environmental modeling testing gis layer relevancy
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Environmental ModelingEnvironmental ModelingTesting GIS Layer RelevancyTesting GIS Layer Relevancy
1. A Habitat 1. A Habitat Model/FactorsModel/Factors
► Determine potential sighting Determine potential sighting locations of Grizzly bear in a parklocations of Grizzly bear in a park
► FactorsFactors 1. Land cover types 1. Land cover types 2. Species richness 2. Species richness 3. Species interspersion 3. Species interspersion
Agee, J.K., S.C.F. Stitt, M. Nyquist, and R. Root, 1989. A geographic Agee, J.K., S.C.F. Stitt, M. Nyquist, and R. Root, 1989. A geographic analysis of historical Grizzly Bear sightings in the North Cascades. analysis of historical Grizzly Bear sightings in the North Cascades. Photogrammetric Engineering and Remote Sensing, 55(11):1637-Photogrammetric Engineering and Remote Sensing, 55(11):1637-
1642.1642.
2. Raw Data2. Raw Data
► Land coverLand cover
Source: satellite images, digital Source: satellite images, digital aerial photos, land cover data, GAP aerial photos, land cover data, GAP data data
► Existing bear sighting data: 91 Existing bear sighting data: 91 locationslocations
3. Data Layer 3. Data Layer PreparationPreparation
1. Land cover1. Land cover
22 types identified 22 types identified
2. Species richness 2. Species richness
The total number of unique land The total number of unique land cover types in a 3x3 or larger cover types in a 3x3 or larger windowwindow
3. Species interspersion 3. Species interspersion
The number of cells with land cover The number of cells with land cover types different from the center celltypes different from the center cell
3. Data Layer Preparation3. Data Layer Preparation
3 4 5 0 1
6 8 3 1 5
3 4 0 2 1
3 8 0 5 1
6 7 5
5 7 5
8 8 6
8 7 8
Richness
Interspersion
Moving windows
These result in three raster layers
3. Data Layer 3. Data Layer PreparationPreparation
4. The window size can be 5x5, 7x7, 4. The window size can be 5x5, 7x7, 9x9, .....9x9, .....
The optimal window size is the one The optimal window size is the one with the greatest difference in with the greatest difference in richness or interspersionrichness or interspersion
The "difference" can be absolute The "difference" can be absolute value range or variance for richness value range or variance for richness or interspersion or interspersion
5. In addition to the 91 sightings 5. In addition to the 91 sightings sites, generate another set of 91 sites, generate another set of 91 random locationsrandom locations
4. Statistical Analysis4. Statistical Analysis► Determine whether each of the three Determine whether each of the three variables is relevantvariables is relevant
► For each of the 91 sighting sites For each of the 91 sighting sites and and
each of the 91 random sites, each of the 91 random sites, record record
1. Land cover types 1. Land cover types (nominal) (nominal)
2. Species richness (ratio) 2. Species richness (ratio) 3. Species 3. Species interspersion (ratio) interspersion (ratio)
4. Statistical 4. Statistical Analysis .. Analysis ..
• Develop the raster layers firstDevelop the raster layers first• Then generate the 91 random sitesThen generate the 91 random sites• Lastly, extract values for the two Lastly, extract values for the two
sets of 91 sitessets of 91 sites
Tech Tips Tech Tips ► To generate random points, use To generate random points, use
Hawth's tools Hawth's tools http://www.spatialecology.com/htools/tooldesc.php
► If Hawth’s tools does not work for If Hawth’s tools does not work for ArcGIS 10.2, ArcGIS 10.2,
try the following:try the following:
ArcToolBox - Data Management Tools ArcToolBox - Data Management Tools – –
Feature Class - Create Random Feature Class - Create Random PointsPoints
Tech Tips .. Tech Tips .. ► To extract values from the raster To extract values from the raster layers and layers and
export to point shapefiles, use export to point shapefiles, use
Extract values to points in Extract values to points in Spatial Analyst Spatial Analyst
Tech Tips .. Tech Tips .. ► To extract centroids of a polygon To extract centroids of a polygon shapefile, shapefile,
Spatial Analyst Tools -> Zonal -> Spatial Analyst Tools -> Zonal -> Zonal Zonal
Geometry on the polygon shapefileGeometry on the polygon shapefile
► In Zonal Geometry, input your In Zonal Geometry, input your polygon data, the polygon data, the
"zone field" can be anything, and "zone field" can be anything, and make sure the make sure the
"geometry type" is centroid "geometry type" is centroid
► The output is a raster that The output is a raster that contains all the contains all the
centroids of the input polygons. centroids of the input polygons. Then convert Then convert
the "point" raster into a point the "point" raster into a point feature classfeature class
Tech Tips .. Tech Tips .. ►
Tech Tips .. Tech Tips ..
