density estimation converts points to a raster the density of points in the neighborhood of a pixel...
TRANSCRIPT
![Page 1: Density Estimation Converts points to a raster The density of points in the neighborhood of a pixel No “Z” value is used ArcMap has a simple “Point Density”](https://reader038.vdocument.in/reader038/viewer/2022110323/56649d745503460f94a5394b/html5/thumbnails/1.jpg)
Density Estimation
• Converts points to a raster• The density of points in the
neighborhood of a pixel• No “Z” value is used• ArcMap has a simple “Point Density” tool
– Each pixel=number of points within radius• Kernel Density is related to Kernel
Smoothing but different
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Density Estimation
• Simple point density: Golf courses
Rockware
Fail
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Density Estimation Using Kernels
• Creates a raster from points– Weight (attribute) optional– Not really interpolation
• “Kernel function” applied to points near target pixel
• Different functions are available• High parameters make a “wide” pile,
small values make a “narrow” pile
![Page 7: Density Estimation Converts points to a raster The density of points in the neighborhood of a pixel No “Z” value is used ArcMap has a simple “Point Density”](https://reader038.vdocument.in/reader038/viewer/2022110323/56649d745503460f94a5394b/html5/thumbnails/7.jpg)
Width of Kernel• Determines
smoothness of surface – narrow kernels
produce bumpy surfaces
– wide kernels produce smooth surfaces
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Kernel Density in ArcGIS 10• Under Spatial Analyst -> Kernel
Density• The kernel function is based on the
quadratic kernel function described in Silverman (1986, p. 76, equation 4.5).
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Overview• This analysis show where point features are
concentrated.• Estimations are based on probability “kernels”
– regions around each point location containing some likelihood of point presence.
• The width of the kernel is based on the smoothing parameter (h)
• The output is often called a Utilization Distribution (UD) Grid.
• Methods include: minimum convex polygons, bivariate ellipses, adaptive and fixed kernels
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How to select parameters?
• What should the cell size be?• What should the search radius be?
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Other tool extensions for kernel density:
• Home Range Tools• Animal Movement • Biotas• Home Ranger 1.5• KernelHR
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Spatial Stats Toolbox
• New in ArcGIS 10• Additional tools in
ArcGIS 10.2• By Lauren
Rosenshein
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Hot-Spot Analysis
• Layer may show “hot-spot” but is it really?
• Z-score and P-value are required– Z-score = high or low values together?– P-value = random?
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Hot-Spot Analysis
• High z-values indicate a significantly high or low value– 2.5=cluster of high or low
values• P-value is the chance a
pattern is random– 0.01=probably not random
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Citations• Bugoni, L., D'Alba, L., and Furness, R. W. (2009) Marine
habitat use of wintering spectacled petrels Procellaria conspicillata, and overlap with longline fishery. Marine Ecology Progress Series 374:273-285.
• Mitchell, Brian R. (2007) Comparison of Programs for Fixed Kernel Home Range Analysis http://www.wildlife.org/wg/gis/newsletter/jun06/hrcompar.htm
• Silverman, B. W. Density Estimation for Statistics and Data Analysis. New York: Chapman and Hall, 1986.
• ArcGIS 10 resource center; Kernel Density (Spatial Analyst) http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//009z0000000s000000.htm– http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#/Un
derstanding_density_analysis/009z0000000w000000/– http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//00
9z00000011000000.htm