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dot density maps arent my favorite, but they can be really rich ways of looking at multigroup segregation. If you know the area a bit, you dont even need a legend to recognize what these categories represent. One thing i havent seen before is a combo of dot density with dasymetric mapping

here im using NLCD to allocate CA's population to only "developed" areas (pixels 22,23,24), which isnt perfect but works pretty well @kylebarron.dev 's `lonboard` continues to impress. This is 15M points (40% of CA's total pop) and embedding the data in standalone html ends up ~450mb w/ no delay

the quality of the allocation is really just a function of the dasymetric mask, so this feels like a pretty useful concept i'll stick in `tobler`. This also lets you play with DGPs other than uniform (e.g. clustered poisson), which can get interesting)