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Land Facet Corridor Designer - GIS Tools and Information for

1. 90 of canyon cells 90 of ridge cells 90 of slope cells _ c the number of clusters 2 Classify cells within each topographic position according to continuous variables into c classes using fuzzy c means cluster analysis Perform gt 25 iterations computing validity mdices for each iteration Identify optimal number of clusters within each topographic position from validity indices If gt 1 partition exists for identify the one with the best validity indices Compute fuzzy membership values Compute confusion index from to the k optimal clusters for all cells fuzzy membership values in the planning area within the respective topographic position a Se ee Se eB ee Se SE Se ee S S M eS Se ee ee ee ee ee ee Se Be ee ee ee 2 eS Se Se Se S S M eS ee S N S S M ee ee EE SE Some example land facets a High elevation steep hot slopes Low elevation gentle warm slopes Low elevation High elevation gentle canyons steep ridges EE eS a as ee a a a SS Se ea SS Se Sa SS ee a SS eae eee SS SS ee aa a Te T SS a T I m s Figure 2 Sequence of operations used to define land facets The procedures in the first 3 lines calculation of topographic and soil variables are conducted in ArcGIS which exports the values of each variable for each pixel These values are processed by the statistical package R which carry out all the other procedures in thi
2. 3 Ifimporting the table from a Comma Delimited Text file csv then the field name should occupy the first row 4 This tool will ignore any OID fields that may be in the table If the table has an OID field in addition to the field of Mean values then the tool will still recognize this table as a valid Mean Vector table 5 The following text is an example of a valid Mean Vector table in Comma Delimited Text format csv Means MW SES SPS P OV OLOLS Oe Formatting Rules for the Covariance Matrix Table 2 Must have only numeric fields in the table 3 The number of rows in the table must be exactly the same as the number of attribute fields Each field represents one variable as does each row 4 There are no restrictions on the field names 5 If importing the table from a Comma Delimited Text file csv then the field names should occupy the first row 6 This tool will ignore any OID fields that may be in the table If the table has an OID field in addition to the Variable Covariance fields then the tool will still recognize this table as a potential Covariance Matrix table 7 The following text is an example of a valid Covariance Matrix table in Comma Delimited Text format csv Elevation Slope SA eS NG A AA EUS a ok cee HOO eee io 2 Last modified 20 ul 10 MANUAL Land Facet Corridor Designer Formatting Rules for Both Tables 62 1 Both tables must have the same number of rows If they
3. Here the argument k specifies that a 4 cluster solution was optimal Since only one optimal partition was found for 4 clusters niter the iteration with the optimal partition does not need to be specified If there were two or more optimal partitions at 4 clusters you would select the partition with the highest value in the bottom row the lowest value in the middle row and the best elbow in the top row 12 Use the Land Facet Clusters from R tool in the Land Facet CorridorDesigner extension to ArcGIS to import the results from these R functions into ArcGIS These results are contained in a bin_width csv the multidimensional half width of the bins used in the kernel density estimation b grid csv the location of bins containing non outlier cells c centroids csv the location of cluster centroids for the optimal fuzzy c partition d params csv the mean and standard deviation of the attributes in the data set e psi csv the value of psi used in the function LF cluster Recall that all of these files were outputted to the working directory Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 94 About the Land Facet Evaluation Tools and Manual IRN REL bof Fp ty ass i f About Land Facet Corridor ron nittoduction Least cost modeling for focal species is the most widely used method for 3 designing conservation corridors and linkages However these linkages E have been based on today
4. Output Raster Format ESRI GRID D arcGilS_stuff consultation brost_climate_change Dutput D ensity 17 pe Cancel Manual A Output Raster Dataset Hame The Select Categorical Raster listbox will contain a list of all rasters that have attribute tables Chose a raster then select the appropriate raster attribute field and finally select the category value you wish to analyze As you select an attribute field the category value list will regenerate itself with a list of all unique values in that attribute field Choose the neighborhood radius you wish to use This tool is written to use circular neighborhoods and the radius units are in cells The actual neighborhood will consist of all cells whose cell centers are lt the radius distance of the focal cell center Note Neighborhood analysis at the edges of the raster are automatically adjusted so that the neighborhood size only reflects the portion of the neighborhood inside the raster In other words the density of a cell at Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 33 the edge or corner of the raster is only based on those neighborhood cells actually inside the raster Optionally you may force the tool to set the density value to NoData if there are any NoData cells in the neighborhood This option is not recommended for the Land Facet corridor functions because NoData cells have infinite resistance in the corridor function essentially exclud
5. 0 6 gz Back Cancel Manual OF Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 32 Density Surface Tool The land facet density surface reflects the proportion of a neighborhood that is composed of a particular land facet If half the cells around a particular cell were composed of Land Facet X then the density of Land Facet X at that point would be 0 5 The density values will range between 0 and 1 The density surface will be used in two procedures 1 Areas of high density within Wildland Blocks will be selected as corridor termini see p 36 and 2 Density is one of the variables used to build the Mahalanobis Cost Surface see p 54 Click the D button to run the tool Density Raster Parameters j ol x a This function will calculate the density of a particular cell value within a specified radius of each cell The output raster will have values ranging from Oto 1 where O means there are no cells of that value in the neighborhood and 1 means that all neighborhood cells have that value Optionally you may choose to automatically Select Categorical Raster Select Raster Attribute Field 1 comb facets VALUE 2 Polplines Po COUNT 3 Land Facet Chi 5 Land Facets 2 6 slopepos r hillshade o urbar rem Categor Value High Elevation Flats Circular Neighborhood A adius 5 Cells Set to NoData if any NoData cells in neighborhood
6. 3 and retains only those polygons that are larger than some specified proportion value For example if the largest polygon in a Wildland Block was 100 hectares in size and the user had specified a size threshold of 50 then the tool would retain all polygons that were gt 50 hectares These polygons are potential termini for the corridor Click the Ij button to run the tool Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 37 Identify Termini Polygons O x This tool vill identify termini polygons located within each Wildland Block based on an analysis raster usually a Density or Diversity raster a raster cell value threshold and a termini polygon size threshold value Analysis Raster Layer All areas with a cell value the specified threshold will Analysis Layer Le Density or Diversity eaaa Analysis Layer Threshold All regions with cell values greater than 0 5 Wildland Block Polygon Layer wildland Block Polygons Relative Size Threshold for Termini Polygons Integer 0 100 AU Output Termini Polgon shapefile Marlis stuffyconsultation brost climate changesout terminis Termini 9 shp oa Cancel Manual a The Analysis Layer dropdown box lists all rasters in your active map Select the raster you wish to analyze typically a Density or Diversity raster The Analysis Layer Threshold is the cut off value Only portions of the raster greater than this thr
7. The four classes are named Canyons Gentle Slopes Steep Slopes and Ridges by default but you can change the names by clicking the Reset Class Names button In general the classes are defined as follows Canyons TPIs lt A Gentle Slopes A lt 7P lt s B Slope Angle lt S Steep Slopes A lt 7P lt B Slope Angle 2 S Ridges 7PI gt B where A and B are threshold TPI values and S is the threshold slope angle TPI threshold units should be the same as the units of the TPI type and Slope angle threshold units should be in Degrees Please see the sections above on TPI types p 44 and Neighborhood types p 45 if you have any questions on these parameters The output raster will be a 4 Category Integer raster with the class names in the attribute table Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer CREATE A 6 CATEGORY TOPOGRAPHIC POSITION RASTER This tool will create a 6 class Topographic Position raster based on TPI values and Slope Angle Click the button to run the tool Last modified 20 J ul 10 6 Category Slope Position Parameters This tool will create a 6 category Slope Classification raster based on the Topographic Position Indes and the Slope of each cell Depending on your threshold values estreme low TPI values will be classitied as alleys moderately low TFI values will be classified as Lower Slopes TPI values around 0 will be gt
8. cell is based on the departure of that cell from the prototypical cell of the focal land facet Our procedures use Mahalanobis distance as the resistance metric Mahalanobis distance can be thought of as the number of multivariate standard deviations between the attributes of a pixel and the characteristic values for the focal land facet type For each land facet type the procedures include the following steps o Calculate Mahalanobis distance for every pixel in the analysis area using the following characteristic values e Mean elevation of pixels of the focal land facet within the Wildland Blocks e Mean insolation of pixels of the focal land facet within the Wildland Blocks e Mean steepness of pixels of the focal land facet within the Wildland Blocks By default the procedure kernel density estimation identifies the most extreme 10 as outliers but the user can over ride this setting Because outliers are defined relative to cells inside Wildland Blocks the proportion of cells in the matrix classed as outliers will differ from 10 or other specified value For most variables used in a Mahalanobis distance analysis the characteristic value is the mean But when one of the variables is of pixels of this facet type within a moving window 100 is used as the characteristic or ideal value even if the 100 value is far above the mean Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 11 O e 100 o
9. land_ facets Note the functions for defining land facets automatically write files to the working directory for compatibility with the Land Facet CorridorDesigner extension to ArcGIS 7 Load the topographic and soils data from ArcGIS into R data lt read csv c land_facets example_data csv head data inspect first six rows of data elevation slope 1 1655 584 29 4104 2 2484 788 32 2004 3 2057 512 20 6244 Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 90 4 2044 320 13 4432 5 1308 766 16 5707 6 1473 009 25 7639 To read a dbf file into R you will need to install and load the foreign package The corresponding function is read dbf 8 To identify outliers first use function LF kde kde lt LF kde x data gridsize 151 The resulting plot of the objects in data and the kernel density estimation should look like this 40 60 slope 20 1000 1500 2000 2500 elevation Examine this plot to determine an appropriate density threshold contour beyond which cells should be classified as outliers An appropriate threshold separates regions in attribute space densely populated by cells from those more sparsely populated Here for example the 90 contour appears to be appropriate This threshold is provided as an argument to function LF outlier in step 8 9 Identify outliers using the density threshold from Step 7 out lt LF outlier x kde threshold 90 The object out contains a variable o
10. likely hotter and future precipitation regimes wetter or dryer depending on location A linkage design with continuous strands of each land facet should provide continuous strands of future vegetation communities without the need to model climate change and vegetation response directly Our procedures can also produce a corridor with high interspersion of land facets such a corridor strand is intended to promote rapid short movements in response to climate change The ensemble of about a dozen corridor strands one for each land facet and one for diversity of facets constitutes a linkage design for climate change Because the approach does not in any way depend on global or regional circulation models emission scenarios species specific climate envelope models or species dispersal models it avoids massive and compounded uncertainties of approaches that depend on these submodels Our procedures can be used to make proposed corridors more robust to climate change or as an alternative useful in areas where no vegetation maps are available e g most of the developing world The procedures A land facet Linkage Design looks a lot like a focal species Linkage Design Figure 1 Like linkages designed for multiple focal species linkages designed for a diversity of land facets contain multiple strands connecting two wildland blocks the natural landscapes to be connected by the linkage such as a National Forest and a National Park Specifical
11. species typically occurs within a particular elevation range on slopes of a particular steepness and perhaps within a certain vegetation density Using Mahalanobis distances we can quantitatively describe the entire landscape in terms of how similar it is to the ideal elevation slope and vegetation density of that animal Moreover Mahalanobis distances are based on both the mean and variance of the predictor variables plus the covariance matrix of all the variables and therefore take advantage of the variable covariance The region of constant Mahalanobis distance around the mean forms an ellipse in 2D space i e when only 2 variables are measured or an ellipsoid or hyperellipsoid when more variables are used Mahalanobis distances are calculated as Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 55 D x m C x m where D Mahalanobis distance x Vector of data m Vector of mean values of independent variables C Inverse Covariance matrix of independent variables T Indicates vector should be transposed For example suppose we took a single observation from a bivariate population with Variable X and Variable Y and that our two variables had the following characteristics Variable X mean 500 SD 79 32 Variable Y mean 500 SD 79 25 Variance Covariance Matrix 6291 55737 3754 32851 3754 32851 6280 77066 If in our single observation X 410 and Y 400 we would calculate the Mahal
12. valley bottom mid slope etc and landform category i e steep narrow canyons gentle valleys plains open slopes mesas etc In designing corridors for land facets we have simply used the Topographic Position Index to classify the landscape into three broad topographic positions namely ridges canyon bottoms and slopes but we describe other options for users that may wish to use TPI in other ways The algorithms are clever and fairly simple The TPI is the basis of the classification system and is simply the difference between a cell elevation value and the average elevation of the neighborhood around that cell Positive values mean the cell is higher than its surroundings while negative values mean it is lower The degree to which it is higher or lower plus the slope of the cell can be used to classify the cell into slope position If it is significantly higher than the surrounding neighborhood then it is likely to be at or near the top of a hill or ridge Significantly low values suggest the cell is at or near the bottom of a valley TPI values near zero could mean either a flat area or a mid slope area so the cell slope can be used to distinguish the two Tends towards Tends towards Flat areas if slope is shallow Valleys and Mid sl a dag A T Ridgetops and Canyon Bottoms i aaa aaa Hilltops em S Negative TPI 0 Positive TPI Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 41 SCALES AND NEIGHBORHOODS TPI
13. 200 300 400 500 600 700 800 900 Independent Variable 1 We can also draw actual ellipses at regions of constant Mahalanobis values Last modified 20 ul 10 57 MANUAL Land Facet Corridor Designer 58 7 O Mahalanobis Distance Ellipses z Independent Variable 2 300 400 500 600 700 800 200 100 100 200 300 400 500 600 700 800 900 Independent Variable 1 One interesting feature to note from this figure is that a Mahalanobis distance of 1 unit corresponds to 1 standard deviation along both primary axes of variance RE SCALING MAHALANOBIS DISTANCES USING CHI SQUARE P VALUES Mahalanobis distances are occasionally converted to Chi square p values for analysis see Clark et al 1993 When the predictor variables are normally distributed the Mahalanobis distances do follow the y distribution with N 7 degrees of freedom where N of habitat variables 2 in the example above Although wildlife habitat variables often fail to meet the assumption of normality Farber and Kadmon 2003 the conversion to Chi square p values is nonetheless a valid way to re scale Mahalanobis distances to a 0 1 scale Mahalanobis distances themselves have no upper limit so this rescaling may be convenient for some analyses In general the p value reflects the probability of seeing a Mahalanobis value as large or larger than the actual Mahalanobis value assuming the vector of predictor values that produced that Mahalanobis value was
14. 3 dimensional array of 91 bins 753 571 bins If you are using more than 3 continuous variables to define outliers 1 e your multivariate space has more than 3 dimensions you will require a smaller gridsize less than 91 we have not experimented with datasets of dimension gt 3 Details LF kde is functional for 1 to 6 dimensional data sets This function automatically plots the objects in x and the density estimation For 1 dimensional data sets the plot shows the univariate density curve and a rug plot of objects in x For 2 dimensional data sets density contours are overlaid onto the bivariate plot of objects in x The Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 84 contours have an interval of 10 from 10 to 70 and a 5 interval from 70 to 100 The contour labeled 10 contains the 10 of objects occurring at highest density For 3 dimensional data this function plots the objects in x and the 3 dimensional density contours For visual clarity only the 25 50 75 90 and 100 density contours are displayed but you can use the plot and data to specify a density threshold other than one of these values Output This function writes to the working directory bin_width csv a comma delimited file that contains the multidimensional half width of bins used in the kernel density estimation Value X dataframe containing topographic and or soil data same as input width multidimensional half width o
