layer will be considered a barrier in computations and the cell locations containing NoData values on the input cost grid dataset or raster layer will co
17. A measurement of locations on the earth s surface expressed in a two dimensional system that locates features based on their distance from an origin 0 0 along two axes a horizontal x axis representing east west and a vertical y axis representing north south A map projection transforms latitude and longitude to x y coordinates in a projected coordinate system projection A mathematical formula that transforms feature locations from the earth s curved surface to a map s flat surface A projected coordinate system employs a projection to transform locations expressed as latitude and longitude values to x y coordinates Projections cause distortions in one or more of these spatial properties distance area shape and direction raster Represents any data source that uses a grid structure to store geographic information See grid Raster Calculator A Spatial Analyst function that provides a powerful tool for performing multiple tasks you can perform mathematical calculations using operators and functions set up selection queries or type in Map Algebra syntax raster cell A discretely uniform unit such as a square meter or a square mile representing a portion of the earth in a raster A cell or pixel has a value that corresponds to the feature or characteristics at that site such as soil type elevation or landuse type GLOSSARY raster dataset Contains raster data organized into bands Each band consists of
18. The viewshed identifies the cells in an input surface that can be seen from one or more observation points working directory A directory specified in the General tab of the Options dialog box that indicates the location on disk to place all results from analysis All permanent and temporary results will be written here unless otherwise specified in a function dialog box zonal functions This group of functions creates an output raster in which the computation of the desired function occurs on the cell values 225 from the input value raster that intersect or fall within each zone of a specified input zone dataset The input zone dataset is only used to define the size shape and location of each zone while the value raster is used to identify the values to be used in the evaluations within the zones zonal statistics A Spatial Analyst function that calculates a statistic for each zone of a zone dataset based on values from a raster dataset A single output value is computed for every zone in the input zone dataset zone All cells in a raster with the same value regardless of whether they are contiguous Z factor The number of ground x y units in one surface z unit The input surface values are multiplied by the specified Z factor to adjust the input surface z units to another unit of measure 226 Usinc ArcGIS Spatiat ANALYST Index A Aggregation aresampling function 100 Allocation assign proximity
19. To find areas of relatively flat land you need to create a map displaying the slope of the land The process model here involves calculating the slope of the land Input dataset needed elevation Is the landuse in these locations of a suitable type You need to decide what makes a suitable landuse type on which to build This is a subjective process according to your problem Here agricultural land is considered the least costly to build on and therefore the most preferable Barren land is next then brush transitional forest and existing built up areas There is no process model involved here just an identification of the input landuse dataset and which landuses are most preferable to build on Input dataset needed landuse 62 Calculate distance school Calculate slope Usina ArcGIS Spatiat ANALYST Step 3 Exploring input datasets Once you have broken down your problem into a series of objectives and process models and decided what datasets you will need you should explore your input datasets to understand their content This involves understanding which attributes within and between datasets are important for solving the problem and looking for trends in the data By exploring your data you can often gain insights about the areas you wish to locate the school in the weightings for input attributes and alterations to your modeling process You can see the locations of existing schools and recreation si
20. Archlap Documents ned Cancel SETTING UP YOUR ANALYSIS ENVIRONMENT Specifying a location on disk for the results The default location for your analysis results 1s your system s temporary directory usually c temp There are two ways to specify where your analysis results should go The first way is to specify a location on disk for your results using the Analysis Options dialog box before you perform any analysis This way all your analysis results will go to this directory The second way 1s to specify a location on disk each time you perform analysis in each of the function dialog boxes This is useful if you want to sort your analysis results into different folders Creating a new working directory Simply type the path to the new location in the Working directory input box Using your working directory Ifyou have set up your working directory type the name for the output in a function dialog box to save it permanently to your working directory 112 Specifying a location for all analysis results via the Analysis Options 1 Click the Spatial Analyst dropdown arrow and click Options Click the General tab 3 Type a location on disk for your analysis results or use the Browse button to navigate to a directory Click OK iY m Specifying a location on disk for each output from a function 1 Type a location on disk and a name for the output when performing any function
21. E 21 E 21 i 41 i 51 fi 61 E 71 E 31 m 91 W101 E ili C 121 E131 E141 o 151 s Treo Arar narte e Haul Cost Analysis E te paar E 171 Pacific Northwest ee P181 i i 200 Mila Radius Onise Cascada Conperulion ofa ac Haul Cost Analysis s z ise C C ion 1 p v J Y v aa orporation Drawing Y k E Ois A 7 eal x fio 7 B Z U A v EM E Brian Liberty Nick Blacklock Copyright 1997 269 03 1466 12 Unknown Uni 1 93 0 21 Inches This map displays the least cost travel for timber transport within a 200 mile radius of each mill It considers obstacles to travel and estimates the cost in dollars to transport wood from each location to the nearest mill INTRODUCING ARCGIS SpatiAL ANALYST Tips on learning Spatial Analyst If you re new to the concept of geographic information systems GIS remember that you don t have to know everything about Spatial Analyst to get immediate results Begin learning Spatial Analyst by reading Chapter 2 Quick start tutorial This chapter introduces you to some of the tasks you can accomplish using Spatial Analyst and provides an excellent starting point as you start to think about how to tackle your own spatial problems Spatial Analyst comes with the data used in the tutorial so you can follow along step by step at your computer If you prefer to jump right in and experiment on your own use Chapter 7 Performing spatial analysis
22. Spherical x 5 Advanced Parameters Search radius type Fixed 6 Search Radius Settings Distance 9589 99312 i 12 1917 99862 fe k Temporary gt a 1 1 Minimum number of points Output cell size T Create Prediction of standard error utput raster Cancel _ 10 12 Usina ArcGIS Spatiat ANALYST Performing surface analysis You can gain additional information by producing a new dataset E Fa that identifies a specific pattern within an original dataset E Patterns that were not readily apparent in the original surface can You may be a farmer interested in B ne be derived such as contours angle of slope aspect hillshade l E l locating a field on an area with a viewshed and cut fill E southerly aspect ms Contours can be useful for finding areas of the same value You sw may be interested in obtaining elevation values for specific mw locations and examining the overall gradation of the land mow Output aspect You can create a hillshade for both analytical and graphical purposes Graphically a hillshade can provide an attractive and realistic backdrop showing how other layers are distributed in relation to the terrain relief Ar ina Input elevation raster Output contours l Output hillshade You may for instance want to know the variations in the slope of From an analytical the landscape because you want to find the areas most at risk of i i point of view you ES landslide
23. an array of cells with optional attributes for each cell or pixel Raster datasets come in many different formats See format raster resolution The size of the cells in a raster See also cell size reclassify A Spatial Analyst function that takes input cell values and replaces them with new output cell values region Each group of connected cells in a zone See zone relational operators Evaluate specific relational conditions Ifa condition is TRUE the output is assigned a value of 1 If the condition is FALSE the output is assigned a value of 0 Relational operators lt gt lt gt gt lt resampling The process of extrapolating new cell values when transforming rasters to a new coordinate space or cell size selected set A subset of the features in a layer or records in a table ArcMap provides several ways to select features and records graphically or according to their attribute values semivariogram The variogram divided by two 223 shapefile A vector data storage format for storing the location shape and attributes of geographic features shortest path A Spatial Analyst function that calculates the least cost path from a destination point to the cheapest source using the Cost Weighted Distance and Cost Weighted Direction datasets created via the Cost Weighted Distance function sill A parameter of a variogram or semivariogram model that represents a value that the vari
24. analysis extent A Spatial Analyst option to set the extent the x y coordinates for the bottom left and the top right corners for the results from spatial analysis analysis mask A Spatial Analyst option that uses a raster dataset in which all cells of interest have a value and all other cells are NoData It enables you to perform analysis on a selected set of cells Processing will only occur on selected cells with other cells being assigned NoData arithmetic functions Functions within the Raster Calculator of Spatial Analyst There are six arithmetic functions Abs Ceil Floor Int Float and IsNull The Abs function takes the absolute value of the values in an input raster Ceil and Floor convert floating point values into integers by rounding up or down respectively Int and Float convert values from and to integer and floating point values The IsNull function returns 1 if the values on the input raster are NoData null and 0 if they are not arithmetic operators Operators within the Raster Calculator of Spatial Analyst They allow for the addition subtraction multiplication and division of two rasters or numbers or a combination of the two aspect Aspect is the direction a slope faces or the direction of steepest descent defined by the cell and its eight surrounding neighbors 217 attribute table A table stored in rows and columns giving information about features on a map Each row relate
25. contour A contour is a line that connect points of equal value on a surface coordinate system A reference system used to measure horizontal and vertical distances on a planimetric map A coordinate system is usually defined by a map projection a spheroid of reference a datum one or more standard parallels a central meridian and possible shifts in the x and y directions to locate x y positions of point line and area features In ArcGIS a system with units and characteristics defined by a map projection A common coordinate system is used to spatially register geographic data for the same area cost dataset An input dataset necessary to run the Cost Weighted Distance function using Spatial Analyst It identifies the cost of traveling through each cell The Cost Weighted Distance function uses this cost raster dataset to calculate the accumulative cost of traveling from every cell in the raster to a source or a set of SOUICES cost weighted allocation A Spatial Analyst function that identifies the nearest source from each cell in a cost weighted distance raster Each cell is assigned to its nearest source cell in terms of accumulated travel cost GLOSSARY cost weighted direction A Spatial Analyst function that provides a road map from the Cost Weighted Distance raster identifying the route to take from any cell along the least cost path back to the nearest source cost weighted distance A Spatial Analyst
26. cost weighted distance calculating 130 described 129 overview 120 straight line Euclidean distance calculating 123 125 described 121 122 124 Altitude defined 217 described 157 Analysis environment analysis mask creating 113 defined 217 described 104 109 using 114 cell size defined 218 described 104 105 setting 117 coordinate system defined 219 described 106 setting 115 extent defined 217 220 described 104 109 setting 116 overview 104 109 snap extent defined 224 described 109 setting 116 working directory defined 225 described 109 setting 112 Analysis extent defined 217 setting 116 Analysis mask creating 113 defined 217 described 104 109 using 114 Application functions described 93 Arithmetic functions defined 217 described 179 using 184 Arithmetic operators and precedence 203 defined 217 described 179 supported 203 Aspect calculating 156 defined 217 described 96 155 Assign proximity See Allocation assign proximity overview Attribute table defined 218 described 76 Autocorrelation defined 218 described 141 Azimuth defined 218 described 157 Barrier defined 218 described 136 227 Bilinear resampling and altering the resolution 100 and geometric transformations 79 options in analysis 105 Bin defined 218 Bitwise operators and precedence 203 supported 203 Block functions 100 Boolean operators and precedence 203 defined 218 described 179 supported 203 C Catalog tree
27. defined 218 Categorical data described 103 Categorical raster defined 218 Cell statistics 92 164 Cell size defined 218 described 74 84 104 105 setting 117 Cell statistics a local function 92 calculating 165 defined 218 described 164 Chart relationships 170 Classify defined 218 Column of a raster dataset 74 228 Combinatorial operators and precedence 203 supported 203 Con function 197 Continuous data and raster encoding 85 attribute values 88 103 defined 219 described 82 Contours creating 152 defined 219 described 97 151 Control points and georeferencing 78 Conversion described 85 86 186 performing 188 Coordinate system and analysis 106 115 and raster datasets 78 defined 219 Cost of travel 7 Cost dataset defined 219 described 126 Cost weighted allocation calculating 130 defined 219 described 129 overview 120 Cost weighted direction calculating 130 defined 219 described 129 overview 120 Cost weighted distance calculating 130 defined 219 described 126 overview 120 Cubic convolution resampling and altering the resolution 100 and geometric transformations 79 options in analysis 105 Curvature correcting for 160 described 97 Cut Fill calculating 163 defined 219 described 162 D Data defined 219 exploration 63 handling in Spatial Analyst 89 permanent 110 temporary 110 Data frame defined 219 Dataset defined 219 Density calculating 134 defined 219 described 133 Deri
28. from every location This could provide useful information for an emergency helicopter when transporting an injured hiker to the nearest town for medical treatment mn I NE Me My sE Ds my sw mw my Nw Finding the direction to the nearest source What is the direction from this location to the nearest town Keep in mind that the Straight Line Distance functions give you information according to Euclidean or straight line distance It may not be possible to travel in a straight line to get to a location you may have to avoid obstacles such as a river or a steep slope In such cases you should consider using the Cost Weighted Distance function to achieve more realistic results see Cost Weighted Distance later in this chapter Usina ArcGIS Spatiat ANALYST Straight line distance The Straight Line Distance function enables you to calculate how far each cell is from the nearest source The source can be anything you choose from a well to a road to a group of retail stores and can be in any supported raster or feature format Tip Setting analysis options Click Options on the Spatial Analyst toolbar to set up your working directory extent and cell size for your analysis results Tip Browsing for files or directories If the file you need is not in your table of contents or if you need to check the directory to place your results click the Browse button Tip Deciding on the maximum distan
29. obtain a value for the cell being processed Tip Highlighting cells on the map Right click the output raster and click Open Attribute Table Click a row in the table to highlight the cells on the map PERFORMING SPATIAL ANALYSIS Creating a map using neighborhood statistics 1 Click the Spatial Analyst dropdown arrow and click Neighborhood Statistics 2 Click the Input data dropdown arrow and click the layer on which you want to perform neighborhood statistics 3 Click the Field dropdown arrow and click the field from the Input data you wish to use 4 Click the Statistic type dropdown arrow and click the type of statistic you wish to compute 5 Click the Neighborhood dropdown arrow and click the type of neighborhood you wish to use 6 Specify the Neighborhood Settings for your chosen neighborhood 7 Optionally change the default Output cell size 8 Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory 9 Click OK Spatial Analyst Spatial Analyst Neighborhood Statistics Layer Jlandcover Ja ih Distance Density interpolate to Raster p Surface Analysis p Cell Statistics Neighborhood Statistics onal Statistics FReclassify Raster Calculator Convert p Options Input data landcover a Field Value 3 Statistic type Vanety Neighborhood Rectangle Neighborho
30. schools 4 Double click each symbol and choose a suitable color to El M rec_sites represent each landuse type a 5 Click OK 7 Scroll to the School 2 symbol and click it 8 Click the color dropdown arrow and click a color 9 Click OK Layer Properties how ONARE m O O OOoooooan E t Gmagogonoaas OBBOUOBROOEES a2 MERIN aas ene ngele eaea SESE RRS REeee BEEBE BEB EEE E a SEG00000Saan Default Colors E SBEOOCoomeE le A Hendcecced Hancicecoed 2 Sa 0G5Snnan Display NoData as met H F Sme Morte Cokin Ho Hona 2 Inter ptt My 1 More Colors The changes you make are reflected in the table of The changes you make are reflected in the table of contents and in the map contents and in the map QUICK START TUTORIAL 15 Highlighting a selection on the map Examining the attribute table gives you an idea of the number of cells of each attribute in the dataset 1 Right click landuse in the table of contents and click Open Attribute Table x Layers BJT an L Copy OA Remove Be Bri Open Attribute Tab EE Joins and Relates b F e e Zoom To Layer Ew te oom To Raster Resolution le Notice that Forest value of 6 has the largest count followed by Agriculture value of 5 then Water value of 2 BS Attributes of landuse _ ObijectID Value Count Landuse _ _ 294 Brush transitiona
31. 315 is NW Altitude is the slope or angle of the illumination source above the horizon The default 1s 45 degrees above the surface Tip Why use a Z factor To get accurate hillshade results the z units must be the same as the x y units If they are not the same use a Z factor to convert z units to x y units For example if your x y units are in meters and your z units are in feet you could use a Z factor of 0 3048 to convert feet to meters Tip Modeling shadows Checking Model shadows will assign a value of 0 to any cell that falls within a shadow By accepting the default not to model shadows the local illumination will be calculated whether the cell falls in a shadow or not 158 Creating a hillshade dataset 1 Click the Spatial Analyst dropdown arrow point to Surface Analysis and click Hillshade 2 Click the Input surface dropdown arrow and click the surface for which you want to calculate hillshade 3 Specify the azimuth you wish to use The default is 315 degrees 4 Specify an altitude The default is 45 degrees 5 Check Model shadows if you wish to model shadows by assigning a value of O to areas in shadow Leaving this unchecked will create an output raster that will give local illumination regardless of shadows 6 Specify a Z factor The default is 1 N Optionally change the default Output cell size 8 Specify a name for the Output raster or leave the de
32. 4 Understanding raster data Each operator and function in Spatial Analyst manipulates the value for each cell in different ways depending on the type of function In this chapter you will learn the general principles of cell based modeling By combining these principles you will be able to solve almost any of your specific problems Not only will you learn about the general principles of cell based modeling but you will also learn what considerations you must be aware of when performing analysis You will understand the effects that the values in the raster dataset cell size NoData projections and analysis extent will have on your analysis It is from this understanding that you will make better decisions when performing cell based analysis 91 Understanding analysis in Spatial Analyst The easiest way to understand cell based modeling is from the perspective of an individual cell the worm s eye approach as opposed to the entire raster the bird s eye approach To do so think of yourself as a cell in a raster dataset You represent a location and you have a value All Spatial Analyst operators and functions will ask you to manipulate your value or remain the same based on a set series of rules For you to calculate an output value for your location using any Spatial Analyst operation or function there are three things you need to know e You need to know your value e You need to know the manipulation of t
33. 50 c spatial schootst 5 Cancel Output cell size Output raster Usina ArcGIS SpatTiAL ANALYST Performing spatial analysis IN THIS CHAPTER Mapping distance Mapping density Interpolating to raster Performing surface analysis Calculating cell statistics Calculating neighborhood Statistics Calculating zonal statistics Reclassifying your data Using the raster calculator Converting your data Spatial Analyst provides you with tools to perform spatial analysis on your data that help you solve your spatial problems The previous chapter gave you information about setting the analysis properties before performing analysis This chapter will provide you with detailed information about the analytical functions in Spatial Analyst explaining what each of these functions do why you might want to use them and how to use these functions to perform tasks The Spatial Analyst functions accept layers added to ArcMap and raster or feature datasets that you can browse to in each function dialog box The Spatial Analyst functions also support selection on layers so you can select certain values in an attribute table or on the map and use this selection in your analysis This chapter is organized in the order of the functions on the user interface so if you want for instance information on converting your data near the bottom of the pulldown menu simply visit the last few pages of this chapter to get more information
34. Alternatively use the Browse button to navigate to a folder on disk By specifying a location and a name the results will be permanent Spatial Analyst Distance Density Interpolate to Raster Surface Analysis Cell Statistics Neighborhood Statistics Zonal Statistics Reclassify Raster Calculator Convert Straight Line Distance to Maximum distance Output cell size I Create direction i Create allocation Output raster Spatial Analyst X Layer elevation d b Yv schools S 3000 30 c spatial direction g emparar g empora rea Options 21x General Extent Cell Size Jes temp Working directory Analysis mask Analysis Coordinate System Analysis output will be saved in the same chordinate system as the input or first raster input if there are multiple inputs Analysis output will be saved in the same coordinate system as the active data frame IV Display waming message if raster inputs have to be projected during analysis operation Cancel Usina ArcGIS SPaTiaL ANALYST Using an analysis mask Sometimes you only want to perform analysis on a selected set of cells and you want to mask out the rest Setting an analysis mask is a two step process First the analysis mask must be created if you do not already have one An analysis mask identifies those cells t
35. CLinlayer2 diff Linlayer3 Usinc ArcGIS Spatiat ANALYST Map Algebra rules for functions All functions begin with the function name followed by the grid dataset grid datasets raster layer or raster layers to which the function is to be applied and the necessary parameters all in parentheses tanCLinlayer focalmaxC inlayerl rectangle 4 4 zonalminC zonelayer valuelayer The arguments or parameters within functions are separated by commas focalminC Linlayerl1 circle 6 zonalmaxC zonelayer c data valuegrid Many functions also have additional parameters These parameters may be keywords numbers names of tables and even other rasters The parameters are function dependent selectboxC inlayerl 45 67 200 360 focalrange inlayerl annulus 2 4 zonalmean zonelayer c data valgrid NoData Compound expressions Functions can be used in compound expressions together with operators grid datasets raster layers shapefiles coverages and numbers sinCLinlayerl1 inlayer2 focalsumC inlayerl rectangle 3 3 tanCLinlayer2 zonalminC zonelayer valuelayer 3 APPENDIX A All functions have the same precedence value therefore when multiple functions are used in an expression they are evaluated from left to right minCLinlayerl inlayer2 inlayer3 absC Linlayer4 ce11C Linlayer1 al a sliceC inlayer2 eqarea 10 popularity 2 inlayerl inl
36. Cubic convolution Cubic convolution is similar to bilinear interpolation except the weighted average is calculated from the 16 nearest input cell centers and their values Cubic convolution will have a tendency to sharpen the data more than bilinear interpolation since more cells are involved in the calculation of the output value Bilinear interpolation or cubic convolution should not be used on categorical data since the categories will not be maintained in the output raster dataset However all three techniques can be applied to continuous data with nearest neighbor producing a blocky output bilinear interpolation producing smoother results and cubic convolution producing the sharpest results UNDERSTANDING RASTER DATA 81 Discrete and continuous data Discrete data which is sometimes called categorical or discontinuous data mainly represents objects in both the feature and raster data storage systems A discrete object has known and definable boundaries It is easy to define precisely where the object begins and where it ends A lake is a discrete object within the surrounding landscape Where the water s edge meets the land can be definitively established Other examples of discrete objects include buildings roads and parcels Discrete objects are usually nouns A continuous surface represents phenomena where each location on the surface is a measure of the concentration level or its relationship from a fixed
37. Distance Weighted interpolation defined 221 described 96 136 using 137 Integer data and tables 76 as attributes 88 Interpolation defined 221 understanding 135 Interval measurement systems 102 Inverse Distance Weighted IDW interpolation defined 221 described 96 136 using 137 K Kriging interpolation defined 221 described 96 141 methods 145 using 147 L Lag defined 221 Lag bins 141 Layer defined 221 Least cost path See Shortest path described Local functions defined 221 described 92 229 Logarithmic functions defined 221 described 179 using 184 Logical operators supported 203 M Make permanent defined 221 Map Algebra defined 221 language components 192 overview 191 performing 185 rules 199 Map calculator See Raster Calculator described Map document defined 221 Map projections and analysis 106 115 and raster datasets 78 defined 221 Map query described 6 69 performing 183 Mask creating 113 described 104 109 using 114 Mathematical functions 179 184 defined 221 in Map Algebra 201 operators 179 defined 222 in Map Algebra 199 Merge 98 230 Model defined 222 process 56 representation 56 suitability 61 Modeling process 58 Mosaic 98 N Nearest neighbor resampling and altering the resolution 100 and geometric transformations 79 defined 222 options in analysis 105 Neighborhood statistics a focal function 93 calculating 169 defined 222 described 166 NoData and a
38. Faster Calculator Convert Options Input data Population field Density type Search radius Area units Output cell size Output raster Cities POF i Kernel Simple 200 square Miles Tempora OO 8 Cancel D C Co ES C Us nG ArcGIS Spatiat ANALYST Interpolating to raster What is interpolation Interpolation predicts values for cells in a raster from a limited number of sample data points It can be used to predict unknown values for any geographic point data elevation rainfall chemical concentrations noise levels and so on 14 24 24 Raster Interpolated from the points Cells highlighted in red indicate the values of the input point dataset 16 18 lie 16 18 30 LET e20 Point dataset of known values The left hand graphic above is a point dataset of known values The right hand graphic is a raster interpolated from these points Unknown values are predicted with a mathematical formula that uses the values of nearby known points Why interpolate to raster Visiting every location in a study area to measure the height magnitude or concentration of a phenomenon is usually difficult or expensive Instead strategically dispersed sample input point locations can be selected and a predicted value can be assigned to all other locations Input points can be either randomly or regularly spaced points containing height concentration or magnitude meas
39. LA Layout View Hillshade can be seen through it Zoom Data gt 1 Click Hillshade of elevation in the table of contents and Zoom Layout gt drag the layer below the landuse layer een ate Toolbars iv Main Menu led E Table Of Contents V Standard Layers iv Status Bar ve Tools E schools Overflow Labels v Draw P Identify Results Layout E rec sites m Scrollbars v Spatial Analyst D ES Rulers El roads De Guides Editor _ Gti Georeferencing Grid E g Yalue Data Frame Properties High 255 Data Frame Tools Utility Network Analyst Low 0 Versioning E landuse Graphics Landuse 3 C griculture beatae C Barren land Customize C Brusky transitional View Source E Built up WS Forest B ater i wetland El elevation Value 2 Click View on the Main menu point to Toolbars and as perenne click Effects Click the Layer dropdown arrow and click landuse U9 4 Click the Adjust Transparency button and move the scroll bar up to 30 percent transparency The Hillshade layer can now be seen underneath the landuse layer giving a vivid impression of the terrain QUICK START TUTORIAL 21 Exploring your data gives you a useful basis of informa tion that will help you during your analysis For ex ample you need to know the different landuse types and their distribution over an area as well as their relative importance in order to decide how much weight each should have
40. The Base contour is the value from which to begin generating contours Contours are gener ated above and below this value as needed to cover the entire value range of the raster The Contour interval specifies the distance between contour polylines The Z factor is the number of ground x y units in one surface z unit The Input surface values are multiplied by the specified Z factor to adjust the Input surface z units to another measurement unit Tip Using the Contour tool Use the Contour tool on the Spatial Analyst toolbar to create contours for specific locations in your input dataset Tip Highlighting contours Use the Select Features tool on the Tools toolbar to select contours then open the table to examine the values Alternatively select contours from the table 152 Creating contours for your whole map 1 Click the Spatial Analyst dropdown arrow point to Surface Analysis and click Contour 2 Click the Input surface dropdown arrow and click the surface you want to contour 3 Type a Contour interval to specify the distance between contours 4 Type a Base contour from which to start contouring or leave the default of 0 5 Optionally type a value for the Z factor 6 Specify a name for the Output features or leave the default which creates a permanent dataset in your working directory 7 Click OK Spatial Analyst Spatial Analyst Laper elevation ey ili
41. Ton 232931 853 Lett 465054 455 Right 500705 68 Bottom 206762 853 elevation bi S Analysis extent Snap estent to Cancel Usina ArcGIS SpatTiAL ANALYST Setting the cell size for results The default cell size or resolu tion for analysis results is set to the input raster dataset with the largest cell size the Maximum of Inputs The default cell size when a feature dataset is used as input to a function is to take the width or the height whichever is shortest of the extent of the input feature dataset and divide by 250 to get 250 cells Exercise caution when specify ing a cell size finer than the input raster datasets No new data is created cells are interpolated using nearest neighbor resampling The result is as precise as the coarsest input The default cell size can be changed on the Cell Size tab of the Options dialog box The cell size you specify will be applied to all subsequent results Other options available Minimum of Inputs sets the cell size of your analysis results to the input raster dataset with the smallest cell size As Specified Below enables you to specify a cell size for analysis results and Same As Layer enables you to select an input raster layer on which to base the cell size of your analysis results gt SETTING UP YOUR ANALYSIS ENVIRONMENT Specifying a cell size for all subsequent analysis results 1 Click the Spatial Analyst dropdown arrow
42. a minimum use duplication or disclosure by the U S Government is subject to restrictions as set forth in FAR 52 227 14 Alternates I II and HI JUN 1987 FAR 52 227 19 JUN 1987 and or FAR 12 211 12 212 Commercial Technical Data Computer Software and DFARS 252 227 7015 NOV 1995 Technical Data and or DFARS 227 7202 Computer Software as applicable Contractor Manufacturer is ESRI 380 New York Street Redlands CA 92373 8100 USA ESRI and the ESRI globe logo are trademarks of ESRI registered in the United States and certain other countries registration is pending in the European Community ArcMap ArcCatalog ArcGIS and GIS by ESRI are trademarks and wwwesri com is a service mark of ESRI Microsoft is a registered trademark and the Microsoft Internet Explorer logo is a trademark of Microsoft Corporation HP and LaserJet are registered trademarks of Hewlett Packard Other companies and products mentioned herein are trademarks or registered trademarks of their respective trademark owners Contents Getting started 1 Introducing ArcGIS Spatial Analyst 3 Deriving information from data 4 Identifying spatial relationships 5 Finding suitable locations 6 Calculating cost of travel 7 Tips on learning Spatial Analyst 8 2 Quick starttutorial 11 Exercise 1 Displaying and exploring your data 13 Exercise 2 Finding a site for a new school in Stowe Vermont USA 23 Exercise 3 Finding an alternative access road to the new sch
43. a nuclear plant and the salt concentration from a salt marsh as it moves inland Floating point raster datasets usually do not have a table associated with them because most if not all cell values are unique and the nature of continuous data excludes other associated attributes Continuous data is best represented by ratio and interval values Many times meaningless results will occur when combining discrete and continuous data for instance adding landuse discrete data to elevation continuous data A value of 104 on the resulting raster dataset could have been derived from adding single family housing landuse type with a value of 4 to an elevation of 100 103 The analysis environment Spatial Analyst allows you to process a subset of cells and to The mask specify the resolution in which to process them For a more detailed discussion of the Spatial Analyst analysis environment see Chapter 6 Setting up your analysis environment The mask identifies those cells within the analysis extent that will not be considered when performing an operation or a function All identified cells will be masked out and assigned to the NoData The analysis extent value on all subsequent output raster datasets When performing analysis the area of interest may be a portion of a larger raster dataset If the area of interest is a portion of a larger raster dataset the analysis extent can be set to encompass only the desi
44. and click Options 2 Click the Cell Size tab 3 Click the Analysis cell size dropdown arrow and choose the appropriate option 4 Click OK Spatial Analyst Spatial Analyst x Layer Jlanduse S ih Distance d Density Interpolate to Faster b Surface Analysis p Cell Statistics Neighborhood Statistics Zonal Statistics Reclassity Raster Calculator Convert General Estent Cell Size Analysis cell size Same at Laver landuse Cell size 25 Mumber of rows 920 Number of columns 9435 Cancel 4 117 Alternatively specify the number of rows and columns to split your analysis extent into and an appropriate cell size will be applied For functions that accept nonraster data you can specify the cell size for your output raster dataset directly in the function dialog box The default is whatever is set on the Cell Size tab of the Options dialog box be this the default or a cell size you specified Finding out a raster layer s cell size To find out the cell size of a raster layer right click the raster layer in the table of contents click Properties then click the Source tab 118 Applying a different cell size than the default for certain functions 1 Type a cell size 2 Click OK The cell size you specified will be applied to your Output raster RIES Features to Raster Input features schools S Field FIL n
45. and level of groupings should reflect the analysis to be completed Whether slope is divided into five categories O to 10 11 to 20 21 to 30 31 to 40 and 50 percent or divided into groupings containing only two percent intervals O to 2 percent 3 to 4 percent and so forth depends on the most detailed breakdown necessary in future analyses When in doubt the most detailed breakdown should be used Information can be grouped into fewer categories more easily than splitting fewer categories into more categories Usina ArcGIS SpatiAL ANALYST Using feature data directly in Spatial Analyst Several of the Spatial Analyst dialog boxes allow you to enter a point polyline or polygon feature directly into the function There are two ways that features are handled in Spatial Analyst It either processes the feature data directly or it converts it to a raster and then processes it Certain functions require that one or more of the inputs be feature data and Spatial Analyst processes the data as feature data For instance the Inverse Distance Weighted and the Kriging functions create a continuous surface raster dataset from a point feature layer of measured sample data The calculations are performed on the point feature data directly Other functions allow you to enter feature data for one or more of the inputs and converts that feature data to a raster before performing the calculations An example of such a function is the zone d
46. as in the case of a cliff or a ridge With a variable radius the count represents the number of points used in calculating the value of the interpolated cell This makes the search radius variable for each interpolated cell depending on how far it gt PERFORMING SPATIAL ANALYSIS Creating a surface using IDW with a Fixed radius 1 Click the Spatial Analyst dropdown arrow point to Interpolate to Raster and click Inverse Distance Weighted 2 Click the Input points dropdown arrow and click the point dataset you wish to use 3 Click the Z value field dropdown arrow and click the field you wish to use 4 Optionally change the default Power value 5 Click the Search radius type dropdown arrow and click Fixed 6 Optionally change the default Distance for the search radius The default radius is five times the cell size of the output raster 7 Optionally change the Minimum number of points 8 Optionally specify a barrier 9 Optionally change the default Output cell size 10 Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory 11 Click OK Inverse Distance Weighted Spatial Analyst Spatial Analyst z Layer Jelevation 42 th d Distance Density Interpolate to Raster Inverse Distance Weighted Surface Analysis Spline Cell Statistics Eriging Neighborhood Statistics Zonal Stat
47. aspect defines the direction of flow The profile curvature is the shape of the surface in the direction of the slope The planform curvature defines the shape of the surface perpendicular to the direction of the slope Contour produces an output polyline dataset The value of each line represents all contiguous locations with the same height magnitude or concentration of whatever the values on the input dataset represent The function does not connect cell centers it interpolates a line that represents locations with the same magnitude Hydrologic analysis The shape of a surface determines how water will flow across it The hydrologic modeling functions provide methods for describing the hydrologic characteristics of a surface Using an elevation raster dataset as input it is possible to model where water will flow create watersheds and stream networks and derive other hydrologic characteristics UNDERSTANDING CELL BASED MODELING Watersheds for each section of a stream network The hydrologic modeling functions are available through the RasterHydrologyOp or through Map Algebra via the Raster Calculator 97 Geometric transformation The geometric transformation functions either change the location of each cell in the raster dataset or alter the geometric distribution of the cells within a dataset to correct a distortion The mosaicking functions another geometric transformation combine multiple raster d
48. at each store and how many cells need to share a portion of the 95 measured quantity the shoppers The cells nearer to the measured points the stores receive higher proportions of the measured quantity than those farther away Surface generation The surface functions use the surface representation of a raster dataset to represent height concentration or magnitude for example elevation pollution or noise Surface generation functions called surface interpolators create a continuous surface from sampled point values Surface generation functions make predictions for all locations in a raster dataset whether a measurement has been taken at the location or not There are a variety of ways to derive a prediction for each location each method is referred to as a model With each model there are different assumptions made of the data for example the data needs to be normally distributed and the model produces predictions using different calculations Below is a brief description of each model that is available in Spatial Analyst Inverse Distance Weighted IDW is based on a basic principle of geography that things close to one another are more alike Thus if you are at a location with no measured value in IDW you will look within a specified neighborhood or distance around you and identify the measured values You know that things close to you are probably more like your unknown value thus they will influence yo
49. based on the angle of slopes in an area steeper slopes can for instance AeA TEA being those most at risk analyze how the pfa K F landscape is A AA illuminated at various times of the day by lowering and raising Steeper the sun angle used in m angie of the analysis slope Output slope PERFORMING SPATIAL ANALYSIS 149 Calculating viewshed is useful when you want to know how visible objects will be For instance you might want to find the location with the most expansive view in an area because you want to know the best location for a lookout Output viewshed Display a hillshade transparently underneath the result from the Viewshed function 150 It is useful to calculate a Cut Fill surface when you want to know the areas and volumes of change between two surfaces It identifies the areas and volumes of the surface that have been modified by the addition or removal of surface material You may want to know the volumes and areas of surface material to be removed and filled in order to level a site for building construction or you might want to identify areas that have been removed and areas that have been filled after a volcanic eruption i Before surface After surface Cut Fill Surface VOLUME B Net Gain C Unchanged We Net Loss Cut Fill surface Usina ArcGIS Spatiat ANALYST Contour What are contours The Contour attribute table contains an elevation at
50. capability you do not have to convert all the feature data to raster datasets before you perform analysis 89 Deriving raster datasets from existing maps When creating raster datasets from existing maps data entry everal factors must be considered to allow for full utilization of the input data Selecting maps When selecting maps for the creation of the database you must be aware of e The age and date of the map e The cartographic accuracy e The resolution and detail e The compatibility of the map with other input maps The age and date will determine whether the map is current enough for the analysis to be completed If it is not then a more current map must be found The cartographic accuracy resolution and detail must be fine enough to complete the analysis at hand but not so detailed that the cost of entry loss in processing speed and size of the database are too inhibiting The input maps must be compatible Simple things such as the location of registration points on different maps can ease database construction Accuracy of analysis depends on the consistency and accuracy of the data variables Potential errors Even with current maps that are accurate at the same resolution with the desired amount of detail and compatible errors can still occur Some of the most common errors include e Drafting errors e Different cartographic projections used to draft the original data 90 e Different
