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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 Density Estimation • Simple point density: Golf courses Rockware Point Density in ArcMap Distance=0.3 Distance=3 Point Density in ArcMap Distance=10 Kernel Smoothing • Kernel Smoothing is interpolation 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 Width of Kernel • Determines smoothness of surface – narrow kernels produce bumpy surfaces – wide kernels produce smooth surfaces 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). 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 Kernel Density in ArcGIS Kernel Density • Cell Size = 0.05 • Search Radius = 0.4? Kernel Density • Cell Size = 0.05 • Search Radius = 10 How to select parameters? • What should the cell size be? • What should the search radius be? Origins of Computer Viruses Origins of Email Spam Kernel Density Analysis Amelia O’Connor Kernel Density Output Other tool extensions for kernel density: • • • • • Home Range Tools Animal Movement Biotas Home Ranger 1.5 KernelHR Spatial Stats Toolbox • New in ArcGIS 10 • Additional tools in ArcGIS 10.2 • By Lauren Rosenshein 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? 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 Hot-Spot Analysis Tool 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.ht m • 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.htm l#//009z0000000s000000.htm – http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#/ Understanding_density_analysis/009z0000000w000000/ – http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#/ /009z00000011000000.htm