15. 5 4 1 and the replacement list would then be used to generate the correlation matrix EXACT VALUES VS INTERPOLATED VALUES You have the option to use the exact cell value for each of your point locations or interpolated values based on the 4 closest cells to that point For interpolated values ArcView uses a 2 step method whereby values are interpolated first vertically and then horizontally For example given 4 cells around a particular location 2 54 Location Lines are first generated between the cell centers of cells A and C and between cells B and D and values are interpolated along these lines at the Y coordinate of the point location Then a final value is interpolated along the X axis between these two interpolated values In this case the interpolated value of the point is approximately 4 31 while the exact cell value of the point is 2 54 Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 64 ADDITIONAL READING The author recommends Clark et al 1993 Knick amp Dyer 1997 and Farber amp Kadmon 2002 for a few good papers illustrating the use of Mahalanobis distances in ecological applications For anyone interested in the details of matrix algebra and computational statistical algorithms the author recommends Conover 1980 Neter et al 1990 Golub and Van Loan 1996 Draper and Smith 1998 Meyer 2000 and Press et al 2002 Last modified 20 ul 10 MANUAL Land Facet Corri
16. Because of the way ArcGIS handles toolbars and command buttons you may add any Land Facet Corridor Designer command buttons to any toolbar you wish For example if you would like to keep the Shannon s Index tool available even when the Land Facet Corridor Designer toolbar is not turned on you may easily add that tool to any of the existing ArcGIS toolbars To do this open your Customize tool by either 1 Double clicking on a blank part of the ArcMap toolbar or 2 Clicking the Tools menu then Customize In the Customize dialog click the Commands tab and scroll down to select Land Facet Corridor Tools Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer Customize Toolbars Commands Options 21 2 xX Show commands containing Categories Ink Inzert Jenness Enterprises Jennessent Tools Label Land Facet Corridor Tools Layer Linear Referencing Map Inquiry Map Navigation Map Service Publishing bd ir he Commands R Export for A Analysis Le Invert Flaster m Land Facet Clusters from Fi My Mahalanobis Distances At Point Mp Mahalanobis Distances Create F of 5 hannon s Diversity Indes Description 53 Slope Position 3 Category Sa Slope Position 4 Category Save in sample_cade mx gt Keyboard Add from file Close Finally simply drag any of the commands out of
17. Brost 2010 explain why fuzzy c means cluster analysis Bezdek 1981 Dimitriadou et al 2009 is superior to hierarchical cluster analysis nonmetric multidimensional scaling and two step cluster analysis 3 Identify the number of classes c that best corresponds to the natural multivariate lumpiness in the continuous variables This requires examining several goodness of fit metrics evaluating interpretability of classes draping maps of facet polygons over a topographic hillshade plotting facet centroids in multivariate space and inspection of the proposed class map by someone familiar with the landscape to assess whether the c clusters correspond to natural units or impose artificially discrete categories on a continuous landscape 4 Usea confusion matrix to identify poorly classified pixels such as slope pixels that assign with roughly equal probability to the warm steep high elevation and the cold steep high elevation classes Remove poorly classified pixels from the analysis to produce a set of distinctive land facets These procedures will typically produce a set of 8 16 land facets such as high elevation steep ridges and low elevation gentle hot slopes MAJOR STEP 2 DEVELOP MAPS OF RESISTANCE In focal species approaches to designing linkages the resistance of a cell represents the difficulty of movement through that cell for a focal species For the land facet approach the resistance of a
18. Class 1 Valleys Select DEM Faster Layer TFI 1 units Slope_4_ 3 Class 2 Lower Slopes Select TPI Type to create 1 units TPI 0 5 units Standardized Elevation Class 3 Gentle Slopes Neighborhood Options 0 5 units TFI 0 5 units elope eidenrees Neighborhood Shape Circle Class 4 Steep Slopes Neighborhood Size Units 0 5 units TFI 0 5 units m Slope gt 5 degrees ells Class 5 Upper Slopes Radius 5 0 5 units TFI 1 units Class 6 Ridges TFI 1 units AJ 1 Blf 25 c 05 D 1 s 5 Set to NoData if any NoData cells in neighborhood Output Raster Format ESRI GRID Output Raster Dataset Name D aroGilS_stuff consultation brost_climate_change TPI_out Slope_6_3 pe Cancel Manual OF A MANUAL Land Facet Corridor Designer 53 The six classes are named Valleys Lower Slopes Gentle Slopes Steep Slopes Upper Slopes and Ridges by default but you can change the names by clicking the Reset Class Names button In general the classes are defined as follows Valleys 7PI lt A Lower Slopes A lt TPI lt B Gentle Slopes B lt 7P s C Slope Angle lt S Steep Slopes B lt TPI lt C Slope Angle 2 S Upper Slopes C lt TPI lt D Ridges 7PI gt D where A B C and D are threshold TPI values and S is the threshold slope angle TPI threshold units should be the same as the uni
19. Features gt Multipart to Singlepart Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 38 The Relative Size Threshold for Termini Polygons specifies how large a polygon must be as a percent of the size of the largest polygon in the Wildland Block to be considered a terminus This value should be between 0 and 100 Density Raster Termini Polygons Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 39 Invert Raster Tool This tool will numerically invert any raster i e each new cell value y where x is the original cell value but it is specifically intended to invert the Shannon s Index raster see p 34 in order to use it as a cost surface in Corridor Designer This tool also lets you add a small constant to each raster value before inverting it to prevent division by zero problems which will result in NoData values in your inverted raster We strongly recommend using this option we find that 0 1 is a good default value for the constant Click the v button to run this tool Invert Raster Parameters iol x This tool will mathematically invert the raster by inverting each cell value i e Inverse s 148 Any cells with U value wall automatically be converted to WoData because you cannot divide a value by 0 Optionally you may add some constant value to all cells before inverting it to prevent this from happening Select Raster Layer Output Raster For
20. Functions for Defining Land Facets This section documents the functions used to define land facets or recurring polygons of relatively homogenous topography and soils These functions are implemented in R a widely used computer language for data manipulation calculation and graphical display It is an environment within which many classical and modern statistical techniques are implemented R has a steeper learning curve than other statistical software packages because of its command line interface however R offers nearly unlimited capabilities for data analysis R is distributed for free from www r project org the R Project for Statistical Computing website It is compatible with Windows MacOS X and Linux operating systems There are two R functions used for identifying outliers in a data set one function for classifying the data set into land facets and a final function for exporting products of the classification in a format compatible with the Land Facet Clusters from R tool of the Land Facet CorridorDesigner extension to ArcGIS The input data for these functions is generated by the Export for R Analysis tool of the same extension Prior to describing the R functions for defining land facets I briefly introduce those features of R statistical language essential for using these functions An Introduction to R by Venables and Smith offers a more comprehensive introduction to the R language It is free and available on the R web
21. Johns Hopkins University Press 694 p Guisan A S B Weiss and A D Weiss 1999 GLM versus CCA spatial modeling of plant species distribution Kluwer Academic Publishers Plant Ecology 143 107 122 Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 98 Franklin J 1995 Predictive vegetation mapping Geographic modeling of biospatial patterns in relation to environmental gradients Progress in Physical Geography 19 474 499 Hannah L G F Midgley and D Millar 2002 Climate change integrated conservation strategies Global Ecology and Biogeography 11 485 495 Jenness Enterprises 2006 Topographic position index Version 1 3a Available from http www jennessent com accessed November 2009 Jones K B D T Heggem T G Wade A C Neale D W Ebert M S Nash M H Mehaffey K A Hermann A R Selle S Augustine I A Goodman J Pedersen D Bolgrien J M Viger D Chiang C J Lin Y Zhong J Baker And R D Van Remortel 2000 Assessing Landscape Conditions Relative to Water Resources in the Western United States A Strategic Approach Environmental Monitoring and Assessment 64 227 245 Knick Steven T and Dyer Deanna L 1997 Distribution of black tailed jackrabbit habitat determined by GIS in southwestern Idaho Journal of Wildlife Management 61 75 85 Lovejoy TE and L Hannah 2005 Climate change and biodiversity Yale Univ Press McCune B and J B Grace 2002 Analysis of ecologica
22. MANUAL Land Facet Corridor Designer 69 CALCULATING MAHALANOBIS VALUES AT SAMPLE POINTS This tool will calculate Mahalanobis distance values at a set of points based on an existing mean vector and covariance matrix See Generating Statistical Matrices on p 73 for a tool to calculating these data Optionally the tool will add the Mahalanobis values to an existing field in the Point layer attribute table to a new field added to the attribute table or to a new table entirely The mean vector and covariance matrix must be selected from tables currently available in your map document Note You must take care to ensure that the order of variables in the tables is the same as the order of variables you use to calculate your Mahalanobis surface If the variable layers are not entered in the same order as they are exist in the mean vector and covariance matrix then the Mahalanobis Distance values will be incorrect Click the button to run the tool Point Layer and Statistical Matrices Step 1 of 3 ol x This tool vill calculate the Mahalanobis distance values at a set of points based on an existing mean vector and covariance matrix Optionally the tool Will add the Mahalanobis values to an existing field in the attribute table ta a nev field added to the attribute table or to a new table entirely The mean vector and covariance matrix must be selected from tables currentie awaiahle in war marn darimernt Ave Ye miit take car
23. a categorical raster then your statistical matrices will be generated from all datasets that intersect the specific raster category you select For example if we wanted to generate statistical matrices for Land Facet 1 then we would fill out the dialog as follows Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer Next choose the layers containing the variables you wish to analyze If you select polygon layers then you will also need to select the attribute field containing the variable data Note If Source for Means and Covariances Step 1 of 3 This tool vill optionally calculate the Mean Vector Covariance Matrix Inverse Covariance Matrix Correlation Matrix and Spearman s Rank Correlation Rho Matrix for raster or vector data occuring within specified r gions of the landscape The Mean Vector and Covariance Matrix may then be used in Mahalanobis calculations provided you take care to enter your Mahalanobis Variables inthe same order that you used to create the original Mean ector and Cowsriaoce hisatriv Please reter tothe manual tor addtional information tt Identify Sample Source for Statistical Matrices 0 Generate from point layer f Generate from categorical raster Select Categoncal Raster Select Raster Attribute Field 1 slopepos VALUE COUNT Category Value Land Fact itsti isY Facet 1 Cancel Manual l nA F 74 you plan to use these statistical matrices i
24. a comma separated value csv file into R Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 80 data lt read csv file C land_facets example_data csv The function is called read csv and its file argument is the location and name of the csv file to be read into R Notice that branches in the file directory containing example_data csv are separated by forward slashes not backslashes After executing this line the object data contains the information stored in the csv file data is a dataframe which is an object that has rows and columns The rows contain values for different observations 1 e raster cells and the columns contain the values of different variables The function head returns the first six lines of the object for inspection head data elevation slope 1655 584 29 4104 2484 788 32 2004 2057 512 20 6244 2044 320 13 4432 1308 766 16 5707 6 1473 009 25 7639 This shows that data contains two variables elevation and slope The first column of numbers indexes the rows in data To refer to a single variable within a dataframe one would type dataframe variable For example data elevation pulls out the column of elevation values from the data dataframe The number of rows in data is O A OO N gt nrow data 1 100000 ISOLATING SUBSETS OF DATA IN A DATAFRAME Subscripts are used to reference subsets of data in a dataframe In R subscripts appear in square brackets i e The rows of a datafram
25. above Use the standard CorridorDesigner tools to create a Diversity corridor between your wildland blocks Use your inverted Shannon s Index raster from step 6 above as your cost surface Use standard ArcGIS tools to combine all individual corridors into a single linkage design Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 24 Land Facet Corridor Analysis Tools Export for R Analysis Land Facet definitions are based on Fuzzy C Means clustering often referred to in the literature as FCM clustering which means that points on the landscape are clustered into relatively homogeneous groups based on the various data layers you are analyzing For example if you use slope elevation and insolation to identify clusters within the canyon bottom topographic position you might find many pixels of high elevation gentle slope and low solar insolation These would become one of your land facets and you might name it High elevation canyon bottoms Fuzzy clustering means that all points on the landscape are assigned a Strength of Membership value to all clusters rather than just assigning it to a specific cluster The cluster assignment would be the one with the highest strength of membership but we can and will exclude pixels that are not strongly identified with any single cluster This tool does not perform the actual Fuzzy Clustering analysis Rather this tool will export one or more tables of
26. both categorical and continuous variables it can readily be adapted to accommodate categorical soil variables such as soil type and continuous soil variables such as soil depth or moisture We strongly encourage use of relevant soil data if they are available throughout a planning area Moore et al 1991 and Franklin 1995 discuss approximately 20 topographic variables that can be derived from a digital elevation model DEM Our procedures allow the user to select up to 5 soil or topographic variables To maintain easily interpretable and biologically meaningful land facets Beier and Brost 2010 recommend using four variables to define land facets from 30 m DEM 1 Topographic position Each pixel is assigned to one of three classes namely canyon ridges and slopes including flat slopes by comparing the elevation of the pixel to the average elevation within a 200 m radius Jenness 2006 2 Annual solar insolation Sum of instantaneous radiation at half hour intervals for one day per month over a calendar year using the Solar Radiation tool in ArcGIS 9 3 ESRI Redlands California The tool calculates half hour radiation as a function of latitude aspect slope and topographic shading but ignores thickness of atmosphere and cloud cover 3 Steepness expressed as slope angle see previous footnote 4 Elevation To ensure that the classification represents the land facets of the Wildland Blocks we use only pixels inside
27. cluster analysis as a comma delimited text file csv As discussed in the section on R Functions for Defining Land Facets p 78 the data are binned to speed up the processing time This file will have exactly 2 rows The Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 28 first row should contain the variable names and the second row should contain the bin width of each variable For example elevation slope G 106686009945654 07 243888379803814 4 A file of the bin coordinates for all the non outlier bins used in the cluster analysis as a comma delimited text file csv The R tools should have excluded a percentage of the most extreme bins as outliers This file of bin coordinates contains all the bins that were not excluded The tool will use this list of non extreme bin coordinates along with the bin widths to determine which regions on your landscape should also be excluded as outliers This file will typically have hundreds or thousands of bin centerpoint coordinates The first row should include the variable names and all subsequent rows should include the centerpoint coordinates for each bin For example elevation slope MOG 52263807 S72 4 Orr 1 OS MOG S635 OF S575 0446913638 LO65 633075 354245596 TO eet Oe aoe Zoo Os ZA SPO OI 6 4 eA AG 2 Ya Maia 16 1 Greer oO Aa O22 5 Optional A file of the FCM Fuzziness parameter used in the analysis as a standard ASCII text file txt This
28. do not then they must not describe the same set of variables and the tool will not let you proceed to the next dialog STATISTICAL MATRIX DEFINITIONS AND FORMULAE e Mean e Variance Covariance Matrix YX a xy Variance of variable X o o estimated by n 2 x 9 Y Covariance between x and y o estimated by a n Therefore given p variables Or O17 gt Olp On On 7 Onn Covariance Matrix Cov X l l Op Pp pp n n bxee XY gt O X Xn X i l i 1 n 1 n 1 OG T X MX z X DOG Xe estimated by _______ doo n 1 n 1 x X X 7 X s x X Xiz 7 X j l j l n 1 n 1 gt x X Xp 7 X i l n 1 n 2 On X Xp Xp e Inverse Covariance Matrix Matrix inversion is computationally complex and the author refers interested readers to the Lower Upper LU Decomposition method in chapter 2 of Press et al 2002 e Pearson Correlation Matrix Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 63 Or On Olp On Oy e Oop Given a Covariance Matrix Cov X i Fpi Qp Te Cpp NONO NONOR VOU V2 pp the Pearson Correlation Matrix o o Ga Al Ons Oz 4 Oi VOU pp VP22 V9 pp y pp yO pp Spearman Correlation Matrix Computationally identical to the Pearson Correlation Matrix except that ranks are used in place of original values For example the list of values 12 3 56 23 1 would be replaced with 3 2
29. e g broad multi stranded swaths of land connecting National Forests and Grasslands to other nearby protected lands are appropriate in landscapes increasingly dominated by human uses However most existing corridor designs rely on current vegetation maps as the primary driving factor reviewed by Beier et al 2008 These corridor designs risk failure because current vegetation and human land uses will change in response to climate change in ways that have proven difficult to predict Only two efforts Williams et al 2005 Phillips et al 2008 designed corridors to facilitate species range shifts caused by climate change Those efforts depended on 50 year projections of a regional circulation model and produced very coarse corridors chains of 2 9 km2 cells Land Facet Corridor Designer is a new approach finer scale free of dependence on global and regional climate models to design corridors robust to climate change Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 7 These GIS procedures produce a linkage design composed of a multiple swaths that provide high diversity and continuity of land facets polygons with relatively uniform topographic and soil characteristics for example high elevation north facing slopes on rocky soils or low elevation flats with thick soils The rationale is that future vegetation communities will be determined by the interaction among topographic elements soil types future temperature regimes
