I'm trying to create 50% and 95% core and home ranges in GME and am running into some problems.

First, when I try to to create my KDE raster, occasionally I get a "Failed to create raster dataset" error. Sometimes I get it and sometimes I don't. As you can see here, all I did was change the name and it worked the second time. Anyone know what might be going on? My settings for the KDE raster are: Bandwidth = PLUGIN and Cell size = 30.

Second, if I do successfully create a KDE raster and try to create my home range raster using the ISOPLETH tool, I always get an error saying that the "Arithmetic operation resulted in an overflow". For the home range raster I've used multiple variations for the quantile (i.e., 0.5, 0.95, c(0.5, 0.95), 50, 95) and none of them have worked. Anyone know what might be going on?

Alternatively, I've tried to do the core and home range in ArcGIS 10.3.1 using the Kernel Density Tool (Spatial Analyst Tools). To get the 50% and 95% range, I need to manually reclassify the layer, correct? I've reduced the classes from 9 to 2 and manually set the breaks at 50% and 95%. Unfortunately, it's not producing a smooth home range polygon and has been producing a square for the 95% range. What am I doing wrong? Also, where can I find the actual metric area? While the graphics are nice, it's really the size of the actual area that I'm most interested in; I'm going to be comparing home range size between genders.

  • Percentiles are not the same as percent volume so, the methodology you are describing in ArcGIS is incorrect. – Jeffrey Evans May 5 '16 at 18:52
  • @JeffreyEvans Is the classification based upon percent volume as opposed to percentiles? If so, is there a way that I could base it on the percentile of observations instead? This is an example of a classification that I attempted. – SRPang May 5 '16 at 19:00
  • Without stepping out to Python this is near impossible in ArcGIS. Take a look at this thread (gis.stackexchange.com/questions/189344/…) for guidance in doing this in R. The GME software is mostly calling R so, you should just implement your analysis in the adehabitatHR R library. You will have considerably more flexibility in the models implemented as well as the Hurlbert model for comparing niche volumes. – Jeffrey Evans May 5 '16 at 19:09
  • @JeffreyEvans That's unfortunate. How hard would you say it is to do this? I've never worked with R or Python and think jumping in to this right now but be a bit much for me. While not as good, I do have the areas calculated for the minimum convex polygons so maybe I'll just go ahead and use that unless you think this is pretty straight forward. – SRPang May 5 '16 at 19:45

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