51. click Save This brings you to the end of this tutorial You have been introduced to some of the functions of Spatial Analyst such as learning how to explore your data producing a suitability map and finding the least cost path You have covered much ground but there 1s a great deal more for you to explore The rest of this book will provide you with a guide as you learn how to solve your own specific spatial problems 54 Usina ArcGIS SpatTiAL ANALYST Modeling spatial problems IN THIS CHAPTER Spatial Analyst can help you perform useful analysis but it cannot solve problems by itself To get the results you are hoping for you have to ask the e Modeling spatial problems right questions and provide the right information This chapter will introduce you to the concept of spatial modeling to help you recognize the conceptual e A con I m for solvin copgeptyal giogo tor solving steps involved in performing spatial analysis spatial problems This chapter will explain e Using the conceptual model to create a Suitability map e Modeling spatial problems e The conceptual modeling process e Stating the problem e Breaking the problem down e Exploring input datasets e Performing analysis e Verifying the model s result e Implementing the result e Following the conceptual modeling process to build a suitability model The suitability model from Exercise 2 of the quick start tutorial Finding a site for a new school
52. datasets that should have more importance in the model a higher percentage influence weight than the others The following percentage influences will be assigned to the suitability maps The values in brackets are the percentage divided by 100 to normalize the values This normalized value will be assigned to each suitability map Distance to recreation sites 50 0 5 Distance to schools 25 0 25 Slope 12 5 0 125 Landuse types 12 5 0 125 So the Distance to recreation sites suitability map has an influence of 50 0 5 on the final result and Distance to schools has an influence of 25 0 25 Slope and Landuse types both have a 12 5 0 125 influence Like assigning scales of suitability assigning weights is a subjective process depending on what objectives are most important to your study The following graphs show the effect of applying the above weights on each suitability map MODELING SPATIAL PROBLEMS 67 Weights assigned to each suitability map Notice how the values of suitability have changed by applying weights For example the suitability value for Agriculture was 10 in the original suitability map By applying a weight of 0 125 or a percentage influence of 12 5 the suitability value for Agriculture is now only 1 25 When these four weighted suitability maps are combined the suitable locations for the school will have been influenced by the assigned weights Areas close to recreation sites will h
53. distance to schools you can simply query the data to find the suitable locations Such a query would be to find all locations on agricultural land with slopes less than 20 degrees where the distance to recreation sites is less than 1 000 meters and the distance to schools is greater than 4 000 meters The above query in the Raster Calculator landuse 5 amp Slope lt 20 amp Distance to rec_ sites lt 1000 amp Distance to schools gt 4000 MODELING SPATIAL PROBLEMS The result would give a Boolean true or false map of locations that meet or do not meet the criteria Step 5 Verifying the model s result Once you have your result from any spatial analysis you should verify that it is correct This should be done if possible by visiting the potential sites in the field Often the result you achieve has not accounted for something important for instance there may be a cow barn upwind of the site producing foul odors or by examining the town hall records you may discover a restriction on building on the desired land of which you were not aware If either is the case then you will need to add this information to the analysis Step 6 Implementing the result The final step in the spatial model is to implement the result building the new school in the chosen location 69 Understanding rasters and analysis Section 2 Understanding raster data IN THIS CHAPTER Understanding a raster dataset Coo
54. function that uses a cost raster to assign a value the least accumulative cost of getting back to the source to each cell of an output raster cut fill A Spatial Analyst function that summarizes areas and volumes of change between two surfaces data A collection of related facts usually arranged in a particular format and gathered for a particular purpose data frame A frame on the map that displays layers occupying the same geographic area You may have one or more data frames on your map depending on how you want to organize your data For instance one data frame might highlight a study area and another might provide an overview of where the study area is dataset Any geographic data such as a coverage shapefile raster or geodatabase Same as data source density A Spatial Analyst function that distributes the quantity or magnitude of point or line observations over a unit of area to create a continuous raster for example population per square kilometer 219 destination The destination point for a path when performing the Shortest Path function discrete raster A raster that typically represents phenomena that have clear boundaries and attributes that are descriptions or categories Each cell in a discrete raster stores an integer value that represents a feature In a raster of land cover for example the value 1 might represent forested land the value 2 for urban land and so on See also catego
55. given higher values in the Cost dataset As the defaults give high values to steeper slopes you do not need to change the default New Values Click OK on the Reclassify dialog box The Reclass of slope layer will be added to the table of contents It shows locations that are more costly than others for constructing a road higher values indicate the more costly areas that should be avoided QUICK START TUTORIAL Reclassifying landuse 1 Click the Spatial Analyst dropdown arrow and click Reclassify Spatial Analyst x Spatial Analyst Layer fianduse tC ip ili Distance gt Density Interpolate to Raster gt Surface Analysis gt Cel Statisties Neighborhood Statistics Zonal Statistics 45 U9 Click the Input raster dropdown arrow and click landuse Click the Reclass field dropdown arrow and click Landuse Click the first New value to edit the values and type in the following values Agriculture 4 Built up 9 Barren land 6 Forest 8 Brush Transitional 5 Water 10 Higher values indicate higher road construction costs 5 Click Wetlands and click Delete Entries 6 Click Change missing values to NoData 7 Click OK 4 2 Reclassify ka x C Input raster landuse gt 46 Reclass field Landuse 3 Set values to reclassify Add Entry Delete Entries 5 IM Change missing values to NoData Clutput raster lt Temporary gt Conce e
56. into consideration rather than the straight line distance see Cost weighted distance later in this chapter 124 Usinc ArcGIS Spatiat ANALYST Allocating cells to sources The Allocation function allows you to allocate cells to the closest source The source can be anything you choose such as a point dataset displaying the location of parks and can be in any supported raster or feature format Tip Deciding on the Maximum Distance Use the Measure tool on the Tools toolbar to decide what the maxi mum distance from each source should be Tip Setting analysis options Click Options on the Spatial Analyst toolbar to set up your working directory extent and cell size for your analysis results Tip Browsing for files or directories If the file you need is not in your table of contents or if you need to check the directory to place your results click the Browse button PERFORMING SPATIAL ANALYSIS Calculating straight line allocation 1 Click the Spatial Analyst dropdown arrow point to Distance and click Allocation N Click the Assign to dropdown arrow and click the layer containing sources to which you wish to assign cells 3 Optionally specify a maxi mum distance Cells outside this distance will not be considered in the calculation and will be given the value of NoData Leaving the Maximum distance blank will not put a limit on how far distances will be measured 4 Speci
57. is specified for the False expressions conC inlayerl gt 5 10 APPENDIX A the results will be the same as the above output except that the cells that have a value of 5 or less in the raster layer inlayer1 will be assigned NoData on the output raster dataset Any valid expression see Map Algebra rules later in this appendix can be used in place of a value for the true_expression and false expression arguments conC Linlayerl1 gt 5 sinCLinlayer1 cos inlayer1 In the above expression the sine of all values greater than 5 and the cosine for all values of 5 or less are calculated and the results are sent to an output raster dataset Multiple conditional statements can be used within the Con function but each must have a value or expression for true_expression that can be used to assign values to the output cells if the result of the evaluation of the condition is True The optional value or expression false expression can be applied if none of the results of the evaluations of the conditions are True conC Linlayerl lt 5 sinC inlayer1 inlayerl1 lt 20 cosC inlayer1 inlayer1 gt 50 100 0 In the above expression the sine is calculated for those values that are less than 5 the cosine is calculated for the values that are 5 or greater but less than 20 the values greater than 50 are assigned 100 and the remaining values which are 20 or greater but less than 50 are assigned 0 Multiple
58. it is appropriate to save the map document Usinc ArcGIS SpatiaL ANALYST Exercise 2 Finding a site for a new school in Stowe Vermont USA In this exercise you will find suitable locations for a new Step 1 school The four steps to produce such a suitability map are outlined below Landuse Elevation Recreation Schools Decide which datasets you need as inputs The datasets you will use in i this exercise are displayed to the right Calculate Slope Find Deane Find Distance Derive datasets Create data from existing data to gain new informa tion Reclassify each dataset to a com mon scale for example 1 10 giving higher values to more suitable Reclassify Reclassify Reclassify Reclassify attributes Weight datasets that should have 4 2 es ad more influence in the suitability oa AN atid PP model if necessary then combine aS Sy ie them to find the suitable locations Your input datasets in this exercise are Landuse Elevation T a Recreation Sites and Existing Schools You will derive Weight and Combine Datasets slope distance to recreation sites and distance to existing schools then reclassify these derived datasets to a common scale from 1 10 You will then weight them according to a percentage influence and combine them to produce a map displaying suitable locations for the new school The diagram to the right shows the process you will take QUI
59. length distance and direction orientation layer A collection of similar geographic features such as rivers lakes counties or cities of a particular area or place for display on a map A layer references geographic data stored in a data source such as a raster coverage or shapefile and defines how to display it least cost path See shortest path GLOSSARY local functions This group of Spatial Analyst functions computes an output raster where the output value at each location is a function of the input value at the same location logarithmic functions Perform exponential and logarithmic calculations on input rasters and numbers There are six logarithmic functions base e Exp base 10 Exp10 and base 2 Exp2 exponential capabilities and natural Log base 10 Log10 and base 2 Log2 logarithmic capabilities make permanent Creates a permanent raster from a temporary analysis result Map Algebra The analysis language for Spatial Analyst It provides access to a wide range of additional functions not included in the user interface and enables you to build more complex expressions and process them as a single command map document The disk based representation of a map Map documents can be printed or embedded into other documents Map documents have a mxd file extension map projection See projection mathematical functions Functions within the Raster Calculator that are appli
60. like bending a sheet of rubber to pass through the points while minimizing the total curvature of the surface It fits a mathematical function to a specified number of nearest input points while passing through the sample points This method is best for gently varying surfaces such as elevation water table heights or pollution concentrations Spline methods There are two Spline methods regularized and tension Regularized The Regularized method creates a smooth gradually changing surface with values that may lie outside the sample data range Tension The Tension method tunes the stiffness of the surface according to the character of the modeled phenomenon It creates a less smooth surface with values more closely constrained by the sample data range PERFORMING SPATIAL ANALYSIS Optional parameters Weight For Regularized weight defines the weight of the third derivatives of the surface in the curvature minimization expression The higher the weight the smoother the surface The values entered for this parameter must be equal to or greater than zero The typical values that may be used are 0 001 01 1 and 5 For Tension weight defines the weight of tension The higher the weight the coarser the surface The values entered have to be equal to or greater than zero The typical values are 0 1 5 and 10 Number of points Number of points identifies the number of points used in the calculation of each interp
61. mathematical computations within and between grid datasets raster layers tables and numbers and between valid combinations of them all 192 The set of operators is composed of arithmetical relational Boolean bitwise and logical operators that support both integer and floating point values and combinatorial operators which simultaneously overlay grid datasets or raster layers and maintain the input attributes Spatial Analyst functions are spatial cartographic modeling tools that analyze cell based data These functions are divided into five main categories local focal zonal global and application specific Local functions include trigonometric exponential reclassification selection and statistical functions The focal functions provide a set of tools for neighborhood analysis The zonal functions allow for zonal analysis and computing zonal statistics The global functions provide tools for full raster layer or grid dataset analysis such as the generation of Straight Line Euclidean and Cost Weighted Distance rasters The application functions provide tools that are applicable to specific tasks such as hydrology data cleanup and geometric transformation Qualifiers Qualifiers are parameters that control how and where an action is to take place Even though operators and functions perform actions the type and manner of the actions vary Actions either allow or require qualifying parameters to identify how to wha
62. model Semivariance Distance This model shows a progressive decrease of spatial autocorrelation equivalently an increase of semivariance until some distance beyond which autocorrelation is zero The spherical model is one of the most commonly used models PERFORMING SPATIAL ANALYSIS e The Exponential model Semivariance Distance This model is applied when spatial autocorrelation decreases exponentially with increasing distance Here the autocorrelation disappears completely only at an infinite distance The exponential model is also a commonly used model The choice of which model to use in Spatial Analyst is based on the spatial autocorrelation of the data and on prior knowledge of the phenomenon Understanding a semivariogram the range sill and nugget As previously discussed the semivariogram depicts the spatial autocorrelation of the measured sample points Because of a basic principle of geography things that are closer are more alike measured points that are closer will generally have a smaller difference squared than those farther apart Once each pair of locations is plotted after being binned a model is fit through them There are certain characteristics that are commonly used to describe these models 143 The range and sill When you look at the model of a semivariogram you will notice that at a certain distance the model levels out The distance where the model first flattens ou
63. navigate to the folder on your local drive where you set up your working directory c spatial Click School site Click Add 41 19 Click the Zoom In tool on the Tools toolbar and zoom in on the area that was deemed most suitable area 1 circled in yellow below Toalz ne Er oE a 1 ey ieee 42 20 Click View point to Toolbars and click Editor Main Menu VIEW SOUTCE 21 Click the Editor dropdown arrow and click Start Editing Start Editing Skop gatia Sare Hate YE o g EAT ayy EMdEdii Eann MoE Usina ArcGIS SpPatiaL ANALYST 22 Click c spatial or wherever you specified your working directory to be for the folder from which to edit data 23 Click OK 24 Click the Task dropdown arrow and click Create New Feature 25 Click the Target dropdown arrow and click School site 26 Click the Create New Feature dropdown arrow and click Create New Feature Target School site 4 Create New Feature 27 Draw a polygon on the screen in the location shown in the diagram Click and hold to add a polygon vertex drag the cursor and add another polygon vertex Continue until the polygon is complete Double click to close the polygon QUICK START TUTORIAL 28 Click the Editor dropdown arrow and click Stop Editing 29 Click Yes to save your edits Note A copy of this school site dataset can be found in the location ArcGIS ArcTutor Spatial Results Ex3
64. or specify a maximum distance or slope to consider Here you have to decide which landuse types are preferable This is subjective depending on your study The easiest way to decide what type of land is preferable for building on and what is not is to decide on the most preferable and then the least preferable Then out of the landuse types left again decide on the most and least preferable Do this until you have put the landuse type in order of preference Landuses of Water and Wetlands have been excluded from the analysis since you cannot build on water and there are restrictions against building on wetlands The chart below shows how the landuse types have been ranked 10 Suitability ae OM oY SX AY ae Se Ga amp Ge amp Landuse types Usinc ArcGIS Spatiat ANALYST Combining the suitability maps The last step in the suitability model is to combine the suitability maps of distance to recreation sites distance to schools slope and landuse If all objectives had equal weight the suitability maps could simply be combined at this point using the Raster Calculator However you know from breaking down the problem that the most preferable objective to satisfy is to locate the school close to recreational facilities and the next is to locate away from existing schools To account for the fact that some objectives have more importance in the suitability model you can weight the datasets giving those
65. over 3 000 meters with a landuse value of 5 will be given a value of 1 in the output raster Cells that do not meet the criteria cells with elevations lower than 3 000 meters and with a landuse value that is not 5 will be given a value of 0 Tip Accessing recently used expressions Right click inside the expression box and click Recent expressions Copy paste expressions into the expression box Tip Writing long expressions If your expression is too long to fit on a single line use the line continuation symbol at the end of the line then continue to type your expression on the next line Type expressions multiline in the online Help index for information on entering multiline expressions PERFORMING SPATIAL ANALYSIS Using the Raster Calculator to make selections on your data 1 Click the Spatial Analyst dropdown arrow and click Raster Calculator 2 Double click the layer you want to make a selection from to add it to the Expres sion box for example elevation 3 Click the operator you wish to use for example gt or And 4 Click or type a value for example 3000 or click another Layer depending on the operator you choose 5 Click Evaluate to perform the calculation The Raster Calculator will be closed and the result displayed Spatial Analyst Distance gt Density Interpolate to Raster gt Surface Analysis gt Cell Statistics Ne
66. parameters can be used in a conditional expression of the Con function conCCLinlayerl gt 5 amp inlayer1 lt 10 5 100 Operators and functions can be applied to the input grid datasets and raster layers in the conditional expression and the results evaluated conCsinC Linlayer1 gt 5 10 100 conC Linlayerl inlayer2 gt 10 100 5 197 conC inlayerl1 gt 5 cosC inlayer1 sinCLinlayer1 A Con function can be nested within another Con function conC inlayerl1 gt 23 5 conC inlayerl1 gt 20 12 conC CLinlayerl gt 2 amp Cingridl lt 17 sinCLinlayer1 100 Multiple grid datasets and raster layers can be used in the conditional statement or in the expression to be performed on the cells conC inlayerl c data ingrid2 gt 7 sinCLinlayerl1 cos c data ingrid2 con inlayerl lt 9 inlayerl c data ingrid2 tanC Linlayer3 cosC inlayer1 198 Usinc ArcGIS Spatiat ANALYST Map Algebra rules The following notes are a quick reference to using Spatial Analyst Map Algebra By stating rules and providing examples an overview of Map Algebra is presented This section only presents the grammar of the language Examples may not replicate your exact expression but by breaking down the components of your expression you should be able to find the grammatical rules that apply to its pieces General Map Algebra rules The result of a Map Algebra expression in the Rast
67. photographic projections used to draft the original data e Physical changes in the materials used for the maps shrinking or swelling Drafting errors can be minimized by taking care in drawing allotting sufficient time for drawing and entry rotating staff frequently from the mundane tasks and assigning dependable individuals to the tasks Maps in different projection systems can be registered in the computer but you must remember to transform these layers to the desired projection at a future time It is difficult to monitor the photographic projections but it can be requested from the supplier that the images be in the same projections before drafting or that the data be transformed in the computer if necessary Using Mylar in a temperature controlled environment will eliminate shrinking and swelling problems Usina ArcGIS SpatTiAL ANALYST Understanding cell based modeling IN THIS CHAPTER Understanding analysis in Spatial Analyst The operators and functions of Spatial Analyst NoData and how it affects analysis Values and what they represent The analysis environment The cell size and analysis Handling projections during analysis One of the strongest aspects of Spatial Analyst is its analytical capabilities Spatial Analyst takes a locational perspective where each cell represents a location and the value associated with each cell identifies the type of phenomenon that is at each location see Chapter
68. point in space or from an emitting source Continuous data is also referred to as field nondiscrete or surface data One type of continuous surface is derived from those characteristics that define a surface where each location is measured from a fixed registration point These include elevation the fixed point being sea level and aspect the fixed point being direction north east south and west 82 Another type of continuous surface includes phenomena that progressively vary as they move across a surface from a source Illustrations of progressively varying continuous data are fluid and air movement These surfaces are characterized by the type or manner in which the phenomenon moves The first type of movement is through diffusion or any other locomotion where the phenomenon moves from areas with high concentration to those with less concentration until the concentration level evens out Surface characteristics of this type of movement include salt concentration moving through either the ground or water contamination level moving away from a hazardous spill or a nuclear reactor and heat from a forest fire In this type of continuous surface there has to be a source The concentration 1s always greater near the source and diminishes as a function of distance and the medium the substance is moving through Usina ArcGIS SpatiaL ANALYST In the source concentration surface above the concentration of the phenomenon at a
69. raster shows the number of points from which it is visible Tip Specifying a Z factor To get accurate viewshed results the z units must be the same as the x y units If they are not the same use a Z factor to convert z units to x y units For example if your x y units are meters and your z units are feet you could specify a Z factor of 0 3048 to convert feet to meters Tip Using optional parameters Optional viewshed parameters SPOT OFFSETA OFFSETB and so on will be used if they are present in the feature observer attribute table For more informa tion search the ArcGIS Desktop Help system for Viewshed PERFORMING SPATIAL ANALYSIS Creating a viewshed dataset 1 Click the Spatial Analyst dropdown arrow point to Surface Analysis and click Viewshed 2 Click the Input surface dropdown arrow and click the input surface from which you want to calculate the viewshed 3 Click the Observer points dropdown arrow and click the feature layer to use as observer points 4 Optionally check use Earth curvature 5 Optionally change the default Z factor 6 Optionally change the default Output cell size 7 Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory 8 Click OK Spatial Analyst Spatial Analyst Layer elevation A MA Distance Density Interpolate to Faster Surface Analysis Cell Statis
70. set up selection queries or type in Spatial Analyst Arithmetic operators function syntax Inputs can be grid datasets or raster layers rn anie a e a T For example the result of Inlayer1 Inlayer2 2 results in an output raster displaying the mean value for every cell Mathematical operators and functions Operators and functions evalulate the expression only for input cells that are spatially coincident with the output cell Input raster Inlayer1 Input raster Inlayer2 Sqrt Inlayer1 Mathematical operators Mathematical operators apply a mathematical operation to i Output raster the values in two or more input rasters Three groups of mean of Inlayer1 and mathematical operators are available in the Raster Inlayer2 Calculator Arithmetic Boolean and Relational All operators including Bitwise Combinatorial and Logical can be typed into the Raster Calculator For supported operators and precedence values see Appendix B PERFORMING SPATIAL ANALYSIS 179 Boolean operators Boolean operators use Boolean logic TRUE or FALSE on input rasters on a cell by cell basis Output values of TRUE are written as 1 and FALSE as 0 Boolean operators And Or Xor Not And amp Finds where values are true nonzero in the cells of both input rasters Input raster Inlayer1 Input raster Inlayer2 Output raster Inlayer1 amp InLayer2 180 Or Finds
71. someone in third place and soil with a pH of 3 is not half as acidic as soil with a pH of 6 To carry this even further someone that is 60 years old is twice as old as someone that is 30 years old But the older of the two individuals can only be twice as old as the younger individual just once in a lifetime Also if their birth dates are examined and if the older individual was born in 1930 and the younger was born in 1960 the value 1930 is not twice the value 1960 The significance of this discussion on numbers is that all numbers cannot be treated the same It is important for you to know the type of measurement system being used in the raster dataset so that the appropriate operations and functions can be implemented and the results will be predictable Measurement values can be broken into four types ratio interval ordinal and nominal Ratio The values from the ratio measurement system are derived relative to a fixed zero point on a linear scale Mathematical operations can be used on these values with predictable and meaningful results Examples of ratio measurements are age distance weight and volume Distance Scale Kilometers 102 Interval Time of day years on a calendar the Fahrenheit temperature scale and pH value are all examples of interval measurements These are values on a linear calibrated scale but they are not relative to a true zero point in time or space Because there is no true zero poi
72. source shp Creating the cost dataset You will now create a dataset of the cost of traveling over the landscape based on the fact that it is more costly to traverse steep slopes and construct a road on certain landuse types 1 Right click the Suitability layer and click Remove 2 Click the Add Data button and navigate to the folder on your local drive where you set up your working directory c spatial U2 Click slope the dataset created in exercise 2 4 Click Add 5 Click the Add Data button again and navigate to the folder on your local drive where you installed the tutorial data the default installation path 1s ArcGIS ArcTutor Spatial 6 Click landuse and click Add 43 7 Right click landuse and click Zoom To Layer E amp Layers a M School_site O E roads Reclassifying slope 1 Click the Spatial Analyst dropdown arrow and click Reclassify Spatial Analyst 44 2 Click the Input raster dropdown arrow and click slope 3 Click Classify Reclassify a V oR e 4 Click the Method dropdown arrow and click Equal Interval 5 Click the Classes dropdown arrow and click 10 6 Click OK Usina ArcGIS Spatiat ANALYST E ee fae iy Fiia E tamnim a e me ier Servier L MM UN l 4 197128389 asa samea Teasa ee E Pines You want to avoid steep slopes when constructing the road so steep slopes should be
73. space to another Types of geometric transformations include rubber sheeting usually used for georeferencing projection using the projection information to transform the data from one projection to another translation shifting all the coordinates equally trotation rotating all the coordinates by some angle and changing the cell size of the dataset Rarely after the geometric transformation is applied to the input raster do the cell centers of the input raster line up with the cell centers on the output raster however values need to be assigned to the centers To derive a value for the center on the output raster a resampling technique must be used Resampling is the process of 79 determining new values for cells in an output raster that result from applying a geometric transformation to an input raster dataset There are several techniques that can be used to derive a value It does not matter if this transformation is a rectification a change in projection a change in cell size or a rotation The first step in transforming a raster dataset is determining the extent of the output dataset This is calculated by applying the transformation to the bounding box around the input raster The output raster extent is then gridded into cells at the resolution specified for the output If no resolution is specified the output resolution is determined from the resolution of the input The coordinate value for each
74. stored many times once for each of the cells in the category which will vary according to the storage technique but the attributes of the code are only stored once This reduces storage and simplifies updating 1 12 2 3 4 5 MNO DATA The field you use in the conversion process will affect the analysis that you can perform on the dataset If you have a polygon feature dataset that contains landuse type and owner for each parcel in a town you can use either attribute If you use 88 landuse type you will be able to ask questions such as Where are all the agricultural areas that are available for building However you cannot add join the owner attribute to the raster dataset because this is a many to one relationship That is there will probably be many owners for parcels containing forest If you use owner you can then ask questions such as Which parcels does Fred Smith own You can also relate the landuse type to the relational table because each parcel will have one landuse type Where this logic collapses is when one person owns multiple parcels with different landuse types In this case you may have to use parcel ID or some other unique feature when converting Usually with continuous data each cell has a unique value and will have no attribute table so there will be no attributes to relate In this case the many to one issue will not be applicable When creating a raster dataset the value
75. two ways 1 Assigning NoData to the output cell location if the NoData value exists for the location on any of the inputs in an operator or local function in its neighborhood in a focal function or in its zone in a zonal function 76 Zone with value 1 Zone with value 2 Zone with value 3 E Zone with value 4 Zone with value 5 E NO DATA 2 Ignoring the NoData cell and completing the calculations with all valid values The second option to ignore the NoData cell is not possible when using operators between two datasets or with local functions When a NoData cell is within the neighborhood of a cell in a focal function or a zone of a zonal function by default the sum median variety majority or minority of all cells with known values can be calculated and assigned to the output raster dataset this default can be overridden The associated table Integer categorical raster datasets usually have an attribute table associated with them The first item in the table is Value which stores the value assigned to each zone of a raster A second item Count stores the total number of cells in the dataset that belong to each zone Both Value and Count are mandatory items Usinea ArcGIS Spatiat ANALYST m 12 E No DATA An essentially limitless number of optional items can be incorporated into the table to represent the other attributes of the zone E NO DATA UNDERSTANDING RASTER DATA
76. using the Programs list in your Start menu 2 Click OK to open a new empty map Start using Arcktap with i A template Templates provide ready to use layouts and base maps for various geographic regions An existing map Browse for maps C spatialS patial T utonal med Immediately add data Do not show this dialog again 3 Click View point to Toolbars and click Spatial Analyst QUICK START TUTORIAL Main Menu File Edit View Insert Selection Tools Window Help ot Data View LA Layout View Zoom Data Zoom Layout er Bookmarks av Main Menu E Table Of Contents iv Standard ve Status Bar Tools Overflow Labels iv Draw Identify Results ce Scrollbars uj e Layout Spatial Analyst Effects Editor The Spatial Analyst toolbar 1s added to your ArcMap session zt al Analyst Laver Ji E Enabling the Spatial Analyst toolbar l 2 U9 Click the Tools menu Click Extensions and check Spatial Analyst Click Close 13 Adding data to your ArcMap session 1 Click the Add Data button on the Standard toolbar Standard Doe ed BK amp Ea 2 Navigate to the folder on your local drive where you installed the tutorial data the default installation path is ArcGIS ArcTutor Spatial on the drive where the tutorial data is installed Click elevation press and hold down the Shift key then click landu
77. weight the smoother the surface For the Tension method the higher the weight the coarser the surface 6 Optionally change the default Number of points to use in the calculation of each interpolated point 7 Optionally change the default Output cell size 8 Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory 9 Click OK Weight 1 Number of pots Output cell size Output raster Spatial Analyst Spatial Analyst Laver elevation iB ith a Distance Density Interpolate to Faster Inverse Distance Weighted Surface Analysis Cell Statistics Eriging Neighborhood Statistics Zonal Statistics Reclassify Raster Calculator Convert p Options Input pointa Sample_paints amp value field ELEVATION Spline type Requiarized oo Emp Coe EoD C Co lt Temporary a Cancel Usinc ArcGIS Spatiat ANALYST Kriging What is Kriging IDW and Spline discussed earlier are referred to as deterministic interpolation methods because they are directly based on the surrounding measured values or on specified mathematical formulas that determine the smoothness of the resulting surface A second family of interpolation methods consists of geostatistical methods such as Kriging that are based on statistical models that include autocorrelation the statistical relationship among th
78. 196 Each command reference in the Spatial Analyst ArcGIS Desktop Help system contains the specific handling of NoData in the computations Assigning values to NoData and NoData to values At times it may be desirable to replace cells with NoData in a grid dataset or raster layer with some other valid value The desired result for the output of the expression is not to treat the NoData values as NoData but to treat them as zeros or some other value There are many ways to change the NoData assignments to valid values in Spatial Analyst From the user interface use the Reclassify dialog box or with the Map Algebra use the IsNull and Con functions conCisnull CLinlayer1 0 inlayer1 The above expression says if Con the cell value on inlayer1 equals NoData IsNull then assign 0 to it true_expression 0 if it does not equal NoData it is a valid value assign the value of inlayer1 false_expression inlayer1 To perform the reverse and set cells with specific values to NoData to mask out cells use the SetNull function setnul CLinlayer1 gt 100 inlayer1 The above expression will assign all values greater than 100 to NoData The cell locations currently with NoData will remain NoData and the remaining cell locations will retain their input values Locations outside the grid dataset or raster layer limits or beyond the analysis extent are considered to be NoData Usinc ArcGIS Spatiat ANALYST Conditi
79. 5 56396 6691 12792 10036 6919 13382 2558 o5 Jo Snap breaks to data values Jo ioa Elot Cancel 30 Usinc ArcGIS SPpatiaL ANALYST You want to locate the school near recreational facilities The output reclassified distance to recreation sites so you will give higher values to locations close to dataset will be added to your ArcMap session as a new recreational facilities as these are the most desirable layer It shows locations that are more suitable for locating another school High values indicate more suitable locations 7 As you did when reclassifying the Slope layer click the first New value record in the dialog box and change it to a value of 10 Give a value of 9 to the next New value 8 to the next and so on Leave NoData as NoData 8 Click OK T Reclassify 2 x Input raster Distance to rec_sftes Reclass field Value bf Set values to reclassify New vates af Classity 0 1348 76279 Unique Randi i i E SER EO Add Entry seeeeeseeeees z errer TETTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTITTTTTTTTTTTETTTTTTTTTTTITITTTTTTTTTTETI Raf iaa gt Delete Entries I Change missing values to NoData Output raster Kmo S l Note A copy of this reclassified distance from recreation Cancel sites dataset can be found in the location ArcGIS ArcTutor Spatial Results Ex2 recR QUICK START TUTORIAL 31 Reclassifying distance to schools It is necessary to locate the new sc
80. Attribute handling within and between raster datasets is most effective and efficient when using nominal measurements Discrete versus continuous data A second subdivision of the values assigned to each cell is whether the values represent discrete or continuous data Discrete data Discrete data sometimes called categorical data most often represents objects These objects usually belong to a class for example soil type a category for example landuse type or a UNDERSTANDING CELL BASED MODELING group for example political party A categorical object has known and definable boundaries An integer value is normally associated with each cell in a discrete raster dataset Most integer raster datasets can have a table that carries additional attribute information Floating point values can be used to represent discrete data Discrete data is best represented by ordinal or nominal numbers Continuous data A continuous raster dataset or surface can be represented by a raster with floating point values referred to as a floating point raster dataset or integer values The value for each cell in the dataset is based on a fixed point such as sea level a compass direction or the distance of each location from a phenomenon in a specified measurement system such as the noise in decibels at various sites near an airport Examples of continuous surfaces are elevation aspect slope the radiation levels from
81. Browse for Coordinate System Lookin jig NAD 1983 303 NAD 1983 StatePlane Vermont FIPS 4400 prj py NAD 1983 StatePlane Virginia North FIPS 4501 pr amp NAD 1983 StatePlane Virginia South FIPS 4502 pr Gh NAD 1983 StatePlane Washington North FIPS 4601 prj Gh NAD 1983 StatePlane Washington South FIPS 4602 prj amp NAD 1983 StatePlane West Virginia North FIPS 4701 prj by NAD 1983 StatePlane West Virginia South FIPS 4702 pr by NAD 1983 StatePlane Wisconsin Central FIPS 4802 prj HE NAD 1983 StatePlane wisi A NAD 1983 StatePlane Wisi A NAD 1983 StatePlane Wye A NAD 1983 StatePlane Wye NAD 1983 StatePlane Wye amp NAD 1983 StatePlane wyc a Name NAD 1983 StatePlane Vermont FIPS 4400 pr Ad Show of type Spatial references aa Cancel QUICK START TUTORIAL 10 l1 12 14 15 16 17 18 Click OK on the Spatial Reference Properties dialog box Click OK on the Create New Shapefile dialog box A new shapefile called School site will be created and added to the Catalog tree Click File click Exit to close ArcCatalog and return to ArcMap Click the Add Data button and navigate to the folder on your local drive where you installed the tutorial data the default installation path is ArcGIS ArcTutor Spatial Click roads shp Click Add Name fioads shp Show of type Datasets and Layers lyr 7 Cancel Click the Add Data button again and
82. CK START TUTORIAL 23 Step 1 Inputting datasets 1 Click the Add Data button on the Standard toolbar Standard Ch toe ted EK freon 2 Navigate to the folder on your local drive where you installed the tutorial data the default installation path is ArcGIS ArcTutor Spatial on the drive where the tutorial data is installed 3 Click elevation then click and hold down the Ctrl key and click landuse rec_ sites and schools 4 Click Add Name Jelevation landuse rec_sites shp schools shp Show of type Datasets and Layers lpr Cancel Each dataset is added to the ArcMap table of contents as a layer 24 Setting the analysis properties Set up the analysis options like you did in Exercise 1 l U9 Click the Spatial Analyst dropdown arrow and click Options Specify a working directory on your local drive in which to place your analysis results Type c spatial to create a folder called spatial on your C drive Click the Extent tab Click the Analysis Extent dropdown arrow and click Same as Layer landuse Click the Cell Size tab Click the Analysis Cell Size dropdown arrow and click Same as Layer elevation Click OK on the Options dialog box Usina ArcGIS SpatTiAL ANALYST Step 2 Deriving datasets Deriving data from your input datasets is the next step in the suitability model You will derive the following e Slope from elevation e Di
83. Click the Extent tab 3 Click the Analysis extent dropdown arrow and choose an option to specify the extent for all subsequent analysis results Click OK The extent of a layer is the x y coordinates for the bottom left and the top right corners The analysis extent for your results can be set in the Extent tab of the Options dialog box The default extent is set to Intersection of Inputs so any analysis will only be performed where all layers overlay the minimum of the 4 inputs You may wish to change the default setting Union of Inputs sets the extent of the results to be the same as the combined extent of inputs to a function You may only wish to perform analysis on the area visible in the map Same as Display or you may wish to make the extent the same as another layer n the table of contents Same as Layer filename Alternatively you can specify a custom extent As Specified Below Tip Setting the snap extent Setting the snap extent to a specific raster dataset will snap all output raster datasets to the cell registra tion of the specified raster dataset 116 Spatial Analyst Spatial Analyst Layer Jlanduse 5 lth zi Distance d Density Interpolate to Raster lr Surface Analysis Cell Statistics Neighborhood Statistics Zonal Statistics Reclazsity Raster Calculator Convert General Extent Cell Size Same as Display