30. geology that are relevant to biodiversity and identifiable without a soil map In the long term better soil maps are needed to ensure rigorous mapping of land facets across the entire planning region Rivers and ephemeral drainages span elevational gradients in a way that increases interspersion and promotes ecological processes and flows such as movement of animals sediment water and nutrients Because mechanical geospatial algorithms may fail to identify important riverine connections that are obvious to a human expert we recommend manual inclusion of riverine elements if necessary e g Cowling et al 1999 2003 MAJOR STEP 5 JOIN THE LAND FACET CORRIDORS AND CORRIDORS FOR HABITAT SPECIALIST SPECIES The preliminary linkage design is the simple union of the least cost corridors for all land facets the land facet diversity corridor and the major riverine or riparian corridors In cases where corridors cannot be modeled for focal species due to lack of land cover maps or lack of knowledge about habitat use or movement by potential focal species this becomes the final linkage design If you can model corridors for focal species we recommend that you do so creating a somewhat larger linkage design Brost 2010 developed linkage designs based on land facets for three landscapes in Arizona where linkage designs for focal species had previously been produced Using two variables to measure linkage utility Brost found that linkages designe
31. of the workspace will be restored when you open R again To limit the clutter in your workspace I recommend not saving on exit Instead use the Save Workspace option under the File menu to save the workspace for your current project under a name you specify that named workspace can then be restored if necessary by using the Load Workspace option under the same menu This lets you choose the amount of clutter or useful information in your workspace Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 82 Overview Of R Functions For Defining Land Facets The Land Facet Clusters from R tool provides four new R functions namely e two functions to identify outliers in a data set LF kde and LF outlier e one function to classify a data set into land facets LF cluster and e one function LF export to export the products of the classification which is necessary for compatibility with the Land Facet Clusters from R tool of the Land Facet CorridorDesigner extension to ArcGIS Unlike built in R functions or those in add on packages function name will not access Help files for these four functions Thus documentation is provided below in a format similar to R reference manuals Documentation for each function includes five sections The Description and Usage subsections describe the function and illustrate its structure respectively The Arguments subsection lists and describes
32. sampled from a population with an ideal mean i e equal to the vector of Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 59 mean predictor variable values used to generate the Mahalanobis value P values close to 0 reflect high Mahalanobis distance values and are therefore very dissimilar to the ideal combination of predictor variables P values close to 1 reflect low Mahalanobis distances and are therefore very similar to the ideal combination of predictor variables The closer the p value is to 1 the more similar that combination of predictor values is to the ideal combination Because P values close to 0 correspond with high Mahalanobis values while P values close to 1 correspond with low Mahalanobis values this transformation also inverts the order of values High cell values in the P value raster surface will correspond with low values in the Mahalanobis raster and vice versa APPLICATIONS TO LANDSCAPE ANALYSIS Suppose we have a grid of elevation values and a grid of slope values and we are interested in identifying those regions on the landscape that have similar slopes and elevations to a mean slope and elevation characteristic of a land facet 1931 54 Covariance Matrix 54 87 Elevation 2121 Vector of Mean Values Slope 18 We can then enter the Elevation and Slope rasters directly into the Mahalanobis equation to produce a Mahalanobis raster Given that D x m C x m Elevation Ra
33. should experiment with values that work in their landscapes Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 50 CREATE A 4 CATEGORY TOPOGRAPHIC POSITION RASTER This tool will create a 4 class Topographic Position raster based on combinations of TPI values and Slope Angle Click the 5a button to run the tool 4 Category Slope Position Parameters This tool will create a 4 categor Slope Classification raster based on the Topographic Postion Indes and the Slope of each cell Depending on your threshold values low TPI values will be classified as 1 Canyons TPI values around O will be classified as either Z Gentle Slopes or 3 Steep Slopes Class 1 1 Canyons Select DEM Raster Layer TFI 4 units DE fl r Class 2 2 Gentle Slopes Select TPI Type to create 1 units TFI 1 units TPI Slope 6 degrees Heighborhood Options Class 3 3 Steep Slopes 1 units TPI 1 units Neighborhood Shape Slope 6 degrees Cice Neighborhood Size Unit Class 4 A Ridges EBIQnbomod Ize LIPS TFI 1 units elz Radius 5 A 1 B 7 si Reset Class Names Set to NoData if any NoData cells in neighborhood Output Raster Format ESRI GRID Output Raster Dataset Hame D arcGlS_stuff consultation brost_climate_change TPI_out Slope_4 Ca Cancel Manual a Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 51
34. summarizing all the input parameters and showing where all the output tables were saved Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 27 Land Facet Clusters from R This tool uses the parameter files produced by your statistical software to generate a set of land facets for a single landscape category e g for the ridgetop topographic position or a particular soil category You will need to repeat this process for each landscape category The final land facet classification for any particular point on the landscape will be based on the highest cluster membership value at that point whether or not the combination of landscape variables makes the point an outlier as determined by the R analysis and whether the confusion index at that point is below a specified threshold Points that are considered outliers and points that exceed the confusion index threshold will be assigned NoData values in the land facet raster All other points will be assigned a land facet category according to the highest cluster membership value Note This tool requires 4 5 files from your statistical output These files must be formatted correctly in order to be read by this tool If you use the R tools supplied with this extension see p 78 then your data files should all be formatted correctly for this tool Otherwise you will need to make sure the files are formatted correctly yourself The required files are 1 A file of the cluster
35. the blocks to define the land facets Later pixels in the rest of the analysis area will be assigned to appropriate land facets Using only the pixels inside the Wildland Blocks the procedures start with these two steps 1 Assign each pixel into broad classes of the categorical variable topographic position This classifies each pixel as a ridge canyon or slope pixel The procedure allows you to choose another categorical variable such as soil type or a combination of a categorical soil variable and a topographic position 2 Characterize each slope pixel based on all three continuous variables steepness elevation insolation Characterize each ridge or canyon pixel based only on steepness and elevation Within each topographic position the procedures involve the following sequential steps We use the term slopes to refer to the topographic position a categorical variable that includes every pixel that is not classified as a canyon bottom or a ridgetop We use the term steepness or slope angle to refer to the continuous variable that can describe any of the 3 topographic positions This can result in awkward phrases like steepness of a slope sorry about that If we ever slip up and refer to slope of a slope we are very sorry Insolation is not used to identify subclasses of ridges or canyons because ridges and canyons are usually symmetrical features that is a high insolation ridge is almost always close to a
36. the raster tools The error would only occur if you had a non raster layer selected in your map when you clicked the tool July 20 2010 e Version 1 2 813 e Repaired a bug in the 3 class slope position tool in which it mislabeled canyons as ridges and vice versa Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 97 Literature Cited Adriaensen F JP Chardon G deBlust E Swinnen S Villalba H Gulinck and E Matthysen 2003 The application of least cost modeling as a functional landscape model Landscape and Urban Planning 64 233 247 Beier P D Majka and WD Spencer 2008 Forks in the road choices in procedures for designing wildlife linkages Conservation Biology 22 836 851 Beier P and B Brost 2010 Use of land facets to plan for climate change conserving the arenas not the actors Conservation Biology DOI 10 1111 j 1523 1739 2009 01422 x Beier P DR Majka and T Bayless 2007 Wildlife linkage designs for the state of Arizona Reports to Arizona Game and Fish Department Phoenix available at www corridordesign org Bezdek C J 1981 Pattern recognition with fuzzy objective function algorithms Plenum Press New York Brost B 2010 Use of land facets to design linkages for climate change Thesis School of Forestry Northern Arizona University Clark Joseph D Dunn James E and Smith Kimberly G 1993 A multivariate model of female black bear habitat use for a geographi
37. your analysis to a particular direction Weiss poster discusses some ideas for future research in which he plans to compare directional TPI values in order to distinguish saddles from flat areas ridges from hilltops and valleys from local depressions as well as identify the general aspect of landforms CLASSIFYING BY TOPOGRAPHIC POSITION TPI values can easily be classified into topographic position classes based on a how much a pixel s elevation differs from the mean of its neighbors and b the steepness slope angle at each point There are a couple of strategies you can take to do this The easiest way is simply to set threshold values for the TPI grids themselves TPI values above a certain threshold might be classified as ridgetops or hilltops while TPI values below a threshold might be classified as valley bottoms or depressions TPI values near 0 could be classified as flat plains if the slope angle is near 0 or as mid slope areas if steeper than a specified threshold Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 43 Dickson and Beier 2006 used this method in a study of the influences of topography on cougar movement A somewhat more sophisticated method illustrated by Weiss in his poster is to define threshold TPI values in terms of standard deviations from the elevation which therefore take into account the variability of elevation values within that neighborhood This means that grid cells with ide
38. Land Facet Corridor Designer corridordesign org Last updated 20 July 2010 Jeff Jenness Brian Brost Paul Beier Produced with the generous support of USDA Forest Service Rocky Mountain Research Station MclIntire Stennis Cooperative Forestry Program Arizona Board of Forest Research A Arizona Board of Forest Research MRS ROCKY MOUNTAIN RESEARCH STATION USDA MelIntire Stennis Cooperative A Forestry Research Program Compatibility Problems with ArcGIS 10 Some of you may have heard that the next release of ArcGIS has been renamed from ArcGIS 9 4 to ArcGIS 10 One of the reasons ESRI has decided to change this from a minor to a major new release is that they are completely changing the way ArcGIS recognizes custom extensions Because of this these Land Facet Corridor tools will likely be completely disabled The Land Facet Corridor tools are written in Visual Basic 6 and ESRI has changed the way that ArcGIS recognizes custom extensions in such a way that there appears to be no simple way to get ArcGIS too see that the tools are even there Jeff Jenness is looking for a way to get the tools to work So far the method that ESRI is recommending is to rewrite them in VB NET and this solution would certainly work Unfortunately the tools are fairly complex and substantial over 85 000 lines of code at latest count and there is no budget for this so it would have to be done in my free time Therefore it probably won t happe
39. NE 0 een een enn a e a a ee eee 78 ASSIOMING Values LO ODIECIS anin a tetas oye deg a a haan coadbaelestovged eos 78 Vona RAI CU ONS r EEA i onnnleumarneuturelentzes anole E E a temeeets 79 Isolating Subsets of Data in a Dataframey ccccc cece cccccceeeccececceeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeees 80 Installing and Loadina R Packages ernia e a eE aE R a e E ea ded a tadeane a E RE 80 Getin HeD ITR oaa e E E E one 81 SOME SU PESON S ase city socase ance E A A E E A a 81 Overview Of R Functions For Defining Land Facets ccccccccccccccccccceeeeceeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeees 82 Kernel Density Estimation Function LF kde icj ccc cctead cousupatecrbedonesedoneatad te tenunoaneseasaevssieedgnenectas eo oenneneees 83 Identify Outliers Pic ten LEGUE eeann a ease abet 85 Fuzzy c means Cluster Analysis Function LF cluster nnnnnnnnnnnnsneunseesesseseeseeeerrrrererereeerrrerererrerees 86 Exporting Information for Land Facet CorridorDesigner Function LF export cccccccccccccceceeeeseseeeeens 88 Downloading The R Functions For Defining Land Facets ccccccscssccccccceeeceeeceeeeeeecseeeeeseeseeseeees 89 Workflow For Defining Land Pace tsa c lt cc c0scaccanstacodendsdasavensadiaecdeacaatosakeas i enie i 89 ABOUT THE LAND FACET EVALUATION TOOLS AND MANUAL eeeeessssececececeeeeeeeeeeeeeeeeeeeeaaaeeees 94 Documents Related to Land Facet Analysis iiscc 2tiedk aia a aca a das ben doen eee ad 94 Las
40. ODELING The procedures to produce a least cost corridor for each land facet type are very similar to those used to develop least cost corridors for focal species Adriaensen et al 2002 Beier et al 2008 O Define corridor termini potential start and end points as areas within the wildland blocks that contained the most occurrences of the focal land facet Calculate the cost weighted distance cumulative resistance from each terminus and sum the two resulting raster outputs to produce the corridor results Select a slice cost contour of the corridor output to delineate the least cost corridor We suggest selecting the slice with an approximate minimum width of 1 km over its length for corridors lt 10 km long increasing to an approximate minimum width of 2 km for much longer corridors We chose these minima because they are similar to the widths recommended by Beier et al 2008 for corridors for focal species To produce a single corridor with maximum interspersion of land facets our procedures use the following steps O To define corridor termini follow these steps within each Wildland Block separately e Identify the half of all cells inside each Wildland Blocks with the highest H values and aggregate them into polygons Adding 0 1 precludes undefined values which would occur in the unlikely event that all cells in a neighborhood are outliers By default the procedure aggregates all cells with at least
41. Order from table 1 basalarea 2 cosaspect Selected Mahalanobis Variables Remove Hold 2 RASTER sinaspect Wor 3 RASTER slope 4 RASTER treedensity t f Exact Cell value at Point Interpolate Value from Four Closest Cells Riasters Only g Back Manual Cancel Net A Select the raster or polygon datasets to extract the sample data from These layers should correspond with the variables used to generate the mean vector and covariance matrix Important Be sure to sort these layers into the correct order Click the Variable Order tab to see the order of variables listed in the specified Covariance Matrix selected in the previous dialog Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 71 Mahalanobis ariables Step 2 of 3 l ol x Select the raster or polygon datasets to extract the sample data from These layers should correspond withthe variables used to generate the mean vector and covariance matrix Important Be sure to sort these layers into the correct order Click the Variable Order tah to see the order af vwarishle lister in the necitied Mahalanobis Variable Order 1 basalarea eee Canopyeowe _ 41 834509 3 small poly Mean 439 029614 4 cosaspect O 120465 5 0 00585193 4 17781 ETE S TELSS Selected Mahalanobis Variables Remove Holo 1 RASTER canopycoyer 2 RASTER sinaspect 3 RASTER slope 4 RASTER tree
42. Shannon s Index Select Raster Layer P vals 2 Output Raster Format Mahal ESRI GRID Mahal hillshade Circular Neighborhood Radius C Set to NoData if any NoD ata cells in neighborhood Output Raster Dataset Hame D arcGlS_stufconsultations brost climate changes TPL out Shannon 2 Cancel Manual You must select the raster you wish to analyze the output format for your Shannon s Index Surface and the neighborhood radius size This tool uses a circular neighborhood If only NoData values are observed in the neighborhood the tool will assign a Diversity value of 0 Otherwise NoData values will be ignored NoData values will not be counted as an additional NoData class Optionally you may force the tool to assign NoData values if any NoData values are found in the neighborhood Click OK and the tool will generate the Shannon s Index raster and add it to your map document Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 35 Land Facets Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 36 Identify Termini Polygons Tool Corridor polygons do not run simply from the edge of one Wildland Block to the edge of the other Wildland Block but instead run between land facet polygons within the Wildland Blocks If there are no land facet polygons within the blocks then there 1s little sense in creating a land facet corridor to connect them This t
43. al procedures in R and an accompanying User s Manual These procedures process outputs from ArcGIS to produce new data that can easily be imported back into ArcGIS for the final linkage design Brian Brost s MS thesis which describes how the procedures were developed The thesis also applies the procedures to three landscapes in Arizona and describes how well the linkage design for land facets matches linkage designs for multiple focal species in the same landscape PDF reprint of a paper introducing the concept of using land facets to design linkages Beier P and B Brost 2010 Use of land facets to plan for climate change conserving the arenas not the actors Conservation Biology DOI 10 1111 j 1523 1739 2009 01422 x Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 17 Installation of Land Facet Corridor Designer Tools Note This extension is intended as a companion to CorridorDesigner available at http www corridordesign org and we recommend that you also download and install those tools The tools in this extension will work fine without CorridorDesigner but some of the general tasks such as creating corridor polygons over a habitat suitability raster or creating patch polygons require functions from CorridorDesigner The tools in Land Facet Corridor Designer provide an alternative way to create the habitat suitability raster 1 e the cost surface but using land facets rather than focal species O
