Kernel density estimation in Python for GIS: bandwidths, GeoTIFF heatmaps and relative risk
Make a kernel density heatmap from points in Python: compare Scott/Silverman, likelihood cross-validation and a fixed planning distance, Gaussian and Epanechnikov kernels and sample weights, export an edge-corrected GeoTIFF with rasterio, show it on a basemap, and map case-control relative risk on Camden's London plane trees.