84. Click the Layer dropdown arrow and click elevation 5 Click the Adjust Transpar ency button and move the scroll bar up to the desired level of transparency try 30 You should now see the hillshade underneath the elevation raster El Hillshade of elevation Value High 255 Low 0 Value Low 438 444458 E elevation High 4361 333496 Main Menu File Edit View Insert Selection Tools Window Help Data View La Layout View Zoom Data oom Layout Bookmarks Toolbars B Table Of Contente ve Status Bar Overflow Labels Identify Results cen Scrollbars Ea Buler bh Fe F YF v Main Menu ve Standard 2 Tools ve Draw Layout ve Spatial Analyst 159 Viewshed What is viewshed Viewshed identifies the cells in an input raster that can be seen from one or more observation points or lines Each cell in the output raster receives a value that indicates how many observer points or lines can be seen from each location If you have only one observer point each cell that can see that observer point is given a value of 1 All cells that cannot see the observer point are given a value of 0 The observer points feature class can contain points or lines The nodes and vertices of lines will be used as observation points Why calculate viewshed Viewshed is useful when you want to know how visible objects might be such as finding well exposed places for communicati
85. Distance function e To set specific values to NoData or to set NoData cells to a value Replacing values based on new information Reclassification is useful when you want to replace the values in the input raster with new values This could be due to finding out that the value of a cell or a number of cells should actually be a different value for example the landuse in an area changed over time Grouping values together You may want to simplify the information in a raster For instance you may want to group together various types of forest into one forest class PERFORMING SPATIAL ANALYSIS Reclassifying values of a set of rasters to a common scale Another reason to reclassify is to assign values of preference sensitivity priority or some similar criteria to a raster This may be done on a single raster a raster of soil type may be assigned values of 1 10 that represent erosion potential or with several rasters to create a common scale of values For example when finding slopes most at risk of avalanche activity input rasters might be slope soil type and vegetation Each of these rasters might be reclassified on a scale of 1 10 depending on the susceptibility of each attribute in each raster to avalanche activity that is steep slopes in the slope raster might be given a value of 10 because they are most susceptible to avalanche activity For more details on suitability modeling see Finding a site for a n
86. Fill results the z units must be the same as the x y units If they are not the same use a Z factor to convert z units to x y units For example if your x y units are meters and your z units are feet you could specify a Z factor of 0 3048 to convert feet to meters PERFORMING SPATIAL ANALYSIS Creating a Cut Fill dataset 1 Click the Spatial Analyst dropdown arrow point to Surface Analysis and click Cut Fill 2 Click the Before surface dropdown arrow and click a surface 3 Click the After surface dropdown arrow and click another surface 4 Optionally change the default Z factor 5 Optionally change the default Output cell size 6 Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory 7 Click OK Before surface Spatial Analyst Spatial Analyst ai Laver After volcano I h Distance H Density interpolate to Raster d Surface Analysis Contour Cell Statistics Slope Neighborhood Statistics Aspect Hillshade Viewshed Zonal Statistics Reclassify Raster Calculator Convert b Options Before volcano After surface Alter volcano 3 Z factor ft 4 Output cell size sO 5 Output raster Tempora o e Cancel 163 Cell statistics What is the Cell Statistics function The following statistics can be computed on a cell by cell basis bet
87. Input surface dropdown arrow and click the surface you want to calculate slope for 3 Choose the Output measure ment units 4 Optionally type a value for the Z factor 5 Optionally change the default Output cell size 6 Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory 7 Click OK Spatial Analyst Distance a Density interpolate to Raster p Surface Analysis Contour Cell Statistics Neighborhood Statistics Aspect Zonal Statistics Hillshade Viewshed Reclazsify Cut Fill Raster Calculator Convert H Options Input surface Degree Percent o t Output measurement amp factor Output cell size Output raster Us nG ArcGIS Spatiat ANALYST Aspect What is aspect Aspect identifies the steepest downslope direction from each cell to its neighbors It can be thought of as slope direction or the compass direction a hill faces It is measured clockwise in degrees from 0 due north to 360 again due north coming full circle The value of each cell in an aspect dataset indicates the direction the cell s slope faces Flat slopes have no direction and are given a value of 1 NW W 270 SW 180 S nO m F 2 ET Imi imin 09 zZ The diagram below shows an input elevation dataset and the output aspect raste
88. Kriging dialog box to specify these parameters if they are known otherwise Spatial Analyst will estimate them for you 148 Creating a surface using kriging interpolation with a fixed radius 1 Click the Spatial Analyst dropdown arrow point to Interpolate to Raster and click Kriging 2 Click the Input points dropdown arrow and click the point dataset you wish to use 3 Click the Z value field dropdown arrow and click the field you wish to use 4 Click the Kriging method you wish to use 5 Click the Semivariogram model dropdown arrow and click the model you wish to use 6 Click the Search radius type dropdown arrow and click Fixed 7 Optionally change the default distance for the search radius setting 8 Optionally change the minimum number of points 9 Optionally change the default Output cell size 10 Optionally check Create Prediction of standard error 11 Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory 12 Click OK Spatial Analyst Distance H Density interpolate to Raster Inverse Distance Weighted Surtace Analysis b Spline Cell Statistics Neighborhood Statistics onal Statistics FReclassify Faster Calculator Convert b Options Input points sample_points Z value field OZONE 3 Kriging method Ordinary C Universal 4 Semivariogram model
89. No matter where on the continuum the feature falls the grid cell storage can represent it to a greater or lesser accuracy It is important to understand the type of data you are modeling whether it be continuous or discrete when making decisions based on the resulting values The exact site for a building should not be solely based on the soils map The square area of a forest cannot be the primary factor when determining available deer habitat A sales campaign should not be based only on the geographic market influence of a television advertising spree The validity and accuracy of boundaries of the input data must be understood 83 The resolution of a raster dataset The size chosen for a raster cell of a study area depends on the data resolution required for the most detailed analysis The cell must be small enough to capture the required detail but large enough so that computer storage and analysis can be performed efficiently The more homogeneous an area is for critical variables such as topography and landuse the larger the cell size can be without affecting accuracy Before specifying the cell size the following factors should be considered e The resolution of the input data e The size of the resultant database and disk capacity e The desired response time e The application and analysis that is to be performed A cell size finer than the input resolution will not produce more accurate data than the input data It
90. OUR ANALYSIS ENVIRONMENT r9 Specifying the coordinate system option for analysis results Click the Spatial Analyst dropdown arrow and click Options Click the General tab 3 Click the Analysis Coordinate System option you wish to use By default analysis results will be saved in the coordi nate system of the first input raster with a defined coordi nate system This minimizes the reprojection of raster data which can be slow and introduce error Alternatively click the second option to have analysis results saved in the coordi nate system of the data frame Click OK Spatial Analyst Distance H Density Interpolate to Faster Surface Analysis f Cell Statistics Neighborhood Statistics onal Statistics FReclassify Raster Calculator Convert General Extent Cell Size fe Stemp re elevation a Analysis Coordinate System Working directory Analysis mask Analysis output will be saved in the same coordinate sustem as the input or first raster input if there are multiple inputs Analysis output will be saved in the same coordinate suetem as the active data frame IY Display warning message if raster inputs have to be projected during analysis operation Cancel 4 115 Specifying an extent for analysis results Setting the extent for results 1 Click the Spatial Analyst dropdown arrow and click Options 2
91. Right click the Spatial folder point to New and click Shapefile 40 H a SCSI aS Copy Cte B Paste Eit X Delete Rename Refresh New Folder BA Search Personal Geodatabase Properties Layer Ma Group Layer Type School site for the name of the new shapefile Click the Feature Type dropdown arrow and click Polygon to choose the type of feature that will be created Click Edit to add spatial reference information to the shapefile Create New Shapefile Name Feature Type Polygon Spatial Reference Description Unknown Coordinate System preeseseseesosesensosessesesesey I Coordinates will contain M values Used to store 3D data I Coordinates will contain Z values Used to store route data Cancel Usina ArcGIS SPaTiaL ANALYST 7 Click Select to use a predefined coordinate system jala Helaian Pooper loc Coordinate System Heme Uniman EJ GQ Select Gabet a pracalren cranizbrimde nyalini impot a copines mabem ardat 2 amd M itoat domar fos on ehh posiate feg inahan dainsri inahan ches nyaj Wew Create anie coordrute iyim pere Edt he popati oof Fa curerdy iatbad carm pominae miem i Gets the coordinate system to Urke 8 Click the Projected Coordinate Systems folder click State Plane then click NAD 1983 and scroll to NAD 1983 StatePlane Vermont FIPS 4400 pry 9 Click Add
92. T The Reclass of landuse layer will be added to the table of contents It shows locations that are more costly than others for constructing a road based on the type of landuse The NoData value Wetlands is currently displayed transparently so you can see the layers underneath To make this value solid change it to white 8 Right click Reclass of landuse and click Properties 9 Click the Symbology tab 10 Click the Display NoData as dropdown arrow and click Arctic White 11 Click OK General Source Extent Display Symbology Fields Show Draw raster assigning a color to each value Value De i Scheme Value No Color z E cmimi f f p imin A S ETE f i E I5im A p pog f E E ITIN BED OSB Usinc ArcGIS SpatiaL ANALYST Spatial Analyst _ Spsttanayt E P E Distance Density Interpolate to Raster gt Surface Analysis gt Neighborhood Statistics Zonal Statistics Reclassify Raster Calculator Combining datasets You will now combine Reclass of slope and Reclass of landuse in order to produce a dataset of the cost of building a road at each location in the landscape in terms of steep ness of slope and landuse type In this model each dataset has equal weighting so it 1s not necessary to apply any weight as we did when finding the suitable location for the school 1 Click the Spatial Analyst dropdown arrow and click Raster Calculator Reclass of landuse
93. The first example shows a remap table with assignment statements that contain only an input cell value Example 1 Remap table for cell value reclassification LOWEST INPUT 3 LOWEST OUTPUT 2 5 6 7 15 Input cell values must always be sorted in ascending order APPENDIX C As with an INFO remap table the successive assignment statements implicitly define ranges of cell values for reclassification Thus it is essential that the input cell values be sorted in ascending order The output reclassified value for each range is automatically calculated from the value specified with LOWEST OUTPUT The first range of cell values is reclassified to the value specified with LOWEST OUTPUT The next range is reclassified to LOWEST OUTPUT plus one and so on until all assignment statements have a reclassified value Any cell values that fall outside the specified ranges are reclassified to NoData The following table summarizes the reclassification Input Cell Value Output Reclassified Value Less than 3 NoData 3 to 5 2 lowest output Greater than 5 to 6 Greater than 6 to 7 Greater than 7 to 15 Greater than 15 3 lowest output 1 4 lowest output 2 5 owest output 3 NoData If LOWEST INPUT has not been specified all cell values less than or equal to 5 would have been reclassified to 2 The reclassified value would have defaulted to 1 if a LOWEST OUTPUT of 2 was not specified The first method shows
94. The location of humans and the existing road network will also influence the moose The interactions between the elements are that moose prefer certain vegetation types and they avoid humans who can gain access to the landscape through roads A series of process models might be needed to ultimately find the locations with the greatest chance of spotting a moose MODELING SPATIAL PROBLEMS During this step you should also identify the necessary input datasets Input datasets might contain sightings of moose in the past week vegetation type and the location of human dwellings and roads Once you have identified them they need to be represented as a set of data layers a representation model To do this you need to understand how raster data is represented in Spatial Analyst Chapter 4 Understanding raster data explains the concepts involved when representing data The overall model made up of a series of objectives process models and input datasets provides you with a model of reality which will help you in your decision making process Step 3 Exploring input datasets It is useful to understand the spatial and attribute relationships of the individual objects in the landscape and the relationships between them the representation model To understand these relationships you need to explore your data A wide variety of tools are available in ArcGIS and Spatial Analyst to explore your data and these tools are cov
95. Usina ArcGIS SpatTiAL ANALYST typing in the known output coordinates The relationship between the control points chosen in the raster dataset and the output coordinate space is then determined Using this relationship and a polynomial transformation the raster dataset is converted from nonreal world space to real world space Polynomial transformation A polynomial transformation computed using the specified control points is applied so the input locations approximate the specified output locations using a least square fit The best fit polynomial transformation yields two formulas one for computing the output x coordinate for an input x y location and one for computing the y coordinate for an input x y location The goal of the least square fit is to derive a general formula that can be applied to all points usually at the expense of slight movement of the to positions of the control points When the general formula is derived and applied to the control point a measure of the error is returned The error is the difference between where the from point ended up as opposed to the actual location that was specified the to point position Links can be removed if the error is particularly large and more points can be added The more control points of equal quality used the more accurately the polynomial can convert the input data to output coordinates Projecting raster datasets The cells of a raster dataset will always b
96. WEST OUTPUT 2 5 69 1 15 Also it is not valid to specify an output reclassified value only on some of the assignment statements in a remap table If a user specified output value is entered it must be specified in all assignment statements APPENDIX C This is an invalid remap table All assignment statements must have a specified output value Invalid remap table for cell value reclassification LOWEST INPUT 3 5 10 6 7262 15 211 Slice and remap tables Slice uses remap tables to change ranges of values Using the Slice function you can identify the item names in the INFO remap table for the input and output columns Slice lt raster gt TABLE lt remap_table gt in item out item in_min Example sliceC Linlayerl table remap_table type code In the above example table is a keyword defining the type of slicing remap_table is the name of the remap table and code is the name of the output column The item containing the values to be sliced and the item containing the output value do not have to be adjacent in the INFO table If no names are specified for the input and output fields the default fields are VALUE and LINK If the specified input or output fields do not exist or if no fields are specified and the INFO table does not have VALUE and LINK fields an error will be returned Grid item syntax can be used in the Raster Calculator In the input Slice expression if no i
97. Weighted 136 Spline 139 Usinc ArcGIS Spatiat ANALYST CONTENTS Kriging 141 Performing surface analysis 149 Contour 151 Slope 153 Aspect 155 Hillshade 157 Viewshed 160 Cut Fill 162 Cell statistics 164 Neighborhood statistics 166 Zonal statistics 170 Reclassification 173 The Raster Calculator 179 Conversion 186 Appendix A 191 Map Algebra language components 192 Map Algebra rules 199 Appendix B 203 Table of supported operators and precedence values 204 About precedence values 205 AppendixC 207 About remap tables 208 Slice and remap tables 212 Reclass and remap tables 215 Slice versus Reclass relative to remap tables 216 Glossary 217 index 227 Getting started Section 1 Introducing ArcGIS Spatial Analyst IN THIS CHAPTER e Deriving information from data e Identifying spatial relationships e Finding suitable locations e Calculating cost of travel e Tips on learning ArcGIS Spatial Analyst A key benefit of geographic information systems GZS is the ability to apply spatial operators to GIS data to derive new information These tools form the foundation for all spatial modeling and geoprocessing Of the three main types of GIS data raster vector and tin the raster data structure provides the richest modeling environment and operators for spatial analysis ESRI ArcGIS Spatial Analyst extension adds a comprehensive wide range of cell based GIS operators to ArcGIS e Derive
98. a cell has area as a property The smaller the cell size the smaller the area and thus the closer the representation of the point feature Points with area have an accuracy of plus or minus half the cell size This is the trade off that must be made when working with a cell based system Having all data types points polylines and polygons in the same format and being able to use them interchangeably in the same language are more important to many users than a loss of accuracy 86 Linear data Linear data is all of those features that at a certain resolution appear only as a polyline such as a road a stream or a power line A line by definition does not have area In Spatial Analyst a polyline can be represented only by a series of connected cells As with a point the accuracy of the representation will vary according to the scale of the data and the resolution of the raster dataset Raster line features Polyline features Polygon data Polygonal or areal data is best represented by a series of connected cells that best portrays its shape Polygonal features include buildings ponds soils forests swamps and fields Trying to represent the smooth boundaries of a polygon with a series of square cells does present some problems the most infamous of which is called the jaggies an effect that resembles stair steps Since Spatial Analyst can handle very large raster datasets with millions of cells the jaggies bec
99. acilities so you will now calculate the straight line distance from Recreation Sites 1 Click the Spatial Analyst dropdown arrow point to Distance and click Straight Line Spatial Analyst Layer Distance elevation 7 4 lh gt Density Allocation Interpolate to Raster gt Cost Weighted Surface Analysis gt Shortest Path Cell Statistics Neighborhood Statistics Zonal Statistics Reclassify Raster Calculator Convert gt Options 2 Click the Distance to dropdown arrow and click rec_ sites Leave the defaults for all other options 26 3 Click OK Straight Line Distance to Maximum distance Output cell size T Create direction T Create allocation Output raster E Cancel The output distance to the rec _ sites dataset will be added to your ArcMap session as a new layer Values of zero indicate the location of a recreation site with values distances increasing as you move away from each of these sites Usinc ArcGIS SpatiaL ANALYST Note A copy of this distance to rec_ sites dataset can be found in the location ArcGIS ArcTutor Spatial Results Ex2 recD 4 Uncheck the box next to Schools to turn off this layer so you only see the locations of the recreation sites and the distance to them Deriving distance from schools You will now derive a dataset of distance from existing schools It is preferable
100. ap document at this point Click the File menu and click Save As Navigate to the location where you set up your local working directory c spatial specify a filename for the map document Spatial Tutorial and click Save Usinc ArcGIS SpatiaL ANALYST Exercise 3 Finding an alternative access road to the new school site In this exercise you will find the best route for a new access road The steps you might follow to produce such a path are outlined below and the steps you will take in this exercise are diagrammed to the right Create the source dataset if necessary The Source is the school site in this exercise Create the cost dataset by deciding which datasets are required reclassifying them to a common scale weighting then combining them Perform cost weighted distance using the Source and Cost datasets as inputs The Distance dataset created from this function is a raster where the value of each cell is the accumulated cost of traveling from each cell back to the source To find the shortest path you need a Direction dataset which can be created as an additional dataset from the cost weighted function This gives you a raster of the direction of the least costly path from each cell back to the source in this exercise the school site Step 3 Perform Shortest Path Crea
101. area such as a building a lake a road or a power line Assemblages of entities such as forest stands in a state soil types in a county or the single family houses in a town are features of an area that will most likely be represented by zones made up of many disconnected groups of connected cells Every cell on a raster belongs to a zone Some raster datasets contain only a few zones while others contain many 75 a 4 a aC pB Zone with value 1 BEon Zone with value 2 E gp Zone with value 3 E a E E Zone with value 4 Te Zone with value 5 Regions Each group of connected cells in a zone is considered a region A zone that consists of a single group of connected cells has only one region Zones can be composed of as many regions as are necessary to represent a feature the number of cells that make up a region has no practical limits Spatial Analyst provides the tools needed to turn regions into individual zones In the raster dataset above Zone 2 consists of two regions Zone 4 of three regions and Zone 5 of only one region NoData If a cell is assigned the NoData value then either no information or insufficient information about the particular characteristics of the location the cell represents is available The NoData value sometimes also referred to as the null value is treated differently from any other value by all operators and functions Cells with NoData values are processed in one of
102. ataset in the zonal statistics function Note that the value raster must be a raster dataset Feature data entered for the zone dataset will take the cell size specified on the cell size tab of the Options dialog box when it is converted to a raster The output resolution can be a specific cell size or the maximum or minimum cell size of the other input raster datasets into the function The default is set to the coarsest input raster dataset into the function For additional information on issues related to converting feature data please refer to Representing features in a raster dataset earlier in this chapter You will know if the input can be either a feature or a raster dataset because when you open the browser to enter the input the browser will say Raster datasets and feature classes in the Show of type input field and both feature and raster data will be displayed in the browser UNDERSTANDING RASTER DATA Choose a value raster xi Show of type Raster datasets gt Cancel If only rasters are allowed as input then the browser will say Raster Datasets in the Show of type input field and only raster datasets will be displayed Choose a source dataset x EE EE 2 Results i destination shp i rec_sites shp 2 roads shp 23 schools shp Show of type Raster datasets and feature classes Cancel Some browsers will allow the input of both feature and raster data Because of this
103. atasets representing adjacent areas into a single raster dataset There are two groups of geometric transformation functions translation and rotation which change the location represented by the cells Translation shifts the coordinates of the raster dataset by a specified x y offset and rotation rotates a raster dataset by a specified amount Flip and mirror are special cases of rotation functions Using flip a raster dataset can be flipped in a specified y direction With mirror a raster dataset can be mirrored in the x direction The geometric transformation functions that alter the geometric distribution within a raster dataset change the count of cells in some areas to correct geometric distortion Geometric distortion occurs when features in a raster dataset are not located where they should be in the real world From a known set of real world coordinates that match known locations in a raster dataset the raster cell locations can be adjusted to more closely represent reality Warp uses a polynomial transformation to correct for distortion in the entire raster dataset Merge and mosaic combine several spatially adjacent raster datasets into a single larger dataset The difference between the two is in how they handle the overlapping areas between the raster datasets In merge the cell is assigned to the last input value from the series of input raster datasets Mosaic smoothes the transition between the adjacent ras
104. ave the most influence on the final suitability map 10 10 8 8 a 6 7 a 2 0 N S fe y N 8 S A A A N LAS S O N Q SP NM VM YP KX WY O Distance to recreation sites meters Slope degrees 10 10 8 8 z gt 6 6 5 E z 3 53 4 4 2 z 2 2 0 0 K P N PD O O A p O o gt gS amp S G se BT pi eo Or aD a D D a ey al i lt gt o on o oe eS of Y d vA a S Q O a a A a A E A 46 y N Wa ha e Qa S Na Re ae N N N N 68 Distance to schools meters Landuse types Us nG ArcGIS Spatiat ANALYST The final suitability map is produced by combining all the maps together Weights can be assigned in the Raster Calculator at the same time as combining the suitability maps For example Distance to rec_sites 0 5 Distance to schools 0 25 Slope 0 125 Landuse 0 125 The result will be a suitability map displaying the best locations for the new school Higher values indicate more suitable locations See Exercise 2 of the quick start tutorial for how to use Spatial Analyst to find the best location for the new school See Exercise 3 of the quick start tutorial for how to use Spatial Analyst to find an alternative access road to the new school site Querying your data The alternative way to find suitable locations for the new school rather than creating a suitability map is to query your data Once you have created all the datasets you need slope distance to recreation sites and
105. ayer2 inlayer3 tanCLinlayer4 All rules that apply to parentheses for expressions built with operators grid datasets and raster layers apply to functions within expressions The function or operator that is within the most deeply nested parentheses will be processed first As for an operator the output of a function is a raster dataset and that raster dataset can be used as further input in the expression CsinCLinlayerl1 focalrange c data ingrid2 circle 7 6 inlayer1l CzonalmaxC Linlayer2 e algebra ingrid3 valuelayer 8 majorityC Linlayerl CLinlayer2 inlayer3 Linlayer4 amp amp A CLinlayer5 10 inlayer6 gt 8 Functions can be composed as long as the output of the inner function is of the same type as the corresponding argument to the outer function sinCfocalmean C Linlayerl1 lt 2 3 regiongroupC reclass inlayer1 c data reclass_table txt majorityCCLinlayerl inlayer2 cos inlayer3 zonalmin C inlayer4 Linlayer5 201 Appendix IN THIS APPENDIX e Table of supported operators and precedence values e About precedence values The Raster Calculator provides the ability to use a full suite of operators to perform analysis within and between multiple rasters This section provides a table which lists all supported operators followed by a discussion on precedence values A brief description accompanies each operator in the table followed by
106. be processed first CLinlayer1 C inlayer2 C Linlayer3 gt gt Linlayer4 Linlayer5 inlayer1 gt gt CCA inlayer2 inlayer3 CLinlayerl1 diff CLinlayer2 CLinlayer3 amp amp CLinlayer4 inlayer5 div Linlayer6 Operators with numbers Numbers can also be used in the expressions inlayerl 5 c data ingridl1 gt 8 inlayerl diff 3 200 Sometimes numbers are used as parameters within an expression involving an operator inlayer in 0 3 5 8 Expressions need not contain any data and can be constructed using only numbers and operators The output dataset will default to the existing dataset size and cell resolution that have been set in the analysis environment 5 The output will be a raster where each cell value contains the value 5 9 20 The output will be a raster where each cell value contains the value 29 Operations with numbers and rasters Numbers can be used in the creation of compound expressions inlayer1 inlayer2 5 inlayer1 lt 2 35 inlayerl lt 40 inlayer2 7 The order of processing is still dependent on the precedence value assigned to the operator The order of processing can be overridden with parentheses All of the rules for the precedence value and parentheses apply when expressions mix grid datasets raster layers numbers and operators CLinlayer1 5 20 inlayer1 inlayer2 5 2 10 CLinlayerl1 6
107. bra language provides tools to perform operations as well as local focal zonal global and application functions The language components The Map Algebra language provides building blocks that can be used singularly or in conjunction with one another to solve problems When combining the blocks a syntax or set of rules must be followed for Spatial Analyst to perform the requested task The grammar of the language establishes the meaning of the building blocks according to the position of a block in an expression If type constraints or syntax rules are violated an error message will be returned by Spatial Analyst and no result will be created The building blocks for the Map Algebra language are objects actions and qualifiers on the actions These delineations are similar to nouns verbs and adverbs Objects Objects either store information or are values They are inputs for computation or can be storage locations for output Grid datasets raster layers tables constants and numbers are all objects in the Map Algebra language Any word used in an expression that is not an operator function or constant is considered the proper name of an existing or new grid dataset or existing raster layer or table The function or operator being used provides the context in which to determine the object types Actions Actions that can be performed on input objects are operators and functions Spatial Analyst operators perform
108. ce Use the Measure tool on the Tools toolbar to decide on the maximum distance from each source PERFORMING SPATIAL ANALYSIS Calculating straight line distance 1 Click the Spatial Analyst dropdown arrow point to Distance and click Straight Line 2 Click the Distance to dropdown arrow and click the layer to find the distance to 3 Optionally specify a maxi mum distance Cells outside this distance will not be considered in the calculation and will be given the value of NoData Leaving the Maximum distance blank will not put a limit on how far distances will be measured 4 Specify an output cell size for the result s 5 Optionally click Create direction to create a raster displaying the straight line direction to the closest source 6 Optionally click Create allocation to create a raster where every cell is assigned the value of the closest source 7 Type a name for the result or leave the default to create a temporary result in your working directory 8 Click OK Spatial Analyst Spatial Analyst Distance Density Interpolate to Raster b Surtace Analysis Cell Statistics Neighborhood Statistics Zonal Statistics Reclassity Raster Calculator Convert p Options Straight Line Distance to Maxinum distance Output cell size QF Create direction oF Create allocation Output raster Allocation Cost Weighted Sho
109. cell in the output raster Density calculations You can calculate density using simple or kernel calculations In a simple density calculation points or lines that fall within the search area are summed and then divided by the search area size to get each cell s density value The kernel density calculation works the same as the simple density calculation except the points or lines lying near the center of a raster cell s search area are weighted more heavily than those lying near the edge The result is a smoother distribution of values Why map density Density surfaces are good for showing where point or line features are concentrated For example you might have a point value for each town representing total population but you want to learn more about the spread of population over the region With census data you may have a point representing the number of people in each town Since all the people in each town do not live at the population point by calculating density you can create a surface showing the predicted distribution of the population throughout the landscape PERFORMING SPATIAL ANALYSIS The following graphic gives an example of a density surface When added together the population values of all the cells equal the sum of the population of the original point layer 133 Density The Density function allows you to create a continuous density surface from a set of input features It can prov
110. ctions in the same manner as the INFO counterpart but allows for much greater flexibility in determining the reclassified values The remap table can be created with any text editor using the formatting rules discussed in the following paragraphs to define the parameters for reclassification The ASCII remap table is made up of optional comments optional keywords and required assignment statements Each statement must be on a separate line Comments are descriptive text that can be used to provide any additional information that needs to be included Comments can appear anywhere in the remap table but must be preceded by a pound sign The keywords establish the parameters in which the reclassification operates The assignment statements assign an output value to a specified input cell value or range of values The keywords are positioned at the beginning of the file before any assignment statements are entered Comments however can be anywhere and may precede the keywords There are two optional keywords that can be included in the lookup table The first is LOWEST INPUT which identifies the lowest cell value in a raster to consider for reclassification LOWEST INPUT is formatted as follows lowest input lt value gt where lt value gt is the minimum cell value to consider for reclassification LOWEST INPUT is used when you want to exclude cells with values below the specified value For example in a raster with cell values rangin
111. d inlayer2 on a cell by cell basis Or the operator can be placed in front of the input grid datasets raster layers numbers or constants Linlayer1 In the above equation an output raster dataset is created where each cell location will contain the negative of the value of the corresponding cell location in the raster layer inlayer1 An expression performing a function is dependent on the syntax and parameters associated with each function sincc data ingrid1 meanC inlayerl inlayer2 inlayer3 focalsumC inlayerl rectangle 3 3 zonalmeanC inlayerl c spatial ingrid2 eucdistance e data2 1ngridsource APPENDIX A All of the previous expressions are valid In the first expression an output raster dataset receives the sine of the values for the grid dataset ingrid1 on a cell by cell basis In the second expression an output raster dataset receives the mean of the values of the raster layers inlayer1 inlayer2 and inlayer3 on a cell by cell basis In the third expression each cell in the output raster dataset receives the result of the sum of the values of the eight immediate neighbors and the processing cell itself The fourth expression results are the mean of the values in the grid dataset ingrid2 delineated by the zones of the raster layer inlayer The final expression assigns to each cell in the output raster dataset its Straight Line or Euclidean distance from the set of source cells in the grid dataset ingr
112. data where the spatial information in the data to compute distances is used to model the spatial autocorrelation Once you have the spatial autocorrelation proceed with prediction using the fitted model thereafter the empirical semivariogram is set aside For the second task use the data again to make predictions Like IDW interpolation Kriging forms weights from surrounding measured values to predict at unmeasured locations As with IDW interpolation the measured values closest to the unmeasured locations have the most influence However the Kriging weights for the surrounding measured points are more sophisticated than those of IDW IDW uses a simple algorithm based on distance but Kriging weights come from a semivariogram model that was developed by looking at the spatial nature of the data To create a continuous surface or map of the phenomenon predictions are made for each location cell centers in the study area based on the semivariogram model and the spatial arrangement of measured values that are nearby Search radius We know from a basic principle of geography that things that are close to one another are more alike than things farther away Using this principle we can assume that as the locations get farther from the prediction location the measured values will have Usinc ArcGIS SpatiaL ANALYST less spatial autocorrelation with the unknown value for the location we are predicting Thus we can eliminate those far
113. dataset of the elevation of the area Landuse Raster dataset of the landuse types over the area Roads Feature dataset displaying linear road network Rec sites Feature dataset displaying point locations of recreation sites Schools Feature dataset displaying point locations of existing schools Destination Feature dataset displaying the destination point for use in finding the shortest path In this tutorial you will first explore your data to learn more about it and to understand its relationships Then you will find suitable locations for the new school based on the fact that it is preferable to locate close to recreational facilities for ease of access to these places for the children and it is also important to locate away from existing schools to spread their locations over the town You also want to avoid steep slopes and certain landuse types 12 Once you have found the best sites you will examine these locations to see which 1s potentially the most suitable You will then examine the data to see if any problems may arise from building the school in the chosen location This tutorial is divided into exercises and is designed to let you explore the functionality of Spatial Analyst at your own pace e Exercise 1 shows you how to display and explore your data using the functionality of ArcMap and Spatial Analyst You will add and display your datasets high light values on the map identify locations to obtain values examin
114. e a histogram and create a hillshade e Exercise 2 helps you to find the best location for a new school by creating a suitability map You will derive datasets of distance and slope reclassify datasets to a common scale weight those that are more important to consider then combine the datasets to find the most suitable locations e Exercise 3 shows you how to find an alternative route the least cost or shortest path for a road to the new school site Copies of the results obtained from each exercise are stored in the Results folder on your local drive where you in stalled the tutorial data the default installation path is ArcGIS ArcTutor Spatial Results You will need about one hour of focused time to complete the tutorial However you can perform the exercises one at a time if you wish saving your results along the way when recommended Usina ArcGIS SpatiaL ANALYST Exercise 1 Displaying and exploring your data You should explore your data to understand it and to identify relationships Understanding your data and recognizing relationships will enable you to more accurately prepare your data for analysis In this exercise you will open ArcMap and add the Spatial Analyst toolbar to your ArcMap session You will then explore your datasets using functionality within ArcMap and Spatial Analyst Starting ArcMap and Spatial Analyst l Start ArcMap by either double clicking a shortcut installed on your desktop or
115. e a temporary dataset in your working directory 10 Click OK on the Reclassify dialog box Reclassify Input raster e spatial dataheleyvation Reclass field Value 3 Set values to reclassify Change missing values to NoData Output raster lt Temporary Fy OF Cancel Classification Classification Statistics Classification Method Count 602765 Minimum 436 Classes Maximum 4383 r Data Exclusion Sum 947399523 Mean 1571 75603 T Use Custom Min amp Mer Exclusion Standard Deviation 701 842713 below custom mit Show class far values I ab Sampling above custom mar Columns 100 I Show Std Dev J Show Mean Break Values Advanced Statistics B58 3 8 E m 759 777344 D 0 W D a o rts 929 375 sels s wl 3 9 1114 39063 S z S ol N a 1268 570321 1453 58594 1684 985547 20000 1946 96094 2255 32031 15000 2640 76953 4383 10000 5000 0 436 1422 75 2409 5 3396 25 4383 Snap breaks to date values Jo Leg Elot 177 Setting specific values to NoData Changing a value to NoData You can type NoData in the input box for a new value to change an input value to NoData 178 1 Click the Spatial Analyst dropdown arrow and click Reclassify Click the Input raster dropdown arrow and click the raster with values you wish to set to NoData Click the Reclass field dropdown a
116. e map docu 2 Navigate to the directory in So ment which makes all which you wish to save the Save ke Lya Fia temporary results permanent result and specify a name Make Permanent in the specified working 3 Click Save Properties directory using the default output names Setting your working directory Click Options on the Spatial Analyst toolbar then click the General tab to set up your working directory for your analysis results Look in ca Spatial Name Slope Save as type ESRI GRID z Cancel 110 Usina ArcGIS SPaTiaL ANALYST Making results paver Why save your map permanent by saving the File Edit View Insert Selection Tools Window Help document map document C CtrleN Saving the map document is a te Open cho quick way to make all your 1 Click the File menu and click save Ctrl S temporary analysis results Save As ki 5 permanent and provides a way to 2 Navigate to the location in save your work in order to which you want to save the continue your analysis at a later map document date 3 Type a filename ue a z dropdown arrow and click N 9 Spatial A quick way to save your ArcMap Documents mxd map document E elevation 5 Click Save E info Once you have specified a location J landuse and name for your map document e simply click the Save button on the Standard toolbar to save your work File name Spatial Analysis mad Save az type
117. e measured points Because of this not only do these techniques have the capability of producing a prediction surface but they can also provide some measure of the certainty or accuracy of the predictions Kriging is similar to IDW in that it weights the surrounding measured values to derive a prediction for an unmeasured location The general formula for both interpolators is formed as a weighted sum of the data Z S AZ s i l where Z s is the measured value at the ith location A is an unknown weight for the measured value at the ith location s is the prediction location N is the number of measured values In IDW the weight 4 depends solely on the distance to the prediction location However in Kriging the weights are based not only on the distance between the measured points and the prediction location but also on the overall spatial arrangement among the measured points and their values To use the spatial PERFORMING SPATIAL ANALYSIS arrangement in the weights the spatial autocorrelation must be quantified Thus in Ordinary Kriging the weight 2 depends on a fitted model to the measured points the distance to the prediction location and the spatial relationships among the measured values around the prediction location To make a prediction with Kriging two tasks are necessary 1 to uncover the dependency rules and 2 to make the predictions To realize these two tasks Kriging goes through a t