44. alysis should have produced four ceyv fles The Centroids file contains the cluster centroid coordinates for all of Your clusters The Bin Widths file contains the parameters used to determine the bin sizes and the Eval Points file contains the bin centroids which are used to determine which values are outliers and are therefore excluded from the analysis The Params file contains the mean and standard deviation of all varlables and i used to standardize the data gt D Load Centroids File Clear Centroids Data D Load Params File Clear Params Data Centroids Filename c niroids csy Variable Count 1 elevation 2 slope Centroid Count 4 Params 1 elevation 2 slope Variable Params elevation Mean 1420 507761357 zl Standard Deviation 205 771 e104 al Slope x Load Bin width File Clear Bin Width Data Load Eval Points File Clear Eval Points Data Bin Widths Filename pin width csv Variable Count 2 1 elevation 2 lope Bin Widths Blevation 6 10668601 Slope 0 24568350 Centroid 71 elevation 1 64078639 Slope 1 04783262 Eval Points Filename eval polnts csy Variable Count 2 1 elevation 2 elope Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 31 Step 3 Identify the layers associated with the input variables These input variable names are extracted from the files you selected in st
45. anobis distance for that single value as Given that Mahalanobis Distance D x m Cc x m 410 500 90 x m 400 500 100 6291 55737 3754 32851 3754 32851 6280 77066 e S 0 00025 0 00015 0 00015 0 00025 0 00025 0 00015 90 Therefore D 90 100 x x 0 00015 0 00025 100 1 825 Therefore our single observation would have a distance of 1 825 standardized units from the mean mean is at X 500 Y 500 Last modified 20 ul 10 Independent Variable 2 MANUAL Land Facet Corridor Designer 56 If we took many such observations graphed them and colored them according to their Mahalanobis values we can see the elliptical Mahalanobis regions come out For example the cloud of data points below are randomly generated from the bivariate population described above Q D gt 20 000 normally distributed random points 800 800 500 600 700 600 700 400 400 300 Independent Variable 2 300 500 200 200 100 100 100 200 300 400 500 600 700 800 900 100 200 300 400 500 600 700 800 900 Independent Variable 1 Independent Variable 1 If we calculate Mahalanobis distances for each of these points and shade them according to their distance value we see clear elliptical patterns emerge Last modified 20 ul 10 MANUAL Land Facet Corridor Designer Mahalanobis Distance Value 0 0 4 0 8 1 4 3 19 Pi Independent Variable 2 300 400 500 600 700 800 900 200 100 100
46. are to calculate the data and follow the examples on p 61 to make sure the data are formatted correctly Mahalanobis values typically reflect the multivariate similarity to the vector of ideal values which are typically but not always the mean values Although the mean elevation slope angle and insolation are meaningful descriptors of a land facet the mean Land Facet Density does not represent the ideal The ideal land facet density would be when the neighborhood was completely covered with this particular land facet i e a land facet density 1 Therefore after you create the mean vector you must change the ideal Land Facet Density value to 1 before running the Mahalanobis analysis Important If you select existing tables for your mean vector and covariance matrix then you must make sure that the order of variables in the tables is the same as the order of variables you use to calculate your Mahalanobis surface Please refer to the discussion of the Mean Vector and Covariance Matrix tables on p 61 for a more detailed explanation of these tables Click the button to run the tool Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 66 Source for Means and Covariances Step 1 of2 gt loj x Mahalanobis distances are calculated based on the means and covariances of a set of variables and therefore the mean vector and covariance matrix must be specified ah The mean vector and covariance
47. ariable to 1 because 1 is the ideal Land Facet Density value v Use the Mahalanobis Distances Create Raster Surface tool Me p 54 to calculate the Mahalanobis Distance value for all cells on the landscape You will choose the 10 Please read the Overview above to understand the rationale for each step in the workflow Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 23 4 5 6 7 8 9 option to use existing mean vector and covariance matrix tables and you will use the data from steps 11 and 111 above vi Use the standard CorridorDesigner tools to create land facet corridors between your wildland blocks Use the Mahalanobis Distance raster from step iv above as the cost surface Use standard ArcGIS tools to combine all land facet categories into a single raster for example the Mosaic to New Raster tool in ArcToolbox gt Data Management Tools gt Raster gt Raster Dataset gt Mosaic to New Raster Make sure that all unique land facets from each raster have a unique value before you combine them Use the Shannon s Index tool p 34 to calculate the diversity of land values within a specified neighborhood around all cells Use the Identify Termini Polygons tool i p 36 to convert the Diversity surface from step 5 into polygons and identify the largest polygons in each Wildland Block Use the Invert Raster tool p 39 to invert the Diversity raster from step 5
48. ations measure how much one variable changes as a second variable changes and in which direction Values range between 1 and 1 with negative values implying a negative relationship 1 e as one variable increases the other decreases Values close to 1 or 1 have high correlation while values close to 0 have low correlation Spearman s rho correlations are identical to Pearson s r except that they are calculated from the relative rank of each value rather than the value itself see Conover 1980 252 Spearman s rho correlations are generally considered more appropriate when the variables are not normally distributed or when the researcher wants to reduce the importance of outliers Warning This tool works well with relatively small datasets N lt 20 000 sample points or so However if you need to calculate statistical matrices for large regions which will require hundreds of thousands or millions of sample locations then we recommend you use the Export to R tool p 24 to create a table of values suitable for analysis in statistical software then use that statistical software to create the matrices See p 61 for a discussion of formatting tips to make sure the tool can read the matrices correctly Click the button to start the process First select the region containing the sample locations If you select a point layer then your statistical matrices will be generated from all your datasets that intersect those points If you select
49. c information system Journal of Wildlife Management 57 519 526 Conover W J 1980 Practical nonparametric statistics 2nd Ed John Wiley and Sons 493 p Cowling R M R L Pressey A T Lombard P G Desmet and A G Ellis 1999 From representation to persistence Requirements for a sustainable system of conservation areas in the species rich Mediterranean climate desert of southern Africa Diversity and Distributions 5 51 71 Cowling R M R L Pressey M Rouget and A T Lombard 2003 A conservation plan for a global biodiversity hotspot the Cape Floristic Region South Africa Biological Conservation 112 191 216 Dimitriadou E K Hornik F Leisch D Meyer and A Weingessel 2009 e1071 Misc Functions of the Department of Statistics e1071 TU Wien R package version 1 5 19 Dickson B and P Beier 2006 Quantifying the influence of topographic position on cougar Puma concolor movement In Southern California USA The Zoological Society of London Journal of Zoology doi 10 1111 1469 7998 2006 00215 x Draper Norman R and Smith Harry 1998 Applied Regression Analysis 3rd Ed Wiley Series in Probability and Statistics 706 p Farber Oren and Kadmon Ronen 2002 Assessment of alternative approaches for bioclimatic modeling with special emphasis on the Mahalanobis distance Ecological Modeling Elsevier Science 160 115 130 Golub Gene H and Van Loan Charles F 1996 Matrix computations 3rd Ed
50. centroids as a comma delimited text file csv The first row of this file should contain the variable names and each row thereafter should contain the X and Y coordinates of the centroids Note These centroids are in graph space or multivariate space not geographic space They are also based on standardized variable data not the original data For example a file containing 4 centroids derived from Elevation and Slope layers will look like the following elevation slope 164016300090946 MeO icy AiG SS 6 17 Ossi chs Z Ice vil ercio Bo O a S T ea a OWNS O 88447 40S596287 7 0 D004 9 153239644100 ZOR SOVAO Ag ers Cho INNS Sy a0 se ols 4 eal e e 2 A file of the standardization parameters i e the mean and standard deviation of each variable as a comma delimited text file csv These values are in units of the original data e g meters of elevation This file will have exactly 3 rows The first row should contain an empty text value then the name of each variable The second row should contain the word mean then the mean for each variable The third row should contain the word sd and then the standard deviation for each variable For example a standardization parameters file for the same analysis illustrated in 1 above will look like the following Lev ae ron MS lopen geen LAZIO SOT Tels 7251 le so44 os T O MesolY 210s 5 1 WIL PIO G4 Ss SS SS S e FS 4s Zs 3 A file of the bin widths used in the
51. contained in LF_R_fxns zip from http www corridordesign org The Zip file contains three files 1 LF_fxns R source code for the R functions for defining land facets 2 LF code R sample code for using the R functions in LF_fxns R 3 sample data csv a sample data set Workflow For Defining Land Facets 1 Use the Export for R Analysis tool in the Land Facet Corridor extension to ArcGIS to export topographic and soil data from ArcGIS in a format compatible with R 2 OpenR Open the LF code R file by selecting Open Script from the File menu and navigating to and selecting the LF _ code R file This file contains all of the R code in the workflow below Note that you will need to change the file directories in this code unless your files are located in the directory C land_ facets 4 The R functions for defining land facets depend on R packages ks e1071 lattice clusterSim and nnclust Install these add on packages install packages ks install packages e1071 install packages lattice install packages clusterSim install packages nnclust 5 Load the R functions for defining land facets into the workspace using the source function source file C land_facets LF_fxns R The file argument to this function is the location of LF_fxns R Execution of this file also loads the add on packages in Step 3 into the workspace 6 Set the working directory setwd c
52. d for land facets served 25 of 28 focal species as well as or better than the focal species designs in these landscapes The three species better served by the focal species approach had the most narrowly distributed habitat Compared to land facet designs focal species linkages provided a similar degree for only about half the land facets These results suggest that a linkage design based on land facets will serve all or most focal species in most landscapes but it will not serve focal species that have limited habitat available in the study landscape Therefore we recommend using the land facet approach to complement rather than replace focal species approaches Because the land facet design tends to be larger than the focal species linkage design and because the land facet design will serve most focal species it is more efficient to start with the land facet design and then overlaying the focal The user can select a different threshold 8 The user can select a different percentage Last modified 20 ul 10 MANUAL Land Facet Corridor Designer species corridors and expanding the design to better serve species not well served by the preliminary linkage design Last modified 20 ul 10 13 MANUAL Land Facet Corridor Designer 14 Digital elevation model of entire planning area Compute topographic variables Use kermel density estimation to remove 10 of cells within each topographic position 1 e
53. data that are suitable for analysis in R or some other statistical software package Statistical software provides methods for both FCM clustering as well as metrics to help you decide what number of clusters is best Please refer to the R Functions for Defining Land Facets p 78 for a discussion of the R tools provided with this extension This Export for R Analysis tool exports your data in a format appropriate for analysis in your statistical software Specifically it creates a separate table of data for each unique initial landscape category such as a TPI based Slope Classification raster or possibly a Soil Category raster Each table contains records for each raster cell from that landscape category in your Wildland Blocks with an attribute value for each analysis layer i e values for elevation slope insolation etc at that location Note This tool does not require that all of your data have the same cell size and projection All data will be internally reprojected and resized to match your initial categorical layer before the table is created This tool should be used in conjunction with the R Functions for Defining Land Facets p 78 and then the Land Facet Clusters from R tool p 27 to actually create your land facets on the landscape Click the R button to run the tool Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 25 Select Raster and Feature Layers to Export Ioj x This tool wall expo
54. density ele Los f Exact Cell value at Point Interpolate Value from Four Closest Cells Riasters Only g Back Manual Cancel Nert A You may select both Raster and Polygon Vector datasets for your input variables For raster datasets you also have the option to use either the exact cell value at each point or an interpolated value from the four nearest points Please see the discussion on Exact Values vs Interpolated Points on p 63 for more details on this concept After you have selected your variable layers click the Next button to move on to the last dialog Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 72 Output Options Step 3 of 3 Use this dialog to specify where you want to save your Mahalanobis values Optionally you may save them to a new table to an existing numeric attribute field in your Point feature class or to a new attribute field in your Point feature class Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 73 GENERATING STATISTICAL MATRICES This function provides a quick way to generate tables containing the mean vector covariance matrix inverse covariance matrix Pearson s r correlation matrix and Spearman s rho rank correlation matrix from multiple raster and polygon datasets in your map The mean vector and covariance matrix tables can be used with the Mahalanobis functions described elsewhere in this manual Pearson s r correl
55. dor Designer 65 Using the Tools CREATE MAHALANOBIS RASTER SURFACE This is the primary tool used to generate the cost surface for the Land Facet corridors nobis Distance Surface a 4 Mahalanobis distances are calculated based on the means and covariances of a set of variables and therefore you must either specify existing tables containing the mean vector and covariance matrix or create them on the fly This tool allows both options If you calculate the data on the fly you have the option to define your sample locations by either a point layer or a single category in a categorical raster Note If you are generating Land Facet corridors using the methods outlined in this document and if you are using Land Facet Density as one of your input variables do not calculate the mean vector and covariance matrix on the fly but rather generate them using the Calculating Statistical Matrices tools included with this extension see p 73 Alternatively if you have a large sample size N gt 20 000 or so and you often will then it might be quicker to use the Export to R tool p 24 to create a table of values suitable for analysis in statistical software In general if you have lt 20 000 observations we recommend you use the Calculating Statistical Matrices tool included in this extension because it ensures that the matrices will be formatted correctly If you have a larger sample then we recommend you use your statistical softw
56. e library package ks loads the ks package into the workspace allowing R to access the functions that it contains Note that packages only need to be installed once but they need to be loaded into the R workspace during each new R session GETTING HELP IN R Help files for R functions can be accessed by typing a question mark followed by the function name So read csv opens the R reference manual for the function read csv Help files contain a description of the function information on its usage including the arguments it accepts and the value s that it returns SOME SUGGESTIONS Although commands can be typed directly into the R Console it is often useful to use R s built in text editor click on New Script under the File menu Not only can commands be typed and edited in the editor but selected lines of code can be executed directly from the editor too Simply highlight the code of interest and press CTRL R Scripts lines of commands can also be saved making it easy to document your work or re run the commands at a later date If you read from or write files to the same path frequently it is sensible to set the working directory using the setwd function setwd dir C land_facets Now to read a csv file into R from the working directory just type data lt read csv file example_data csv When you exit R you are given the option of saving the workspace If you do save it the contents
57. e Elevation and divides it by the Neighborhood Standard Deviation Units are in standard deviations Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 45 such that a Standardized Elevation value of 1 would mean that this particular cell is 1 standard deviation higher than the average elevation in the neighborhood 3 Standardized TPI This option takes the TPI values from option above and standardizes them by the mean and standard deviation of all TPI values in the raster A value of 1 would imply that this cell is one standard deviation higher than the average TPI value of the entire TPI raster Note This option is probably less useful than Options 1 and 2 in most analyses and we only offer it because users have requested it This particular option can classify ridges as valleys and vice versa In most types of analyses Options and 2 will make far more sense Neighborhood Types When generating TPI or Slope Classification rasters you will be asked to define your neighborhood You can choose between a circle annulus doughnut shape rectangle or wedge You can also enter your neighborhood parameters in units of either grid cells or map units i e meters feet etc SEE CARE lA TN 1 Circle A circular neighborhood defined by a radius length ey ELL extending outward from the cell center This neighborhood A Ty is composed of all grid cells whose cell centers lie within that distance of the focal cell ce
58. e are referenced by the first left hand subscript and the columns by the second right hand subscript For example data 2 1 1 2484 788 is the value in data at the intersection of row 2 and column 1 To select all entries in a row or column leave the respective subscript blank For example data 2 would return all values in the second row of data and data 2 would return all values in its second column Logical subscripts can be use to isolate subsets of a dataframe that satisfy a specified condition For example data data elevation gt 1000 selects only those rows in data that have an elevation value greater than 1000 Other logical operators include lt for less than or equal to or that s two equal signs back to back for equal to just to name a couple INSTALLING AND LOADING R PACKAGES Many functions are built into the base R environment 1 e functions that automatically come with R Many more functions are supplied as add on packages To install an add on package use the install packages command For example install packages pkgs ks Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 81 installs the ks package for multivariate kernel density estimation You will be asked to select the mirror or repository nearest you for fast downloading Everything else is automatic To use the package the user first needs to load it into the workspace using the library function For exampl
