Incremental Spatial Autocorrelation (ISA)

[AlperALTINOK]

Thanks for this great tool, I am currently using it for hotspot analyses. In some of my ISA graphs, I observe 3-4 sharp peaks, with an obvious distance between them. I am using a point dataset produced from "make query table", so its 1:M joined, and every record has date attribute.

Now I start wondering which records (point pairs?) from my 1:M dataset are producing these peaks? Is there any way to find these recs (or pairs)? If I can see these records on the map, I may comment on possible reasons of SA, whether they are related to months, seasons, or any other attribute.. Since I am not a statistician, please forgive me if I am asking for something technically impossible.

Regards,

[LaurenRosenshein]

Hi Alper,

Thanks for your question.  If I understand your question correctly, you want to know which individual features are related to the peaks in your resulting graph from Incremental Spatial Autocorrelation.  Is that right?

Actually, the peaks in the graph don't represent individual peaks, they represent the entire dataset at a particular distance band.  What does this mean?  Spatial Autocorrelation is a global spatial autocorrelation tool, which means that it is measuring the intensity of clustering for the entire dataset given a particular distance band.  A peak in the graph indicates a distance at which the clustering is the most intense.  So, if you have several peaks that means that there are several distances, or neighborhood sizes, that reflect intense spatial processes (clustering).  That distance band can then be used as the distance band for further analysis, for instance in a Hot Spot Analysis, or as the radius size in a density analysis.  We talk a lot more about using this tool in this free training seminar: Introduction to Spatial Pattern Analysis.

If you are interested in changes in clustering over time, then what you'd want to do is run the Spatial Autocorrelation (Moran's I) tool multiple times using data from different time periods.  You could do this be doing a Select by Attribute on your data and choosing only data from, for instance, the first month of your dataset and running Spatial Autocorrelation on that subset of your data and see how intense the clustering is.  You could then do the same analysis for the next month worth of data, and so on.  We've got some great examples of this type of "change over time" analysis in this tutorial: Spatial Statistics Modelbuilder Tutorial for ArcGIS 10.  The tutorial does a Hot Spot Analysis instead of a Spatial Autocorrelation analysis...but it helps explain the idea.  This video also talks about analysis over time: The Spatial Distribution of Piracy.

Hope this helps!

Lauren Rosenshein
Geoprocessing Product Engineer

[AlperALTINOK]

Hi Lauren,

You (again) made it crystal clear, wiped the confusion, thank you. And I was doing exactly the same what you advised on clustering over time. Just a little question more if you dont mind, not directly related to ISA but OLS;

I could not be sure whether regular OLS  tool is taking "all" records in my 1:M dataset into consideration or first records for each of point features? (or maybe I should ask which spatial analysis tools are able to handle all records in 1:M sets..? (including GWR))

Regards,

[AbrahamCoiman]

Hi, I can't perform this tool, I always have got this message: <type 'exceptions.ImportError'>: No module named ErrorUtils
Failed to execute. Someone can help me?