I'm writing a dissertation on different parameter settings in GWR . In order to perform tests I'd need the availability of geo-referenced data that show some sort of spiatial correlation (i.e. values are not independent of their geographic position but vary according to space having zones with high values as well as zones with low values). Datasets should have geographical coordinates (i.e. latitude and longitude) and their density patterns should vary. As an example: data with one/two/three centroids or with uniform distribution or data concentrated more in a corner or on the edges of the map, etc..
A good starting point for me was reading this question: http://gis.stackexchange.com How can I conduct Geographically Weighted Principal Component Analysis using ArcGIS, Python and SPSS/R?
However I'm stack in the process of giving these data a spatial autocorrelation. Any idea on how to achieve this? I would appreciate if the code is in either Python or R.
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A good starting point for me was reading this question: http://gis.stackexchange.com How can I conduct Geographically Weighted Principal Component Analysis using ArcGIS, Python and SPSS/R?
However I'm stack in the process of giving these data a spatial autocorrelation. Any idea on how to achieve this? I would appreciate if the code is in either Python or R.
أكثر...