59. e p values serves only to recode the Mahalanobis distances to a 0 1 scale Mahalanobis distances themselves have no upper limit so this rescaling may be convenient for some analyses Please see the discussion on Chi Square transformation on p 58 for more details Click the x button to run the tool Chi Square Transformation Parameters Ioj x This tool will transform a raster of Chi Square values Le Mahalanobis distance values to P values based on the Chi Square distribution with N 1 degrees of freedom IF and only if the H input variables are normally distributed then the Mahalanobis values will follow a Chi Square distribution with H 1 degrees of Select Raster Layer Output Raster Format Mahal ESRI GRID L Chi Square Degrees of Freedom H Varables 1 Output Raster Dataset Mame D arcllS stufPyconsultationbrost climate change T Pl out P_ vals Cancel Manual Select the raster layer of Chi Square values i e the Mahalanobis raster layer from the list and enter the number of degrees of freedom to use in the Chi Square transformation The degrees of freedom should be equal to Number of Variables 1 used in the original Mahalanobis analysis For example if 6 rasters were used to create the Mahalanobis raster then the Degrees of Freedom would be 6 1 5 Finally specify the name of your new raster and where to save it Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 78 R
60. e to Identify Point Layer Select Point Layer f Analyze All Paints n 50 paints C Use Only Selected Points n 8 of 50 points Identify Source for Mean Yector and Covariance Matrix Select Mean Vector Select Covariance Matrix Covariance Matre Cancel Manual l In the first dialog identify the point layer you wish to analyze If any of your points are selected then you have the option to analyze only those selected points Next specify the correct mean vector and covariance matrix These objects must be available as tables in your map document and they must be formatted correctly in order to be recognized as potential Mean and Covariance tables Please see the discussion of the Mean Vector and Covariance Matrix tables on p 61 for explanations of these tables After you have selected your sample point layer mean vector table and covariance table click the Next button to move to the next dialog Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 70 Mahalanobis ariables Step 2 of 3 ol x Select the raster or polygon datasets to extract the sample data from These layers should correspond with the variables used to generate the mean vector and covariance matrix Important Be sure to sort these layers into the correct order Click the Variable j Order tah to see the order af wariahles lister in the necitied Raster Layers Polygon Layers Variable
61. eeuceueceuseseeneees 24 Peon DER An ae ee ee ee ee ec ne ee nn ne ere ee eter 24 Land Facer Chisters TOM R eredoen E eane aE eE E OEE Eea 21 Pona n Ce Too esr E A EA EAA EE AA E E EE 32 Shannon s Index TOO sessccacssinssrnneaardraaiandhacwinaneannsdenaensoraeateaidanwinabeagaasarsigonsadbientdabinowanepieaaibebtuateiansiasadts 34 Identity Termini Polygons Topless ornini a E E N EE E EEEE EDE 36 TOPOGRAPHIC POSITION INDEX TOOLS cciecsintsswiniisnvesrivsneinessvaesaivlaneierdineeniasseei rede aiei 40 DeD er E E ee eee ee ee eee 40 Sales and Nen HOOT MO OCS Teron EE E ONE NEE 41 Classifying by Topographic Position o0ssennnnnnnnnennnnunnnnsrsrrerrrrrrerrrrrrrrrrrrrerrrerrrrrrrrrrrrrrrerrrrrrrrerreeeens 42 A E re B D oe e a E E A A E O E A E O E E O E 44 PN UO OG LES ee E E E a E E AES 45 MS a TIS TOONS PE E E E E I EN E BE IE E E EET 46 Calculate a TPI Re ise cinas arncnidetis ce ona easuab batiaanaasaadnoneduesndstaauiens ede sani snansenideusesyiebunvebeh ai sacihicoesneencoats 46 Create a 3 Category Topographic Position Raster ccccccccccccccecceeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeees 48 MANUAL Land Facet Corridor Designer 4 Create a 4 Category Topographic Position Raster icisernsisns hs iewontinetreidseiaaewns 50 Create a 6 Category Topographic Position Raster cccccccccccccccceceeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeees 52 MAHALANOBIS DISTANCE TOOLS cccecsecsecsececcescecceccecceesscsaceace
62. elevation Standardized Elevation Neighborhood Shape Hemhborhood Options Circle Radius 5 Neighborhood Size Units Cells Set to NoData if any NoData cells in neighborhood Output Raster Format ESRI GRID Output Raster Dataset Mame D arcGlS_stuff consultation brost_climate_change Qutput TPI_2 E Cancel Manual F Simply select your analysis parameters and click OK Please see the sections above on TPI types p 44 and Neighborhood types p 45 if you have any questions on these parameters The output raster will be a continuous floating point raster Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 48 CREATE A 3 CATEGORY TOPOGRAPHIC POSITION RASTER This tool will create a 3 class Topographic Position raster based on TPI values Click the 33 button to run the tool We used this tool in all of our land facet analyses 3 Category Slope Position Parameters P imi X This tool will create a 3 category Slope Classification raster based solely on the Topographic Position Indes of each cell Depending on your threshold values low TP values will be classified as Canyons TPI values around O will be classified as Slopes and high TFI values will be classified as Ridges You may change the Class 1 Canyons Select DEM Raster Layer TFI 4 units Slope_4_ 3 Class Slopes Select TFI Type to create 1 units TPI 1
63. ep 2 above You may select either raster or polygon vector layers Classify Land Facets Step 3 of 4 ol x Select Layers that Correspond with Variables Varable 1 elevation elevation ASS TER Varlable 2 slope zlope RASTER Back Cancel Manual l Step 4 Enter the fuzziness parameter used in the original FCM analysis you may also load this value from a file and the confusion index threshold Only raster cells with a confusion index below this threshold will be included in the Land Facet raster Classify Land Facets Step 4 of 4 oj x Fuzzy C Means Clustering FCM is a method for separating data into some pre determined number of relatively homogeneous clusters FCM does not simply assign each cell to a cluster but rather calculates the strength of membership of that cell to all clusters Cells are generally assigned to the cluster with the highest cluster membership value Fuzziness Parameter The fuzziness parameter p affects how the algorithm classifies data When performing the FCM analysis in A you must Cluster membership u for cell to cluster c calculated as ey where pa d d Euclidian distance between cell i and cluster c centroid a9 Fuzziness parameter we use 1 5 k Number of clusters 2 Highest membership value Highest membership value Confusion Index Fuzziness Parameter 1 5 Load Confusion Index Threshold
64. eraoaanss 6 AGE OCIUIC FH Olt soneneaccanatsxe ser A E setececnotcesnenoets aserdegovorantsceer oter aaueut toner E E 6 Toe Proc E een nee ee E E ee ee ee ee 7 Major Step 1 Define and map land facets ccc cccccccceceeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeees 8 Major Step 2 Develop Maps of Resistance 0 0 0 0 cccccccssssssecsecsessscsssssssssaeeeeeeceeceeeeeeeeeeeeeeeeeeeeeeeeeeeees 10 Major Step 3 Least cost Corridor Modeling ou ccccsssecceccceceeeeeceeeeeeeeeeeeeeeeeeeeeseseeeeeeeeeessesseeeess 11 Major Step 4 Add a riparian corridor if needed ccccccsccseccceceeeeeceeeeeececeseeeeeseseeeeeeeseeeseeseeeess 12 Major Step 5 Join the land facet corridors and corridors for habitat specialist species 06 12 Web based distribution of the tools ccccccessssssecceceeeeeeeeeeeeeseeeessseneeeeeeeeeeeeeeeeeseeeeeesesaaeeeeeeeeeseeseeeegas 16 INSTALLATION OF LAND FACET CORRIDOR DESIGNER TOOLS eee 17 Uninstalling Land Facet Corridor Designer cccccccccscececcececceececcceeceeeecaeacecccecececeeeeeeeeeeeeeeeeeeeeees 19 Copying Land Facet Corridor Designer Tools to Other Toolbars 0 0 0 0 cccccccccccccccccceeeeeeeeeeeeeeeeeeeeeees 20 If the Land Facet Corridor Designer Crashes cccccccccsscccccecccceceeeeceeeceeeeeeeeeeeeeeeeeseseeeeeeeeseseseeeseeeeeeess 21 SAMPLE WOREFLOW eiorinn e EEA 22 LAND FACET CORRIDOR ANALYSIS TOOLS cccccccccccccscccseccesscceeccceucseeecsusceeessseuss
65. es Step 2 of 2 Select the raster or polygon datasets to build the Mahalanobis Distance raster from For raster datasets you have the option to use ether the exact cell value at each point or an interpolated value Fror the four nearest points Please refer to the manual for details d Mahalanobis Variable Order l elevation HMean 1 747 993291 slope 8a Saage gt Covariance Table Covarlance gt Means Table Means Selected Mahalanobis Variables Renigve dd HARR Output Mahalanobis Surtace A aster rcGS_stuff consultation brost_climate_change Mahalanobis a g Back Manual Cancel of P You may select both Raster and Polygon Vector datasets for your input variables For raster datasets you might have the option to use either the exact cell value at each point or an interpolated value from the four nearest points This option is only available if you are generating your mean vector and covariance matrix on the fly from a set of sample points extracted from a point layer Please see the discussion on Exact Values vs Interpolated Points on p 63 for more details on this concept Note If you are performing a Land Facet analysis using Density as one of your variables then you are likely using existing mean and covariance data and therefore you will not see this option Click OK and the tool will produce the Mahalanobis Raster surface and add it to your map Last modified 20 J ul 10
66. eshold value are converted to polygons Typically we recommend using a threshold value of 0 for Land Facet Density rasters so that all regions with any density gt 0 are used or a value the median H value for Diversity rasters so that approximately the greatest 50 of diversity values are used The Wildland Block Polygon Layer dropdown box lists possible Wildland Block polygon layers in your map Note Only polygon layers containing exactly two polygons are listed If your Wildland Blocks are not available in this format then the following standard ArcGIS tools may be helpful 1 Append If your Wildland Blocks are in separate feature classes then this tool may be used to add features from one feature class to the other Location ArcToolbox gt Data Management Tools gt General gt Append 2 Merge If your Wildland Blocks are in separate feature classes then this tool may be used to combine them into a new feature class Location ArcToolbox gt Data Management Tools gt General gt Merge 3 Dissolve If your Wildland Blocks are composed of multiple discrete polygons this tool will combine them into a single multi part polygon object Location ArcToolbox gt Data Management Tools gt Generalization gt Dissolve 4 Multipart to Singlepart If both of your Wildland Blocks are combined into a single multi part object this tool will split them into separate objects Location ArcToolbox gt Data Management Tools gt
67. ex PBM PBM index CH Calinski Harabasz index FSil Fuzzy Silhouette index Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 88 Exporting Information for Land Facet CorridorDesigner Function LF export Description Outputs to the working directory three comma delimited files necessary for compatibility with the Land Facet CorridorDesigner extension to ArcGIS 1 cluster centroids for the optimal fuzzy c partition 2 mean and standard deviation of attributes elevation and slope in the sample data set across all non outliers regardless of cluster these are needed later to standardize your data and 3 value for psi used in function LF cluster the mean and SD of elevation and Usage LF export x k iter 1 Arguments X object returned from LF cluster k optimal number of clusters iter iteration having optimal validity indices for k clusters Necessary only for instances where multiple solutions minimize the within cluster variances for k partitions Output Outputs to the working directory 1 centroids csv which contains the location of cluster centroids for the optimal fuzzy c partition 2 params csv which contains the mean and standard deviations of the attributes in the data set and 3 psi csv which contains the value of psi used in function LF cluster Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 89 Downloading The R Functions For Defining Land Facets Download and extract the files
68. f bins used in the kernel density estimation Same as values outputted in bin_width csv eval points points at which the density estimate is evaluated For each bin this is the center point not the centroid of observations falling in the bin estimate kernel density estimate at eval points Kernel density estimates sum to one H bandwidth matrix This is a technical detail you can ignore h scalar bandwidth 1 dimension only names names of variables in x W weights This is another technical detail you can ignore Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 85 Identify Outliers Function LF outlier Description Function LF outlier is the second step in identifying outliers It first assigns individual cells the kernel density estimate of the bins into which they were grouped Then it identifies which cells occur beyond the user specified density threshold defining outliers This density threshold can be estimated from the plot generated by function LF kde Function LF outlier also outputs to the working directory information about the location of bins containing non outlier cells Usage LF outlier x threshold 90 Arguments X an object returned from function LF kde threshold threshold corresponding to the density contour from contour plot of LF kde beyond which observations are identified as outliers For example a threshold of 90 identifies the 10 of cells beyond the 90 contour as outliers 1 e
69. f pixels in a 100 m radius are pixels of the focal facet type Use aerial photographs to digitize urban or developed areas such as mines that are unlikely to support wildlife movement even if they otherwise are of a focal facet type Assign no data resistance values equivalent to infinite resistance to these pixels This prevents a corridor from being identified through areas unlikely to support species movements We caution against wholesale exclusion of agricultural areas especially if they can be restored to natural vegetation or occupy a large portion of the most productive land facets those with gentle slopes and high soil moisture In addition to linkage for individual land facets you can also design a single corridor with maximum interspersion of land facets To do so our procedures produce a resistance map as follows O Calculate Shannon s index H of land facets in a 5 pixel radius McCune amp Grace 2002 Shannon s index incorporates richness and evenness into a single measure Thus a high index is achieved by not only maximizing the number of land facets within the neighborhood but also by balancing representation of those facets Calculate resistance of a pixel as 1 H 0 1 This formula assigns low resistance to pixels with a high diversity index As in designing linkages for individual land facets remove areas unsuitable for connectivity from the resistance surface MAJOR STEP 3 LEAST COST CORRIDOR M
70. file should have only a single row with a single numeric value The tool requires that you use the same fuzziness parameter here that you used in the FCM analysis but you can either enter it manually or load the value from a file A file indicating a fuzziness parameter of 1 5 will look like the following Click the button to run the tool You will need to step through 4 dialogs in order to specify all the required analysis parameters Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 29 Step 1 Identify the same categorical raster used in the Export for R Analysis tool p 24 You will also need to identify specifically which landscape category you are creating land facets for Recall that you need to repeat this process for each landscape category Also specify where to save your new land facet raster and in what format All land facets for this landscape category will be in this single raster Optional Save Table with Fuzzy Cluster Statistics Optionally you can generate a table with all the data necessary to create the land facets yourself This is not necessary but it is useful if you want to confirm the output or if you want to know more about the cluster properties of any of the pixels This table will contain one row for each cell in this landscape category The attribute fields will include X and Y coordinates an ID value for the landscape category values for all input variables cluster membership values for all cl
71. g to their iteration In the plot a blue 1 lies underneath each red 2 indicating that there was only one optimal partition for each value of c although performing two iterations does not give much opportunity to identify multiple optimal solutions Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 92 1400 1600 1800 2 Clusters 3 Clusters 4 Clusters Slope 1400 1600 1800 1400 1600 1800 elevation The second plot is a graph of validity indices for each iteration of each c Note that this plot will likely need to be resized to prevent panel text from getting cut off The top two indices are read like a scree plot where an elbow in the plot indicates the optimal number of clusters The middle three indices are minimized for the optimal partition whereas the bottom three are maximized This plot suggests that a four cluster solution is optimal Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 93 Fukuyama Sugeno Average Within Cluster Distance O 8 oO Oo Oo wT oO O 2 i l O m oo a l Xie Beni Xie Beni Davies Bouldin ni wW N D So So S 3 v Iteration gt N O x E 1 S a re A U oOo O Q O 5 ce oO 3 _ a eel Calinski Harabasz Fuzzy Silhouette 2 0 oO e O co S 2 A Q So N T Te N 5 2 2 3 4 S 6 T 2 3 4 5 6 r 2 3 4 5 6 7 Number of clusters c 11 Export information about the cluster analysis LF export x clust k 4
72. hold an argument in LF outlier the next function Function LF kde implements the Hpi diag and kde functions of package ks for bandwidth selection and multivariate kernel density estimation respectively Because raster data sets are large this function bins the data set individual cells in the raster are grouped according their attribute values into bins of equal interval across the range of each variable Kernel density estimation is performed on these bins reducing computation time by several orders of magnitude We experimented with different numbers of bins to develop the recommendations below specifying more bins larger grid size greatly increases computation time without increasing your ability to identify outliers LF kde automatically outputs to the working directory information on the bins used for the kernel density estimation Usage LF kde x gridsize Arguments X the matrix or dataframe containing topographic and or soil data Consists of one row per raster cell and one column per topographic or soil variable gridsize The number of equal intervals into which the range of each variable will be split for the purpose of creating bins Due to memory constraints gridsize 151 is appropriate for 2 dimensional data in this case kernel density estimation is performed on a 2 dimensional array of 151 bins 22 801 bins For 3 dimensional data gridsize 91 is appropriate in this case kernel density estimation is performed on a