4. Statistical Analysis4. Statistical Analysis
1. Does the allocation of land cover 1. Does the allocation of land cover types differ between the bear sighting types differ between the bear sighting sites and the random sitessites and the random sites
► Null HNull H11: the number of each cover : the number of each cover type used by bear = that of each type type used by bear = that of each type of the random sitesof the random sites Assuming that the random sites represent the entire areaAssuming that the random sites represent the entire area
►22 test test Accept or reject the null Accept or reject the null
►This could have been the case, but the This could have been the case, but the paper tested it in a different waypaper tested it in a different way
4.1 Stats 4.1 Stats
► Null HNull H1paper1paper: % of each cover type used : % of each cover type used by bear = by bear =
% of each type in the % of each type in the entire study areaentire study area
►22 test test
number of categories?number of categories?
in each categoryin each category
number of expected? number of expected?
number of observed? number of observed?
► Land cover types of the area and at bear Land cover types of the area and at bear sighting sitessighting sites
Cover typeCover type %Area%Area Expected#Expected# Actual#Actual#
Douglas FirDouglas Fir 10.110.1 9.29.2 7 7Subalpine fir Subalpine fir 10.210.2 9.39.3 10 10Whitebark pineWhitebark pine 2.2 2.2 1.51.5 8 8Mountain hemlock Mountain hemlock 3.8 3.8 3.53.5 5 5Pacific silver firPacific silver fir 8.4 8.4 7.77.7 4 4Western hemlock Western hemlock 10.110.1 9.29.2 7 7Hardwood forestHardwood forest 1.2 1.2 1.11.1 0 0Tall shrubTall shrub 4.9 4.9 4.54.5 4 4Lowland herbLowland herb 8.5 8.5 7.77.7 12 12…… …… … ….. ….. .. ….. …. ….
Total (22 types)Total (22 types) 100%100% 9191 9191
4.1 Stats 4.1 Stats
► Null HNull H1paper1paper: % of each cover type of : % of each cover type of random sites = % of type in the random sites = % of type in the entire study areaentire study area
►22 test test
number of categories?number of categories?
in each categoryin each category
number of expected? number of expected?
number of observed? number of observed?
4. Statistic Analysis4. Statistic Analysis
2. Does species richness differ between 2. Does species richness differ between the sighting sites and the random sites?the sighting sites and the random sites?
Or whether richness makes a difference?Or whether richness makes a difference?
► Null HNull H22: richness of sighting sites = : richness of sighting sites =
richness of random sites, richness of random sites, Test ?Test ?
► Accept or reject the nullAccept or reject the null
richness of sighting sites = random richness of sighting sites = random sites?sites?
4. Statistic Analysis4. Statistic Analysis
3. Does species interspersion differ 3. Does species interspersion differ between the sighting sites and the between the sighting sites and the random sites?random sites?
Or whether interspersion makes a difference? Or whether interspersion makes a difference?
► Null HNull H33: interspersion of sighting : interspersion of sighting sites = sites =
interspersion of random interspersion of random sites, Test ?sites, Test ?
► Accept or reject the nullAccept or reject the null
Mean interspersion sighting sites = Mean interspersion sighting sites = random sites?random sites?
5. GIS Overlay5. GIS Overlay
► Keep the variables that are tested Keep the variables that are tested significantly different between significantly different between sighting sites and random sitessighting sites and random sites
cover type: ? cover type: ? richness: ? richness: ?
interspersion: ? interspersion: ?
► Prepare a data layer for each Prepare a data layer for each significant variablesignificant variable
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