Hi, I'm new to GIS so this is probably pretty simple stuff. I have a set of co-ordinates and I am doing kernel density on it. Rather than randomly just picking an arbitrary search radius is there any way that I can find out what the most appropriate search radius is for my points? I have 20 different categories and they are all quite different in their distribution patterns so I am wary of just applying the same search radius to them all. Thanks.
And with the "Incremental Spatial Autocorrelation" (Toolbox)
I don´t know if it is perfect but I think it´s ok.
Can anyone here give me a feedback if: 1.) it is right to use the "Incremental Spatial Autocorrelation" (Toolbox) searching for the best search radius in density analysis (for the density of the number of observations for house prices - I have point data and want to know the density per point of a unit)? 2.) I have realy problems with the units. The Map is in Meter and I want as a result points per square Kilometer or points per Hectar! - So what I have to do (What output cell size and so on)?
So I have started with the fowolling steps: 1) Integrate (to summarize the points in a area) 2) Collect events (to get a count field) 3) Calculate Distance Band (as shown in the video spatial best-practices) 4) Calculate the "search radius" - one of the inputs for the density tool - Load "Incremental Spatial Autocorrelation" toolbox (as shown in the video spatial best-practices) - Values from Distance Band Maximum Distance = Beginning Distance Average Distance = Distance Increment