73. ifferent proportions of cells with lowest accumulative cost Remove urban or disturbed areas Least cost corridors representing several most permeable fractions of the landscape Select corridor with an approximate minimum width of 1 km Corridor design for land facet Figure 3 Sequence of operations used to design a corridor for one land facet This process is repeated for each land facet The resulting corridors plus a corridor for high interspersion of land facets and a corridor of riparian habitat are then joined to create the linkage design All procedures in this flow chart are carried out in ArcGIS 9 3 The 3 variables are illustrative of the topographic or soil variables the analysts can use We used solar insolation to calculate resistance surfaces for land facets in the slopes topographic position only The user can over ride these default thresholds radius of 3 cells largest 50 of polygons 1 km width The area threshold for defining termini can be adjusted to avoid highly linear corridors Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 16 Web based distribution of the tools The materials available for download include ArcGIS 9 3 tools for designing corridors of land facets including an on line User s Manual These tools must be used in concert with certain statistical procedures outside ArcGIS Source code for the ArcGIS tools A package of statistic
74. ing them from corridor analysis Furthermore if your land facet type is sparsely distributed across the landscape or you use a large neighborhood you could end up with a raster composed entirely of NoData cells Land Facet Land Facet Density Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 34 Shannon s Index Tool Shannon s Index H is a measure of diversity and evenness that reflects both the number and the balance of unique values within an area in this case the area is a moving window H values increase with both the number of classes observed and with how evenly distributed they are There are alternative methods for calculating this index and this tool uses the following Shannon s Index H D p In p i l where p Proportion of observations in land facet i n number of observations in land facet i N Total number of observations S Number of land facets By this formula Shannon s Index values range from 0 to In S where S the number of unique categories 1 e land facets that occur in the landscape Click the 3 button to run the tool Shannon s Index Parameters Ioj x This tool will calculate Shannon s Indes for all cells within a specified circular neighborhood In general higher values reflect more diversity and better balance among Unique values There are multiple definitions of this statistic so please refer to the manual for the exact formula used IF you plan to use the
75. is naturally scale dependent The same point at the crest of a mountain range might be considered a ridgetop to a highway construction crew or a flat plain to an insect living in the soil The classifications produced by this tool depend entirely on the scale you use to analyze the landscape For example in the illustration below TPI is calculated for the same point on the landscape using 3 different scales In each case the point is located on top of a small hill set inside a larger valley In Case A the scale is small enough that the point is at about the same elevation as the entire analysis region so the TPI value would be approximately 0 In Case B the analysis region is big enough to encompass the entire small hill and the point is consequently much higher than its neighbors and has a correspondingly high TPI value In Case C the neighborhood includes the hills on either side of the valley and therefore the point is lower than its neighbors and has a negative TPI value TPI Values at 3 Different Scales A B C Users should consider what scale is most relevant for the phenomenon being analyzed If you are interested in topographic habitat characteristics of large wide ranging animals you would likely define your landscape classifications in terms of large distinctive topographic features Cougars for example may be influenced by a tall ridgeline on the horizon more than by minor ripples immediately surrounding them Furthermore a
76. istinguish between these 2 possibilities is to check the slope angle at that point If the angle is near 0 then the point is probably on a flat area A high slope angle means that the point is on a slope In his poster Weiss demonstrates one possible classification process using both TPI and slope to generate a 6 category Slope Position grid _ Elevation ra 2200m 350m 80 Sample Criteria Set Weiss 2001 Valley TPI lt 1SD O Lower Slope 1SD lt TPI lt 0 5SD O Flat Slope 0 5 SD lt TPI lt 0 5 SD Slope lt 5 Middle Slope 0 5 SD lt TPI lt 0 5 SD Slope gt 5 Upper Slope 0 5SD lt TPI lt 1SD Fa Sel a A X od l y t A w 4 ee A K iS wf PAS i F f A MFE ro J es Slope Position Ridge men Slope Position 500m Neighborhood 2000m Neighborhood TPI Types This tool offers three variations of TPI 1 TPI This is the traditional definition of TPI where each cell is defined as the difference between the elevation cell value and the average elevation of all cells in the neighborhood TPI units are in elevation units such that a TPI value of 10 would mean that this particular cell is 10 units generally meters or feet higher than the average elevation of the neighborhood 2 Standardized Elevation This is very similar to TPI but taken one step farther This takes the TPI defined as Elevation cell value Neighborhood Averag
77. iversity available online Publications from this thesis with Brian Brost as senior author should appear in the peer reviewed literature in 2011 Until now practitioners designed corridors to promote movement of focal species through today s land cover map Because land cover maps are likely to change in this century any corridor linkage based on those maps might fail during climate change By conserving strands of land facets linkage designs based on our new procedures should preserve the arenas that support current and future biodiversity without relying on the modeled responses of the temporary occupants of those arenas Conservation practitioners now have a flexible tool to design and map corridors of land facets at high resolution 30 m or 10 m depending on resolution of the DEM that have a high probability of allowing for animal movement including shifts of species geographic ranges during and after climate change This can enhance the ability to design wildland networks robust to climate change reducing the impact of climate change on the biota of natural landscapes These procedures are transparent and do not depend on global or regional circulation models Introduction In the face of impending climate change improving connectivity among protected wildlands is the primary conservation strategy Hannah et al 2002 Lovejoy amp Hannah 2005 Although there are several ways to enhance connectivity wildlife corridors
78. l communities MjM Software Design Gleneden Beach Oregon Meyer Carl D 2000 Matrix analysis and applied linear algebra Society for Industrial and Applied Mathematics Philadelphia 718 p Moore I D R B Grayson and A R Ladson 1991 Digital terrain modeling A review of hydrological geomorphological and biological applications Hydrological Processes 5 3 30 Neter John Wasserman William and Kutner Michael H 1990 Applied Linear Statistical Models 3rd Ed 1181 p Press William H Teukolsky Saul A Vetterling William T and Flannery Brian P 2002 Numerical recipes in C the art of scientific computing 2nd ed Cambridge Cambridge University Press 994 pages Phillips S J P Williams G Midgley and A Archer 2008 Optimizing dispersal corridors for the Cape Proteaceae using network flow Ecological Applications 18 1200 1211 Sanchez P A et al 2009 Digital soil map of the world Science 325 680 681 Weiss A 2001 Topographic Position and Landforms Analysis Poster presentation ESRI User Conference San Diego CA Available by permission from the author at http www jennessent com arcview TPI_Weiss_poster htm Williams P L Hannah S Andelman G Midgley M Araujo G Hughes L Manne E Martinez Meyer and R Pearson 2005 Planning for climate change identifying minimum dispersal corridors for the cape Protaceae Conservation Biology 19 1063 1074 Last modified 20 J ul 10
79. land facets please let us know If we have time we will do our best to incorporate them into the toolset Notice that on the About Land Facet Corridor Analysis dialog above there is a Suggestions button Just click that button to open up an email pre addressed to Jeff Jenness Compose Question Suggestion for Land Facet Analysis Tools 1 2 6011 z iol x Fie Edit wiew Insert Format Options Tools Help Sa Yy U A Send Contacts Spell ttach Security Save From Jeff Jenness lt jeffji jennessent cam gt Jeff To jefFi jennessent com Subject Question Suggestion For Land Facet Analysis Tools v 1 2 601 Body Text variable width E A A B I U L EE E Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 96 Updates March 31 2010 e Version 1 2 598 Initial Release April 20 2010 e Version 1 2 797 e Added a tool to identify Termini polygons e Added documentation for all tools e Fixed a number of bugs found in various tools April 27 2010 e Version 1 2 805 e Primarily modifed manual to clarify and further explain several tools e Minor modifications to dialog control names June 24 2010 e Version 1 2 808 e Several minor code changes throughout extension e Added discussion of R tools to the manual July 1 2010 e Version 1 2 809 e Fixed a Type Mismatch error that occurred when you clicked the button for many of
80. low insolation ridge A classification that used insolation to define land facets within ridges would identify different land facets for their opposing sides such as north facing and south facing ridgelines despite their otherwise similarity This unnecessarily complicates corridor design because the opposing sides of canyons and ridges are generally close in proximity and can be treated as a unit for conservation purposes Splitting ridges and canyons on insolation would produce redundant corridors such as a cold high elevation steep ridge corridor that is completely intertwined with a hot high elevation steep ridge corridor Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 10 1 Identify outliers i e cells with combinations of values of the continuous variables that rarely occur in the Wildland Blocks and remove them from the analysis These cells often occur in isolated patches and are limited to a small portion of the landscape Outliers produce clusters that span a large fraction attribute space with a diffuse or diluted ecological interpretation Extreme cells also shift the position of the cluster centroid to a sparse region of multivariate space 2 Use fuzzy c means clustering to classify the pixels into c natural clusters or groups for each value of c from 1 to 10 For instance a 3 way split of ridges might include high elevation steep low elevation steep and low elevation gentle classes Beier and
81. ly the Linkage Design for land facets includes o Several typically 5 15 corridors each of which is designed to maximize continuity of one of major land facets that occurs in the planning area Each such strand or corridor is intended to support occupancy and between block movement by species associated with that land facet in periods of climate quasi equilibrium Like each focal species corridor each land facet corridor is produced by least cost modeling o One corridor with high local interspersion of facets to support range shift species turnover and other ecological processes relying on interaction between species and environments The high diversity corridor is also produced by least cost modeling o A riverine strand to support aquatic species nutrient and sediment flows and upland wetland interactions Although such a corridor could be produced by an automated GIS procedure we believe that hand drawing the major riverine connection 1s typically easier and just as accurate Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 8 Wildland Block Wildland Figure 1 Illustration of a multistranded linkage of land facets designed to allow species to shift their range in response to climate change and to support movement between Wildland Blocks during periods of quasi equilibrium Area A optimizes continuity for high local diversity of land facets Other areas provide the best continuity of high insolation steep slo
82. mat comb_facets ESRI GRID W Add 0 1 to all cells to avoid NoData when input cell values 0 Output Raster Dataset Marne DsNarcllS stufPyconsultation brost_ climate change TPL outhlnvert Cancel Manual Simply select the raster to invert the output format whether you wish to add a value to each cell and finally the output filename The tool will then invert the raster and add it to your map document Shannon s Index Inverted Raster Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 40 Topographic Position Index Tools Land Facet Analysis x Land Facet Corridor Tools Y E R Export For R Analysis T Land Facet Clusters from Ri D Calculate Density Surface S Shannon s Diversity Index T Identify Termini Polygons le Invert Raster Topographic Position Index Tools TP Calculate TFI Raster Mahalanobis Distance Tools d S3 Slope Position 3 Category wee About Land Facet Corridor Tools Sa Slope Position 4 Category 6 Slope Position 6 Category Description Andrew Weiss presented an interesting and useful poster at the 2001 ESRI International User Conference describing the concept of Topographic Position Index TPI and how it could be calculated Weiss 2001 see also Guisan et al 1999 and Jones et al 2000 Using this TPI at different scales plus slope users can classify the landscape into both topographic position i e ridge top
83. matrix may be calculated on the fly from WoUr data ether based on point locations or from areas with a particular Catenion wale in A raster In these cazes this tool swil calcite the means x Identify Source for Mean Yector and Covariance Matrix C Generate from point layer Options to Save Additional Data C Generate from categorical raster Options to Save Additional Data f Use existing mean vector and covariance matrix tables Select Mean Vector select Covariance Matis 2 m EEE 3 Correlation 4 Spearman_Aho Cancel Manual Net In the first dialog select the source for your Mean Vector and Covariance Matrix You may either generate them on the fly or extract them from existing tables If you create them on the fly you will have the option to save them as standalone tables by clicking the Options to Save Additional Data button Save Statistical Data Options 0 x W Save Vector of Mean values D NarcllS stuffyconsultation brost climate _change TPL out Means_ 2 dbf a If Save Covariance Matrix stuffyconsultation brost climate changes TP out Covarnance 2 dbf S Save Correlation Matrix sarcGilS_stuffconsultation brost_cimate_change TPI_out Correlation_2 db Cancel Manual oo A After you have specified the source for your mean vector and covariance matrix click the Next button to move to the next dialog Last modified 20 J ul 10 MANUAL Land Face
84. n a Mahalanobis analysis make sure to keep track of the order of the variables dialogs Last modified 20 ul 10 The variables will need to be entered in the same order in the Mahalanobis MANUAL Land Facet Corridor Designer 15 Matrix Yariables Step 2 of 3 Select the raster or polygon datasets to build the statistical matrices from For raster datasets you have the option to use either the exact cell value at each point or an interpolated value from the four nearest points Please refer to the manual for details Raster Layers Polygon Layers 1 slopepos 2 Land Facets Selected Mahalanobis Variables Remove dd 2 RASTER slope Finally choose which statistical matrices you wish to generate and where you want to save them Save Statistical Data Options Step 3 of 3 iol x IW Save Vector of Mean Values D areGIS_stuff consultation brost_climate_change TPI_out Means_2 dbt M Save Covariance Matrix saroGl _stuff consultation brost_climate_change TP _out Covariance_2 dbf M Save Inverse Covariance Matris GIS_stuff consultation brost_climate_change TPI_out Inv_Covariance_2 dbt M Save Correlation Matrix areGlS_stuff consultation brost_climate_change TPI_out Correlation_2 dbt lt Back Cancel Manual Oox s Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 76 Upon completion the tool will add these tables to your map document and open
85. n anytime soon If we can find a way to get ArcGIS 10 to recognize these tools then we will post the solution on the Corridor Design site Installing ArcGIS 9 3 1 Alongside ArcGIS 10 Some of you may also have heard that ESRI was going to change the installation and registration of ArcGIS in such a way that you could install both ArcGIS 9 3 1 and ArcGIS 9 4 now ArcGIS 10 on the same system This was one of the major announcements at last year s ESRI User s Conference and it might be a reasonable solution to allow you to continue using the Corridor Evaluation tools Unfortunately ESRI has backed off from this promise explaining that it turned out to be much more complicated than they had anticipated At this point it sounds like they do not mind if you have both versions installed but you will need to install one of them in a virtual environment such as the Windows XP Virtual Machine available in Windows 7 Professional and Ultimate www corridordesign org Produced with the generous support of USDA Forest Service Rocky Mountain Research Station and Arizona Board of Forestry McIntire Stennis Cooperative Forestry Program Land Facet Corridor Designer http www corridordesign org OVERVIEW OF LAND FACET CORRIDOR ANALYSIS ceesssssecceeeeeeeceeeeeeeteeeseestttssccceeeaaaaeeeeeeeeees 6 EXCCUUIVES SUMMNALY ccciesaneessasasnsneasagnsniaeagnanisasagaanioaiagnsqeasagaaniowenonnniianaaasioniaonaienaseeasapasqeeakoaenstixeaassexaeeacs
86. nce you have created that cost surface raster then you can use the standard CorridorDesigner tools to create the corridor polygons Step 1 First turn off ArcGIS Step 2 Install the Land Facet Corridor Designer tools by double clicking on the file LandFacetCorridor exe and following the instructions The installation routine will register the TopoCorridor dll with all the required ArcMap components The default install folder for the extension is named Land Facet Corridors and is located inside the folder Program Files This folder will also include some additional files and this manual Step 3 Turn ArcGIS back on This tool requires some functions from the ESRI Spatial Analyst extension so you may need to turn on that extension in ArcMap after you have installed it CorridorDesigner refers to the ArcGIS tools to create linkage designs based on focal spp Land Facet Corridor Designer refers to the tools described herein Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 18 Untitled ArcMap arc iew l Joj xj Eile Edit wiew Insert Selection Tools Window Help k a E amp i EA 22 Editor Toolbar AEE 0 2h Laver Graph F E E E Bi S d am Spatial Analyst Layer ee ee Reports Editor h Taski a a Target Al Sues XE Q Gy 4 Add xy Data x FF Add Route Events a 3 a Arccatalog Extensions hl Online Services b Select the e
87. nter sti i zO Yd p en 2 Annulus An annular neighborhood looks like a ring or AHH doughnut defined by an inner and outer radius length extending outward from the cell center This neighborhood i iF a a an is composed of all cells whose cell centers lie within this NAD Wi ring T l 3 Wedge A wedge shaped neighborhood looks like a slice of pie cut out of a circular neighborhood and is defined by a starting angle and ending angle and a radius Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 46 4 Rectangle A square or rectangular neighborhood defined by width and height which will be centered around your focal cell center Cells will be included in the neighborhood if the cell centers lie within this rectangle Using the tools CALCULATE A TPI RASTER This tool simply converts an elevation DEM raster into a TPI raster No further classification or categorization is done Click the I button to run the tool Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 47 Topographic Position Index Parameters ol x The topographic position index reflects the difference in elevation between a focal cell and all cells in the neighborhood This tool offers three methods for calculating TPI which differ in units of the final TPI raster 1 Type TPE Units are in elevation units usually meters or feet Select DEM Raster Layer Select TPI Type