118. e square and of equal area with respect to the Cartesian coordinate system map coordinate space associated with the raster dataset The shape and area a cell represents on the surface of the earth will never be constant across a raster dataset Since the area represented on the face of the earth by the cells will vary across the raster UNDERSTANDING RASTER DATA dataset the output cell size and the number of rows and columns may change when projected Converting from one projection to another can also change the shape and area a cell represents on the surface of the earth Each projection treats the relationship between a three dimensional world and a two dimensional one differently You should be aware of the properties and assumptions for each projection before selecting one When displaying and performing analysis with raster datasets they should be in the same coordinate space and in the same projection If two raster datasets are in different coordinate systems the values of the coordinates are on different scales Errors will occur when comparing such datasets because they will represent different locations Geometric transformation When you rectify a raster dataset project it convert the raster dataset from one projection to another or change the cell size you are performing a geometric transformation Geometric transformation is the process of changing the geometry of a raster dataset from one coordinate
119. e this raster you need to identify the cost of constructing a road through each cell Although the cost raster is a single dataset it is often used to represent several criteria In the following example landuse and slope influence the construction costs These datasets are in different measurement systems landuse type and percent slope so they cannot be compared relative to one another and must be reclassified to a common scale Us nG ArcGIS SPaTiaL ANALYST Creating a cost raster Weighting datasets according to percent influence Reclassifying your datasets to a common scale The next step in producing the cost raster is to add the reclassified datasets together The simplest approach is to just add them together However you may know that some factors are more important than others For instance avoiding steep slopes may be twice as important as the landuse type so you might for example give this dataset an influence of 66 percent and the landuse dataset an influence of 34 percent to make 100 percent The following diagram shows the conceptual process In this example slope and landuse have been reclassified on a scale of 1 10 The attributes of each dataset should be examined in turn to decide on their contribution to the cost of building a road For example it is more costly to traverse steep slopes so steeper slopes will be assigned higher costs when reclassifying this dataset The graphics below display the results
120. e time Range determines the range of values on a cell by cell basis period in this case highlighting areas of urban sprawl areas between inputs shaded red Standard Deviation computes the standard deviation of the values on a cell by cell basis between inputs Sum computes the sum of the values on a cell by cell basis between inputs Variety determines the number of unique values on a cell by cell basis between inputs 164 Us nG ArcGIS Spatiat ANALYST Calculating cell Statistics The Cell Statistics function allows you to compute a statistic for each cell in an output raster based on the values of multiple input rasters If any cell in one of the input rasters contains a value of NoData the value of the cell in the same location in the output raster will be NoData Tip Setting analysis options Click Options on the Spatial Analyst toolbar to set up your working directory extent and cell size for your analysis results Tip Browsing for files or directories If the file you need is not in your table of contents or if you need to check the directory to place your output raster click the Browse button PERFORMING SPATIAL ANALYSIS Creating a dataset using Cell Statistics 1 Click the Spatial Analyst dropdown arrow and click Cell Statistics Click the Layers you want to use in the calculation use the Shift key to highlight multiple layers Alternatively click the Browse button to access
121. eate a temporary dataset in your working directory 12 Click OK Spatial Analyst Distance b Density Interpolate to Raster Inverse Distance Weighted Surace Analysis Ir Spline Cell Statistics Neighborhood Statistics onal Statistics Reclassify Raster Calculator Convert b Options Input points sample_points Z value field OZONE 3 Kriging method Ordinary C Universal Semivariogram model Spherical a 5 Advanced Parameters Search radius type Variable z 6 Search Radius Settings Output cell size T Create Prediction of standard error Number of points Maximum distance 12 1000 A 1917 998962 9 g Temporary gt 5 k Temporary gt 4 1 1 iutput raster Cancel 10 12 147 With a Fixed radius the radius of the circle used to find input points is the same for each interpolated cell The default radius 1s five times the cell size of the output raster By specify ing a minimum number of points you can ensure that within the Fixed radius at least a minimum number of input points will be used in the calculation of each interpolated cell Tip Deciding on the radius or the number of points Use the Measure tool on the Tools toolbar to measure distance between points to get an idea of the radius and number of points to use Tip Changing the lag size major range partial sill and nugget Click Advanced Parameters on the
122. ebra syntax Click About Building Expressions to access help for the Raster Calculator including the Spatial Analyst functional reference PERFORMING SPATIAL ANALYSIS Using the Raster Calculator to perform Spatial Analyst functions 1 Click the Spatial Analyst dropdown arrow and click Raster Calculator Type in the Map Algebra function for example slice 3 Type an open bracket 4 Double click the layer you want to use as an input dataset Type a close bracket or type a comma add other parameters then close the brackets Click Evaluate Spatial Analyst Spatial Analyst Layer fianduse O I ih Distance gt Density Interpolate to Raster gt v Surface Analysis Cell Statistics Neighborhood Statistics Zonal Statistics Reclassify Raster Calculator Convert Options Raster Calculator Layers elevation aff se of ad aps e ee effet se e shcel elevation eqinterval 20 wa j bout building expressions 185 Conversion Converting from features to raster Polygons polylines and points from any type of source file can be converted to a raster It doesn t matter if the source data for the features comes from a CAD drawing coverage or shapefile it can be converted to a raster You can convert features using both string and numeric fields If you use a string field then each unique string in the field is a
123. ed to the values of a single input raster There are four groups of mathematical functions available Logarithmic Arithmetic Trigonometric and Powers 221 mathematical operators Operators within the Raster Calculator that apply a mathematical operation to the values in two or more input rasters There are three groups of mathematical operators available Arithmetic Boolean and Relational Arithmetic Boolean And Or Xor Not Relational gt lt lt gt lt model 1 An abstraction of reality 2 A set of clearly defined analytical procedures used to derive new information nearest neighbor resampling Uses the value of the closest cell to assign a value to the output cell when resampling neighborhood statistics A focal function that computes an output grid where the value at each location is a function of the input cells within a specified neighborhood of the location NoData Some rasters have empty cells within the area for which data was collected For grids these cells are assigned NoData while for other formats they are often assigned a special value such as 9999 Rasters with some NoData cells can also be created using the Spatial Analyst Reclassify function You can control the display of NoData by setting the NoData color on the Symbology tab of the Layer Properties dialog box 222 normalize To make conform to or reduce to a standard or norm Data can be normali
124. efault is 45 degrees The hillshade to the left has an azimuth of 315 and an altitude of 45 degrees PERFORMING SPATIAL ANALYSIS Azimuth is the angular direction of the sun Using for display l j mn By placing an elevation raster on top of a created hillshade then making the elevation raster transparent you can create realistic images of the landscape Add other layers such as roads or streams to further increase the informational content in the display Using hillshading in analysis By modeling shade the default option you calculate the local illumination whether the cell falls in a shadow or not By modeling shadow you can identify those cells that will be in the shadow of another cell at a particular time of day Cells that are in the shadow of another cell are coded 0 all other cells are coded with integers from 1 to 255 You can reclassify values greater than 1 to 1 producing a binary output raster In the example below the black areas are in shadow The azimuth is the same but the sun angle altitude has been modified Sun angle 45 degrees Sun angle 60 degrees 157 Computing hillshade The Hillshade function is typically used to create a shaded relief map from an elevation raster The default azimuth and altitude values work well for graphical display For analysis you may wish to modify these values Azimuth is the angular direction of the sun the default angle of
125. emove all layers except Cost aa School site and Roads Reclassify 7 Click Reclass of landuse press and hold down the Ctrl adi Convert gt key click Reclass of slope slope and landuse ptions 8 Right click one of the layers and click Remove 48 Usinc ArcGIS SpatiaL ANALYST Mn A W Cost Weighted Click the Distance to dropdown arrow and click School site Click the Cost raster dropdown arrow and click Cost Check Create direction Click OK ost raster aximum distance Jutput cell size lt Temporary gt I Create allocation lt Temporary gt war Output raster I lt Temporary gt Cancel The Distance and Direction datasets are added to your ArcMap session as layers Click the output Distance layer in the table of contents click again and rename it Distance Click the output Direction layer in the table of contents click again and rename it Direction QUICK START TUTORIAL amp Layers E roads E School_site E Distance lt VALUE gt E 0 23 804 6063 E 23 804 6063 47 609 2125 E 47609 2125 71 413 8188 B 771 413 8188 95 218 425 E 95 218 425 119 023 031 E 119 023 031 142 827 638 E 142 927 638 166 632 244 E 166 632 244 190 436 85 E 190 436 85 214 241 456 WB 214 241 456 238 046 063 E Direction VALUE P Source 0 E Right 1 E Lower Right 2 Step 3 Performing shortest path You are now almost ready t
126. er Suitable locations ih amp amp Joshua Tree NP a E Campgrounds Suitability Analysis Winter Climbing Locations A g Suitable locations Joshua Tree National P ark Rock climbing areas E Most Suitable E Major Roads a nterstate State Hwy Secondary minor road Ramp E Trails Type Other Dirt ee Dirt 464 EM DEM Value n High 2657 Low 64 E HillShade Value High 254 Low 0 E B Park overview E Campsites aA a O Roads E Streets E Trails rm RA hd sier Dasda THE E gt Drawing k C O A E faria z fn 7 B Z u A Be ee 8 11 14 0 05 Inches Suitable locations for winter rock climbing based on distance from a campsite and steep south facing slopes Usina ArcGIS Spatiat ANALYST Calculating cost of travel Travel cost analysis involves modeling to generate the cost surface and then calculating optimum corridors across the surface Calculating travel cost can provide a rich set of information for decision making HaulCostAnalysis mxd ArcMap Arcinfo Eie Edt View Inset Selection Tools Window Help Dae S s BAX so Z 32 RP Spatiatanayst Layer Hilshade A h 1 2 3 9 a E amp Pacific Northwest Rivers E Roads Travel Cost Per Linear Mile Interstate US Route Primary State Route Secondary Roul Road Class 3 4 Jeep Trail Above Ave Hillshade Value High 254 Low 0 Haul Cost Amounts Cost E iii
127. er landuse 231342 353 471090 085 434665 083 200342 353 A Lok cancel Usina ArcGIS Spatiat ANALYST Click the Cell Size tab Click the Analysis Cell Size dropdown arrow and click Same as Layer elevation Click OK on the Options dialog box This will set the cell size for your analysis results to be at a 30 meter resolution the largest cell size of your datasets Examining a histogram 1 Click the Layer dropdown arrow and click landuse 2 Click the Histogram button Spatial Spatial Analyst Layer landuse The histogram displays the number of cells of each type of landuse 3 Close the Histogram QUICK START TUTORIAL Creating a hillshade Creating a hillshade from elevation data and adding trans parency gives you a good visual impression of the terrain and can greatly enhance the display of your map 1 Click the Spatial Analyst dropdown arrow point to Surface Analysis and click Hillshade Spatial Analyst x Spatial Analyst a Layer landuse x ye Hih Distance gt Density Interpolate to Raster Contour Cell Statistics Slope Neighborhood Statistics Aspect Zonal Statistics Viewshed Cut Fill Reclassify Raster Calculator Convert gt Options 2 Click the Input surface dropdown arrow and click elevation Leave the defaults for all other options Hillshade Input
128. er Calculator can be a raster dataset a shapefile a table or a file stored on disk such as an ASCII file All operators must be separated from their operands by blank spaces on both sides inlayerl1 inlayer2 div c data ingrid3 inlayerl amp inlayer2 inlayerl c results ingrid2 inlayer3 Parentheses are not operators and do not need the blank spaces on both sides CLinlayerl div inlayer2 inlayer3 inlayerl1 CLinlayer2 8 CCLinlayerl1 6 inlayer2 amp d data ingrid3 Grid datasets raster layers shapefiles coverages tables and item names can consist of most combinations of characters and numbers Linlayer_1 inlayer2 Linlayer12345 inlayer2 Symbols such as and cannot be used in a name APPENDIX A Map Algebra rules for operators Most operators can be utilized on multiple integer or floating point grid datasets or raster layers inlayerl inlayer2 inlayerl1 amp amp inlayer2 inlayer1 diff inlayer2 Generally the operator is placed between two input grid datasets or raster layers however due to the nature of the operator unary operators are placed before a single input grid dataset or raster layer Linlayer1 AA c mydirectory ingrid1l A inlayer1 Whenever the NoData value is encountered at a cell location on any of the input grid datasets or raster layers no matter what the operator the output for that location will receive N
129. ered throughout the various books accompanying ArcGIS Step 4 Performing analysis At this stage you need to identify the tools to use to build the overall model Spatial Analyst provides a wide variety of tools to serve this purpose In our moose spotting example you may need to identify the tools necessary to select and weight certain vegetation types and buffer houses and roads and weight them appropriately Chapter 5 Understanding cell based modeling presents the principles for performing cell based modeling and the issues that must be considered Chapter 6 Setting up your analysis environment and Chapter 7 Performing spatial analysis show how these principles are realized in Spatial Analyst 59 Step 5 Verifying the model s result Check the result from the model in the field Do certain parameters need changing to give you a better result If you created several models determine which model you should use You need to identify which model is best Does one particular model clearly meet your initial goal better than the rest Step 6 Implementing the result Once you have solved your spatial problem verifying that the result from a particular model meets your initial expectations outlined in step 1 implement your result When you visit the locations with the greatest chance of spotting moose do you in fact see any 60 Usinc ArcGIS Spatiat ANALYST Using the conceptual model to create a sui
130. eturn raster datasets in which the associated table has additional items For combinatorial operators and functions the output not only contains the Value and Count of a new raster dataset but also identifies the combination of values in the input that resulted in each output value Multiple outputs While most functions generate a single new raster dataset as output a few functions such as the Euclidean Allocation and Cost Allocation create multiple output raster datasets A function that generates multiple output raster datasets returns one of the raster datasets as its primary result The remaining raster datasets appear as optional output arguments to the function They will be permanently saved to the current working directory if output raster names are supplied for the arguments or to the directory you specify if a full pathname is supplied Primary output Input raster datase Optional outputs 22 Us nG ArcGIS Spatiat ANALYST Output value types The input value type can determine the value type of the resultant raster dataset Generally when an operator not a function is applied to one or more input integer grid datasets or raster layers the result will be an integer raster dataset when an operator is applied to one or more floating point grid datasets or raster layers the result will be a floating point raster dataset When an operation is performed on two or more grid datasets or raster layers and a
131. ew school in Stowe Vermont USA in Chapter 2 Setting specific values to NoData or setting NoData cells to a value Sometimes you want to remove specific values from your analysis This might be for example because a certain landuse type has restrictions such as wetland restrictions which means you cannot build there In such cases you might want to change these values to NoData in order to remove them from further analysis In other cases you may want to change a value of NoData to be a value such as in the case where new information means a value of NoData has become a known value 173 Reclassifying your data The Reclassify dialog box enables you to modify the values in an input raster and save the changes to a new output raster There are many reasons why you may wish to do this including replacing values based on new information grouping entries reclassifying values to a common scale for example for use 1n suitability analysis or setting specific values to NoData or setting NoData cells to a value The Load button enables you to load a remap table that was previously created by pressing the Save button and apply it to the input raster gt Tip Replacing NoData values NoData values can be turned into numeric values in the same way as replacing any value Tip Changing the classes of your old values Click Classify to classify your old values differently Click Unique to separate c
132. examining the data you have on each potential area 26 Right click the output layer in the table of contents and click Make Permanent 27 Navigate to the folder on your local drive where you set up your working directory c spatial 28 Type Suitability and click Save The temporarily created dataset will now be perma nently stored on disk 38 Note A copy of this Suitability dataset can be found in the location ArcGIS ArcTutor Spatial Results Ex2 Suitability 29 Click the output raster twice slowly Rename the layer Suitability E roads E Value MB 3 25 3 825 E 3 825 4 4 E 4 4 4 975 Mi 4 975 5 55 You decide that the best location is somewhere within Area l as there are three recreation sites in the neighboring area the ski resort being one of them Also although you know that a considerable volume of traffic already uses the current access road to this potential site you are involved in plans for constructing an alternative road to this area which will help alleviate the volume of traffic on the current access road 30 Click the Schools layer in the table of contents press the Ctrl key and click all other layers except Suitability use the scroll bar to move down the table of contents 31 Right click one of the highlighted layers and click Remove You have now completed Exercise 2 You can continue on to Exercise 3 or you can stop and continue later Which ever option you choose save the m
133. f all groups of cells that are less than 7 200 square meters These cells may be either misclassified or too small for upcoming analysis Effect of Nibble applied to the base classification UNDERSTANDING CELL BASED MODELING Other generalization functions include BoundaryClean and MajorityFilter which smooth the boundaries between different zones Expand which expands specified zones Shrink which shrinks specified zones and Thin which thins linear features in a raster dataset and is particularly useful for cleaning up scanned paper maps Effect of MajorityFilter applied to the output from Nibble 99 Resolution altering The resolution altering functions change the resolution of an existing raster dataset If you have one raster dataset at a finer resolution than the rest of the raster datasets you may wish to resample the finer resolution dataset to the same resolution of the coarser ones to make all the raster datasets the same resolution This speeds up processing and reduces the data size The effect on the raster of resampling to a coarser resolution The two principal ways to determine values when changing the resolution of a raster dataset are interpolation and aggregation One group of resampling interpolation functions uses either the nearest neighbor bilinear or cubic methods on the values of the input raster dataset A second group of resampling interpolation functions uses a specified statistical agg
134. f the file you need is not in your table of contents or if you need to check the directory to place your results click the Browse button PERFORMING SPATIAL ANALYSIS 1 Click the Spatial Analyst dropdown arrow point to Convert and click Raster to Features Click the Input raster dropdown arrow and click the raster you want to convert to a feature Click the Field dropdown arrow and click the field with which you want to define features in the Input raster Click the Output geometry type dropdown arrow and click the type of feature you want to create from your raster data Specify a name for Output features or leave the default to create a temporary dataset in your working directory Click OK Spatial Analyst Spatial Analyst Layer Jianduse I Hin E Distance b Density interpolate to Raster f Surtace Analysis a Cell Statistics Neighborhood Statistics onal Statistics Reclassity Faster Calculator Features ta Raster Raster to Features Options Raster to Features Input raster Field Output geometry type Output features 189 Appendix IN THIS APPENDIX e Map Algebra language components e Map Algebra rules In addition to the many functions that are available through the Spatial Analyst user interface a wide variety of additional functions are available through Map Algebra including Spatial Analyst f
135. f the world as an array of equally sized square cells or pixels arranged in rows and columns Each grid cell is referenced by its geographic x y location See raster hillshade The hypothetical illumination of a surface histogram A chart representing a frequency distribution The width of each rectangle in this chart represents a class interval The area of each rectangle is proportional to the corresponding frequency Usinc ArcGIS Spatiat ANALYST interpolation A set of Spatial Analyst functions that predict values for a surface from a limited number of sample data points creating a continuous raster Inverse Distance Weighted An interpolation method where cell values are estimated by averaging the values of sample data points in the vicinity of each cell The closer a point is to the center of the cell being estimated the more influence or weight it has in the averaging process kriging A surface interpolation method available in Spatial Analyst It is a geostatistical interpolation method based on statistical models that include autocorrelation the statistical relationship among the measured points Kriging weights the surrounding measured values to derive a prediction for an unmeasured location Weights are based on the distance between the measured points the prediction location and the overall spatial arrangement among the measured points lag The line vector that separates any two locations A lag has
136. fault to create a temporary dataset in your working directory 9 Click OK Spatial Analyst Spatial Analyst Layer J elevation Sa ih E Distance b Density Interpolate to Raster b Surface Analysis Contour Cell Statistics Slope Neighborhood Statistics Aspect Zonal Statistics Viewshed Cut Fill Beclassify Raster Calculator Convert b Options Hillshade Input surbace Azimuth 315 Altitude 45 Qo Model shadows Z factor 1 Output cell size lt Temporary gt Cancel Output raster ET E a bed Us nG ArcGIS Spatiat ANALYST Using transparency Transparency can be a useful tool for graphical display of your information Applying a percentage of transparency to certain layers allows you to see multiple layers of information at the same time Transparency can be applied to both raster and feature data Tip Adjusting brightness and contrast Use the Adjust Brightness and Adjust Contrast buttons on the Effects toolbar to adjust the brightness or contrast of the hillshade layer for even better display PERFORMING SPATIAL ANALYSIS Displaying hillshade transparently 1 Follow steps 1 through 9 for Creating a hillshade dataset N Click and drag the elevation raster to the top of the table of contents over the created hillshade 3 Click View point to Toolbars and click Effects 4
137. for the Output raster or leave the default to create a temporary dataset in your working directory 5 Click OK Spatial Analyst Spatial Analyst Laver elevation AS ith b Distance Density interpolate to Raster H Surface Analysis Cell Statistics Neighborhood Statistics Zonal Statistics Beclassify Faster Calculator Convert Options Aspect Input surface Output cell size Output raster Contour Slope Hillshade Viewshed Cut Fill elevation 30 kT empora Usina ArcGIS Spatiat ANALYST Hillshade What is the Hillshade function The Hillshade function obtains the hypothetical illumination of a surface by determining illumination values for each cell in a raster It does this by setting a position for a hypothetical light source and calculating the illumination values of each cell in relation to neighboring cells It can greatly enhance the visualization of a surface for analysis or graphical display By default shadow and light are shades of gray associated with integers from 0 to 255 increasing from black to white QO N W measured from north in clockwise degrees from 0 to 360 An azimuth of 90 is east The default is 315 NW S Altitude is the slope or angle of the illumination source above the horizon The units are in degrees from 0 on the horizon to 90 degrees overhead The d
138. fy an Output cell size for the result the default cell size is that specified in the Options dialog box 5 Type a name for the result or leave the default to create a temporary result 6 Click OK Spatial Analyst Spatial Analyst Laver Jrec_sites Ae Hih Distance Straight Line Density Interpolate to Raster d Cost Weighted Surface Analysis Shortest Path Cell Statistics Neighborhood Statistics Zonal Statistics FReclassily Raster Calculator Convert b Options Assign to Masmum distance 30 Output cell size Output raster Cost weighted distance What is cost weighted distance mapping Cost weighted distance mapping finds the least accumulative cost from each cell to the nearest cheapest source Cost can be money time or preference The functions that perform cost weighted distance mapping are similar to the Straight Line Distance functions but instead of calculating the actual distance from one point to another they compute the accumulative cost of traveling from each cell to the nearest source based on the cell s distance from each source and the cost to travel through it for example it is easier to walk through a meadow than a swamp Why use the Cost Weighted Distance function Cost weighted distance modeling is useful whenever movement is based on geographic factors such as animal migration studies or consumer travel behav
139. g from one to 20 setting LOWEST INPUT to 5 would exclude all those cells with a value less than 5 If not specified LOWEST INPUT defaults to the minimum value in the input raster The second optional keyword LOWEST OUTPUT identifies the lowest output value or starting point for the reclassified values This keyword is used to set the output reclassified values automatically for cases where the assignment statements Usinc ArcGIS Spatiat ANALYST described later in this appendix specify only an input value LOWEST OUTPUT is formatted lowest output lt value gt where lt value gt is the lowest output reclassified value If not specified LOWEST OUTPUT defaults to 1 The assignment statements follow the keywords They can be formatted using several different methods The general form of an assignment statement establishes the relationship between an input cell value and its reclassified value input cell value gt output reclassified value The input cell value can be either an integer or a real number The output reclassified value however can only be an integer Several methods can be used to specify an input value and its associated reclassified value These methods are best presented with examples The remaining discussion on ASCII remap tables presents a remap table and describes how the input cell values are reclassified according to the table All examples use a raster dataset with cell values from one to 20
140. hat will be considered when performing an operation or function All NoData cells in the analysis mask will be masked out and as signed the NoData value on all subsequent output raster datasets An analysis mask can be created via the Reclassify dialog box Second the analysis mask must be specified in the General tab of the Options dialog box in order for t to be used n all subsequent analyses SETTING UP YOUR ANALYSIS ENVIRONMENT Creating the analysis mask by reclassifying 1 Click the Spatial Analyst dropdown arrow and click Reclassify 2 Click the Input raster dropdown arrow and click the raster from which you wish to create the analysis mask 3 Click the Reclass field dropdown arrow and click the field you want to use 4 Click the values you wish to exclude from any further processing 5 Click Delete Entries 6 Check the Change missing values to NoData check box The values you deleted will be turned to NoData in the output raster 7 Type a location on disk and a name for the mask Alternatively click the Browse button to browse to a folder in which to place the result 8 Click OK Reclassify Input raster landuse Reclass field Landuse 3 Set values to reclassify Old values New values Brush transitional I Change missing values to NoData lt Temporary gt oren Output raster Reclassify x Input raster landuse S Reclass field Landu
141. he operator or function e You need to know which other cell locations and their values need to be included in your calculations How do you determine these three things You automatically know what your value is for your location Each operator and function in Spatial Analyst manipulates the value at your location in different ways You will know how to manipulate your value based on the operator or function being applied from knowledge built into Spatial Analyst With some Spatial Analyst operations and functions you can calculate an output value just from knowing the value of your location such as raising your value by a specified power a local function To complete other operations and functions you need to know the values of other locations within the raster dataset you belong to such as looking in a neighborhood around you a focal function or you will include cell locations and their values belonging to other raster datasets such as zonal functions Let s walk through the three step process for several functions If the Cos function is being applied to your raster dataset for you to return an output value for your location you will need to know 92 your value and how to take the cosine of your value If a focal function is applied looking for the maximum value within a 3 by 3 neighborhood you will learn more about focal functions later in this chapter you must know your value and the values of the eight immed
142. he source from each of these cells This process is done for all cells in the cost weighted distance raster to produce the direction raster which tells you the direction to travel from every cell in the cost weighted distance raster back to the source PERFORMING SPATIAL ANALYSIS Direction Cost Weighted Distance Both the cost weighted distance and direction rasters are required if you want to go on to calculate the least cost shortest path between source locations and destination locations Allocation The cost allocation raster identifies the nearest source from each cell in the cost weighted distance raster It is conceptually similar to the Straight Line Distance Allocation function where each cell is assigned to its nearest source cell However near is expressed in terms of accumulated travel cost All cells are allocated to the school source 129 Cost weighted distance The Cost Weighted Distance function calculates a value for every cell that is the least accumulated cost of traveling from each cell to the source The source can be anything you choose such as a point layer displaying the location of a road junction or a building and can be in any supported raster or vector format The Maximum Distance option allows you to specify that the processing is only done on cells up to a certain distance away from each source Tip Setting analysis options Click Options on the Spatial Analyst t
143. hool away from existing schools in order to avoid encroaching on their catchment areas You will reclassify the Distance to schools layer giving a value of 10 to areas away from existing schools the most suitable locations giving a value of to areas near existing schools east suitable locations and ranking the values in between By doing this you will find out which areas are near and which areas are far from existing schools 1 Click the Spatial Analyst dropdown arrow and click Reclassify Spatial Analyst Spatial Analyst Layer elevation ip ih E Distance b Density Interpolate to Raster gt Surface Analysis b Cell Statistics Neighborhood Statistics Zonal Statistics Raster Calculator Convert gt Options 2 Click the Input raster dropdown arrow and click Distance to schools 3 Click Classify 32 Input raster Reclass field Set values to reclassify Output raster Distance to schools Value x T Change missing values to NoData lt Temporary gt Add Entry Delete Entries Cancel Click the Method dropdown arrow and click Equal Interval Click the Classes dropdown arrow and click 10 Click OK 0 A231 OF ANZ 8469 94974 120545 9334 8927 2085 rises Usinc ArcGIS SpatiaL ANALYST You want to locate the school a
144. how reclassification can be limited to those cell values that fall between a minimum and a maximum value It does not however provide control over the cell values within the minimum and maximum To obtain this kind of 209 control explicit ranges of input values can be specified For example Example 2 Remap table for cell value reclassification LOWEST OUTPUT 2 2 59 13 15 With this method LOWEST INPUT is ignored LOWEST OUTPUT automatically causes the reclassified values to be generated for the input ranges Remember that the ranges must be sorted in ascending order They also should not overlap except at the border of two ranges Thus an input range from 5 to 9 followed by an input range from 8 to 12 is not valid For the above remap table the input cell values are reclassified as shown below Input Cell Values Output Reclassified Value Less than 3 3to5 Greater than 5 to 9 Greater than 9 to 13 NoData Greater than 13 to 15 4 Greater than 15 NoData By omitting an assignment statement for the range for nine to 13 all cells that fall within this range are reclassified as NoData and are displayed with the symbol for NoData User specified output values for each input value or input range can be specified by adding an additional field to the remap table 210 The input cell value or value range is followed first by a colon and then by the desired output reclassified value When an explicit out
145. iate neighbors around you You will assign the highest of the nine values to your location on the output raster dataset If a zonal function is applied with the mean option you will learn more about the zonal functions later in this chapter you need to know your value and must take the mean of all the values of the cell locations that belong to the same zone as you defined by a zone raster dataset If the addition operator is applied to your raster dataset and to two other raster datasets you need to add your value to the values of the same location you represent in the two other raster datasets in order to return an output value for your location If the Straight Line Euclidean Distance function is applied you will need to determine how far you are from the closest source which is defined by a source dataset in order to return an output value for your location The three step process occurs for each location in the raster dataset All operators and functions work on a cell by cell basis and each calculation for each cell needs to know the value of the cell the manipulation that is being applied and which other cell locations to include in the calculations The Spatial Analyst operators and functions are grouped into categories based on how they manipulate values Instead of trying to memorize each operator and function you need only to understand how the cell values are manipulated in the different categories For many functi
146. ically put them in the same space using the following rules The default behavior If only one raster dataset is input the output will be in the same coordinate space as the input a very common situation If multiple raster and feature datasets are in the same coordinate space the output will also be in that same coordinate space If more than one raster dataset is input the output will be in the same coordinate space as the first input If feature and raster data with different coordinate spaces are input to the same function the feature dataset will be projected to the coordinate space of the raster the output will be in the coordinate space of the raster If feature data is input the output will be in the same coordinate space as the first input Overriding the default On the General tab of the Options dialog box you can set the coordinate space of all output raster datasets to be the same as that specified for the data frame Automatically transforming a raster or feature dataset into the common coordinate system in the cases identified above is referred to as projecting on the fly To maintain the speed of 106 on the fly projection a low order polynomial transformation is applied to the dataset The on the fly projection transformation is less accurate than if you project the dataset using the geometric transformation tools that are available in ArcMap and Spatial Analyst which are discussed in Chapter 4
147. ick the Chart statistic dropdown arrow and click the type of statistic you wish to chart 8 Specify a name for the Output table or leave the default to create a table in your working directory 9 Click OK Spatial Analyst Spatial Analyst Layer J elevation Zones Sm ih 4 Distance d Density Interpolate to A aster a Surface Analysis b Cell Statistics Neighborhood Statistics onal Statistics Reclassity Raster Calculator Convert b Options onal Statistics one dataset elevation zones S Zone field Value 3 Value raster vegetation types oa 4 QO Ignore HoD ata in calculations O T Join output table to zone layer I Chart statistic Variety 7 Output table Je data wariety dbf nas 8 Us nG ArcGIS Spatiat ANALYST Reclassification What is reclassification Reclassifying your data simply means replacing input cell values with new output cell values The input data can be any supported raster format If you add a multiband raster the first band will be taken and used in the reclassification Why reclassify your data There are many reasons why you might want to reclassify your data Some of the most common reasons are e To replace values based on new information e To group certain values together e To reclassify values to a common scale for example for use in suitability analysis or for creating a cost raster for use in the Cost Weighted
148. ide a more realistic interpretation of your values point values are spread out giving you a better indication as to their distribu tion over a surface Tip Deciding on the search radius Click the Measure tool on the Tools toolbar and measure distance from a certain point The distance is reported in the status bar It will help you reach a decision on how big to make the search radius Tip Setting analysis options Click Options on the Spatial Analyst toolbar to set up your working directory extent and cell size for your analysis results 134 Calculating density 1 Click the Spatial Analyst dropdown arrow and click Density Click the Input data dropdown arrow and click the input layer Click the Population field dropdown arrow and click the field you want to use Click either Kernel or Simple Density type Type a value in the Search radius text box to determine the distance to search for points or lines from each cell in the output raster Click the Area units dropdown arrow and choose the units in which the density values should be presented Specify an Output cell size 8 Type a name for the result or leave the default to create a temporary result Click OK Spatial Analyst Spatial Analyst x Layer Jelevation IE E fk Distance Interpolate to Raster Surface Analysis Cell Statistics Neighborhood Statistics onal Statistics Aeclassity
149. idsource Compound or nested expressions that perform multiple tasks can also be created They are formed by combining constants numbers grid datasets raster layers item names and tables with operators and functions Each compound expression can consist of multiple actions as in sinCLinlayer1 powC inlayer2 2 Each operator has an assigned precedence value see Table of supported operators and precedence values in Appendix B Spatial Analyst processes the operator with the highest precedence first the next highest precedence second and so on If two operators in an expression have the same precedence value Spatial Analyst which reads left to right will process the operator that is located farthest to the left first All functions have equal precedence and therefore are processed simply from left to right Parentheses overrule precedences so Spatial Analyst completes all operations within parentheses first Parentheses can be nested with the deepest nested operator or function being processed first 193 Spatial Analyst Map Algebra is similar to and follows many of the conventions of the standard algebraic order of operations The main difference between the two is that Spatial Analyst Map Algebra has been designed to work on grid datasets and raster layers while standard algebra works on numbers Map Algebra input types Valid input types in the Map Algebra language are grid da
150. ify Npwvalues a Classy a i Je eeecescccesccsscoscccosssoecosescocccessocesossesosessecess Unique 23 1334 UDERNA AddEnty 30 8446075 38 5557594 6 x 4 gt Delete Entries Load Save E s airn Bee B Change missing v i to NoData lent Herra uder F Per st Al at P peyote me Output raster lt Temporary gt a The output reclassified slope dataset will be added to your ArcMap session as a new layer Locations with higher values less steep slopes are more suitable than locations You want to reclassify the Slope layer so steep slopes with lower values steeper slopes are given low values as these are least suitable for building on 7 Click the first New value record in the Reclassify dialog box and change it to a value of 10 Give a value of 9 to the next New value 8 to the next and so on Leave NoData as NoData 8 Click OK l 594370168 7RB505554 gia pme ET in ores i tapii QUICK START TUTORIAL 29 Note A copy of this reclassified slope dataset can be found in the location ArcGIS ArcTutor Spatial Results Ex2 slopeR Reclassify Input raster Distance to rec_sites Reclass field Value 7 Reclassifying distance to recreation sites Set values to reclassify The school should be located near recreational facilities You will reclassify this dataset giving a value of 10 to areas closest to recreation sites the most suitable loca tion
151. ighborhood Statistics Zonal Statistics Reclassify Raster Calculator Convert Options Raster Calculator elevation gt 3000 amp landuse About building expressions 183 Use the Raster Calculator to perform mathematical functions on your data The example used 1n the task 1s Exp Use the following syntax when using raster layers from the Layers list those layers you added to ArcMap Exp Dens ty If you have not added the raster dataset you wish to use as a raster layer to ArcMap it will not appear as a layer in the Layers list If the raster dataset is a grid you can specify the path to the grid dataset on disk Exp c data Density gt Tip Expanding the expression box Click and drag the bottom of the Raster Calculator dialog box to expand the expression box For more information on Map Algebra syntax and rules see Appendix A For supported operators and precedence values see Appendix B Click About Building Expressions to access help for the Raster Calculator including the Spatial Analyst functional reference 184 Using the Raster Calculator to perform mathematical functions on your data 1 Click the Spatial Analyst dropdown arrow and click Raster Calculator 2 Click the Expansion button to expand the Raster Calculator and reveal the mathematical functions 3 Click the function you want to use 4 Double click the layer t
