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I think you should play around with GeoServer, and you can start with the examples here. It should be easy enough to follow. GeoServer will be doing something that you have less control over, though, and if you want to actually to interpolation, I'd use QGIS, or if you have money, ArcGIS (it does Kriging easily, which is super-fancy mathematically magical ...


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This is not exactly what you asked for, but it could be a suitable starting point for your heatmap. I created a simple python script for converting geohashes to 3d Google Earth representations. This isn't exactly what you asked for, but if you'd like to create a cool looking thematic map (based on geohash) this will get you started. You can get the code ...


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I created a simple python script for converting geohashes to 3d Google Earth representations. This isn't exactly what you asked for, but if you'd like to create a cool looking thematic map (based on geohash) this will get you started. You can get the code on github here: geohash2kml


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Good thing about open-source is you can see the source code of the heatmap plugin and see how it is calculating the value for each pixel https://github.com/qgis/QGIS/blob/master/src/plugins/heatmap/heatmap.cpp From a quick study of the code this is what the plugin is doing For each point in the vector, Define the area of the output it will affect For ...


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The QGIS 2.2 User Guide Documentation at page 274 contains a section detailing how the different parameters operate such as the cell size, Kernel shape, Decay ratio etc. The following quote from the manual is a basic introduction to using the plugin: "The Heatmap plugin uses Kernel Density Estimation to create a density (heatmap) raster of an input ...


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Here is an older post about "How does QGIS calculate heatmap values?", but may it helps: How does QGIS calculate heatmap values?



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