88. ntical TPI value may be classified differently in different areas depending on the variability in their respective neighborhoods This method may or may not be useful in your analysis You would use this method if you felt that cells with high neighborhood elevation variability should have to meet a higher TPI threshold in order to be classified into some category As with TPI values in general neighborhood size is also a critical component of the Slope Position classification process Small neighborhoods capture small and local hills and valleys while large neighborhoods capture larger scale features Small Neighborhood Slope Position Classification Slope Valley eer S S SS eS SS eS eS ee fe fee eS eS eS eS eS eS eS ee _ reer ff fe Se eS eS eS eS SS Se Low TPI Very High TPI Mid TPI Mid TPI Very Low Steep Slope Shallow Slope TPI Large Neighborhood Slope Position Classification L z A Ridge v Ridge 4 Middle i Slope Valley E i 4 g l j i i i Valley i 4 a j4 4 1 4 4 1 4 4 4 1 4 l 4 1 y 4 4 4 1 j i j 4 j 4 1 4 4 4 4 4 j 4 4 1 4 4 4 l p 4 1 Very High TPI Very Low TPI Mid TPI High TPI Very Low Steep Slope TEI Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 44 TPI values near 0 mean only that the elevation is close to the mean elevation of the neighborhood cells and this could happen if that cell is in a flat area or if it is on a slope An easy way to d
89. odatabase History Rename C Geodesic Tools C Geometric Network Editing Delete L Georeferencing C Graphics Reset Graphics and Shapes Layout C Mahalanobis Tools Map Cache Keaen adimen He Close You should now see the Land Facet Corridor Designer Uninstalling Land Facet Corridor Designer 1 Click the Start button 2 Open your Control Panel 3 Double click Add or Remove Programs 4 Scroll down to find and select Land Facet Corridor Tools 5 Click the Remove button and follow the directions Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 20 fe Add or Remove Programs i f Oj x 7 Currently installed programs Show updates Sart by Mame Change or Remove Programs F HDF Explorer Size 24 16MB a i hp color LaserJet 2550 series Size 127 00MB 5 HF Software Update Size 0 84MB Add Mew Programs if InteR PRO Ethernet Adapter and Software S JavalTh 6 Update 18 Size 91 04MB O a Land Facet Corridor Tools Add Remove windows Components To change this program or remove it from your computer click Therge Ramaz Change Remove i Click here For support information iH Lizardtech Divu Control Size 0 84MB SI s Logitech Desktop Messenger Size 13 08MB Access and Defaults J Logitech SetPoint Size 16 88MB i MathType 6 Size 11 735MB Copying Land Facet Corridor Designer Tools to Other Toolbars
90. ographic Position raster p 40 Use the Export for R Analysis tool p 24 to export tables of data one for each class in step 1 above to R or some equivalent statistical software package This tool also allows you to restrict exporting data to only those regions within wildland blocks or any polygon layer For each Class from Step 1 do the following a b c Use your statistical software to import the appropriate data table from Step 2 and perform Fuzzy C Means Clustering to determine the appropriate number of clusters and the cluster centroids for this class We have provided a set of R tools to assist with this see R Functions for Defining Land Facets p 78 Use the Land Facet Clusters from R tool p 27 import the statistical output files and classify each original class from Step 1 into multiple land facet categories For each Land Facet category do the following 1 Use the Calculate Density Surface tool Q p 58 to compute the density of this land facet within a specified neighborhood 11 Use the Identify Termini Polygons tool U p 36 to convert the Density surface into polygons and identify the largest polygons in each Wildland Block 111 Use the Statistical Matrices Vector and Raster Inputs tool Pr in the Mahalanobis Distance Tools menu p 73 to calculate a vector of mean values and a covariance matrix for all your variables iv Change the mean value of the Land Facet Density v
91. one occurrence of the facet within a 3 cell radius into polygons and retains the largest 50 of these polygons in each respective wildland block as termini The user can over ride these settings In 3 Arizona landscapes the largest polygons produced by these settings always contained a high density of the focal facet type Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 12 e Retain the largest 50 of the polygons as termini o Calculate the cost weighted distance cumulative resistance from each terminus and sum the two resulting raster outputs to produce the corridor results o Select a slice cost contour of the corridor output that is approximately 1 km to 2 km wide as for the least cost corridors for individual land facets MAJOR STEP 4 ADD A RIPARIAN CORRIDOR IF NEEDED As stated above we recommend using soil attributes to define land facets when good soils data are available but often they are not available When soil variables can t be used we suggest using presence of streams standing water or riparian plants to map important moist soils In arid southwestern United States for example typically only 1 or 2 of several watersheds in a potential reserve or linkage area support perennial stream flows Thus even without a good soil map conservation planners can prioritize the impervious soils associated with these watersheds Similarly vernal pools and karst lakes are features related to soil and
92. ool creates land facet termini polygons within the Wildland Blocks based on a raster surface such as the Density surface p 24 or the Shannon s Index surface p 34 All regions with cell values greater than some specified value are considered eligible to become termini polygons In practice we recommend using X gt 0 for Density surfaces and H gt Median H for Diversity surfaces Not all regions that are eligible to become termini polygons are necessarily desirable as corridor termini A very small island of a land facet within a Wildland Block may be too small to be a meaningful corridor terminus Generally we want to connect the largest concentrations of land facet type within each Wildland Block and therefore we only want to retain the larger termini polygons This tool takes several steps to identify the appropriate termini polygons within each Wildland Block 1 First it identifies all cells above the specified threshold within each Wildland Block i e with a Density value above 0 or with a Diversity value above the median value 2 It then aggregates those cells into disconnected polygons Cells that touch along an edge or at a corner are considered part of the same polygon 3 It then calculates the area of the largest polygon within each Wildland Block 4 Analyzing each Wildland Block separately it compares the area of each polygon in that Wildland Block with the area of the largest polygon in that block from Step
93. pes area B low elevation gentle canyons area C and low elevation gentle ridges area D Area E encompasses the region s main river and its only perennial tributaries from each wildland block In practice a design would include about 10 15 strands but for clarity fewer are illustrated here The conceptual approach to using land facets in conservation planning is described by Beier and Brost 2010 we recommend this paper as an accessible introduction to the topic We describe our procedures in the following narrative in terms of five Major Steps The details of the first three Major Steps are illustrated in two flow charts Figures 2 and 3 MAJOR STEP 1 DEFINE AND MAP LAND FACETS Ideally soil attributes should be used along with topographic attributes to define land facets Unfortunately soil maps have many limitations Sanchez et al 2009 For instance polygons may lack values for a certain attribute or contain several states of that attribute indicating the presence of unmapped heterogeneity In most nonagricultural parts of the western United States soil maps consist of large heterogeneous polygons from which inferences about relevant traits such as moisture texture depth or soil nutrients cannot be made Beier and Brost 2010 Therefore in this description of the approach land facets are based only on topographic Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 9 variables Because the approach can use
94. point on top of a small hill at the bottom of a canyon may be classified as a canyon bottom at one scale or a hilltop at a different scale Both are valid classifications the user must decide what scale is reasonable for their analysis Scale is determined by the neighborhood used in the analysis The TPI values reflect the difference between the elevation in a particular cell and the average elevation of the cells around that cell The Neighborhood defines what cells are considered to be around that cell In the illustration below TPI values were calculated using 2 different neighborhoods The left example used a circular neighborhood with a 500m radius meaning that the TPI value for each cell reflected the difference between the elevation of that cell and the average elevation of all cells within 500m of that cell The example on the right used a circular neighborhood with a 2000m radius Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 42 Elevation 350 650 0 0 350 650 500m Neighborhood TPI 2000m Neighborhood TPI These examples used circular neighborhoods but other options are available Weiss examples used annular ring or doughnut shaped neighborhoods where only cells within a specified distance range are considered Some researchers use rectangular neighborhoods although in most cases circular or annular neighborhoods are more reasonable Wedge shaped neighborhoods are useful for restricting
95. rations for each value of c The function automatically computes eight cluster validity indices used to determine the optimal number of clusters for the given data set Once complete this function generates two plots The first is a plot of cluster centroids for each iteration of each c which 1s useful for detecting cases in which more than one partition for a given c minimizes the within cluster variance The second plot graphs the validity indices for each iteration of each c which is necessary for identifying k the optimal number of clusters for the given data set The Fukuyama Sugeno and Average Within Cluster Distance indices are interpreted as a scree plot where an elbow in the plot indicates the optimal number of clusters The Xie Beni Xie Beni and Davies Bouldin indices are minimized for the optimal number of clusters whereas the PBM Calinski Harabasz and Fuzzy Silhouette indices are maximized Usage LF cluster x nclust c 2 7 niter 30 psi 1 5 max 1000000 Arguments X the matrix or dataframe containing topographic and or soil data minus rows identified as outliers by function LF outlier Consists of one row per non outlier raster cell and one column per topographic or soil variable nclust range of values of c for which to perform the cluster analyses niter number of iterations of the cluster analysis to perform for each value of c psi a weighting parameter that determines the overlap between clusters A crisp clas
96. rt multiple raster and polygon datasets to tables of data suitable for analysis in a stand alone statistics program such as A twill produce a separate table for each unique category it finds in the specified categorical raster Select Categorical Raster slopepos Select Hasters to Export 14 Land Facets 2 18 elevation 19 hillshade 20 insolation 21 slope Select Feature Classes to Export 1 Canopy Density Density saat hd Add Hew Remove __Clear All Clear All Add combined roulti band raster to map M Clip data to Polygon layer f3 habitat blocks a i Format dBASE dbf Folder D areGIS_stuffsconsultationsbrost_climate_change Qut2 pe Cancel Manual oK A Select Categorical Raster You must provide an initial categorical raster This breaks up the landscape into your initial categories e g Topographic Position Classes or Soil Classes This tool will generate a separate table for each unique category value it finds in your raster Later you will generate separate sets of land facets within each category This initial categorical raster is also used as the template for all other data used in the analysis The output tables produced by this tool will have rows of data reflecting cell locations from this raster If your other data are in different projections or have different extents or cell sizes then those other data will be reprojected re
97. s flow chart The outputs from R land facet code and mean value of each variable for each pixel are then used by ArcGIS to carry out the procedures in Figure 3 These 4 variables were useful in landscapes we analyzed the analyst can select other topographic or soil variables The user can over ride these default thresholds 10 of cells 0 6 value of confusion index We identified outliers and clusters with respect to elevation and slope for cells within the canyons and ridges topographic positions Elevation slope and insolation were used for cells within the slopes topographic position Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 15 DP aT OT aS OORT AT mma Compute density of land facet in 3 cell neighborhood Land facet raster for planning area Group all cells within a 3 cell radius of a land facet into polygons Elevation raster for planning area Slope angle raster fo Ae Extract polygons gt half planning area the size of largest polygon in each respective wildland block Corridor termini Insolation raster for planning area Ge ee 6 6 ee eee ee eee a ee eee eee eee Sane eT aa 7 Ye ar onscenen mbteh une enenen mies eben meee Resistance surface Calculate Mahalanobis distance If necessary exponentiate resistance surface to avoid linear suboptimal corridors Modified resistance surface Least cost analysis Cost distance raster Extract d
98. s species distributions and land cover factors that will change wih large scale climate change One method to develop corridors that accommodate species shitting distributions is to incorporate climate models into their design But this approach is enormously complex and i _jprone to error propagation because i involves many linked highh uncertain Sr Carnie oie Seer erie lobes seed pesos eire latinn eee is a ee a ee ee Lc i ee ee TEM 1 2 605 l Available At Atto www Corridorbesign org Contact us Jeff Jenness jeff jennessent com Brian Brost bmbrost email com Paul Beier Paul Beie rnau edu The About dialog includes links to the Corridor Designer website as well as email links to all the authors The full manual in PDF format is available by clicking the Open Manual button Documents Related to Land Facet Analysis The Additional Docs button on the About dialog above will open a list of documents that may be of interest Simply select the documents you wish to open and click OK and your computer will open them for you Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 95 Suggestions for Improvements We want these tools to be as useful as possible to you and we definitely want to correct any bugs that you might find Many of the tools currently available here came directly from user suggestions If you have any ideas for new methods or metrics for creating and analyzing
99. scacsecescssssessesaceaceacasereessssaeeaceae 54 Discussion of Mahalanobis Distances sterii eg e p aaea a e a a a a esia 54 General CONCEDIS erea aa ee ee ee ree 54 RE Scaling Mahalanobis Distances using Chi Square P values cccccccccccccccccccccccceeeeeeeeeeeeeeeeeeeeees 58 Applications to Landscape Analysis ericeira eee E E axe aes 59 Mean Vector and Covariance Matrix Tables cccccccccccccsssseeessnnneceeeeeeeeeeeesssseesesssneaeeeeeeeeeeeeeeeeegs 61 Statistical Matrix Definitions and Formulae ccccssssccccccceeccceeeesseeeeesnnsneeeeeeeeeeeeessssseeessnsnaaeeees 62 Exact Values vs Interpolated V allics 260 stere it ciereusd hewn een oleate vetdastae ewer a ea a a e 63 Additonal IRE AC NINO erea nes ato Ese oO 64 Usine Die FOO S paces vcesctasec pesto seated ctecte seek acinoanGeseo seein rad eatecme sank asnoerGhesne a necaetaceeaeeahaestececaueaeeetteset eas 65 Create Mahalanobis Raster Surface cccssccccccccsssssssseeccenssscccccessessssesssssecnccesssaecceeeessssessseeseees 65 Calculating Mahalanobis Values at Sample Points cccccccccccccceceeeceeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeees 69 Generating Statistical Matrices ies tactile aed Macca ett ed See ee ah el Seas 73 Chi Square Raster TransToN aini tincaaaldassadaadancadeidssaneadtuntadalaeaidaaceauessouseseadeas 77 R FUNCTIONS FOR DEFINING LAND FACETS pesani a A R 78 ATE a a a a a tteadee mesa snde sh etntdamess tad 78 Usna R asa Or el O
100. sification i e no overlap between classes corresponds to psi 1 larger values of pSi produce increasingly fuzzy classifications Based on our limited experimentation we recommend using the default value of 1 5 we welcome feedback from users who experiment with different values max the maximum number of observations upon which to perform the cluster analysis Provided to avoid memory limitations encountered on large data sets Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 87 Details Depending on the size of the data set this function could take hours to complete For example testing nclust c 2 7 and niter 30 on a data set containing 2 attributes and 256205 objects took 6 hours to complete on a Microsoft Windows XP platform with 3 0 GHz Intel Core 2 Duo processor Computation time increases with the size of x raster cells in your landscape which you cannot control the number of values of c to be evaluated we never found an optimum at c gt 5 SO We recommend stopping at c 7 unless your validity indices suggest that additional values should be tested and number of iterations we recommend stopping at 30 Value centroids location of cluster centroids for each iteration of each c validity validity indices for each iteration of each c Contents C number of clusters Z Iteration FS Fukuyama Sugeno index AWCD Average Within Cluster Distance XB Xie Beni index XB_star Xie Beni index DB Davies Bouldin ind
101. site under the Manuals section An excellent but not free reference that covers data handling graphics mathematical functions and a wide range of statistical techniques in R 1s The R Book by Michael Crawley An R Primer After installation R can be started like any other application that is by double clicking the R icon This opens the R Console the window through which the user communicates with R The gt symbol at the beginning of the input line in the R Console is the prompt from the application after which an expression is entered for R to evaluate If the expression is complete R returns its product If it is incomplete the prompt changes to a to indicate more input is required Any text after a is ignored by R which is a simple way of embedding comments in lines of R code USING R AS A CALCULATOR Arithmetic expressions can be typed directly into the R console If the expression in red is complete the line is evaluated and the result in blue is printed The 1 at the beginning of the response is an index indicating that what follows is the first and in this case only element of a numeric vector For example 5 1 1 4 7 10 2 1 35 ASSIGNING VALUES TO OBJECTS R is an object oriented language which means that variables data functions and results are stored in the form of objects All currently defined R objects are contained in the R workspace Objects have a name and the