152. in Stowe Vermont USA will be broken down conceptually to explain each of the modeling steps 55 Modeling spatial problems In general terms a model is a representation of reality Due to the inherent complexity of the world and the interactions in it models are created as a simplified manageable view of reality Models help you understand describe or predict how things work in the real world There are two main types of models those that represent the objects in the landscape representation models and those that attempt to simulate processes in the landscape process models Representation models Representation models try to describe the objects in a landscape such as buildings streams or forest The way representation models are created in a GIS is through a set of data layers For Spatial Analyst these data layers will be either raster or feature data Raster layers are represented by a rectangular mesh or grid and each location in each layer is represented by a grid cell which has a value Cells from various layers stack on top of each other describing many attributes of each location gt OFOGRAPHY LAN Use eee UTILITIES i SIREETS l _OISTRICTs J PARCELs ra n n ER m E 56 The representation model attempts to capture the spatial relationships within an object the shape of a building and between the other objects in the landscape the distribution of buildings Along
153. in a suitability model Alternatively you need to know how rugged the terrain is so you know to include slope as a factor in determining the east cost path Having explored your data you are now in a position to begin to find suitable locations for the new school First you will need to remove all the layers used in this exercise Click the top layer in the table of contents to highlight it Press and hold the Shift key and click all other layers Right click one of the layers in the table of contents and click Remove 22 o QE L 32 Gopy E E lt amp Zoom To Layer Oe Tite a k mi Ww Gaye As Laver File E Hills h S iina Properties E elevation Value High 4361 All layers will be removed from the ArcMap data frame Low 438 This exercise showed you how to display and explore your data In the next exercise you will use the Spatial Analyst functions to find a potential site for a new school You can continue on with the tutorial or close ArcMap and continue at a later date There is no need to save the map document at this point Note To save your work at any time click the File menu and click Save As Navigate to the location where you set up your local working directory C Spatial specify a filename for the map document Spatial_Tutorial and click Save Simply open Spatial Tutorial mxd when you wish to continue with the tutorial You will however be prompted when
154. ing the areas that have been eroded the areas of deposition and the areas of no change It also calculates the volume of surface material that has been cut or filled in each area The diagrams below show how the Cut Fill function uses the Before and After surface to calculate the areas filled cut and areas that did not change as a result of the St Helen s volcano in 162 change are displayed in yellow on the Cut Fill diagram Before surface After surface Cut Fill surface Why use the Cut Fill function With the Cut Fill function you can Identify regions of sediment erosion and deposition in a river valley Calculate the volumes and areas of surface material to be removed and areas to be filled to level a site for building construction Identify areas that become frequently inundated with surface material during a mudslide in a study to locate safe areas of stable land for building homes Usina ArcGIS Spatiat ANALYST Calculating Cut Fill The Cut Fill function enables you to create a map based on two input surfaces before and after displaying the areas and volumes of surface material that have been modified by the addition or removal of surface material The Z factor is the number of ground x y units in one surface z unit The Input surface values are multiplied by the specified Z factor to adjust the Input surface z units to another unit of measure Tip Specifying a Z factor To get accurate Cut
155. ing patterns in existing surfaces Slope identifies the slope or maximum rate of change from each cell to its neighbors An output slope raster dataset can be calculated as either a percentage of slope for example 10 percent slope or a degree of slope for example 45 degree slope Aspect identifies the steepest downslope direction from each cell to its neighbors The value of the output raster dataset represents the compass direction of the aspect 0 is true north a 90 degree aspect is to the east and so forth Hillshade is used to determine the hypothetical illumination of a surface for either analysis or graphical display For analysis hillshade can be used to determine the length of time and intensity of the sun in a given location For graphical display hillshade can greatly enhance the relief of a surface Usinc ArcGIS Spatiat ANALYST Viewshed identifies either how many of the observation points specified on the input observation raster dataset can be seen from each cell or which cell locations can be seen from each observation point Curvature measures the slope of the surface at each cell It calculates the second derivative of the input surface raster dataset the slope of the slope The result of the curvature function can be used to describe the physical characteristics of a surface such as the erosion and runoff processes within a landscape The slope identifies the overall rate of downward movement and
156. ing variances it is necessary to fit a model that is a continuous function or curve to the empirical semivariogram Abstractly this is similar to regression analysis where a continuous line or curve is fitted We select some function that serves as our model for example a spherical type that rises at first and then levels off for larger distances beyond a certain range There are deviations of the points on the empirical semivariogram from the model some points are above the model curve and some points are below But if we add the distance each point is above the line and add the distance each point is below the line the two values should be similar There are a lot of different semivariogram models to choose from Usina ArcGIS Spatiat ANALYST Different types of semivariogram models Spatial Analyst provides the following functions to choose from to model the empirical semivariogram Circular Spherical Exponential Gaussian and Linear The selected model influences the prediction of the unknown values particularly when the shape of the curve near the origin differs significantly The steeper the curve is near the origin the more influence the closest neighbors will have on the prediction As a result the output surface will be less smooth Each model is designed to fit different types of phenomenon more accurately The diagrams below show two common models and identify how the functions differ e The Spherical
157. inuous cells with the same value are grouped together to form polygons Cells that are NoData in the input raster will not become features in the output polygon feature Input raster Output polygons Raster to polylines When you convert a raster representing linear features to polyline features a polyline is created from each cell in the input raster passing through the center of each cell Cells that are NoData in the input raster will not become features in the output polyline feature PERFORMING SPATIAL ANALYSIS BO C S i i a ed destin a mi as E Input raster Output polylines Raster to points When you convert a raster representing point features to point features for each cell of the input raster a point will be created in the output Each point will be positioned at the center of cell that it represents NoData cells will not be transformed into points Output points Input raster 187 Converting your data Data can be converted from raster to features or from features to raster When converting feature data to a raster you have the option to specify a cell size for your output raster The cell size you choose should be based on several factors the resolution of the input data the output resolution needed to perform your analysis and the need to maintain a rapid processing speed Larger rasters will require longer processing times A fine resolution and thus slo
158. ions except that the definition of which cells to include in the processing the neighborhood in a zonal function is defined by the configuration of the zones or features in the input zone dataset not by a specified neighborhood shape Each zone can be unique Operations that can be completed on these cells return the mean sum minimum maximum or range of values from the first dataset that fall within a specified zone of the second 94 Global functions Global or per raster functions compute an output raster dataset in which the output value at each cell location is potentially a function of all the cells in the input raster datasets There are two groups of global functions Euclidean distance and weighted distance Euclidean distance global functions assign to each cell in the output raster dataset its distance from the closest source cell a source may be the location from which to start a new road The direction of the closest source cell can also be assigned as the value of each cell location in an additional output raster dataset Usina ArcGIS Spatiat ANALYST Cost Weighted Distance Raster Dataset Cost Raster Dataset By applying a global function to a weighted cost surface you can determine the cost of moving from a destination cell the location where you wish to end the road to the nearest source cell To take this one step further the shortest path over a cost surface can be calculated over a
159. ior Cost weighted distance may also be used to minimize construction costs for routing new roads transmission lines or pipelines s The straight line distance between two points is not necessarily the best In the graphic to the left the shortest path over the mountain takes three hours The longer path around only takes two hours If time were a cost then the route with the longer distance should be taken However the aim may be to climb over the mountain Applying cost weighted distance enables you to specify preferences in your input data It may for example take longer to travel over the mountain due to steep slopes so steep slopes should be given a higher cost when finding a suitable path from A to B 126 Example Finding the least cost route for a road In the following example the Cost Weighted Distance functions are used to find the least cost path for a new road The Cost Weighted Distance function is the prerequisite to the Shortest Path function which is discussed in the next section The Shortest Path function determines the actual route for the road To calculate the least accumulative cost from each cell to the nearest source the Cost Weighted Distance function needs a source and a cost raster The source The source as you can see in the graphic below in red is the starting point for the proposed road The cost raster The cost raster identifies the cost of traveling through every cell To creat
160. irection Leave the defaults for the other options 8 Click OK Shortest Path Destination Path to Cost distance raster Direction For E ach Cell bi Output features c spatial patht hp cae Cost direction raster Path type 50 El Distance The shortest path is calculated and the resulting layer 1s added to your ArcMap session It represents the least cost path least cost meaning avoiding steep slopes and on landuse types considered to be least costly for constructing the road from the school site to the road junction 9 Click Distance in the table of contents press the Ctrl key and click Direction and Cost 10 Right click Cost and click Remove to remove all three layers VALLE gt fi O 23 804 6063 P 23 904 6063 47 609 2125 B 47 609 2725 71 413 8188 Be 771 413 8188 95 218 425 WB 96 218 425 119 023 03 p 115 023 0351 142 827 638 WS 142 827 6358 166 632 244 B 166 632 244 190 436 55 E 190 436 95 214 241 456 B 214 241 456 238 046 063 Sou x Remove E Fig E Group E Lo fo Dov ie Zoom To Layer EE Low Visible Scale Range P E Lett B Upp Sare As aver Kile i eap Properties Usinc ArcGIS SpatiaL ANALYST Displaying the results To see exactly where this path should be constructed you will now create a more detailed map Adding the datasets 1 Click the Add Data button on the Standard toolbar 2 Na
161. is defined with respect to a map projection Map projections transform the three dimensional surface of the earth to allow the raster to be displayed and stored as a two dimensional map The process of rectifying a raster dataset to map coordinates or converting a raster dataset from one projection to another is referred to as geometric transformation Georeferencing a raster dataset To georeference a raster dataset from image space to a real world coordinate system you need to know the location of recognizable features in both coordinate spaces These locations are used to create control points The control points are used to build a polynomial transformation that will warp the image from one coordinate space to another This can be done with the Georeferencing toolbar click View point to Toolbars and click Georeferencing Control points are locations that can be accurately identified on the raster dataset and in real world coordinates These identifiable locations may be road and stream intersections building corners bridges the mouth of a stream rock outcrops and identifiable points on geometric landscape features such as the end of a jetty of land the corner of an established field or the intersection of two hedgerows For each control point selected on the input raster dataset the output location may be specified either by graphically selecting a point that is already in the desired output coordinate system or by
162. is generally accepted that the resultant raster dataset should be the same or coarser than the input data Spatial Analyst allows for raster datasets of different resolutions to be stored and analyzed together in the same database Since Spatial Analyst provides this capability the four decisions discussed above can be made separately for each dataset rather than simultaneously for all of the rasters in the database Raster datasets that store different types of information can be stored at different resolutions to meet the needs of the data and of the analysis that will be completed with the raster A raster dataset representing a state s watershed boundaries can be stored at a coarser cell resolution than a raster dataset representing the distribution of endangered species The major disadvantage of raster cell representation of map data is the loss of resolution that accompanies restructuring data to fixed raster cell boundaries Resolution increases as the size of the cell decreases however cost normally also increases both in 84 disk space and processing speeds For a given area changing cells to half the current size requires as much as four times the storage space depending on the type of data and the storage techniques used For most users the efficiency of cell based analysis more than compensates for the loss of resolution Input vegetation Coarse resolution Larger cells may encompass more than one data val
163. is map simply use the Reclassify function As it is preferable to locate away from existing schools give a value of 1 to distances close to existing schools and a value of 10 to distances far from existing schools then rank the distances linearly in between as the following chart shows Suitability Distance meters 65 Ranking the areas on relatively flat land To avoid steep slopes and find areas that are relatively flat to build on you need to know the slope of the land The Spatial Analyst Slope function will create such a map identifying for each cell the maximum rate of change in value from each cell to its neighbors To rank this map simply use the Reclassify function As it is preferable to locate on relatively flat slopes give a value of 1 to locations with steep slopes 10 to locations with the least steep slopes then rank the values linearly in between as the following chart shows 10 Suitability Slope degrees Ranking the areas on suitable landuse types To rank the map representing landuse types use the Reclassify function As it is preferable to build on certain landuse types due to the costs involved you need to decide how to rank the values Ranking distance or slope values is relatively straightforward You simply have to decide whether short or long distances are 66 preferable and whether steep slopes or less steep slopes are preferable then rank the rest of the values linearly
164. istance from a certain object for more details see Finding a site for a new school in Stowe Vermont USA in Chapter 2 In the example below the distance to each town is found This sort of information could be extremely useful for planning a hiking trip You may want to stay within a certain distance of a town in case of emergencies or know how much further you have to travel to pick up supplies The straight line distance to the nearest town from every location 121 Optional outputs The Straight Line Allocation raster dataset Every cell in the Straight Line Allocation raster is assigned the value of the source to which it is closest The nearest source is determined by the Straight Line Distance Use this function to assign space to objects such as identifying the customers served by a group of stores In the example below the allocation function has identified the town that is closest to each cell This could be valuable information if you need to get to the nearest town from a remote location for more information see Allocation in this chapter Allocating cells to sources Which areas are served by which town 122 The Straight Line Direction raster dataset The Straight Line Direction raster contains the azimuth direction from each cell to the nearest source The directions are measured in degrees where north is 0 degrees In the example below the direction to the nearest town is found
165. istics FReclassity Raster Calculator Convert p Options Input pointa Sample_points Z value field O 0NE 3 Power E 4 Search radius type Fined 5 Search Radius Settings Distance Minimum number of points Use barrier polylines Output cell size Output raster lt Temporary gt a 10 Cancel 11 137 has to stretch to reach the specified number of input points Specify a maximum distance to limit the potential size of the radius of the circle If the number of points is not reached before the maximum distance of the radius 1s reached fewer points will be used in the calculation of the interpolated point Tip Deciding on the distance or the number of points Use the Measure tool on the Tools toolbar to measure distance between points to get an idea of the distance and number of points to use when setting the Search Radius Tip Fixed or variable Use a fixed radius type if your input sample points are plentiful and are regularly spaced Use a variable radius type if your sample points are sparse and are randomly placed 138 Creating a surface using IDW with a variable radius 1 Click the Spatial Analyst dropdown arrow point to Interpolate to Raster and click Inverse Distance Weighted Click the Input points dropdown arrow and click the point dataset you wish to use Click the Z value field dropdown arrow and click the field you wish to use Opti
166. its precedence value For more information on the operators refer to The Raster Calculator in Chapter 7 203 Table of supported operators and precedence values The table below lists all supported operators A brief description accompanies each operator followed by a precedence value OPERATORS Operator Arithmetic S S mod div Boolean S d O not amp and or xor Relational o G o lt It flessthan 6 O lt le _less than and equalto 6 g weert 6 gt ge greaterthanandequalto 6 eq _equalto oS S 6 O lt gt ne notequalto 6 O Bitwise ee eee Mm gt gt lt lt amp amp bitwise exclusive or I bitwise or Combinatorial Po cand and O ae cor por i 8 cxor fexclusiveor _ __ _ 8 Logical Pf diff logical difference 8 in contained in a over over 8 204 Usinc ArcGIS Spatiat ANALYST About precedence values The precedence value determines the priority of processing for each operator The larger the precedence number assigned in an operator the higher its priority and thus the sooner the Spatial Analyst interpreter will process it The Spatial Analyst interpreter processes the operator with the highest priority first the second highest priority second and so on inlayer1 inlayer2 div inlayer3 In the above expression the negative of inlayer1 is first calculated then inlayer2 is divided by inlayer3 and finall
167. ive a scientific justification to describe it By using a variable search radius you can specify the number of points to use in calculating the value of the interpolated cell This makes the search radius variable for each interpolated cell depending on how far it has to stretch to reach the specified number of input points Specifying a maximum distance limits the potential size of the radius of the circle If the number of points is not reached before the maximum distance of the radius 1s reached fewer points will be used in the calculation of the interpolated cell gt PERFORMING SPATIAL ANALYSIS Creating a surface using kriging interpolation with a variable radius 1 Click the Spatial Analyst dropdown arrow point to Interpolate to Raster and click Kriging 2 Click the Input points dropdown arrow and click the point dataset you wish to use 3 Click the Z value field dropdown arrow and click the field you wish to use 4 Click the Kriging method you wish to use 5 Click the Semivariogram model dropdown arrow and click the model you wish to use 6 Click the Search radius type dropdown arrow and click Variable 7 Optionally change the default number of points 8 Optionally specify a maxi mum distance 9 Optionally change the default Output cell size 10 Optionally check Create Prediction of standard error 11 Specify a name for the Output raster or leave the default to cr
168. k start tutorial assume you are familiar with the fundamentals of GIS and have a basic knowledge of ArcGIS If you are new to GIS or ArcMap you are encouraged to take some time to read Getting Started with ArcGIS and Using ArcMap which you received in your ArcGIS package It is not necessary to do so to continue with this book simply use these books as references Chapter 3 Modeling spatial problems takes you through the spatial modeling process helping you to break down your spatial problems into manageable pieces Chapter 4 Understanding raster data helps you to understand raster data and Chapter 5 Understanding cell based modeling explains the process of cell based modeling Chapter 6 Setting up your analysis environment tells you how to set up your analysis options before performing analysis and Chapter 7 Performing spatial analysis provides detailed information to help you perform each spatial function The appendices are split into three sections Appendix A explains Map Algebra syntax and rules for the Raster Calculator Appendix B provides a table of supported operators and precedence values for use in the Raster Calculator and Appendix C explains remap tables for use when reclassifying data using the Raster Calculator Getting help on your computer In addition to this book use the ArcGIS Desktop Help system to learn how to use Spatial Analyst and ArcMap To learn how to u
169. l 62187 Water 28 Banennd 36034 Built up 85054 Agriculture 671722 Forest 1228 Record KI KI 1 frij Show All Selected Records 0 out of 7 Selected Options 2 Click the row representing Wetlands value of 7 16 Options ll E Attributes of landuse 62187 wae 4 Bultup uilt up 5 e5054fAgricutue BB 671722 Forest S Ho o 7 o 1224 Wetlands Record J 1 mai Show All Selected Records This selected set all areas of Wetlands is highlighted on the map 3 Click the Options button on the Open Attribute Table dialog box then click Clear Selection th Find amp Replace a Select By Attributes Select All Hl Clear Selection switch Selection Add Field Related T ables b Create Graph Add Table to Layout Reload Cache C2 Export Appearance 4 Click the Close button to close the Attributes of landuse Usinc ArcGIS SpatiaL ANALYST Identifying features on the map 5 3 6 1 Click the Identify tool on the Tools toolbar identit Results T m l IE i O J 2 Click the Rec_ site shown in the map below to identify BAe i TE the features in this particular location i roads O E MOUNTAIN RESORT RD landuse 2 1 5 AREA 0 elevation PERIMETER 0 i MAP 90021 1519 SITE_NAME Stowe Mountain Resort FIPS_CODE 15040 ALT_NAME S_ADDRESS 5781 Mountain Road Using Spatial Analyst to explore your da
170. l within the wedge are included in the processing of the neighborhood The neighborhood function for an individual cell Take the processing cell with a value of 5 in the diagram that follows With a rectangular 3 x 3 cell neighborhood the sum of the value of neighboring cells plus the value of the processing PERFORMING SPATIAL ANALYSIS cell equals 24 So a value of 24 is given to the value of the cell in the output raster in the same location as the processing cell in the input raster Input processing cells Output value for one cell The neighborhood function on an entire dataset Each cell in the output raster below has been calculated by summing the cells in a 3 x 3 neighborhood for each cell The cells highlighted in yellow identify the neighborhood of the input processing cell with a value of 5 and output cell value of 24 This process is performed on every input processing cell to calculate an output value for each cell Output raster Input processing raster 167 Processing cells of NoData If a cell of NoData is present in the neighborhood it will be ignored in the processing If the entire neighborhood consists of cells of NoData the output cell value will be NoData Why calculate neighborhood statistics Calculating neighborhood statistics is useful for obtaining a value for each cell based on a specified neighborhood For example when examining ecosystem stability it might be useful to obtai
171. lass of Slope of elevation 0 125 and Wetlands in this color 25 Click OK Raster Calculator Ed Layers 4 About building expressions Cancel pS Draw raster grouping values into classes Fields Classification Value Value z Equal fnterval Normalization lt NONE gt Classify Color ame a _Symbol_ Rawe s C ide o al 4 4 4 975 4 975 5 55 5 55 6 125 6 125 6 7 6 7 7 275 4 27 85 The output raster dataset shows you how suitable each location 1s for locating the new school according to the criteria you set in the suitability model Higher values indicate locations that are more suitable Classes 10 The suitable locations are those areas that are close to recreation sites away from existing schools on rela gp Fin Colas tively flat land and on certain types of landuse The ES higher weightings set for Distance to schools and Reve Sotra Distance to rec_sites have a powerful influence on aie os Sets Edit Description deciding which areas are more suitable than others QUICK START TUTORIAL 37 You decide that there are three main potential areas for locating the school They are labeled in the diagram below Area 2 Area 3 Area 1 You should now assess these locations to see which might be the best location This should be done in the field as well as by
172. lasses of old values into unique values 174 Replacing values based on new information 1 Click the Spatial Analyst dropdown arrow and click Reclassify 2 Click the Input raster dropdown arrow and click the raster with values you wish to change 3 Click the Reclass field dropdown arrow and click the field you wish to use 4 Click the New values you wish to change and type a new value 5 Click all the other New values while holding down the Shift key then click Delete Entries All other values will remain the same in the Output raster 6 Optionally click Save to save the remap table 7 Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory 8 Click OK Reclassify Input raster landuse Reclass field Landuse K Set values to reclassify Old values New values Massip iculture Unique 4 Add Entry Delete Entries 5 I Change missing values to NoData Dutput raster lt Temporary gt cea Reclassify x Input raster landuse Reclass field Landuse m Set values to reclassify Massip Unique Add Entry Load Save I Change missing values to NoData Output raster lt Tempqrary gt 7 OK Cancel Us nG ArcGIS Spatiat ANALYST The Save button enables you to save a remap table for later use Tip Ungrouping entries To ungroup entries right click the group and click Ungrou
173. lculator to weight rasters 1 Click the Spatial Analyst dropdown arrow and click Raster Calculator 2 Double click the layer to which you want to add weight The layer will be added to the expression box 3 Click the Multiply button 4 Type a value to weight the dataset 5 Follow steps 1 through 5 for all datasets you want to weight 6 Click Evaluate Using the Raster Calculator to combine rasters 1 Click the Spatial Analyst dropdown arrow and click Raster Calculator Double click the first layer Click the Add button Click the next layer Oo KR wo DN Repeat steps 3 and 4 to add all your datasets together 6 Click Evaluate zt ets oe ae EEE A ES RARAS EA a ass soils reclassed soils reclassed 0 25 About building expressions Evaluate Raster Calculatcr distance from rodds recla landuse reclassed_x0 66 slope reclassed 0 33 soils reclassed th ef sf f ad ponpen AEAEE distance from roads reclassed landuse reclassed_x0 66 slope reclassed_x0 33 soils reclassed About building expressions Cancel gt gt Us nG ArcGIS SPaTiaL ANALYST The Raster Calculator enables you to perform many different types of queries on your data For example elevation gt 3000 amp landuse will identify all those cells of the elevation raster that are higher than 3 000 meters with a landuse value of 5 Cells that meet the criteria cells
174. le of contents defined 225 Target layer defined 225 Temporary results creating 110 defined 225 Tension Spline Method 139 Transformation geometric 79 Translation 98 Transparency applying 159 Trend surface interpolation described 96 Trigonometric functions defined 225 described 179 using 184 V Values of raster cells 75 Variogram defined 225 Variography defined 225 described 141 232 VAT See Attribute table described Viewshed calculating 161 defined 225 described 97 160 Visibility See Viewshed described W Warp 98 Watersheds 97 Weight and combine datasets 67 optional parameter for Spline interpolation 139 Working directory defined 225 setting 112 Z Z factor defined 226 Zonal functions defined 225 described 92 Zonal statistics a zonal function 93 calculating 172 defined 226 described 170 Zone defined 226 described 75 Us nG ArcGIS Spatiat ANALYST
175. ls and what input datasets you will need You are now in the position to perform analysis The ESRI Guide to GIS Analysis describes in detail the many tasks that can be solved with ArcGIS When finding the best location for the new school there are two ways to go about performing analysis You can create a suitability map to find out the suitability of every location on the map or you can simply query your created datasets to obtain a Boolean result of true or false Creating a suitability map Creating a suitability map enables you to obtain a suitability value for every location on the map Once you have created the necessary layers how do these created layers get combined to create a single ranked map of potential areas to site the school You need a way to compare the values of classes between layers One way to do this is to assign numeric values to classes within each map layer Each map layer is ranked by how suitable it is as a location for a new school You may for instance assign a value to each class in each layer on a scale of 1 10 with 10 being the best This is often referred to as a suitability scale NoData can be used to mask off areas that should not be considered Having all measures on the same numeric scale gives them equal importance in determining the most suitable locations The model is initially constructed in this way then while testing alternative scenarios weight factors can be applied to layers
176. m this function Primary output Straight Line Distance gives the distance from each cell in the raster to the closest source Example of usage What is the distance to the closest town Optional outputs e Straight Line Allocation identifies the cells that are to be allocated to a source based on closest proximity Example of usage Which town am I closest to Straight Line Direction gives the direction from each cell to the closest source Example of usage What is the direction to the closest town The source The source identifies the location of the objects of interest such as wells shopping malls roads forest stands and so on If the source is a raster it must contain only the values of the source cells all other cells must be NoData If the source is a feature it will internally be transformed into a grid when you run the function The straight line distance raster The straight line distance raster contains the measured distance from every cell to the nearest source The distances are measured PERFORMING SPATIAL ANALYSIS in projection units such as feet or meters and are computed from cell center to cell center The Straight Line Distance function is used frequently as a standalone function for applications such as finding the nearest hospital for an emergency helicopter Alternatively this function can be used when creating a suitability map when you need to include data representing the d
177. map tables and reclass 215 and slice 212 described 208 Representation model 56 Resampling and geometric transformations 79 and resolution altering 100 INDEX Resampling continued defined 223 options in analysis 105 Resolution See Cell size described Rotation 98 Row of a raster dataset 74 S Search radius 134 136 144 Selected set defined 223 Semivariogram defined 223 described 141 models 143 Shapefile defined 224 Shortest path calculating 132 defined 224 described 131 Sill 144 defined 224 Slope calculating 154 defined 224 described 96 153 Snap extent defined 224 setting 116 Source defined 224 described 126 Spatial analysis defined 224 in Spatial Analyst 92 process 55 Spatial continued data defined 224 function defined 224 reference defined 224 relationships 5 Spline interpolation defined 224 described 96 139 using 140 Statistics block 100 per cell 92 164 per neighborhood 92 166 per zone 92 170 Straight line allocation calculating 123 125 defined 224 described 122 124 overview 120 Straight line direction calculating 123 defined 224 described 122 overview 120 Straight line distance calculating 123 defined 225 described 121 overview 120 Stream networks 97 Suitability map 6 64 model 61 defined 225 scales 64 Summarize zones See Zonal statistics described 231 Surface analysis 96 149 generation 96 135 Symbol defined 225 Symbology defined 225 Tab
178. mpling to the coarsest resolution of the input rasters can be changed in the Cell Size tab of the Options dialog box to a specific cell size or to the minimum of the input raster datasets Caution must be taken when specifying a finer cell size than the coarsest input because the resolution of the output cannot be more accurate than the coarsest of the inputs Specifying a cell size of 50 meters when the input raster datasets are 100 meters creates an output raster with a cell size of 50 meters but the accuracy is still 100 When performing analysis make sure you are asking appropriate questions of the cell size That is you will not study mouse movement when the cell size is five kilometers and you will not want to use five kilometer cells when studying the effects of global warming over the earth UNDERSTANDING CELL BASED MODELING 105 Handling projections during analysis Raster datasets must be registered with one another before completing any analysis or processing between them Each location on the ground must be represented by the same x y cell address on the different input datasets This means that the input raster datasets have to be in the same coordinate space or coordinate system in the same projection The coordinate space of the output will be dependent on the coordinate space of the input datasets If two or more input raster datasets in an expression are not in the same coordinate space Spatial Analyst will automat
179. n An alternative to setting an analysis mask For layers for which you can access the table right click the layer in the table of contents and click Open Attribute Table Select rows from the table This selection will be respected when you perform a spatial function so analysis will only be performed on the selected set 114 Usina ArcGIS SpatiaL ANALYST About the coordinate system and l analysis When performing analysis you can control the changing of coordinate systems To make on the fly projection of raster data for display fast an approximation of the actual projection transformation 1s used and only the pixels that need to be drawn on the screen are transformed This transformation approxima tion can introduce error It 1s well suited for use in low to mid latitudes and study areas of local or regional scale It 1s not well suited for global or conti nental scale analysis At high latitudes it is only appropriate for small study areas approxi mately two degrees of latitude 4 and longitude at 60 degrees and less than one degree at 75 degrees and higher When working at the equator with cylindrical projections areas as large as 10 degrees can be used with minimal error introduced by the projection Improved projection results can be achieved by using a rigorous cell by cell or piecewise reprojection of your data Use the ARC commands PROJECT or PROJECTGRID respectively SETTING UP Y
180. n ne Change missing values to NqData Output raster Tempprary gt 7 175 Use the Reclassify dialog box to apply a common scale of values to your rasters when doing suitability modeling This involves reclassifying each raster on the same scale giving higher new values to those old values that are more important to consider Tip Changing the classes of your old values Click Classify to change the classification of your old values Click Unique to separate classes of old values into unique values For more details on suitability modeling see Finding a site for a new school in Stowe Vermont USA in Chapter 2 176 Reclassifying values of a set of rasters to a common scale 1 Click the Spatial Analyst dropdown arrow and click Reclassify 2 Click the Input raster dropdown arrow and click the raster with values you wish to prioritize 3 Click the Reclass field dropdown arrow and click the field you wish to use 4 Click the New values input box for each entry and prioritize the entries this is subjective according to your spatial problem for ex ample preference cost or time 5 Optionally click Save to save the remap table 6 Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory 7 Click OK Spatial Analyst Distance H Density Interpolate to Raster Surface Analysis H Cell Sta
181. n arrangement that produces a Cartesian matrix The rows of the matrix are parallel to the x axis of the Cartesian plane and the columns to the y axis Each cell has a unique row and column address All locations in a study site are covered by the matrix Usina ArcGIS SPaTiaL ANALYST Aava Values Each cell is assigned a specific value to identify or describe the class category or group the cell belongs to or the magnitude or quantity of the phenomenon the raster describes The characteristics the values represent include soil type soil texture landuse class water body type road class and housing type A value can also represent the magnitude distance or relationship of the cell on a continuous surface Elevation slope aspect noise pollution from an airport and pH concentration from a bog are all examples of continuous surfaces For rasters representing images and photographs the values can represent colors or spectral reflectance Both integer and floating point values are supported in Spatial Analyst Integer values are best used to represent categorical data and floating point values to represent continuous surfaces UNDERSTANDING RASTER DATA _ Cell with Value ad Zones Any two or more cells with the same value belong to the same zone A zone can consist of cells that are connected disconnected or both Zones whose cells are connected usually represent single features of an
182. n be used in the Raster Calculator through the Reclass and Slice functions This chapter explains the rules for creating these INFO and ASCII remap tables giving examples of their use in the Reclass and Slice functions 207 About remap tables Overview of reclassification Remap tables can be applied to rasters via the Raster Calculator using either the Reclass or the Slice function However you do not need to use remap tables to reclassify your data using Spatial Analyst You can simply use the Reclassify function on the Spatial Analyst toolbar to reclassify your data and save the table you create if you wish Doing so will enable you to load it again at a later date Remap tables described here cannot be used in the Reclassify dialog box Remap tables Remap tables can be either ASCII files or INFO tables They consist of two parts The first part identifies the particular cell value to be reclassified and the second part is the cell s reclassified output value INFO remap tables Cells with a value less than or equal to 3 are assigned symbol 1 Cells with a value greater than 3 and less than or equal to 5 are assigned symbol 2 Cells with a value greater than 5 and less than or equal to 10 are assigned symbol 3 Cells with a value greater than 10 and less than or equal to 15 are assigned symbol 4 Cells with a value greater than 15 are assigned NoData 208 ASCII remap tables The ASCII table fun
183. n the output raster The following statistics can be computed within the neighborhood of each processing cell then sent to the corresponding cell location on the output raster Majority determines the value that occurs most often in the neighborhood Maximum determines the maximum value in the neighborhood Mean computes the mean of the values in the neighborhood Median computes the median of the values in the neighborhood Minimum determines the minimum value in the neighborhood Minority determines the value that occurs least often in the neighborhood Range determines the range of values in the neighborhood Standard Deviation computes the standard deviation of the values in the neighborhood Sum computes the sum of the values in the neighborhood Variety determines the number of unique values within the neighborhood 166 Neighborhood shapes The neighborhoods that can be specified are a rectangle of any dimension a circle of any radius an annulus a doughnut shape of any radius and a wedge in any direction Rectangle The width and height units of a rectangular neighborhood can be in cells or in map units The default is a neighborhood of 3 x 3 cells Circle The size of the circle depends on the specified radius The radius is identified in cells or map units measured perpendicular to the x or y axis Any cell center encompassed by the circle will be included in the processing of the neighborhood
184. n the variety of species for each neighborhood to identify the locations that are lacking a variety of species The example below takes a raster displaying land cover and calculates the variety of different land cover types in each neighborhood br anety of land cover Count _ 2771514 Land cover type 168 A value is given to each cell in the output raster based on the cell s value and the values in a specified neighborhood A quick overview of the region shows you the areas with more than one land cover By zooming in on a particular region you can see more clearly that there are neighborhoods with three and even four types of land cover The attribute table for the output raster tells you how many cells there are that contain multiple types of land cover within the specified neighborhood Usinc ArcGIS Spatiat ANALYST Calculating neighborhood Statistics The Neighborhood Statistics function allows you to calculate a statistic for each cell based on the value of that cell and the values in a neighborhood you specify Use it for example to find the most dominant species in a neighborhood mayority or to see how many species are located in each neighbor hood variety The Neighborhood dictates the shape of the area used to obtain a value for the cell being processed The Neighborhood Settings dictate the size of the shape the number of cells or map units that is used to
185. n thematic raster data represent some measured quantity or classification of a particular phenomena such as elevation pollution concentration or population For example in a landcover map the value 5 may represent forest and the value 7 may represent water The values of cells in an image represent reflected or emitted light or energy such as that of a satellite image or a scanned photograph The analysis tools of Spatial Analyst are primarily intended for use on thematic raster data All Spatial Analyst functions process the first band of any raster dataset This section will provide an overview of raster data and how it is created The composition of a raster dataset A raster dataset like a map describes the location and characteristics of an area and their relative positions in space Because a single raster typically represents a single theme such as landuse soils roads streams or elevation multiple raster datasets should be produced to fully depict an area 74 The cell A raster dataset is made up of cells Each cell or pixel is a square that represents a specific portion of an area All cells in a raster must be the same size The cells in a raster dataset can be any size that you desire but they should be small enough to accomplish the most detailed analysis A cell can represent a square kilometer a square meter or even a square centimeter Rows and columns Cells are arranged in rows and columns a
