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total generated data set is 144mb,

number of tiles that has smaller size than 100bytes is : 321796

number of tiles that has size between 100b, 1kb is : 13693

number of tiles that has size between 1kb, 5kb is : 8486

number of tiles that has size between 5kb, 50kb is : 5275

number of tiles that has bigger size than 50kb is : 279

empty tiles occupies 32 byte each and avg size for non empty tiles is ~4kb


Added the missing OSM attribution


Thank you :)


You are right, it's my mistake


I don't have the exact size comparison between this approach vs PNG compression, but i guess the difference would be similar to the difference between DEFLATE vs brotli.

I'm curious about what you just asked of me though, i will make the actual measurements, and will update this page with the results when i got time.


Great thanks - perhaps obvious, but worth running the PNGs through something like pngcrush.

I'm thinking about it the other way also, that is could your approach be used to reduce the size of DEMs encoded as PNGs. While I can see brotli being more efficient, by not using a image compression algorithm you perhaps lose out on exploiting the 2D nature of the data, as if I understood correctly when you're compressing the data you treat the tile as a 1D blob of binary data.


just summing the selection area around the cursor


Displaying so many points is something spatial people have struggled with for a long time. Would you consider writing a leaflet plugin that helps with your approach?


I've tried this software and it is super practical, it outputs a nice h264 encoded mp4 file. Configuring video FPS (currently defaults to 15) and having an option 'correspond to device pixel ratio' would be nice though.


Premium version coming soon which will have further features. Scaling for one, but also setting FPS.

When you say 'correspond to device pixel ratio', do you mean 50% scale when on retina e.g.?


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