topic Re: Spatial Autocorrelation in Spatial Statistics Questions

Spatial Autocorrelation

sarahvoeller — Fri, 12 Feb 2016 23:33:31 GMT

I have samples of individuals from various areas in South and Central America (12 samples, so 12 locations). Each sample has a different number of individuals with a measurement assigned to them. Each sample also has somewhere between 4-40 individuals. So there are coincident data at each location.

I would like to see if there is spatial autocorrelation (clustering/dispersion) among the samples taking into account this measurement. I am using the Spatial Autocorrelation Moran's 1 tool. Having done something similar to this before, I felt each location could only have one value. In the past (using geostatistical analyst), it would just average the values at each location. So I went ahead and did that myself. Thus I had 12 locations, each with one data point. I ran the spatial autocorrelation tool, and there was nothing significant.

I am doing it again without averaging the samples. Thus each location as between 4-40 data points. After running the tool again, it finds significant clustering. However, if there are 12 locations with a ton of data points, I feel this is due to sampleing bias. Is that right?

Any suggestions on the best way to do this?

Re: Spatial Autocorrelation

DanPatterson_Retired — Fri, 12 Feb 2016 23:55:55 GMT

from the help Spatial Autocorrelation (Global Moran's I)—Help | ArcGIS for Desktop

this Optimized Hot Spot Analysis—Help | ArcGIS for Desktop would be worth looking at as well,

Since you have multiple people ascribed to a polygon, one does have to consider how applicable the polygon boundaries are

Re: Spatial Autocorrelation

sarahvoeller — Sat, 13 Feb 2016 00:41:45 GMT

It is actually point data. I read each observation in with a lat and long coord. So there is a couple points on top of eachother in each of the 12 locations. There are a total of 255 points. I suppose the hotspot analysis would idenfity clusters if there were any. I will give that a try and see what results suggest.