186. nalysis 101 and changing cell values 196 and conversion 186 defined 222 in operators and functions 195 values in rasters 76 Nominal measurement systems 102 Normalize defined 222 Nugget 143 defined 222 O Objectives break problems into 59 Operators and precedence 203 Operators continued defined 222 supported 203 Ordinal measurement systems 102 P Path defined 222 Permanent dataset defined 222 Permanent results creating 110 Pixel See Raster cell described Polynomial transformation 79 Power described 136 Power functions defined 223 described 179 using 184 Problem breakdown 59 Process model 56 Projected coordinate system defined 223 Projection defined 223 of raster datasets 79 R Range 143 Raster defined 223 Raster Calculator defined 223 described 179 using 182 Us nG ArcGIS SPaTtiaL ANALYST Raster cell defined 223 described 74 Raster dataset and coordinate space 78 84 assigning attributes to 88 cell size 84 converting to 86 creating 85 defined 223 deriving from an existing map 90 discrete and continuous 82 measurement systems 102 understanding 74 Raster resolution defined 223 Ratio measurement systems 102 Reclassification and remap tables 207 defined 223 described 173 performing 174 Rectify through a geometric transformation 79 Region defined 223 described 76 Regularized Spline method 139 Relational operators and precedence 203 defined 223 described 179 supported 203 Re
187. nce for all pairs of points that are greater than 40 meters apart but less than 50 meters The empirical semivariogram is a graph of the averaged semivariogram values on the y axis and distance or lag on the x axis see diagram below Semivariance o O eo T ee o o o o O m Distance 142 Spatial autocorrelation quantifies a basic principle of geography things that are closer are more alike than things farther apart Thus pairs of locations that are closer far left on the x axis of the semivariogram cloud should have more similar values low on the y axis of the semivariogram cloud As pairs of locations become farther apart moving to the right on the x axis of the semivariogram cloud they should become more dissimilar and have a higher squared difference move up on the y axis of the semivariogram cloud Fitting a model to the empirical semivariogram The next step is to fit a model to the points forming the empirical semivariogram Semivariogram modeling is a key step between spatial description and spatial prediction The main application of Kriging is the prediction of attribute values at unsampled locations We have seen how the empirical semivariogram provides information on the spatial autocorrelation of datasets However it does not provide information for all possible directions and distances For this reason and to ensure that Kriging predictions have positive Krig
188. ndix A or through the Spatial Analyst object model The following sections provide an overview of the application functions For additional information on the application functions that are available through the Spatial Analyst user interface see Chapter 7 Performing spatial analysis and refer to the online command references for information on those application functions available only through Map Algebra and the object model Density The Density function distributes a measured quantity of an input point layer throughout a landscape to produce a continuous surface For example a retail store chain has multiple stores in a particular district For each store management has sales figures on its customers Management assumes that customers patronize one store over another based on how far they have to travel In this example it is assumed that the customer will always choose the closest store The farther away from the closest store the farther the customer will need to travel to that store But shoppers farther away will also shop at other stores Management wishes to study the distribution of where the customers live From the sales figures and the spatial distribution of the stores management wishes to create a surface of their customers by intelligently spreading them out across the landscape To accomplish this task Spatial Analyst considers where each store is in relation to other stores the quantity of customers shopping
189. nes the value that occurs least often in the zone Range determines the range of values in the zone Standard Deviation computes the standard deviation of the values in the zone Sum computes the sum of the values in the zone Variety determines the number of different values within the zone Usinc ArcGIS Spatiat ANALYST Why use zonal statistics You might calculate the mean elevation for each forest zone or the number of accidents along each of the roads in a town Alternatively you might want to know how many different types of vegetation there are in each elevation zone variety The graphics below show an example of the inputs and outputs from the Zonal Statistics function The variety of vegetation species per elevation zone is displayed in the output table and chart The most variety of species occurs at elevation levels of around 2 500 meters Be E Attributes of ones T VALUE VARIETY Q e nn Qo m a E E a eo e e I e o n Oo a al Record Ki a 0 pia Input zone dataset elevation zones Output table Input value raster vegetation type Elevation range from 1 547 to 3 358 meters w Variety of Vegetation types Within Zones of Elevation LJ a E Boa Bo Bw Ba E i4 a 1 J 1547 1773 1999 2226 2452 ZB79 2905 3132 3358 Zones Output chart PERFORMING SPATIAL ANALYSIS 171 Calculating zonal Statistics The Zonal Statistics function allows y
190. new information Apply Spatial Analyst tools to create useful information watershed delineation surface estimation and classification for example derive distance from roads or calculate population density e Identify spatial relationships Explore relationships between layers through weighted overlay and combinations Spatial Analyst contains a rich set of Map Algebra tools for cell based modeling e Find suitable locations By combining layers find areas that are the most suitable for particular objectives e g siting a new building or analyzing high risk areas for flooding or landslides e Calculate travel cost Create travel cost surfaces to identify optimum corridors Factor in economic environmental and other objectives e Work with all cell based GIS data Regardless of the raster format Spatial Analyst allows you to combine them in your analysis These operations and much more are possible As a GIS modeler this is the central toolset yov ll use for analysis and modeling The next few pages will introduce you to what is possible with ArcGIS Spatial Analyst Deriving information from data Using Spatial Analyst functions you can create a rich set of informative maps from your data Create a hillshade to use as a backdrop of the terrain to support other data layers Calculate slope aspect and contours or create a map displaying visibility Use derived data together to help solve spatial problems ep18 mxd ArcMa
191. nonnetworked surface from a source cell to a destination cell In all the global calculations knowledge of the entire surface is necessary to return the solution Application functions There is a wide series of cell based modeling functions that are developed to solve specific applications The local focal zonal and global functions are not specific to any application There is some overlap in the categorization of an application function and the local focal zonal and global functions such as the fact that even though slope is usually used in the application of analyzing surfaces it is also a focal function Some of the application functions are more general in scope such as surface analysis while other application functions are more narrowly defined such as the hydrologic analysis functions The categorization of the application functions is an aid to group and understand the wide variety of Spatial Analyst operators and functions You may find UNDERSTANDING CELL BASED MODELING that a specific application function can manipulate cell based data for an entirely different application than its category Some of these application functions are available in the Spatial Analyst user interface Others are available in other dialog boxes such as the Georeferencing toolbar Some are available through sample applications built by ESRI and other users while others are only available through the Raster Calculator via Map Algebra see Appe
192. nstant so for each interpolated cell the radius of the circle used to find input points is the same The Minimum number of points indicates the minimum number of measured points to use within the neighborhood All the measured points that fall within the radius will be used in the calculation of each interpolated cell When there are fewer measured points in the neighborhood than PERFORMING SPATIAL ANALYSIS the specified minimum the search radius will increase until it can encompass the minimum number of points The specified fixed search radius will be used for each interpolated cell cell center in the study area thus if your measured points are not spread out equally which they rarely are then there will likely be a different number of measured points used in the different neighborhoods for the various predictions Variable search radius With a variable search radius the number of points used in calculating the value of the interpolated cell is specified which makes the radius distance vary for each interpolated cell depending on how far it has to search around each interpolated cell to reach the specified number of input points Thus some neighborhoods can be small and others can be large depending on the density of the measured points near the interpolated cell You can also specify a maximum distance in map units that the search radius cannot exceed If the radius for a particular neighborhood reaches the maximum radiu
193. nt relative comparisons can be made between the measurements but ratio and proportion determinations are not as useful Acidic Neutral Basic 0 1 2 3 4 5 6 7 6 9 10 11 12 13 14 pH scale Ordinal Ordinal values determine position These measurements show place such as first second and third but they do not establish magnitude or relative proportions How much better worse prettier healthier or stronger something is cannot be demonstrated from ordinal numbers Usinc ArcGIS Spatiat ANALYST Nominal Values associated with this measurement system are used to identify one instance from another They may also establish the group class member or category with which the object is associated These values are qualities not quantities with no relation to a fixed point or a linear scale Coding schemes for landuse soil types or any other attribute qualify as a nominal measurement Other nominal values are social security numbers ZIP Codes and telephone numbers Spatial Analyst does not distinguish between the four different types of measurements when asked to process or manipulate the values Most mathematical operations work well on ratio values but when interval ordinal or nominal values are multiplied divided or evaluated for the square root the results are typically meaningless On the other hand subtraction addition and Boolean determinations can be very meaningful when used on interval and ordinal values
194. ntain NoData on the output The input source grid dataset or raster layer must have valid values for source cells and NoData for nonsource cells e For the remaining global functions when NoData exists at any location on the input grid dataset or raster layer the output value for that location will receive NoData e With the Select function when the results of the evaluation of the conditions are not True in the expression NoData is returned rather than 0 This is in contrast to the Relational operators and the Test function which will return 0 for those cells for which the results of the evaluation are False e For the conditional function Con if no value is assigned to the false expression output argument which is used when the result of the evaluation of the condition is False cells that evaluate to False will receive NoData on the output e Some local functions such as Popularity Majority and Minority evaluate the number of occurrences of a value not the value itself If there is no single value found to be the nth most popular minority or majority NoData will be assigned to the output for the location This situation occurs when all input values at a location are different No value ever occurs the majority or the minority of times Returning one of the input values such as the first one encountered would be incorrect You would not know whether the value is truly a majority minority or the nth most popular value
195. ntrast when looking for the minimum value in a neighborhood that contains a NoData value an assumption can be made or a risk taken that the cell location with the NoData value will not be the minimum value The focal function can thus be used to return the minimum value of the remaining valid values in the neighborhood Spatial Analyst fully supports the NoData concept If NoData exists in any of the input raster datasets in the Spatial Analyst expression the output values will be affected The behavior of NoData is addressed for each operator and function in the online command references UNDERSTANDING CELL BASED MODELING It is important to understand how NoData is handled in a particular function before making a decision You may need to know if a location with NoData on the output ever had a value or if it received NoData from the operator or function Sometimes when locations receive values it may be important to know if the output value really is the actual minimum or maximum value or if it is the minimum or maximum value of the existing known values 101 Values and what they represent The type of measurement system used may have a dramatic effect on the interpretation of the resulting values A distance of 20 kilometers is twice as far as 10 kilometers and something that weighs 100 pounds is a third as much as something that weighs 300 pounds But someone who came in first place may not have done three times as well as
196. ny location is a function of the capability of the event to move through the medium Another type of concentration surface is governed by the inherent characteristics of the moving phenomenon For example the movement of the noise from a bomb blast is governed by the inherent characteristics of noise and the medium it moves through Mode of locomotion can also limit and directly affect the surface concentration of a feature as is the case with seed dispersal from a plant The means of locomotion whether it be bees man wind or water all affect the surface concentration of seed dispersal for the plant Other locomotion surfaces include dispersal of animal populations potential customers of a store car being the means of locomotion and time being the limiting factor and the spreading of a disease When representing and modeling many features the boundaries are not clearly continuous or discrete A continuum is created in representing geographic features with the extremes being pure UNDERSTANDING RASTER DATA discrete and pure continuous features Most features fall somewhere between the extremes Illustrations of features that fall along the continuum are soil types edges of forests boundaries of wetlands and geographic markets influenced from a television advertising campaign The determining factor for where a feature falls on the continuous to discrete spectrum is the ease in defining the feature s boundaries
197. o which you want to apply the function 5 Click Evaluate Spatial Analyst Layer Jlanduse z I Spatial Analyst Distance gt Density Interpolate to Raster gt Surface Analysis gt Cell Statistics Neighborhood Statistics Zonal Statistics Reclassify Raster Calculator Convert Options Raster Calculato Arithmetic Trigonometric jt ef ofan mein ST an AAAA AA e e see i Layers Logarithms Log D Log2 Logi0 Exp Density Corcel About building expressions Us nG ArcGIS Spatiat ANALYST Use the Raster Calculator to perform Spatial Analyst functions For example slice elevation eqinterval 20 SLICE splits the input data elevation into 20 equal interval classes For all Map Algebra expres sions specify the Map Algebra function an open bracket the input raster and then any other parameters and a closed bracket Type the following syntax when using raster layers from the Layers list those layers you added to ArcMap slice elevation eqinterval 20 Otherwise if the input data is a coverage shapefile table or grid dataset you can specify the path to the input data on disk slice c data elevation eqinterval 20 Tip Obtaining usage information Type a Spatial Analyst function select it then right click and click Usage to see Map Alg
198. o find the shortest path from the school s te You have performed cost weighted distance creating a Distance dataset and a Direction dataset using the school s te as the source However you will need to decide on and then create the destination point for the road As you have already learned how to create a new shapefile this destination point shapefile has been created for you 1 Click the Add Data button 2 Navigate to the folder on your local drive where you installed the tutorial data the default installation path is ArcGIS ArcTutor Spatial 3 Click Destination and click Add Locating the destination point for the road in the position identified by the Destination shapefile will take much of the traffic away from the current road and provide a back route to the area for school buses and other vehicles 49 4 Click the Spatial Analyst dropdown arrow point to Distance and click Shortest Path Spatial Analyst Spatial Analyst Layer Distance Straight Line Density Allocation Interpolate to Raster gt Cost Weighted Surface Analysis gt Cell Statistics Neighborhood Statistics Zonal Statistics Reclassify Raster Calculator Convert gt Options 5 Click the Path to dropdown arrow and click Destination 6 Click the Cost distance raster dropdown arrow and click Distance 7 Click the Cost direction raster dropdown arrow and click D
199. o the input value depending on the option selected In the following example a cell value is identified and then changed INLAYER1 OUTGRID A VALUE NODATA VAT VALUE COUNT 0 5 1 5 2 3 4 2 ASCII_Remap _ Table 0 10 1 50 2 100 4 75 reclassC Linlayerl c data ASCII_Remap_Table txt APPENDIX C 215 slice versus Reclass relative to remap tables Reclass easily changes single values to alternative values while Slice specializes in changing the ranges of values Slice also has several special capabilities such as dividing the cell values into groupings based on the value ranges or on the number of cells in each grouping With certain types of reclassifications either function can be used and in others only one can be used efficiently The following list differentiates the two commands as they are used in remap tables e Slice always evaluates on ranges of values while Reclass changes values singly unless the input explicitly specifies ranges e Reclass can copy over the original input values to the output values In Slice all values are affected e Reclass cannot specify ranges through an INFO remap table 216 Usinc ArcGIS Spatiat ANALYST Glossary altitude 1 The height z value or vertical elevation of an object above a surface 2 The angle above the horizon measured in degrees from which a light source illuminates a surface used when calculating a hillshade
200. oData as a result of the operation Multiple operators can be used in building an expression inlayer1 inlayer2 inlayer3 e sp ingrid1 mod inlayer2 div e sp ingrid3 A inlayerl1 amp inlayer2 Parentheses and expressions with multiple operators grid datasets and raster layers When multiple operators are used in an expression the order of processing is dependent on the precedence value assigned to the operator see Appendix B The higher the precedence value the sooner the operation will be processed 199 When two operators in the same expression have the same precedence value the one that is farthest to the left is processed first inlayer1 c input_data ingrid2 inlayer3 Precedence values can be overridden using parentheses The expression within the innermost parentheses is processed first no matter what the precedence value of the operator CLinlayer1 diff inlayer2 inlayer3 inlayerl C c data ingrid2 amp inlayer3 Linlayerl C inlayer2 inlayer3 When two or more sets of parentheses at the same level are used each set has the same precedence value therefore the expression in the set of parentheses farthest to the left is processed first CLinlayer1 inlayer2 C inlayer3 inlayer4 CLinlayerl1 inlayer2 gt gt CLinlayer3 mod c spatial ingrid4 Parentheses can be nested The expression within the innermost parentheses will
201. ocation near recreational facilities as many of the families who have relocated to the town have young children interested in pursuing recreational activities It is also important to be away from existing schools to spread their locations over the town The school must also be built on suitable land that is relatively flat The graphic below outlines the objectives Best site for a new school You want to know the following Where are locations with relatively flat land Is the landuse in these locations of a suitable type Are these locations close enough to recreation sites Are they far enough away from existing schools 61 Are these locations close enough to recreation sites You know that it is preferable to locate the school close to recreational facilities so you need to create a map displaying the distance to recreation sites to locate the school in areas that are close to them The process model here involves calculating the distance from recreation sites Input dataset needed location of recreational facilities Are they far enough away from existing schools You want to site the school away from existing schools to avoid encroaching on their catchment areas So you need to create a map displaying the distance to schools Here the process model involves calculating the distance from existing schools Input dataset needed location of existing schools Where are locations with relatively flat land
202. od Settings Height fi 3 width amp C Map Units Cell AO lt Temporary gt za Output cell size Output raster 169 Zonal statistics What is the Zonal Statistics function With the Zonal Statistics function a statistic is calculated for each zone of a zone dataset based on values from another dataset A zone 1s all the cells in a raster that have the same value regardless of whether or not they are contiguous However both raster and feature datasets can be used as the zone dataset So for example residential is a zone of a landuse raster dataset or a roads feature dataset can be the zone for an accident dataset Zonal statistical functions perform operations on a per zone basis a single output value is computed for every zone in the input zone dataset Zone layer Defines the zones shape values and locations Value raster Contains the input values used in calculating the output for each zone Input Zone layer A field can be added to the zone layer attribute table containing the Statistics calculated for each zone 170 The following statistics can be computed within each zone Majority determines the value that occurs most often in the zone Maximum determines the maximum value in the zone Mean computes the mean of the values in the zone Median computes the median of the values in the zone Minimum determines the minimum value in the zone Minority determi
203. ogram tends to when distances get very large At large distances variables become uncorrelated so the sill of the semivariogram is equal to the variance of the random variable slope Slope is the incline or steepness of a surface at a specific location The slope for a cell in a raster is the steepest downhill slope of a plane defined by the cell and its eight surrounding neighbors Slope can be measured in degrees from horizontal 0 90 or percent slope As slope angle approaches vertical 90 degrees the percent slope approaches infinity snap extent Setting the snap extent to a specific raster will snap all layers to the cell registration of the specified raster All layers will share the lower left corner and cell size of the specified raster source dataset A necessary input to the Cost Weighted Distance function The source is the point or group of points that the Cost Weighted Distance function uses when calculating the accumulated cost of traveling through each cell to the nearest source 224 spatial analysis The study of the locations and shapes of geographic features and the relationships between them Spatial analysis is useful when evaluating suitability when making predictions and for gaining a better understanding of how geographic features and phenomena are located and distributed spatial data The locations and shapes of geometric features with descriptions of each spatial function An operation
204. olated cell The more input points you specify the more each cell is influenced by distant points and the smoother the surface 139 Spline interpolation The Regularized Spline type ensures that you create a smooth surface and slope The Tension Spline type tunes the stiffness of the surface according to the character of the modeled phenomenon The Number of points option specifies the number of points used in the calculation of each interpolated point The more input points you specify the smoother the surface Tip Choosing a weight for Spline interpolations Regularized spline The higher the weight the smoother the surface Weights between 0 and 5 are suitable Typical values are 0 001 01 1 and 5 Tension spline The higher the weight the coarser the surface and the more the values conform to the range of sample data Weight values must be greater than or equal to zero Typical values are 0 1 5 and 10 140 Creating a surface using Spline interpolation 1 Click the Spatial Analyst dropdown arrow point to Interpolate to Raster and click Spline 2 Click the Input points dropdown arrow and click the point dataset you wish to use 3 Click the Z value field dropdown arrow and click the field you wish to use 4 Click the Spline type dropdown arrow and click the Spline method you wish to use 5 Optionally change the default Weight For the Regularized method the higher the
205. ome insignificant Usina ArcGIS SpatiaL ANALYST Polygon features Raster polygon features To iterate the accuracy of the above representation is dependent on the scale of the data and the size of the cell The finer the cell resolution and the greater the number of cells that represent small areas the more accurate the representation UNDERSTANDING RASTER DATA 87 Assigning attributes to a raster dataset The value associated with a cell is an identifier that defines to which class group category or member the cell belongs The value is a number either an integer or floating point Cell locations with the same value belong to the same zone Cells of the same zone do not have to be connected When an integer value is used it is often a code for a much more complex identification For example a 4 may equate to single family residential parcels on a landuse raster dataset Associated with the 4 might be a series of attributes such as the average commercial value average number of inhabitants or census code These additional attributes are either managed by the user manually or in a relational database There is usually a one to many relationship between the cell values or codes and the number of cells that are assigned the code That is there might be 400 cells with the value 4 single family residential and 150 cells associated with 5 commercial zoning on the landuse raster dataset The code is
206. on the output raster The nearest neighbor assignment does not change any of the values of cells from the input raster dataset The value 2 in the input raster will always be the value 2 in the output raster it will never be 2 2 or 2 3 Since the output cell values remain the same nearest neighbor assignment should be used for nominal or ordinal data where each value represents a class member or classification categorical data such as a landuse soil or forest type Bilinear interpolation Bilinear interpolation uses the value of the four nearest input cell centers to determine the value on the output raster The new value for the output cell is a weighted average of these four values adjusted to account for their distance from the center of the output cell in the input raster This interpolation method results in a smoother looking surface than can be obtained using nearest neighbor Since the values for the output cells are calculated according to the relative position and the value of the input cells bilinear interpolation is preferred for data where the location from a known point or phenomenon determines the value assigned to the cell that is continuous surfaces Elevation slope intensity of noise from an airport and salinity of the groundwater near an estuary are all phenomena represented as continuous surfaces and are most appropriately resampled using bilinear interpolation Usina ArcGIS SpatTiAL ANALYST
207. on towers In the example that follows the viewshed from an observation point is identified The elevation raster displays the height of the land darker locations represent lower elevations and the observation point is marked as a green triangle Cells in green are visible from the observation point and cells in red are not visible The elevation in the area of the observation point Green cells are visible from the observation point red cells are not visible 160 Displaying a hillshade underneath your elevation and the output from the Viewshed function is a useful technique for visualizing the relationship between visibility and terrain The relationship between visibility and the terrain The Viewshed function can correct for the curvature of the earth and refraction of light rays passing through the atmosphere if the input surface has a projection file in which the ground units and surface z units are expressed in standard units feet meters or units meter Usina ArcGIS Spatiat ANALYST Finding viewshed The Viewshed function allows you to identify the places that can be seen from one or more observation points or lines If lines are used as input the observation points occur at the vertices of the lines The raster created from this function contains cells coded to indicate whether they are visible to or hidden from the observer If there is more than one observer point each visible cell in the
208. onal statements The Con function The Con function s name is short for conditional statement The Con function is a local function that is evaluated on a cell by cell basis The usage of the Con function is Con condition true_expression condition true_expression condition true_expression false_expression where condition is a conditional expression that is evaluated for each cell in the analysis extent If the condition is True true_expression identifies the value used to compute the output cell value Additional condition statements can be tested on the values of the input grid dataset or raster layer with a mandatory true_expression identifying the value to be applied to those cells where the additional statement is True If none of the results of the evaluations of the conditional statements are True a value or expression can be applied to the cells through the false_expression optional argument If no value is specified at the false_expression argument any cell that does not meet any of the conditions within the expression will be set to NoData An example of a simple Con function is conC inlayerl1 gt 5 10 100 In the above expression if the value of a cell location in the raster layer inlayer1 is greater than 5 10 will be assigned to that cell location on the output raster dataset while locations on inlayer1 with values 5 or lower will be assigned 100 on the output raster dataset If no value or expression
209. onally change the default Power value Click the Search radius type dropdown arrow and click Variable Optionally change the default number of points to use in the calculation of each interpolated point Specify a maximum distance for the radius to expand to in search of the number of points specified 8 Optionally specify a barrier 9 Optionally change the 10 11 default Output cell size Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory Click OK Spatial Analyst Spatial Analyst Layer Jelevation Ja lin 7 Distance Density Interpolate to Raster Inverse Distance Weighted Surface Analysis Spline Cell Statistics Eriging Neighborhood Statistics Zonal Statistics FReclassify Raster Calculator Convert p Options Inverse Distance Weighted Input poms Sample_ points is 2 value held O ONE 3 Power B 4 Search radius type Varnable 5 Search Radiue Settings Humber of points Maximum distance T Use barrier polylines 30 9 lt Temporary i 10 cancel _ Output cell size Output raster 11 Usina ArcGIS Spatiat ANALYST Spline What is Spline Spline estimates values using a mathematical function that minimizes overall surface curvature resulting in a smooth surface that passes exactly through the input points Conceptually it is
210. onnections that provide access to geographic data stored in folders on local disks or shared on the network It also includes folders that let you manage database connections and coordinate systems The Catalog tree provides a hierarchical view of the geographical data in those folders categorical raster A raster that represents the world with a set of values that have been aggregated into classes For example a satellite image that has been reclassified to extract a number of land cover types is a categorical raster The cells of categorical rasters represent areas See also discrete raster cell See raster cell cell size The length in map units of a side of a cell The cell size is the same in both the x and y directions cell statistics A Spatial Analyst function that calculates a statistic for each cell of an output raster that is based on the values in the same cell location of each cell of multiple input rasters classify The process of sorting or arranging attribute values into groups or categories all members of a group are represented on the map by the same symbol Usinc ArcGIS Spatiat ANALYST continuous raster A raster that represents the world with a set of values that vary continuously as a surface For example a raster digital elevation model and an interpolated chemical concentration surface are continuous rasters The cells of continuous rasters represent the values at the center of the cell
211. ons you can refine how the manipulation the calculations will be performed through parameters For example for a focal function the cells to include may vary based on the neighborhood that s specified Usinc ArcGIS Spatiat ANALYST The operators and functions of Spatial Analyst The functions associated with raster cell cartographic modeling can be divided into five types e Those that work on single cells ocal functions e Those that work on cells within a neighborhood focal functions e Those that work on cells within zones zonal functions e Those that work on all cells within the raster global functions e Those that when combined in a series perform a specific application application functions Each of these categories is influenced by or is based on the spatial or geometric representation of the data not solely on the attributes that they portray That is a function that is to add two layers together work on single cells is dependent on the location and the value of its counterpart on another layer Functions applied to cells within neighborhoods or zones rely on the spatial configuration of the neighborhood or zone as well as the cells and values in the configuration Local functions Local or per cell functions compute an output raster dataset where the output value at each location is a function of the value associated with that location on one or more raster datasets That is the value of the
212. ool site 39 3 Modeling spatial problems 55 Modeling spatial problems 56 A conceptual model for solving spatial problems 58 Using the conceptual model to create a suitability map 61 Understanding rasters and analysis 4 Understanding raster data 73 Understanding a raster dataset 74 Coordinate space and the raster dataset 78 Discrete and continuous data 82 The resolution of a raster dataset 84 Raster encoding 85 Representing features in a raster dataset 86 Assigning attributes to a raster dataset 88 Using feature data directly in Spatial Analyst 89 Deriving raster datasets from existing maps 90 5 Understanding cell based modeling 91 Understanding analysis in Spatial Analyst 92 The operators and functions of Spatial Analyst 93 NoData and how it affects analysis 101 Values and what they represent 102 The analysis environment 104 The cell size and analysis 105 Handling projections during analysis 106 Performing analysis 6 Setting up your analysis environment 109 Creating temporary or permanent results 110 Specifying a location on disk for the results 112 Using an analysis mask 113 About the coordinate system and analysis 115 Setting the extent for results 116 Setting the cell size for results 117 7 Performing spatial analysis 119 Mapping distance 120 Straight line distance 121 Allocation 124 Cost weighted distance 126 Shortest path 131 Mapping density 133 Interpolating to raster 135 Inverse Distance
213. oolbar to set up your working directory extent and cell size for your analysis results Tip Browsing for files or directories If the file you need is not in your table of contents or if you need to check the directory to place your results click the Browse button 130 Calculating cost weighted distance 1 Click the Spatial Analyst dropdown arrow point to Distance and click Cost Weighted 2 Click the Distance to dropdown arrow and click the source layer 3 Click the Cost raster dropdown arrow and click the raster to use 4 Optionally specify a Maxi mum distance Cells outside this distance will not be considered in the calculation and will be given the value of NoData Leaving the Maximum distance blank will not put a limit on how far distances will be measured 5 Specify an Output cell size for the result 6 Optionally check Create direction to create a direction raster This is a required input for the Shortest Path function 7 Optionally check Create allocation to create an Allocation raster 8 Type a name for each result or leave the default to create a temporary result 9 Click OK Spatial Analyst Spatial Analyst Layer elevation A E fk Distance Straight Line Density Allocation Interpolate to Raster d Cost weighted Surface Analysis j Shortest Path Cell Statistics Neighborhood Statistics onal Statistics
214. opdown arrow and click the raster you want to use 4 Click the Cost direction raster dropdown arrow and click the raster you want to use 5 Click the Path type dropdown arrow and choose an option depending on how many paths you wish to be found 6 Type a name for the result or leave the default to create a temporary result 7 Click OK Spatial Analyst Spatial Analyst r Layer elevation JS ih Distance Density interpolate to Raster Suttace Analysis Cell Statistics Neighborhood Statistics onal Statistics Reclassify Raster Calculator Convert Options Shortest Path Path to Cost distance raster Cost direction raster Path type Output features Straight Line Allocation Cost Weighted destination a distance direction For Each Cell ep Eup CD Ce Cancel Us nG ArcGIS Spatiat ANALYST Mapping density What is density By calculating density you spread point values over a surface The magnitude at each sample location line or point is distributed throughout a landscape and a density value is calculated for each cell in the output raster Density maps are predominantly created from point data and a circular search area is applied to each cell in the output raster being created The search area determines the distance to search for points in order to calculate a density value for each
215. or the full pathname to the dataset must be provided e The accumulative operators are not supported e Spatial Analyst functions can be run in the Raster Calculator slope Inlayer1 calculates the slope of Inlayer1 mean Inlayer1 Inlayer2 Inlayer3 calculates the mean value between rasters on a cell by cell basis hillshade e spatial ingrid creates a hillshade from a grid dataset on disk For more on Map Algebra see Appendix A or search the ArcGIS Desktop Help index for Map Algebra 181 Using the Raster Calculator The Raster Calculator gives you access to numerous tools Use Map Algebra to weight rasters and combine them as part of a suitability model make selec tions on your data in the form of queries apply mathematical operators and functions or type Spatial Analyst functions Use layers from the table of contents or type the full pathname to the grid dataset shapefile coverage or table on disk For example typing c spatial elevation 2 will use the elevation dataset in the location specified and multiply it by two gt Tip Changing the font used to build an expression Right click inside the expression box and click Font Tip Creating permanent output Either specify an output name in the expression outgrid inlayer inlayer2 or create a temporary result then right click the output in the table of contents and click Make Permanent 182 Using the Raster Ca
216. ou to compute statis tics for each zone of a zone dataset based on the informa tion in a value raster This could be average population density per zone of pollution or vegetation type per zone of elevation The zone dataset can be feature or raster data The value raster must be a raster dataset Tip Using NoData Uncheck the Ignore NoData in calculations check box if you want NoData values to be included in the calculation If there are NoData values within a zone the output value for the zone will be NoData because there is insufficient information to complete the calculation Leave the Ignore NoData in calculations check box checked if you want NoData values to be ignored Only cells on the value raster that have data values within each zone will be used in the calculation 172 Creating a chart using zonal statistics 1 Click the Spatial Analyst dropdown arrow and click Zonal Statistics 2 Click the Zone dataset dropdown arrow and click the layer you want to use 3 Click the Zone field dropdown arrow and click the field of the Zone layer you wish to use 4 Click the Value raster dropdown arrow and click the raster you wish to use 5 Uncheck Ignore NoData in calculations to use the NoData values of the Value raster in the calculation 6 Check the check box to Join the output table to the zone layer Note that this option is only available for layers not datasets you browsed to 7 Cl
217. our problem You may just need a single operation or function but sometimes hundreds of operations and functions may be necessary Types of process models There are many types of process models to solve a wide variety of problems Some include e Suitability modeling Most spatial models involve finding optimum locations such as finding the best location to build a new school landfill or resettlement site e Distance modeling What is the flight distance from Los Angeles to San Francisco e Hydrologic modeling Where will the water flow to e Surface modeling What is the pollution level for various locations in a county A set of conceptual steps can be used to help you build a model The remainder of this chapter explains these steps 57 A conceptual model for solving spatial problems Step 1 Stating the problem What is your goal Step 2 Breaking the problem down What are the objectives to reach your goal What are the phenomena and interactions process models necessary to model What datasets will be needed Step 3 Exploring input datasets What is contained within your datasets What relationships can be identified Step 4 Performing analysis Which GIS tools will you use to run the individual process models and build the overall model Step 5 Verifying the model s result Do certain criteria in the overall model need changing If Yes go back to ste
218. output cell is then determined To find the value each cell should receive on the output raster the center of each cell in the output must be mapped to the original input coordinate system Each cell center coordinate is transformed backwards to identify the location of the point on the original input raster Once the input location is identified a value can be assigned to the output location based on the nearby cells in the input It is rare that an output cell center will align exactly with any cell center of the input raster Therefore techniques have been developed to determine the output value depending on where the point falls relative to the center of cells of the input raster and the value associated with these cells The three techniques for determining output values are nearest neighbor assignment bilinear interpolation and cubic convolution Each of these techniques assigns values to the output differently thus the values assigned to the cells of an output raster may differ according to the technique used Nearest neighbor assignment Nearest neighbor assignment is the resampling technique of choice for categorical data since it does not alter the value of the input cells Once the location of the cell s center on the output 80 raster dataset is located on the input raster nearest neighbor assignment determines the location of the closest cell center on the input raster and assigns the value of that cell to the cell
219. owever the more input points and the greater their distribution the more reliable the results 135 Inverse Distance Weighted What is Inverse Distance Weighted IDW IDW estimates cell values by averaging the values of sample data points in the vicinity of each cell The closer a point is to the center of the cell being estimated the more influence or weight it has in the averaging process This method assumes that the variable being mapped decreases in influence with distance from its sampled location For example when interpolating a surface of consumer purchasing power for a retail site analysis the purchasing power of a more distant location will have less influence because people are more likely to shop closer to home Power With IDW you can control the significance of known points upon the interpolated values based upon their distance from the output point By defining a high power more emphasis is placed on the nearest points and the resulting surface will have more detail be less smooth Specifying a lower power will give more influence to the points that are furthur away resulting in a smoother surface A power of 2 is most commonly used and is the default Search radius The characteristics of the interpolated surface can also be controlled by applying a search radius fixed or variable which limits the number of input points that can be used for calculating each interpolated cell Fixed search