102. sized and rescaled to match this initial raster If you use any polygon layers then those polygon layers will be converted to a raster with the same extent projection and cell size of this initial raster If you do not wish to use any initial categorization of your landscape 1 e if you just want to consider the entire landscape as a single category you still must specify a raster which designates the enter landscape as a single class because the tool needs to use this raster as a template You can easily create a constant value raster with the raster calculator or the ArcTool Create Constant Raster ArcToolbox gt Spatial Analyst Tools gt Raster Creation gt Create Constant Raster Make sure to set the raster to the appropriate cell size and extent You can use the Topographic Position Index tools p 40 to create topographic position class categorical rasters Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 26 Rasters To Export This list shows all rasters in your active map Select all the ones you wish to include in the data tables Feature Class to Export If you wish you may also add data from polygon feature classes Click the Add New button to show a list of polygon layers in your map and select both the layer and appropriate attribute field Select Feature Layer and Yalue Field Ioj x Select Feature Layer and Mumeric Attribute Field to convert to a raster The feature class attribute
103. ster 2121 Slope Raster 18 18997 54 0 00046 0 01173 Therefore D c s mad oone a Elevation Raster at hei ere gone cae x Slope Raster 18 18997 0 00046 0 01173 Slope Raster 18 18997 Mahalanobis Distance Raster Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 60 Elevation 1600 2000 2400 10 200 aes Mahalanobis Distances Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 61 MEAN VECTOR AND COVARIANCE MATRIX TABLES The Mahalanobis tools included with this extension require a vector of mean values and a matrix of variance covariance values The Mahalanobis Raster tool p 65 can calculate these means and covariances on the fly while it conducts the Mahalanobis analysis or extract them from existing tables in your map document The Mahalanobis Values at Sample Points tool p 69 requires that you use existing tables If you use the Covariance tools provided with this extension see Generating Statistical Matrices p 73 then the tables will be formatted correctly However if you have used another statistical software package to create these tables then make sure the tables are formatted as follows Formatting Rules for the Mean Vector Table 1 Must have only a single attribute field which contains the mean values for each variable 2 This single field must be numeric 1 There is no restriction on the name of this field
104. t Corridor Designer 67 Mahalanobis ariables Step 2 of 2 Select the raster or polygon datasets to build the Mahalanobis Distance raster from For raster datasets you have the option to use either the exact cell value at each point or an interpolated value Fror the four nearest points Please refer to the manual for details Raster Layers Polygon Layers Variable Order from table 1 slopepos 2 Land Facets 3 elevation 4 slope Selected Mahalanobis Variables Hemave Aco HAR Output Mahalanobis Surtace Faster rcGS_stuff consultation brost_climate_change Mahalanobis Manual Cancel al A Select the raster or polygon datasets to use in the analysis These layers should correspond with the variables used to generate the mean vector and covariance matrix In our analyses using land facets to design corridors we used the density of the land facet slope elevation and insolation as variables for land facets within the Canyon Bottom or Ridge topographic positions We used these variables plus insolation for land facets within the Slopes topographic position See the Overview for an explanation Important Be sure to sort these layers into the correct order Click the Variable Order tab to see the order of variables listed in the specified Covariance Matrix selected in the previous dialog Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 68 Mahalanobis ariabl
105. t modified 20 ul 10 MANUAL Land Facet Corridor Designer 5 SUGGESTIONS FOR IMPROVEMENTS lorraine E A E EE E TNA EE 95 UPDA TE y aA A E E A E EA O 96 LITERATURE CITED erronei O E EE A 97 Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 6 Overview of Land Facet Corridor Analysis Executive Summary Land Facet Corridor Designer is a geographic approach to designing wildlife linkages that will be useful in the face of impending climate change This novel GIS based procedure identifies the geographic portion of a region that maximizes continuity and diversity of landscape units defined by topographic and soil traits such as high elevation north facing slopes with rocky soils or low elevation flats with thick soils that are expected to facilitate wildlife movement We refer to these topographic soil units as land facets The rationale is that future vegetation and indirectly animal assemblages and human land uses will be determined primarily by the interaction among land facets soil and topography and future climate regimes The conceptual basis for this approach was recently published Beier P and B Brost 2010 Use of land facets to plan for climate change conserving the arenas not the actors Conservation Biology DOI 10 1111 1523 1739 2009 01422 x Land Facet Corridor Designer is explained in detail and applied to three landscapes in Arizona by Brost 2010 MS Thesis School of Forestry Northern Arizona Un
106. the 10 of cells with the lowest kernel density estimates would be identified as outliers Output This function outputs to the working directory grid csv a comma delimited file that contains the location of bins containing non outlier cells Value outlier a vector of length nrow x consisting of values 0 indicates non outlier or 1 indicates outlier density a vector of length nrow x containing the interpolated kernel density for each object in x Each raster cell is interpolated by assigning it the density of the bin in which it falls Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 86 Fuzzy c means Cluster Analysis Function LF cluster Description Function LF cluster is used to classify the non outlier cells into land facets This function implements the cmeans function of package e1071 to perform fuzzy c means cluster analysis an iterative procedure that assigns each raster cell to one of c clusters in a way that minimizes the c within cluster variances Each such assignment is called a partition of the cells Because there may be more than one partition that minimizes within cluster variances for a given value of c you are encouraged to repeat the procedure 30 times iterations take lots of computing time and our experiments suggest that 30 iterations are sufficient to detect such cases Function LF cluster requires the user to specify the range of values of c to be evaluated and the number of ite
107. the Customize dialog up into any of the existing ArcGIS toolbars If the Land Facet Corridor Designer Crashes If the tool crashes you should see a dialog that tells us what script crashed and where it crashed I would appreciate it if you could take screenshots of those dialogs and email them to me at jeff LFCD jennessent com Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 22 Sample Workflow A typical Land Facet Corridor analysis might follow these steps 1 Select or Create an Initial Classification Raster These classes are your first pass at classifying your landscape and each class will be further divided into land facets 2 3 a b c If you prefer not to use an initial classification raster then you will still need to use a raster which designates the entire landscape as a single class A simple way to create this raster would be to use the raster calculator or the Create Constant Raster ArcTool ArcToolbox gt Spatial Analyst Tools gt Raster Creation gt Create Constant Raster to create a raster of some constant value across the entire study area Make sure to set the raster to the appropriate cell size and extent If you already have a general classification raster such as a soil type landform or topographic position raster you may use that Alternatively use one of the Topographic Position Index tools 33 a or 56 to create either a 3 class 4 class or 6 class Top
108. the arguments to each function whereas Details provides information about the function If the function automatically outputs information for compatibility with the Land Facet CorridorDesigner extension to ArcGIS these files are described in the Output subsection Finally the Values subsection lists and describes the values returned by the function The functions are presented in the order in which they are intended to be used They depend on R packages ks e1071 lattice clusterSim and nnclust The last part of this Section Workflow for Defining Land Facets illustrates how these functions are implemented Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 83 KERNEL DENSITY ESTIMATION FUNCTION LF KDE Description Function LF kde is the first step in identifying outliers or cells with combinations of values for continuous variables that rarely occur in a data set Outliers occupy the tails of the multivariate distribution generated from a kernel density estimation a non parametric procedure that estimates the probability density function of a random variable or group of variables This function automatically plots the kernel density estimation allowing the user to determine an appropriate density threshold contour beyond which cells are identified as outliers An appropriate threshold separates regions in attribute space densely populated by cells from those more sparsely populated You will use this thres
109. them Ea Attributes of Means Ol x Ea Attributes of Covariance E ojx ow Means ow elevation slope P o rarasan 0 133a a96995 1 471005 Soi sss i ananos 22225851 ecra aa T oael rera af E le E Attributes of Iny_Covariance e ol xj J om elevation stope Sf of 0 000075 ona E c 000t4t 0 045240 Record 14 1 fol wi gt E Attributes of Correlation F o x sp of Spearman Rho je oj xj om elevation slope ow elevation slope mo st overs a E or soreres ee scora f AE ra Note If you plan to use these tables in the Mahalanobis analysis and if you are using Land Facet Density as one of your variables then you must change the mean density value to 1 before you run the analysis so that the Mahalanobis Distance value will reflect the distance from 1 i e the ideal density value rather than the actual mean Last modified 20 ul 10 MANUAL Land Facet Corridor Designer 77 CHI SQUARE RASTER TRANSFORM This tool will transform a raster of Chi Square values i e Mahalanobis distance values to P values based on the Chi Square distribution with N 7 degrees of freedom If and only if the N input variables are normally distributed then the Mahalanobis values will follow a Chi Square distribution with N degrees of freedom Farber and Kadmon 2003 warn that wildlife habitat variables often fail to meet the assumption of normality so in this case the conversion to Chi squar
110. ts of the TPI type and Slope Angle threshold should be in Degrees Please see the sections above on TPI types p 44 and Neighborhood types p 45 if you have any questions on these parameters The output raster will be a 6 Category Integer raster with the class names in the attribute table Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 54 Mahalanobis Distance Tools Land Facet Analysis X Land Facet Corridor Tools 7 R Export for R Analysis Qe Land Facet Clusters from R D Calculate Density Surface S Shannon s Diversity Index T Identify Termini Polygons iy Invert Raster Topographic Position Index Tools p Mahalanobis Distance Tools Me Mahalanobis Distances Create Raster Surface aie About Land Facet Corridor Tools My Mahalanobis Distances At Points I Statistical Matrices Vector and Raster Inputs x Chi Square Raster Transform Discussion of Mahalanobis Distances GENERAL CONCEPTS Mahalanobis distances provide a powerful tool for describing how similar some set of conditions is to an ideal or prototypical set of conditions and can be very useful for identifying which regions in a landscape are most similar to a prototype in this case a land facet For example in the field of wildlife biology we might define an ideal landscape as that which best fits the niche of some wildlife species Through observation we may find that a wildlife
111. units Standardized Elevation Class 3 Ridges Neighborhood Options TPI 1 units Neighborhood Shape Circle Neighborhood Size Units Cels Radius F A 1 B Set to NoData if any NoD ata cells in neighborhood Output Raster Format ESRI GRID Output Raster Dataset Name D arcGilS_stuffsconsultation brost_climate_change TPI_out Slope_3 _4 Cancel Manual OK A Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 49 The three classes are named Canyons Slopes and Ridges by default but you can change the names by clicking the Reset Class Names button In general the classes are defined as follows Canyons TPIs lt A Slopes A lt 7P lt B Ridges 7PI gt B where A and B are threshold TPI values set by the user The threshold units should be the same as the units of the TPI type Please see the sections above on TPI types p 44 and Neighborhood types p 45 if you have any questions on these parameters The output raster will be a 3 Category Integer raster with the class names in the attribute table In our work designing land facet corridors we experimented with various neighborhood sizes in three diverse landscapes A radius of 5 cells produced land facets that made sense to end users who were familiar with the landscapes we analyzed We used raw not standardized TPI We typically used 6 m and 6 m for A and B respectively but users
112. user can act on them with operators arithmetic logical etc and functions Note that R is case sensitive The assignment operator is the two character sequence Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 79 lt Typing the name of the object will cause R to print out the contents of the object The function Is lists the names of objects in the current workspace whereas the rm function removes objects For example x lt 3 assign the object x a value of 3 X 1 3 y lt 9 X y 1 2 Is list all objects in the current workspace 1 x y rm x remove the object x from the workspace Is 1 y Multiple values can be assigned to a single object using the concatenate function c For example y lt c 2 5 7 assign the object y the values 2 5 and 7 y 1 257 To assign a sequence of integer values to an object place a colon between the first and last numbers of the sequence like this y lt c 2 7 assign the object y the integer values 2 7 y 11234567 USING R FUNCTIONS The structure of a typical R statement is new object lt function arguments where function is the name of a previously defined or built in function arguments 1s a list of one or more arguments specific to that function and new object is the name of a new object containing the product s of the function To illustrate the following statement is used to read data in the format of
113. usters Cluster ID values for the clusters with 1 and 2 highest strengths of membership the confusion index value at this cell and whether or not R classified the cell as an outlier Classify Land Facets Step 1 of 4 Oo x This tool will classify the study area into land facets based on output from A or a milar statistical package In this first step you will select the region to consider for this classification IF you have divided the landscape into topographic position categories and are now planning to classify land facets within a particular Select Categorical Raster Select Raster Attribute Field A Land_Facet_1 6 Land Facets r comb facets o Polvlines Po 9 Land Facet Clip 10 Land Facets _6 11 Land Facets 2 Category Value 2 COUNT Output Land Facet Dataset Output Raster Format ESRIGRID l M Save Table with Fuzzy Cluster Statistics dBASE cbf D areGI5_stuff consultation brost_climate_change Qutput Cell_ Stats_6 dbf Cancel Manual Ad Output Raster Dataset Hame Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 30 Step 2 Identify the CSV files containing the cluster centroids standardization parameters bin widths and bin locations As you select each file the tool will show you the information included in that file as well as the actual file text Classify Land Facets Step 2 of 4 iol x Your statistical an
114. utlier accessed by outlier outlier indicating which rows of data are outliers 1 and which are not 0 To keep things clean let s add this information to a column named outlier in the object data data outlier lt outSoutlier head data elevation slope outlier 1 1655 584 29 4104 0 Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 91 2 2484 788 32 2004 3 2057 512 20 6244 4 2044 320 13 4432 5 1308 766 16 5707 6 1473 009 25 7639 0 Next tabulate the number of outliers in data table data outlier 0 1 89842 10158 That s 10 158 outliers 10 2 and 89 842 non outliers The proportion of outliers 10 2 differed slightly from the 10 you specified because the most extreme 10 of the 22 801 bins contained a bit more than 10 of your 100 000 raster cells O lt i 10 Classify the non outlier cells into land facets using the function LF cluster clust lt LF cluster x data data outlier 0 1 2 nclust c 2 7 niter 2 psi 1 5 max 1000000 Note the argument for niter used here is demonstration only A larger number of iterations for each c 1 e niter 30 is necessary to identify partitions with multiple optimal solutions Once LF cluster is finished iterating it generates two plots Save each of these plots by selecting Save as from the File menu in the plot window The first plot is a graph of cluster centroids for each iteration of each c Centroids in this plot are numbered accordin
115. values will be transherred to the raster cells Select Feature Layer habitat blocks Geographic habitat_blocks Add combined multi band raster to map This option will add a multi band raster layer to your map containing all the analysis layers included as separate bands This is not necessary for the analysis but it might be informative to you just to see how the tool reprojects resizes rescales and clips all data layers to a common format Clip data to Polygon Layer This option is recommended for Land Facet analysis This will clip the input layers so that only those regions that lay within the Wildland Blocks are exported to the output tables By using this option you ensure that the cluster analysis produces clusters that represent regions inside the Wildland Blocks rather than the entire study area Output Tables This tool will produce a separate table for each unique category in your initial categorical raster Each table will be named FuzzyData ClassX where X is the numeric value of the category from the initial categorical raster If a table already exists with that name in your specified folder then this tool will automatically append a numeric value to make the name unique 1 e FuzzyData ClassX 2 FuzzyData ClassX 3 etc The tool will open these tables in your map document so you can review them before analyzing them in your statistical software Upon completion the tool will give you a report
116. xtensions you want to use fat My Places j 3D Analyst poe O Cargill Digitizing Tools E i HM Coridor Designer Tools Customize g spatial Analyst Extensions i j Styles b Options gh Display Source Selection ao ce mE 2 Description emj i Arial Bjen k i Av Spatial Analyst 9 3 na I I IUII III La i Manipulates the extensions Copyright 1999 2009 ESAI Inc All Rights Reserved Provides spatial analysis tools for use with raster and feature data About E stensions You should see the following new toolbar in your map it may also be embedded in your standard ArcMap toolbars rather than as a standalone object weieeauee x Land Facet Corridor Tools Y Export For R Analysis Land Facet Clusters From R Calculate Density Surface Shannon s Diversity Index Identify Termini Polygons saee ltcr Invert Raster Topographic Position Index Tools b Mahalanobis Distance Tools b ae About Land Facet Corridor Tools If you do not see this toolbar then open your Customize dialog by 1 Double click on a blank part of the ArcMap toolbar or Last modified 20 J ul 10 MANUAL Land Facet Corridor Designer 19 2 Click the Tools menu then Customize In the Customize dialog click the Toolbars tab and check the box next to Land Facet Analysis 21x Toolbars Commands Options Toolbars GPS Hew Geocoding LI Ge

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