220. own arrow and click Arctic White to show NoData values Water and Wetlands 1in this color 11 Click OK QUICK START TUTORIAL Layer Properties Unique Values Note A copy of this reclassified landuse dataset can be found in the location ArcGIS ArcTutor Spatial Results Ex2 landuseR 35 Step 4 Weighting and combining datasets After applying a common scale to your datasets where higher values are given to those attributes that are consid ered more suitable within each dataset you are ready to combine them to find the most suitable locations If all datasets were equally important you could simply combine them at this point however you have been informed that it is preferable to locate the new school close to recreational facilities and away from other schools You will weight all the datasets giving each a percentage influence The higher the percentage the more influence a particular dataset will have in the suitability model You will give the layers the following percent influence Each percentage 1s divided by 100 to normalize the values 50 Reclass of Distance to schools 0 25 25 0 125 12 5 0 125 12 5 1 Click the Spatial Analyst dropdown arrow and click Raster Calculator Reclass of Distance to rec_ sites 0 5 Reclass of landuse Reclass of slope 36 Spatial Analyst Layer elevation 7 j p Distance gt Density Interpolate to Raste
221. p ArcInfo File Edit View Insert Selection Tools Window Help eH Ss Ba BX a fis396 ef ER Laver Phone D x D Spatial Analyst Y Layer z O QAI OOE S PROMS RPE g W o E amp Rock Creek Park Fire Boundary Trails x o KI Commcercial Residences Park Boundary Park landuse US Highways Major Highways Major Roads Ramps Local Roads DBCRCRCRORCMC CIC HANA Streams fl K Schools Military Mask DC Not Park Hilli Om Terrain 10m Hee ee Kgg Ko Rock Creek Park Fire Display Source TE Drawing kOJO Ay 1 Java z fic B Z UA v v 2 533722 89 4938003 62 Meters Ui In order to break a suspect s alibi a viewshed analysis finds out if he actually would have been able to see the location of the fire from where he called it in claiming he saw flames Areas drawn in yellow identify the locations from which the fire would have been seen This visibility analysis demonstrates that he could not have seen the flames from the phone booth 4 Usina ArcGIS Spatiat ANALYST Identifying spatial relationships Spatial Analyst provides tools to model spatial relationships Trafficking mxd ArcMap Arcinfo Piel Es File Edit View Insert Selection Tools Window Help Dw we S amp a ex wD OM fr 95 539 R Layer x1 Population Plus Kids at Risk p gt i amp EEES a a e Hlk ah 5i Spatial Analyst
222. p 4 Step 6 Implementing the result 58 Usina ArcGIS Spatiat ANALYST Step 1 Stating the problem To solve your spatial problem you need to start off by clearly stating the problem you are trying to solve What is your goal Following the steps below will help you realize your goal Step 2 Breaking the problem down Once the goal of the problem is understood you must then break the problem down into a series of objectives identify the elements and their interactions that are needed to meet your objectives and create the necessary input datasets to develop the representation models By breaking the problem down into a series of objectives you will discover the necessary steps to reach your goal which will help you to solve the problem If your goal was to find the best sites for spotting moose your objectives might be to find out where moose were recently spotted what vegetation types they feed on most and so on By arranging the objectives in order you will begin to understand the big picture of what you are ultimately trying to solve Once you have established your objectives you need to identify the elements and the interactions between these elements that will meet your objectives The elements will be modeled through representation models and their interactions through process models Moose and vegetation types will be only a few of the elements necessary for identifying where moose are most likely to be
223. p Entries Tip Changing the classes of your old values Click Classify to change the classification of your old values Click Unique to separate classes of old values into unique values PERFORMING SPATIAL ANALYSIS Grouping entries 1 Click the Spatial Analyst dropdown arrow and click Reclassify Click the Input raster dropdown arrow and click the raster with values you wish to group Click the Reclass field dropdown arrow and click the field you wish to use Click the Old values you wish to group click one then hold down the Shift key and click the next one then right click and click Group Entries Give the grouped entry and other Old values the New values you wish for them to have Optionally click Save to save the remap table Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory Click OK Spatial Analyst Spatial 4nalyst Layer Jlanduse JE ili Distance Density Interpolate to Raster b Surface Analysis e Cell Statistics Neighborhood Statistics Zonal Statistics Raster Calculator Convert b Options Reclassify Input raster landuse Reclass field Landuse K Set values to reclassify Old values Agriculture Elassitp Unique Group Entries 4 Add Entry Ungoup Eriti Remove Entries Saccdesdeaseedessecaaibessedsaeaaatnassasseee i
224. pdown list that determines to which layer new features will be added The target layer is set by clicking a layer in the Target Layer dropdown list For instance if you set the target layer to Buildings any features you create will be part of the Buildings layer You must set the target layer whenever you re creating new features temporary dataset A raster dataset temporarily stored on disk All output raster results from Spatial Analyst are temporary unless you specify a location on disk and a filename in a function dialog box make the temporary dataset permanent or save the map document In these GLOSSARY three cases temporary results will become permanent datasets on disk See make permanent trigonometric functions Perform various trigonometric calculations on the values in an input raster Available trigonometric functions Sin Cos Tan Asin Acos Atan variogram A function of the distance and direction separating two locations that is used to quantify autocorrelation The variogram is defined as the variance of the difference between two variables at two locations The variogram generally increases with distance and is described by nugget sill and range parameters variography The process of estimating the theoretical variogram It begins with exploratory data analysis then computing the empirical variogram binning fitting a variogram model and using diagnostics to assess the fitted model viewshed
225. points as possible Experts should be knowledgeable about the objective being studied For example it is more meaningful to ask commuters to rank their opinions on drive time desirability than to ask a city official when he thinks traffic is worst Usinc ArcGIS Spatiat ANALYST Ranking the areas close to recreation sites To site the school close to recreational facilities you need to know the distance to them The Spatial Analyst Straight Line Distance function will create such a map calculating the straight line distance from any location to the nearest recreation site The result is a raster dataset in which every cell represents the distance to the nearest recreation site To rank this map simply use the Reclassify function As it is preferable to locate close to recreation sites give a value of 1 to distances far from recreation sites and a value of 10 to distances close to recreation sites then rank the distances linearly in between as the following chart shows 10 Suitability Distance meters MODELING SPATIAL PROBLEMS Ranking the areas away from existing schools To avoid the catchment areas of the other schools you need to know the distance to them The Spatial Analyst Straight Line Distance function will create such a map calculating the straight line distance from any location to the nearest school The result is a raster dataset in which every cell represents the distance to the nearest school To rank th
226. put reclassified value is specified LOWEST OUTPUT is ignored For example Example 3 Remap table for cell value reclassification LOWEST INPUT 3 5 10 6 16 Tepo 15 28 The reclassification is summarized in the following table Input Cell Values Output Reclassified Value Less than 3 NoData 3to5 10 Greater than 5 to 6 16 Greater than 6 to 7 62 Greater than 7 to 15 28 Greater than 15 NoData Similarly an output value can be specified for explicit input ranges Example 4 Remap table for cell value reclassification 39 9 59 8 13 15 59 Us nG ArcGIS SPaTiaL ANALYST The reclassification is summarized as shown below Input Cell Values Output Reclassified Value Less than 3 NoData 3 to 5 Greater than 5 to 9 Greater than 9 to 13 Greater than 13 to 15 Greater than 15 NoData All of the examples presented above are valid ASCII remap tables that can be used to reclassify cell values Each of the four methods presented above shows the acceptable syntax for an ASCII remap table The syntax cannot be mixed among the four types For example it is not valid to specify an assignment statement that contains a single input value followed by another assignment statement that contains an input range This is an invalid remap table Single input cell values and input ranges cannot be specified in the same remap table Invalid remap table for cell value reclassification LOWEST INPUT 3 LO
227. r 4 PERFORMING SPATIAL ANALYSIS Z NnnnAmM2Z2z2ii7 2 RU mW a Why use the Aspect function With the Aspect function you can e Find all north facing slopes on a mountain as part of a search for the best slopes for ski runs e Calculate the solar illumination for each location in a region as part of a study to determine the diversity of life at each site e Find all southerly slopes in a mountainous region to identify locations where the snow is likely to melt first as part of a study to identify those residential locations that are likely to be hit by meltwater first e Identify areas of flat land to find an area for a plane to land in an emergency 155 Calculating aspect The Aspect function enables you to create a map displaying the steepest down slope direction from each cell to its neighbors for an entire region It is most commonly used with an elevation raster to identify the direction of slope Tip Identifying slope direction Use the Identify tool on the Tools toolbar to identify locations This will give you the compass direction for a specific location on your output Aspect dataset 156 Creating an aspect dataset 1 Click the Spatial Analyst dropdown arrow point to Surface Analysis and click Aspect 2 Click the Input surface dropdown arrow and click the surface for which you want to calculate aspect 3 Optionally change the default Output cell size 4 Specify a name
228. r gt Surface Analysis gt Cell Statistics Neighborhood Statistics Zonal Statistics Reclassify Faster Calculator Convert gt Options 2 Double click Reclass of Distance to rec_ sites from the Layers list to add it to the expression box Click Multiply Click 0 5 Click Add Double click Reclass of Distance to schools Click Multiply Click 0 25 Click Add 10 Double click Reclass of landuse 11 Click Multiply 12 Click 0 125 13 Click Add 14 Double click Reclass of slope 15 Click Multiply oN DM fw Usina ArcGIS SpatiAL ANALYST 16 Click 0 125 18 Right click the newly created raster layer in the table of 17 Click Evaluate to perform the weighting and combining contents and click Properties of the datasets 19 Click the Symbology tab 20 Click Classified from the Show list 21 Click the Classes dropdown arrow and click 10 E E al 3 e o And 22 Scroll to the last three classes click one then press and a a 5 6 gt o hold the Shift key and click the other two a 23 Right click the highlighted classes click Properties for ea ped eae PE ane teas ot landuse selected Colors and click a bright color l i a m 2 Ner 24 Click the Display NoData as dropdown arrow and click Reclass of Distance to rec_sites 0 5 Reclass of Distance to schools the color black This displays values of NoData Water 0 25 Reclass of landuse 0 125 Rec
229. radius A fixed search radius requires a distance and a minimum number of points The distance dictates the radius of the circle of the neighborhood in map units The distance of the radius is constant so for each interpolated cell the radius of the circle used to find input points is the same The minimum number of 136 points indicates the minimum number of measured points to use within the neighborhood All the measured points that fall within the radius will be used in the calculation of each interpolated cell When there are fewer measured points in the neighborhood than the specified minimum the search radius will increase until it can encompass the minimum number of points The specified fixed search radius will be used for each interpolated cell cell center in the study area thus if your measured points are not spread out equally which they rarely are then there are likely to be a different number of measured points used in the different neighborhoods for the various predictions Variable search radius With a variable search radius the number of points used in calculating the value of the interpolated cell is specified which makes the radius distance vary for each interpolated cell depending on how far it has to search around each interpolated cell to reach the specified number of input points Thus some neighborhoods can be small and others can be large depending on the density of the measured points near the in
230. raster datasets on disk 3 Click Add 4 Click the Overlay statistic dropdown arrow and click the type of statistic you want to compute on your input layers Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory Click OK Spatial Analyst Spatial Analyst Layer elevation He Hin E Distance b Density Interpolate to Raster Surface Analysis b Cell Statistics Neighborhood Statistics Zonal Statistics FReclazsify Raster Calculator Convert p Options Cell Statistics Input rasters Pollution Jan Pollution Feb Pollution Mar Pollution Apr Pollution May Pallution Jan Pallution Feb Pollution Wlar Pollution Apr Pollution hay renee Remove lt Mean lt Temporary gt Cancel Overlay statistic Output raster 165 Neighborhood statistics What is the Neighborhood Statistics function The Neighborhood Statistics function is a focal function that computes an output raster where the value at each location is a function of the input cells in some specified neighborhood of the location For each cell in the input raster the Neighborhood Statistics function computes a statistic based on the value of the processing cell and the value of the cells within a specified neighborhood then sends this value to the corresponding cell location o
231. rdinate space and the raster dataset Discrete and continuous data The resolution of a raster dataset Raster encoding Representing features in a raster dataset Assigning attributes to a raster dataset Using feature data directly in Spatial Analyst Deriving raster datasets from existing maps When using Spatial Analyst for some or all of your processing you will have to use or create raster datasets In this chapter you will be exposed to how a raster dataset is represented in Spatial Analyst and the issues you need to be aware of when using and creating rasters This chapter will focus on the concerns of the raster representation while Chapter 5 Understanding cell based modeling a companion chapter to this one will address the issues that must be considered when performing analysis From this chapter you will learn About the structure of raster datasets The importance of coordinate space and raster datasets The difference between discrete and continuous types of raster datasets About the resolution or cell size when creating a raster dataset How raster datasets are encoded and how points lines and polygons are represented as cells Other issues you need to be aware of such as when adding other attributes to raster datasets and creating raster datasets from existing maps 73 Understanding a raster dataset Raster data is generally divided into two categories thematic data and image data The values i
232. re the slope input raster had a weight or influence of 66 percent By giving the slope input raster a higher weight more attention was given to avoiding steeper slopes in the red path The point to understand from this is that it is important to spend time considering how to weight the rasters that make up the cost raster How you weight your rasters depends on your application and the results you wish to achieve 131 Finding the shortest path The Shortest Path function finds the shortest or least cost path from a source or a set of sources to a destination or set of destinations such as finding the least cost path from several suburban locations sources to the closest shopping mall destinations The Path type indicates the number of paths that will be found A path For Each Cell finds a path for each cell in each zone each cell in every suburb receives its own path A path For Each Zone finds the one least cost path for each zone each suburb receives only one path The Best Single path finds the least cost path for all the zones only the shortest path between one suburb and one mall is computed See Cost weighted distance earlier in this chapter 132 Performing shortest path 1 Click the Spatial Analyst dropdown arrow point to Distance and click Shortest Path 2 Click the Path to dropdown arrow and click your destina tion layer 3 Click the Cost distance raster dr
233. red cells All subsequent results from analysis will be to this extent The analysis extent is a rectangle and is specified by identifying the coordinates of the window in map space Raster dataset Analysis result using a mask The cell size The output cell size or resolution for any operation or function can be set to any size desired The default output resolution is determined by the coarsest of the input raster datasets Performing analysis on a small section of the raster 104 Usina ArcGIS Spatiat ANALYST The cell size and analysis Cells in different raster datasets do not need to be stored in the same resolution But when processing between multiple datasets the cell resolution as is the case with the registration needs to be the same When multiple raster datasets are input into any Spatial Analyst function and their resolutions are different one or more of the input datasets will be automatically resampled using the nearest neighbor assignment for additional information see Chapter 4 Understanding raster data to the coarsest input The nearest neighbor assignment resampling technique is used since it is applicable to both discrete and continuous value types while bilinear and cubic are only applicable to continuous data A resampling technique is necessary because rarely do the centers of the input cells align with the transformed cell centers of the desired resolution The default resa
234. regation method within a neighborhood to derive values Unlike the cell size setting in the analysis environment the resolution altering functions are applied only to the resultant dataset The aggregation functions group a series of cells to the same value To perform an aggregation the block functions are implemented With a block function Spatial Analyst calculates a specified statistic within nonoverlapping neighborhoods 100 Usina ArcGIS Spatiat ANALYST NoData and how it affects analysis Every cell location in a raster has a value assigned to it When inadequate information is available for a cell location the location can be assigned NoData NoData and 0 are not the same 0 is a valid value The fact that a location can have NoData instead of a valid value has ramifications in operators and functions NoData means that not enough information is known about a cell location to assign it a value There are two ways that a location with NoData can be treated in the computation of an expression e Return NoData for the location no matter what e Ignore the NoData and compute with the available values Depending on the operator or function one of the above approaches will make greater sense than the other For instance when adding two raster datasets together if a cell location in one of the datasets contains NoData there is no basis for assigning a value to the corresponding location on the output raster dataset In co
235. rical raster Euclidean distance See straight line distance extent The minimum rectangle bounding the area of a geographic dataset feature A representation of a real world object in a layer on a map feature dataset A collection of feature classes in a geodatabase that share the same spatial reference field A column in a table Each field contains the value for a single attribute focal functions This group of Spatial Analyst functions computes an output raster where the output value at each location is a function of the input cells in some specified neighborhood of the location 220 format The pattern into which data is systematically arranged for use on a computer A file format is the specific design of how information is organized in the file For example raster datasets come in different formats such as ESRI grid TIFF and MrSID from LizardTech Software function See spatial function or mathematical functions GIS Geographic information system An organized collection of computer hardware software geographic data and personnel designed to efficiently capture store update manipulate analyze and display all forms of geographically referenced information global functions This group of Spatial Analyst functions computes an output raster where the output value at each location is potentially a function of all the cell s in the input raster grid A geographic representation o
236. rrow and click the field you wish to use Click the input boxes for the New values you wish to change to NoData Click Delete Entries Check Change missing values to NoData Optionally click Save to save the remap table Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory Click OK The values you deleted will be changed to NoData in the Output raster Reclassify Input raster landuse a Reclass field Landusel 3 Set values to reclassify Mew values 2 Elasstp Forested wetlands HayPernanent Pasture Unique 4 Mined Forest Add Entry Non Forested Wetlands iam l x i l Si Delete Entries 5 Load Save Change missing values to NoData Output raster lt Temporary gt area Reclassify Ea Input raster Jlanduse S Reclass teld Landusel iad Set values to reclassify Load Save IM Change missing values to NoDhata Ohutput raster e datafeclass 8 a 6 7 9 Us nG ArcGIS SPaTiaL ANALYST The Raster Calculator What can you do with the Raster Calculator Arithmetic operators The Raster Calculator provides you with a powerful tool for Arithmetic operators allow for the addition subtraction performing multiple tasks You can type in Map Algebra syntax multiplication and division of two rasters or numbers or a to perform mathematical calculations using operators and combination of the two functions
237. rtest Path rec_ sites Temporar a lt Temporary A lt Temporary OF 8 123 Allocation What is the Allocation function Why use the Allocation function The Allocation function allows you to identify which cells belong Use the Allocation function to perform analyses such as to which source based on closest proximity in a straight line Identifying the customers served by a series of stores An output raster is produced that records the identity of the closest source cell for each cell Each cell in an allocation raster Eas receives the value of the source cell to which it will be allocated e Finding areas with a shortage of fire hydrants e Locating areas that are not served by a chain of supermarkets e Finding out which hospital is the closest The example to the left identifies the areas of land supported by a recreation site You can easily identify the areas that may be in need of more recreation sites mainly areas in the northeast half of the raster Note that the Allocation function can also be performed via the Straight Line Distance function or the Cost Weighted Distance function Performing the Allocation function via the Straight Line Distance function allows you to find the cells that are to be allocated to which source based on closest proximity in a straight line Performing the Allocation function via the Cost Weighted Distance function takes the cost of traveling over the land
238. s e What an analysis mask is and how to apply one e How to set the extent for your analysis results e The importance of cell size and how to specify this for your analysis results 109 Creating Making your results Slope Fea permanent within a ee c spaia covaion MA temporary or function dialog box oe eei 5 permanent i hen performing any Output measurement Degree f Percent results function type the name for gee or 1 the output and it will be gupa e w By default most results from permanently saved to your i f analysis are temporary Excep working directory eee 7 p tions are the conversion func tions and functions that do not output raster data In these cases results will be permanent by default Results from all other functions can be made permanent 1n three Cancel Alternatively type a location on disk and a name for the output or use the Browse button to navigate to a folder on disk Results will be permanent ways e z oOo SU aL ae Making temporary results E7 mr result in a function dialog ENC Slope of ejani permanent VALI BE Copy box E 0 77 Remove E 7712 stoute Table e By creating a temporary 1 Right click the temporary mah jeans l result then making the result in the table of contents TE e nn temporary result permanent and click Make Permanent m 527 Zoom To Raster Resolution r 3 eae Visible Scale Range gt e By saving th
239. s giving a value of to areas far from recreation sites the least suitable locations and ranking the values g f g i T Change missing values to NoData in between By doing this you will find out which areas are end N near and which areas are far from recreation sites concel_ Unique Add Entry hi Delete Entries 1 Click the Spatial Analyst dropdown arrow and click Reclassify 4 Click the Method dropdown arrow and click Equal Interval Spatial Analyst SpatislAnayst Layer elevation 2m 5 Click the Classes dropdown arrow and click 10 E Distance b Density 6 Click OK Interpolate to Raster gt Surface Analysis b Cell Statistics Neighborhood Statistics Zonal Statistics Classification r Classification Statistics Method 602862 0 Raster Calculator Classes Maximum 13382 2558 Data Exclusion __ Sum 2585888020 Convert b Mean 4289 35314 Use Custom Min amp May Exclusion Standard Deviation 2855 988061 Options E gs l Below custom min ae ae i Show cese forvalter J aboye custom mar aes Advanced Statistics Columns jo I Show Std Dev J Show Mean Break Values x 1338 225568 2676 45117 1338 225568 2676 45117 4014 67675 5352 90233 6691 12792 8029 3535 9367 57909 2 Click the Input raster dropdown arrow and click Distance to rec_ sites 3 Click Classify 13382 2558 0 334
240. s before obtaining the specified number of points the prediction for that location will be performed on the number of measured points within the maximum radius Kriging methods Spatial Analyst provides two kriging methods Ordinary and Universal Ordinary kriging Ordinary kriging is the most general and widely used of the kriging methods It assumes the constant mean is unknown This is a reasonable assumption unless there is some scientific reason to reject this assumption 145 Universal kriging Universal kriging assumes that there is an overriding trend in the data for example a prevailing wind and it can be modeled by a deterministic function or polynomial This polynomial is subtracted from the original measured points and the autocorrelation is modeled from the random errors Once the model is fit to the random errors before making a prediction the polynomial is added back to the predictions to give you meaningful results Universal kriging should only be used when you know there is a trend in your data and you can give a scientific justification to describe it 146 Usinc ArcGIS Spatiat ANALYST Kriging interpolation There are two kriging methods Ordinary and Universal Ordinary kriging is the most general and widely used of the kriging methods and 1s the default It assumes the constant mean is unknown Universal kriging should only be used when you know there is a trend in your data and you can g
241. s is the only situation that is possible However for discrete data it is assumed that the feature homogeneously fills the entire extent of the cell There is some chance that the cell center is not representative of the entire cell but the size of the cells can be reduced if desired If the input features are points then any cell extent that encompasses a point will receive the value of the attribute of the point data that is being converted By definition a point has no area and you are converting the data to a locational representation that has area With a cell representation there is some generalization of the original data If two or more points fall within the extent of a cell Spatial Analyst randomly selects one of the points when assigning a value to the cell Thus it is possible to have fewer cells with values than there are points being converted You should make your cell size small enough to capture enough of the input points for the desired analysis UNDERSTANDING RASTER DATA Converting linear features to a raster dataset is similar to converting point features For any line that passes within the extent of a cell the cell will receive the value of the attribute identified in the conversion If multiple lines pass through a single cell Spatial Analyst will randomly select one of the lines to represent that cell location on the output raster dataset As with point data linear features will be as wide as the si
242. s to a single feature each column contains the values for a single characteristic In an Integer Categorical raster attribute table the first field in the table is value which stores the value assigned to each zone of a raster A second field count stores the number of cells that belong to each zone autocorrelation The statistical relationship among the measured points where the correlation depends on the distance and or direction that separates the locations azimuth The direction measured in degrees from which a light source illuminates a surface used when calculating a hillshade barrier A line or polygon dataset that limits the search for input sample points when performing interpolation The line can represent a cliff ridge or some other interruption in the landscape Only the sample points on the same side of the barrier as the current processing cell will be considered bin A classification of lags where all lags that have similar distance and direction are put into the same bin Bins are commonly formed by dividing the sample area into grid cells or sectors Boolean operators Operators within the Raster Calculator of Spatial Analyst They use Boolean logic TRUE or FALSE on the input rasters on a cell by cell basis Output values of TRUE are written as 1 and False as 0 218 Boolean operators And Or Xor Not For example inraster or inraster2 Catalog tree Contains a set of folder c
243. se rec_ sites roads and schools 4 Click Add U9 elevation landuse rec_sites shp roads shp schools shp Show of type Datasets and Layers lyr 14 The datasets are added to the ArcMap table of con tents as layers x E amp Layers E schools ry E rec_sites roads E landuse VALUE elevation Value High 4361 Low 438 Displaying and exploring data You will now explore the display capabilities of ArcMap by changing the symbology of some of the layers 1 Right click landuse in the table of contents and click Properties E amp Layers E schools E rec_sites E roads E m lar lar eon E X Remove Open Attribute Table E Joins and Relates gt Co lt amp Zoom To Layer fe Eo Zoom To Raster Resolution E ele Wisible Scale Range gt Set Data Source m Save As Layer File Usina ArcGIS SPpatiaL ANALYST 2 Click the Symbology tab You can also change the color and properties of symbols via All landuse categories are currently drawn using cell the table of contents values as the Value Field and in random colors You will 6 Click the point representing schools in the table of change the Value Field to be more meaningful and contents change the color of each symbol to show a more appropriate color for each landuse on the map 5 El Layers 3 Click the Value Field dropdown arrow and click landuse
244. se the ArcGIS Desktop Help system see Using ArcMap Usinc ArcGIS Spatiat ANALYST Contacting ESRI If you need to contact ESRI for technical support see the product registration and support card you received with ArcGIS Spatial Analyst or refer to Contacting Technical Support in the Getting more help section of the ArcGIS Desktop Help system You can also visit ESRI on the Web at www esri com and support esri com for more information on Spatial Analyst and ArcGIS ESRI education solutions ESRI provides educational opportunities related to geographic information science GIS applications and technology You can choose among instructor led courses Web based courses and self study workbooks to find education solutions that fit your learning style For more information go to www esri com education INTRODUCING ARCGIS SpatiAL ANALYST Quick start tutorial IN THIS CHAPTER Exercise 1 Displaying and exploring your data Exercise 2 Finding a site for a new school Exercise 3 Finding an alternative route to the new school site With Spatial Analyst you can easily perform spatial analysis on your data You can provide answers to simple spatial questions such as How steep is it at this location or What direction is this location facing or you can find answers to more complex spatial questions such as Where is the best location for a new facility or What is the least cost path from A to B
245. se z Set values to reclassify Old values Massip ruen een ee NoData NoData Unique Add Entry Delete Entries prreeesesssessssesesesesssessssesssssssssessssesssssesssessssssssesssssessseenesi E E R fe spatial_analysis mask Cancel Wutput raster 113 Using the mask dataset in 2 An alternative way to all subsequent analysis create an analysis mask i E che ae Click the Spatial Analyst ather than CEGUN EEE e analysis dropdown arrow and click General Extent Cell Size mask based on attributes you can Options ee 3 specify a spatial boundary as the p Working directory Je temp al mask Create a new feature dataset Click the General tab in ArcCatalog digitize the spatial Click the Analysis mask boundary in ArcMap th t l a a E E A dropdown arrow and click the these features to a raster to create created mask the mask All NoData cells areas outside of the original features in 4 Click OK the analysis mask will be set to the NoData value on all subsequent output raster datasets i Analysis mask landuse ri 3 Analysis Coordinate System Analysis output will be saved in the same coordinate system as the input or first raster input if there are multiple inputa Analysis output will be saved in the same coordinate sistem as the active data frame IY Display warning message if raster inputs have to be projected during analysis operatio
246. single cell regardless of the values of neighboring cells has a direct influence on the value of the output A per cell local function can be applied to a single raster dataset or to multiple raster datasets For a single dataset examples of per cell functions are the trigonometric functions for example sin or the exponential and logarithmic functions for example exponential or log UNDERSTANDING CELL BASED MODELING Examples of local functions that work on multiple raster datasets are functions that return the minimum maximum majority or minority value for all the values of the input raster datasets at each cell location Focal functions Focal or neighborhood functions produce an output raster dataset in which the output value at each location is a function of the input value at a location and the values of the cells in a specified neighborhood around that location A neighborhood configuration determines which cells surrounding the processing cell should be used in the calculation of each output value 93 Neighborhood functions can return the mean standard deviation sum or range of values within the immediate or extended neighborhood Zonal functions Zonal functions compute an output raster dataset where the output value for each location depends on the value of the cell at the location and the association that location has within a cartographic zone Zonal functions are similar to focal funct
247. ssigned a unique value in the output raster A field will be added ii Input polylines Output raster to the table of the output raster to hold the original string value iii from the features Point features to raster Polygon features to raster When you convert points cells are given the value of the points found within each cell Cells that do not contain a point are given When you convert polygons cells are given the value of the the value of NoData l fi h f each cell polygon found at the center of each ce If more than one point is found in a cell the cell is given the value of the first point it encounters when processing Using a smaller cell size during conversion will alleviate this Input polygons Output raster Polyline features to raster Input points Output raster When you convert polylines cells are given the value of the line that intersects each cell Cells that are not intersected by a line are given the value of NoData If more than one line is found in a cell the cell is given the value of the first line it encounters when processing Using a smaller cell size during conversion will alleviate this 186 Usinc ArcGIS Spatiat ANALYST Converting from raster to features Raster to polygons When you convert a raster representing polygonal features to polygon features the polygons are built from groups of contiguous cells having the same cell values Arcs are created from cell borders in the raster Cont
248. stance from recreation sites e Distance from existing schools Deriving slope Since the area 1s mountainous you need to find areas of relatively flat land to build on so you will take into consid eration the slope of the land 1 Click the Spatial Analyst dropdown arrow point to Surface Analysis and click Slope Spatial Analyst Spatial Analyst Layer elevation S h E Distance b Density interpolate to Raster b Surface Analysis Contour Cell Statistics Neighborhood Statistics Aspect Zonal Statistics Hillshade Viewshed Reclassity Eut Fill Raster Calculator Convert b Options 2 Click the Input surface dropdown arrow and click elevation QUICK START TUTORIAL 3 Type slope in the Output raster text box to permanently save your output slope dataset to the location of your working directory c spatial You will use this dataset again in Exercise 3 Note A copy of this slope dataset can be found in the location ArcGIS ArcTutor Spatial Results Ex2 Slope 4 Click OK Input surface Output measurement Degree Percent 2 factor Output cell size Output raster The output slope dataset will be added to your ArcMap session as a new layer High values red areas indicate steeper slopes 25 Deriving distance from recreation sites In this model it is preferable that the school be built near recreational f
249. surface Azimuth 315 Altitude lS Model shadows Z factor fo Output cell size a Output raster lt Temporay gt a Cancel 19 Click OK on the Hillshade dialog box The result of the Hillshade function is added to the map as a new layer All results from analysis functions are temporary If you want to make any result available for future use you should make the dataset permanent Right click the created hillshade layer and click Make Permanent Navigate to the folder on your local drive where you set up your working directory C Spatial 6 Type Hillshade in the Name text box 7 Click the Save as type dropdown arrow and click ESRI GRID Click Save Note A copy of Hillshade can be found in the location ArcGIS ArcTutor Spatial Results Ex 1 Hillshade on the drive where the tutorial data is installed 20 E amp Layers E schools El rec_sites E roads E Hills hygeine y Copy HX Remove Ld Open Attribute Table E landu Joins and Relates gt an A lt amp Zoom To Layer CIB a Zoom To Raster Resolution E F Set Data Source W Save s Layer File EM cevap Yi H Properties Look in Spatial Name JHillshade ESRI GRID Save as type Usinc ArcGIS SpatiaL ANALYST Applying transparency Main Menu File Edit View Insert Selection Tools Window Help You will now make the landuse layer transparent so the R Data View
250. t extent and with which values the actions are to take place Which grid dataset or raster layer values should be used in a zonal function which cells should be included in a focal neighborhood and what power to raise the input values in a power function are examples of parameters necessary for the completion of a Spatial Analyst action Constants and numbers are single value objects usually numerical that can be used in conjunction with an operator or function to achieve a desired result Some of the built in constants available in the Map Algebra syntax and language are Usinc ArcGIS Spatiac ANALYST PI 3 14 E 2 718 and DEG 57 296 degree radian All of the values of a grid dataset or raster layer can be multiplied or divided by any number or a number can be added to or subtracted from each value in a grid dataset or raster layer Numbers can be used in most operations on a grid dataset raster layer or constant When used in a function a number can also set a parameter such as a neighborhood width the maximum distance to which to calculate the Straight Line Euclidean distance or the test for a conditional statement Map Algebra syntax Operators can be placed between one or two input grid datasets raster layers numbers or constants inlayer1 inlayer2 In the above equation an output raster dataset is created storing the results from an expression adding the values for the raster layers inlayer1 an
251. t is known as the range Sample locations separated by distances closer than the range are spatially autocorrelated whereas locations farther apart than the range are not Y Si S Partial Sill 0 Distance The value at which the semivariogram model attains the range the value on the y axis is called the sill The partial sill is the sill minus the nugget see following section The nugget Theoretically at zero separation distance that is lag 0 the semivariogram value is zero However at an infinitely small separation distance the semivariogram often exhibits a nugget effect which is some value greater than zero If the semivariogram model intercepts the y axis at 2 then the nugget is 2 The nugget effect can be attributed to measurement errors or spatial sources of variation at distances smaller than the sampling interval or both Measurement error occurs because of the error 144 inherent in measuring devices Natural phenonema can vary spatially over a range of scales that is micro or macro scales Variation at micro scales smaller than the sampling distances will appear as part of the nugget effect Before collecting data it is important to gain some understanding of the scales of spatial variation that you are interested in Making a prediction The first task of uncovering the dependence autocorrelation in your data has been accomplished You have also finished with the first use of the
252. t least one of the input grid datasets or raster layers contains floating point values a floating point raster dataset will result There are exceptions to these rules The Boolean and combinatorial operators for example always output integer values no matter what the input types are Integer input Integer input Integer output Integer input Floating point input Floating point output Floating point input Floating point input Floating point output Floating point values are returned by all functions that perform Statistical calculations such as the mean and standard deviation for local focal and zonal functions Some global functions such APPENDIX A as the distance and interpolation functions return floating point results With other functions such as Select FocalSum and ZonalMin the input value type dictates the output value type The output type is specifically listed with each command in the ArcGIS Desktop Help system Map Algebra provides several functions for converting between floating point and integer raster types For additional information refer to the ArcGIS Desktop Help system discussions of Int Float Floor and Ceil NoData in operators and functions The general behavior of NoData in Spatial Analyst is as follows e For any operator or local function if any cell location of any of the input grid datasets or raster layers is assigned NoData the output for the cell location will be NoData
253. ta You will now create a histogram from the landuse layer and a hillshade from the Elevation layer to gain more of an understanding of the nature of the landscape Setting the analysis properties Before you use Spatial Analyst you should set up the analysis options stating the working directory the extent and the cell size for your analysis results These settings are specified in the Options dialog box Note Your display will not be zoomed in this much this is only to show the location of the recreation site to click 3 Click the Layers dropdown arrow on the Identify Results dialog box and click All layers 4 Click the Rec site again to identify the features in this particular location for all layers 5 Expand the tree of each layer to obtain the value for each layer in this location 6 Close the Identify Results dialog box QUICK START TUTORIAL 17 1 Click the Spatial Analyst dropdown arrow and click Options Spatial Analyst elevation __ __ H Options 2 Specify a working directory on your local drive in which to place your analysis results For example type c spatial to create a folder called spatial on your C drive for use throughout this tutorial 3 Click the Extent tab 4 Click the Analysis extent dropdown arrow and click Same as Layer landuse The extent of all subsequent resulting datasets will be the same as the landuse layer 18 moes Same as Lay
254. tability map Step 1 Stating the problem To solve a spatial problem you should first state the problem you are trying to solve What is your goal Start with a concept of the intended output of the study visualize the type of map you want to produce To understand the step process you will work through a sample problem for the remainder of this chapter Your problem is to find the best location for siting a new school The result you seek is a map showing potential sites ranked best to worst that could be suitable for building a new school This is called a ranked suitability map because it shows a relative range of values indicating how suitable each location is on the map taking into account the criteria you put into the model To help you model your spatial problem draw a Best site diagram of the steps involved for a new Start with the statement of the problem As you work through the problem you will expand the diagram to show objectives process models and necessary input datasets to use to reach your goal school MODELING SPATIAL PROBLEMS Step 2 Breaking down the problem Once the problem is stated break it down into smaller pieces until you know what steps are required to solve it These steps are objectives that you will solve When defining objectives consider how you will measure them How will you measure what is the best area for the new school In siting the school it is preferable to find a l
255. tasets raster layers shapefiles coverages tables constants and numbers All input grid datasets raster layers shapefiles and tables must exist prior to processing the expression When entering a grid dataset shapefile coverage or table into an expression the name can be used directly if it resides in the current working directory set in the Options dialog box as in the following example cos inlayer1 The full pathname to the grid dataset shapefile coverage or table must be identified if it is not in the current workspace and is not a raster layer added to your ArcMap session cos E mydirectory ingrid1 If the input is a raster layer in the Layers list in the Raster Calculator the name of the layer needs to be in brackets cos inlayer1 Map Algebra results The result from a Map Algebra expression can be a raster a shapefile a table or a file stored on disk such as an ASCII file The output dataset name does not need to be specified as a temporary dataset can be created Spatial Analyst will name the temporary output dataset calc followed by a number that is 194 calcl The number following calc will increase incrementally to the next unique value for the name of each new output dataset Any integer raster dataset returned as the result of a function or operator will usually have an associated table a Value Attribute Table or VAT with two default items Value and Count Some operators r
256. te the destination dataset 1f necessary In this exercise the Destination is a point at a road junction Perform shortest path using the Distance and Direction datasets created from the cost weighted function QUICK START TUTORIAL Step 1 Create Source and Cost Datasets Source Step 2 Cost Weighted Distance Destination Distance Direction a Step 3 Shortest Path 39 Step 1 Creating the source and cost datasets To find the best route to the potential school site you will first need to create the Source dataset the school site from the suitability map and a Cost dataset and use these as inputs into the cost weighted function Creating the source dataset If you want to know how to create the Source dataset follow the next 29 steps Alternatively click the Add Data button and navigate to the location where you installed the tutorial data ArcGIS ArcTutor Spatial Click Roads then click Add Then click the Add Data button again and navigate to ArcGIS ArcTutor Spatial Results Ex3 Click School site then click Add and skip the next 29 steps You will first create an empty shapefile in ArcCatalog then digitize the location of the site using the editng tools in ArcMap 1 Click the ArcCatalog button on the Standard toolbar Dia SB 2 BX Hh frro3is 2 a2 2 Navigate in the Catalog tree to the folder on your local drive where you set up your working directory c spatial 3
257. tem is identified for the input the values in the input field in the INFO table will be mapped to the VALUE item in the grid s VAT The input field name in the INFO remap table does not have to be VALUE for this mapping to occur If a range exists in the INFO remap table that is beyond the values in the VALUE field of the VAT the range will be ignored The values associated with the specified VAT item are mapped to the corresponding cell locations The INFO remap table item is then used to reclassify the cell values The pages that follow give a graphical representation of the use of remap tables in the Slice function 212 Usinc ArcGIS Spatiat ANALYST INLAYER1 OUTGRID Lal VALUE NODATA INFO table VALUE 0 1 2 4 slice inraster1 table c data remap_table value link APPENDIX C 213 INLAYER1 OUTGRID o VALUE NODATA INFO table Table Remap slice inlayer1 ph table c data Remap_Table ph link 214 Usinc ArcGIS Spatiat ANALYST Reclass and remap tables The Reclass function is designed for nominal data whereas the Slice function is designed for ordinal data The principal difference is the behavior of the Reclass function on input values that are not explicitly listed as entries in the remap table Rather than assign such input values an output based on an inferred range Reclass assigns them either an output of NoData or an output value identical t
258. ter datasets in the overlapping areas These functions are used when several raster datasets come from a tiled continuous data source such as 98 adjacent satellite scenes neighboring towns or states that are separately managed Some of the geometric transformation functions are available on the Georeferencing toolbar in ArcMap and all are available through Map Algebra which is accessed through the Raster Calculator Generalization Sometimes a raster dataset contains data that is erroneous or irrelevant to the analysis at hand or is more detailed than you need For instance if a raster dataset was derived from the classification of a satellite image it may contain many small and isolated areas that are misclassified The generalization functions assist with identifying such areas and automating the assignment of more reliable values to the cells that make up the areas The generalization functions are available through RasterGeneralizeOp or through Map Algebra via the Raster Calculator These tools provide capabilities for aggregation edge smoothing intelligent noise removal and more Usinc ArcGIS Spatiat ANALYST The base classification from a satellite image Use Nibble to remove the single misclassified cells in the classified image This function will remove small areas of misclassified cells and assign them the most common value in their immediate neighborhood For example you may want to get rid o
259. terpolated cell You can also specify a maximum distance in map units that the search radius cannot exceed If the radius for a particular neighborhood reaches the maximum distance before obtaining the specified number of points the prediction for that location will be performed on the number of measured points within the maximum distance Barrier A barrier is a polyline dataset used as a break that limits the search for input sample points A polyline can represent a cliff ridge or some other interruption in a landscape Only those input sample points on the same side of the barrier as the current processing cell will be considered Usinc ArcGIS Spatiat ANALYST Inverse Distance Weighted interpolation IDW has two options a Fixed search radius type and a Variable search radius type With a Fixed radius the radius of the circle used to find input points is the same for each interpolated cell By specifying a minimum count you can ensure that within the fixed radius at least a minimum number of input points will be used in the calculation of each interpolated cell A higher Power puts more emphasis on the nearest points creating a surface that has more detail but is less smooth A lower Power gives more influence to surrounding points that are farther away creating a smoother surface Use a barrier to limit the search for input sample points to the side of the barrier on which the interpolated cell sits such
260. tes and you can tell from the elevation dataset where the higher elevations are The landuse dataset tells you what types of landuse are in the area and where they are located in relation to the other datasets See Exercise 1 of the Quick start tutorial for how to use some of the tools of ArcMap and Spatial Analyst to explore your data Identify features to get information from all layers Identify Results Layers lt a layers gt 7 El rec_sites Location 484848 701952 218993 362001 E Golden Eagle Resort l roads i E PALISADES LN elevation 769 B landuse eed MAP io SITE_NAME Golden Eagle Resort B Hillshade of elevation FIPS CODE 15040 E 221 ALT_NAME S_ADDRESS Mountain Road S_TOWN Stowe YT 05672 5 PHONE 802 253 4811 PERIMETER MODELING SPATIAL PROBLEMS Examine the attribute table for each layer E Attributes of landuse _ Op x _ ObiectiD Value Count Landuse Pt 294 Brush transitional BNF water m8 3 8 Barren land mA aT 38034 Bult 8 E Agricul ee A teat welds Record IET 1 gt ral Show f All Selected Records Create and examine histograms from each layer w Histogram of landuse Oy x Histogram of landuse Field Landuse esOO000 BOOOOO 400000 200000 0 Calculate hillshade to examine the relief 63 Step 4 Performing analysis You have decided on your objectives the elements and their interactions the process mode
261. tes within each dataset that are more suitable for locating the school e Reclassify slope e Reclassify Distance to recreation sites e Reclassify Distance to schools e Reclassify landuse Reclassifying slope It is preferable that the new school site be located on relatively flat ground You will reclassify the Slope layer giving a value of 10 to the most suitable slopes those with the lowest angle of slope and to the least suitable slopes those with the steepest angle of slope 1 Click the Spatial Analyst dropdown arrow and click Reclassify Click the Input raster dropdown arrow and click Slope Click Classify NO U9 28 Spatial Analyst Fa Spatial Analyst Layer elevation d 2 ih Distance gt Density Interpolate to Raster k Surface Analysis gt Cell Statistics Neighborhood Statistics Zonal Statistics Raster Calculator Convert gt Options Reclassify Input raster Slope Reclass field Value z Set values to reclassify Unique Add Entry Delete Enties J Change missing values to NoData Output raster lt Temporary gt men Us nG ArcGIS Spatiat ANALYST 4 Click the Method dropdown arrow and click Equal 7 Interval Reclassify 71x 5 Click the Classes dropdown arrow and click 10 rea rant Slope 7 5 6 Click OK Reclass field Value Set values to reclass
262. that performs spatial analysis All spatial operations on the Spatial Analyst user interface are classified as spatial functions for example distance slope or density spatial reference Specifies the coordinate system of the dataset spline An interpolation method where cell values are estimated using a mathematical function that minimizes overall surface curvature resulting in a smooth surface that passes exactly through the input points straight line allocation Identifies which cells belong to which source based on closest proximity in a straight line straight line direction Identifies the azimuth direction from each cell to the nearest source Usinc ArcGIS Spatiat ANALYST straight line distance Calculates the distance in a straight line from every cell to the nearest source suitability model A model that aids in finding optimum locations A suitability model might identify suitable locations for a new facility or a road symbol A graphic representation of an individual feature or class of features that helps identify it and distinguish it from other features symbology The criteria used to determine symbols for the features in a layer A characteristic of a feature may influence the size color and shape of the symbol used table of contents Lists all the data frames and layers on the map and shows what the features in each layer represent target The setting of the Target Layer dro
263. ther locations with little influence Not only is there less relationship with farther locations it is possible that the farther locations may have a negative influence if they are located in an area much different than the prediction location Another reason to use search neighborhoods is for computational speed The smaller the search neighborhood the faster the predictions can be made As a result it is common practice to limit the number of points that are used when making a prediction by specifying a search neighborhood The specified shape of the neighborhood restricts how far and where to look for the measured values to be used in each prediction Other neighborhood parameters restrict the locations that will be used within that shape such as defining the maximum and minimum number of measured points to use within the neighborhood You can determine the weights for the measured locations using the configuration of the valid points within the specified neighborhood around the prediction location in conjunction with the model fit to the semivariogram From the weights and the values a prediction can be made for the unknown value at the prediction location Spatial Analyst has two neighborhood types fixed and variable Fixed search radius A fixed search radius requires a distance and a minimum number of points The distance dictates the radius of the circle of the neighborhood in map units The distance of the radius is co
264. tics Neighborhood Statistics onal Statistics Reclassify Raster Calculator Convert Options Input surace elevation Observer points view point T Use Earth curvature Contour Slope Aspect Hillshade Cut Fill Z factor Output cell size Output raster lt Temporary gt 161 Cut Fill What is Cut Fill the Pinochet Natioal Forest Filled areas are displayed in green cut areas in red and areas where the surface material did not Cut Fill summarizes the areas and volumes of change between two surfaces It identifies the areas and volume of the surface that have been modified by the addition or removal of surface material By taking two surfaces of a given area from two different time periods the Cut Fill function will produce a raster displaying regions of surface material addition surface material removal and areas where the surface has not changed over the time period Negative volume values indicate areas that have been filled positive volume values indicate regions that have been cut Taking river morphology as an example to track the amount and location of erosion and deposition in a river valley a series of cross sections need to be taken through the valley and surveyed on a regular basis to identify regions of sediment erosion and deposition Erosion Deposition The Cut Fill function peforms the surveying for you identify
265. tistics Neighborhood Statistics onal Statistics Raster Calculator Convert b Options Reclassify Input raster slope Reclass field Value K Set values to reclassify Old values Mew values 2 D 7 Be r 4 dogada aT E Fee AAE EEE mmm ZABIT EEE J1 J422 A Add Entry SNe ee IJAE T 74 aaa am Delete Entries Load Save Change missing values to NdData Output raster Temporary 6 Cancel Us nG ArcGIS Spatiat ANALYST Changing the classification of input ranges Changing input ranges to be unique values If your input values are split into ranges and you want them to be unique values click Unique See Standard classification schemes in Using ArcMap for information on classification schemes PERFORMING SPATIAL ANALYSIS 1 Click the Spatial Analyst dropdown arrow and click Reclassify Click the Input raster dropdown arrow and click the raster with values you wish to reclassify Click the Reclass field dropdown arrow and click the field you wish to use Click the Classify button Click the Method dropdown arrow and choose a classifi cation method to use to reclassify your input data Click the Classes dropdown arrow and choose the number of classes into which your input data will be split Click OK Modify the New values for your Output raster if appropri ate Specify a name for the Output raster or leave the default to creat
266. to further explore the data and its relationships 64 Creating suitability scales As is the case with this example many scales are synthetic These are often a ranked measure of suitability or preference from best to worst It is based on something you can measure such as distance to schools but in the end it is a subjective measure of how suitable a certain distance is from a school for locating another school There are natural scales that are commonly associated with some objectives Cost is a good example but needs to be defined in sufficient detail In a study of building suitability an objective of low real estate cost would be measured on a scale of dollars Be sure to adequately define the scale For something as well understood as dollars there are other variables such as whether it s U S dollars Australian dollars or an exchange rate between monies Many scales are not linear relationships although they are often presented that way to save time and money or because all options were not considered For example if assigning a scale to travel distance traveling 1 5 or 10 kilometers would not be ranked as a suitability of 10 five and one if you were walking Some people may think walking 5 kilometers is only two times as bad as kilometer while others may think it s 10 times as bad When you construct a suitability scale work with experts to find the best and worst of a scenario and as many intermediate
267. to locate the new school away from existing schools to spread out their locations through the town 1 Click the Spatial Analyst dropdown arrow point to Distance and click Straight Line 2 Click the Distance to dropdown arrow and click schools Leave the defaults for all other options Click OK U9 Straight Line Distance to Maximum distance Output cell size 30 J Create direction kT empora w J Create allocation lt Temporary gt to Output raster lt Temporay gt 5 Cancel QUICK START TUTORIAL The output distance to schools dataset will be added to your ArcMap session as a new layer 4 Check the box next to the schools layer to turn it back on and uncheck the box next to rec_ sites to turn this layer off so you only see the locations of the schools and the distance to them Note A copy of this distance to schools dataset can be found in the location ArcGIS ArcTutor Spatial Results Ex2 schD 27 Step 3 Reclassifying datasets You now have the required datasets to find the best location for the new school The next step is to combine them to find out where the potential locations can be found In order to combine the datasets they must first be set to a common scale That common scale is how suitable a particular location each cell is for building a new school You will reclassify each dataset to a common scale within the range 1 10 giving higher values to attribu
268. tribute for each contour polyline Contours are polylines that connect points of equal value such as elevation temperature precipitation pollution or atmospheric pressure The distribution of the polylines shows how values FID Shape ID CONTOUR l change across a surface Where there is little change in a value O Poine ft Sd 800 the polylines are spaced farther apart Where the values rise or ype oo am i e 2 Polline IHE 3o i fall rapidly the polylines are closer together siPobine 4 fam 4 Poline 51200 Why create contours O 5 Powline 6 30 efai p p By following the polyline of a particular contour you can identify M7 e 8 E 8fPopines 3 0 which locations have the same value Contours are also a useful E SlPobline 10 m surface representation because they allow you to simultaneously b visualize flat and steep areas distance between contours and Record 14 1 jr Show ai Selected F ridges and valleys converging and diverging polylines The example below shows an input elevation dataset and the output contour dataset The areas where the contours are closer together indicate the steeper locations They correspond with the areas of higher elevation in white on the input elevation dataset Input elevation dataset Output contour dataset PERFORMING SPATIAL ANALYSIS 151 Creating contours The Contour function allows you to create contours for an entire dataset
269. ue which must be aggregated or prioritized and each cell given a single value thereby decreasing data resolution The optimum cell size to capture the appropriate detail varies from study to study The smaller the cells the greater the resolution and accuracy but coding database storage and processing speed for analysis are more costly Polygons Raster from polygons Usinc ArcGIS SpatiaL ANALYST Raster encoding The process of creating a raster dataset is like draping a fishnet containing square cells over the study area A code is assigned to each cell according to the feature that is at the center of the cell The code or value of a cell is a numeric value that corresponds to an attribute type Numeric values speed processing and allow for data compression Each cell represents a specified portion of the world A cell can be any size you define there are no practical limits The main consideration is that the size be appropriate for the analysis For example you would not normally use a one kilometer cell size when studying a field mouse habitat If the input data is polygonal then each cell on the resulting raster dataset from the conversion process is assigned the value of the feature that passes through the center of the cell It is only guaranteed that the feature that the value represents is present at the center of the cell For continuous data see Discrete and continuous data earlier in this chapter thi
270. umulated least costly way of getting from the cell colored dark red to the school is 10 5 Two additional outputs direction and allocation rasters can be created from the Cost Weighted Distance function These are explained on the following pages Usina ArcGIS Spatiat ANALYST Direction The cost weighted distance raster tells you the least accumulated cost of getting from each cell to the nearest source but it doesn t tell you which way to go to get there The direction raster provides a road map identifying the route to take from any cell along the least cost path back to the nearest source Cost Weighted Direction Direction Coding The algorithm for computing the direction raster assigns a code to each cell that identifies which one of its neighboring cells is on the least cost path back to the nearest source In the direction coding diagram above 0 represents every cell in the cost weighted distance raster Each cell is assigned a value representing the direction of the nearest cheapest cell on the route of the least costly path to the nearest source For example in the graphic above the cheapest way to get from the cell with a value of 10 5 is to go diagonally through the cell with a value of 5 7 to the source the school site The direction algorithm assigns a value of 4 to the cell with a value of 10 5 and 4 to the cell with a value of 5 7 because this is the direction of the least cost path back to t
271. unctions You can access Map Algebra through the Raster Calculator dialog box Map Algebra expressions can be constructed using the buttons of the Raster Calculator or they can be typed into the expression box The expressions will be processed when you click Evaluate Map Algebra is the analysis language for Spatial Analyst It is a simple syntax that is similar to any algebra Output data will result from some manipulation of the input The input can be as simple as a single grid dataset raster layer or shapefile and the manipulation can be calculating the sine of each of the location s values or there can be a series of input grid datasets or raster layers that the manipulation is applied to such as when adding three grid datasets or raster layers together Not only does the algebra allow access to additional functions not available in the user interface but it also allows you to build more complex expressions and process them as a single command For instance you can calculate the sine of an input grid dataset or raster layer and add that to two other input grid datasets or raster layers Like all languages Map Algebra is composed of a series of rules By understanding these basic rules you will be able to use Spatial Analyst in new ways This appendix outlines the syntax of Map Algebra 191 Map Algebra language components The major strength of Spatial Analyst is its analytical capabilities Spatial Analyst through the Map Alge
272. ur prediction more than those measured locations farther away you will weight the closer measured points more than those farther away Hence the name IDW as the distance increases you will inversely weight the values This process continues for each location in the study site Polynomial trend surface is conceptually similar to taking a piece of paper and trying to pass it through measured points that are raised to the height of their values That paper is fitted so that overall it fits best to all the points 96 Spline is conceptually like taking a rubber membrane and once the measured points are raised to the height of their values trying to fit it through the points the best you can The criterion imposed on fitting this membrane is that it must pass through the measured points Kriging is a statistical method that quantifies the correlation of the measured points through variography When making a prediction for an unknown location kriging weights the nearby measured points by their configuration around the prediction location and uses the fitted model from variography to determine a value For additional information on kriging see Chapter 7 Performing spatial analysis ArcGIS Geostatistical Analyst provides additional tools for more advanced surface generation Surface analysis The premise behind the surface analysis functions is that additional information can be derived by producing new data and identify
273. urements PERFORMING SPATIAL ANALYSIS The assumption that makes interpolation a viable option is that spatially distributed objects are spatially correlated in other words things that are close together tend to have similar characteristics For instance if it is raining on one side of the street you can predict with a high level of confidence that it is also raining on the other side of the street You would be less sure if it was raining across town and less confident still about the state of the weather in the next county Using this analogy it is easy to see that the values of points close to sampled points are more likely to be similar than those that are further apart This is the basis of interpolation A typical use for point interpolation is to create an elevation surface from a set of sample measurements Each symbol in the point layer represents a location where the elevation has been measured By interpolating the values between these input points will be predicted O OERE ENERO _ amp Details on the interpolators The available interpolation methods are Inverse Distance Weighted Spline and Kriging They make certain assumptions about how to determine the best estimated values Based on the phenomena the values represent and on how the sample points are distributed different interpolators will produce better estimates relative to the actual values No matter which interpolator is selected h
274. use i BEEBE BOOOSOCE EE 52 Zooming in on the area 1 Click the Zoom In tool on the Tools toolbar 2 Click and drag a rectangle around the location of the new road to zoom in on this area the area to zoom to is highlighted in red on the map below Usina ArcGIS Spatiat ANALYST Prop 2rties Geheral Source Selection Display Symbology Fields Defihition Query Labels Joins amp Relates Label Features Method Label all the features the same way All features will be labeled using the options specified m Test String Label Field STREET_NAM Expression m Text Symbol AaBbYyZz Symbol m Other Options Pre defined Label Style Label Placement Options Scale Range Label Styles Cancel Apply Labeling the roads Label the road network to be able to identify which existing roads may be of use in constructing the new road The road names are labeled on the map 1 Right click Roads in the table of contents and click Properties 2 Click the Labels tab Check Label Features 4 Click the Label Field dropdown arrow and click STREET NAM 5 Click OK U9 QUICK START TUTORIAL 6 Click the File menu and click Save If this is the first time you are saving the map document navigate to the location where you set up your working directory c spatial specify a filename for the map document Spatial Tutorial and
275. ut raster Exp Inlayer1 Arithmetic functions There are six Arithmetic functions The Abs function takes the absolute value of the values in an input raster Two rounding functions Ceil and Floor convert decimal point values into whole numbers Int and Float convert values from and to integer and floating point values The IsNull function returns 1 if the values on the input raster are NoData and 0 if they are not Trigonometric functions The Trigonometric functions perform various trigonometric calculations on the values in an input raster The sine Sin cosine Cos tangent Tan inverse sine PERFORMING SPATIAL ANALYSIS Asin inverse cosine Acos and inverse tangent Atan functions exist Power functions Three Power functions are available The square root Sqrt of the values on the input raster can be calculated the square Sqr determined or the values raised to a power Pow Map Algebra syntax Map Algebra is the analysis language for Spatial Analyst An output will result from some manipulation of the input Type Map Algebra syntax to access a variety of functions Basic rules and limitations e Inputs can be grid datasets raster layers shapefiles coverages tables constants or numbers e Outputs can be grid datasets shapefiles tables and files stored on disk such as ASCII files e Multiline expressions are supported e The raster layer name if the raster layer is in the table of contents
276. vigate to the folder on your local drive where you set up your working directory c spatial 3 Click Hillshade and click Add Note A copy of this hillshade dataset can be found in the location ArcGIS ArcTutor Spatial Results Ex 1 Hillshade 4 Click the Add Data button on the Standard toolbar 5 Navigate to the folder on your local drive where you installed the tutorial data the default installation path is ArcGIS ArcTutor Spatial 6 Click landuse and click Add Applying transparency 7 If the Effects toolbar is not already present click View on the Main menu point to Toolbars and click Effects 8 Click the Layer dropdown arrow on the Effects toolbar and click landuse 9 Click the Adjust Transparency button and move the scroll bar up to a transparency of 30 percent QUICK START TUTORIAL Layer landuse 51 Changing the default field for landuse You will now change the value field for the landuse layer so you can more easily distinguish each landuse type 1 Right click Landuse in the table of contents and click Properties 2 Click the Symbology tab 3 Click the Value Field dropdown arrow and click landuse 4 Click OK Change the color of the symbols in the table of contents to more appropriate colors for each type of landuse 5 Right click the symbols representing landuse types in the table of contents and pick an appropriate color for each one S landuse Land
277. ving information 4 Destination defined 220 described 131 Discrete data and raster encoding 85 attribute values 88 103 described 82 Discrete raster defined 220 Distance mapping allocation assign proximity calculating 123 125 Usinc ArcGIS Spatiat ANALYST Distance mapping continued allocation assign proximity continued described 122 124 129 130 overview 120 cost weighted calculating 130 described 126 example 126 overview 120 straight line Euclidean calculating 123 described 121 overview 120 E Euclidean distance defined 220 See Straight line distance described Extent analysis defined 220 described 104 109 setting 116 F Feature defined 220 Feature data converting 85 86 186 188 defined 220 Field defined 220 Find Distance See Straight line distance described Flip 98 Floating point data as attributes 88 Focal functions defined 220 described 92 INDEX Format defined 220 Function defined 220 G Generalization functions described 98 Geographic information systems GIS defined 220 Geometric transformation and analysis 106 described 78 functions 98 Georeferencing described 78 GIS Geographic information systems defined 220 Global functions defined 220 described 93 Grid a raster dataset 74 defined 220 H Hillshade calculating 158 defined 220 described 96 157 displaying 159 Histogram defined 220 Hydrologic analysis 97 Identify features 63 IDW Inverse
278. way from existing schools so you will give higher values to locations farther away as these locations are most desirable As the default gives high New values more suitable to high Old values locations farther away from existing schools you do not need to change any values this time Click OK Reclassify i 1 xi Input raster Distance to schools 7 Reclass field Value x Set values to reclassify Add Entry Delete Enties I Change missing values to NoData Output raster lt Temporary gt OK Cancel The output reclassified distance to schools dataset will be added to your ArcMap session as a new layer It shows locations that are more suitable for locating another school Higher values indicate more suitable locations QUICK START TUTORIAL Note A copy of this reclassified distance from schools dataset can be found in the location ArcGIS ArcTutor Spatial Results Ex2 schR 33 Reclassifying landuse At a town planners meeting it was decided that certain landuse types were better for building on than others taking into consideration the costs involved in building on different landuse types You will now reclassify landuse A lower value indicates that a particular landuse type is less suitable for building on Water and Wetlands will be given NoData as they cannot be built on and should be excluded 1 Click the Spatial Analyst dropdown arrow and click Reclassify
279. ween input rasters then sent to the corresponding cell The Cell Statistics function is a local function where the value at location on the output raster each location on the output raster is a function of the input values at each location Majority determines the value that occurs most often on a cell ne o by cell basis between inputs By computing cell statistics you can compute a statistic for each cell in an output raster that is based on the values of each cell of Maximum determines the maximum value on a cell by cell basis multiple input rasters between inputs Mean computes the mean of the values on a cell by cell basis Why calculate cell statistics between inputs Calculate cell statistics when you want to calculate a statistic Median computes the median of the values on a cell by cell between multiple rasters for instance to analyze a certain basis between inputs phenomenon over time such as the average crop yield over a i Minimum determines the minimum value on a cell by cell basis 10 year period or the range of temperatures between years between inputs In the graphic below the variety of landuse types between cells of rasters from different years is calculated to identify the areas where the variety is greater than one areas shaded gray This Minority determines the value that occurs least often on a cell by cell basis between inputs indicates the areas that have changed landuse type over th
280. wer processing speeds may sometimes be essential to your analysis The default cell size 1s the smaller of the width or height of the input features extent divided by 250 unless you specified a cell size n the Options dialog box Tip Setting analysis options Click Options on the Spatial Analyst toolbar to set up your working directory extent and cell size for your analysis results 188 Converting feature data to raster 1 Click the Spatial Analyst dropdown arrow point to Convert and click Features to Raster Click the Input features dropdown arrow and click the feature you want to convert to a raster Click the Field dropdown arrow and click the field you want to copy to the Output raster Optionally type an Output cell size Specify a name for the Output raster or leave the default to create a temporary dataset in your working directory Click OK Spatial Analyst Spatial Analyst z Layer Jlanduse SS ih d Distance Density interpolate to Raster p Surace Analysis lr Cell Statistics Neighborhood Statistics Zonal Statistics Reclassify Raster Calculator Convert Options Features to Raster Input features Field Output cell size Output raster TSC Features to Rasher Raster to Features Usinc ArcGIS Spatiat ANALYST Converting raster data to features Browsing for files or directories I
281. where nonzero values are present in the cells of one or both input rasters Xor Finds where nonzero values are present in the cells of one input raster or another input raster but not both Not Finds where nonzero values are not present in the cells of a single input raster Relational operators Relational operators evaluate specific relational conditions Ifa condition is TRUE the output is assigned 1 if a condition is FALSE the output is assigned 0 Relational operators gt lt lt gt gt lt For example the result of Inlayer1 lt gt 3 where values in Inlayer1 are not equal to 3 might give an output raster showing all other landuses except forest if forest was represented by a value of 3 Output raster Inlayer1 lt gt 3 Input raster Inlayer1 Usinc ArcGIS Spatiat ANALYST Mathematical functions Mathematical functions are applied to the values in a single input raster There are four groups of mathematical functions Logarithmic Arithmetic Trigonometric and Powers Logarithmic functions The Logarithmic functions perform exponential and logarithmic calculations on input rasters and numbers The base e Exp base 10 Exp10 and base 2 Exp2 exponential capabilities and the natural Log base 10 Log10 and base 2 Log2 logarithmic capabilities are available For example the result of Exp Inlayer1 is shown below 20 10 20 10 Input raster Inlayer1 Outp
282. with establishing the spatial relationships the GIS representation model is also able to model the attributes of the objects who owns each building Representation models are sometimes referred to as data models and are considered descriptive models Process models Process models attempt to describe the interaction of the objects that are modeled in the representation model The relationships are modeled using spatial analysis tools Since there are many different types of interactions between objects ArcGIS and Spatial Analyst provide a large suite of tools to describe interactions Process modeling is sometimes referred to as cartographic modeling Process models can be used to describe processes but they are often used to predict what will happen if some action occurs Each Spatial Analyst operation and function can be considered a process model Some process models are simple while others are more complex Even more complexity can be added by including logic combining multiple process models and using the Spatial Analyst object model and Microsoft Visual Basic Usinc ArcGIS Spatiat ANALYST One of the most basic Spatial Analyst operations is adding two rasters together Complexity can be added through logic MODELING SPATIAL PROBLEMS And even more complexity is added by combining several functions and logic A process model should be as simple as possible to capture the necessary reality to solve y
283. wo step process 1 variograms and covariance functions are created to estimate the statistical dependence called spatial autocorrelation values which depends on the model of autocorrelation fitting a model and 2 prediction of unknown values are made It is because of these two distinct tasks that it has been said that Kriging uses the data twice the first time to estimate the spatial autocorrelation of the data and the second time to make the predictions Variography Fitting a model or spatial modeling is also known as structural analysis or variography In spatial modeling of the structure of the measured points we begin with a graph of the empirical semivariogram computed as Semivariogram distance 0 5 average value at location i value at location for all pairs of locations separated by distance A4 The formula involves calculating the difference squared between the values of the paired locations The diagram that follows shows the pairing of one point the red point with all other measured locations This process continues for each measured point 141 The pairing of one point the red point with all other measured locations Often each pair of locations has a unique distance and there are often many pairs of points To plot all pairs quickly becomes unmanageable Instead of plotting each pair the pairs are grouped into ag bins For example compute the average semivaria
284. y the two temporary resultant rasters are added together the result of inlayer1 the result of inlayer2 div inlayer3 Operators with the same precedence level are processed from left to right inlayer1 inlayer2 div inlayer3 To process the above expression the Spatial Analyst interpreter will first multiply inlayer1 with inlayer2 then divide the result by inlayer3 The left to right rule applies to all operators except for shift operators lt lt and gt gt with precedence level 7 and unary operators unary and with precedence level 12 These two operators have a right to left association A AA inlayer1 First the bitwise complement of inlayer1 is calculated then the Boolean complement is taken from the results of the bitwise complement and finally the unary minus is determined from the previous resultant raster AppPENDIxX B 205 Appendix IN THIS APPENDIX e About remap tables e Slice and remap tables e Reclass and remap tables e Slice versus Reclass relative to remap tables The Reclassify function in the Spatial Analyst user interface enables you to quickly and easily reclassify your data and save the reclassification table if you wish for later use The format of this table is such that it allows the mapping of NoData to a value mapping a value range or string to NoData or Mapping strings to new values As an alternative remap tables INFO and ASCII ca
285. ze of the cell For example if the linear features that are being converted represent roads and if the size of the cells is a kilometer the road will be a kilometer wide on the output raster dataset Obviously a road is not a kilometer wide thus you should select a cell size that is appropriate to the linear feature that you are representing If the cell size is a meter then the road would only be a meter wide For additional information and understanding of the issues of the raster encoding of the different feature types refer to the next section Representing features in a raster dataset 85 Representing features in a raster dataset When converting points polylines and polygons to a raster you should be aware of how the raster dataset will represent the features Point data A point feature is any object at a given resolution that can be identified as being without area Although a well a telephone pole or the location of an endangered plant are all features that can be rendered as points at some resolutions at other resolutions they do in fact have area For example a telephone pole viewed from an airplane two kilometers high will be represented by only a point but the same pole viewed from an airplane 25 meters high will be represented by a circle Point features Raster point features Point features are represented by the smallest unit of a raster a cell It is important to remember that
286. zed by applying a percentage influence to each dataset divided by 100 when performing suitability modeling This process normalizes the values in the output suitability map to those of the input datasets nugget A parameter of a covariance or semivariogram model that represents independent error measurement error and or microscale variation at spatial scales that are too fine to detect The nugget effect is seen as a discontinuity at the origin of either the covariance or semivariogram model operator A mathematical symbol that performs an operation Operators are provided in the Raster Calculator to enable analysis to be performed within and between multiple rasters For a list of available operators see Appendix B path The location of a file or directory on a disk A path is always specific to the computer operating system permanent dataset A raster dataset permanently stored on disk All output raster results from Spatial Analyst are temporary unless you specify a location on disk and a filename in a function dialog box or you make the temporary dataset permanent or you save the map document In these three cases temporary results will become permanent datasets on disk See make permanent pixel See raster cell Usinc ArcGIS Spatiat ANALYST power functions Apply a Power function to the values in a single input raster Three Power functions are available Sqrt Sqr or Pow projected coordinate system

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