PMTiles VS tippecanoe

I am a novice at GIS and mapping but when I got started I thought a map/tile server was the only way to build mapping webapps.

But, in my admittedly simple application PMTiles can cover a lot of my visualization use cases with a thing Django app doing GEOJson for interactive stuff.

https://github.com/protomaps/PMTiles

This is awesome. Such a great use case for nix.

I do a lot of geospatial processing in the cloud and I've been using Tippecanoe a lot to create vector tiles. It pairs well with PM Tiles for storing on the cloud. It seriously increases the web app performance for massive data sets. I queue these up with ECS tasks to process our json/csv/parquet input and create optimize vector tile outputs.

https://github.com/felt/tippecanoe

https://github.com/protomaps/PMTiles

Tippecanoe would be a great addition to your nix packages. I've been thinking more and more about how Nix could fit into this pipeline.

Great work!

The thing being discussed is designed for cloud, so I think self managed is a better description?

https://protomaps.com/docs/cdn

Self hosting pmtiles is straightforward also, make a file available to a server that supports range requests:

https://protomaps.com/docs/pmtiles#2.-serve-your-file-locall...

It might've just been this: https://github.com/protomaps/PMTiles/tree/main/serverless/aws

There isn't a tool to do that right now. It could be a fit in either https://github.com/protomaps/go-pmtiles or https://github.com/protomaps/PMTiles/tree/main/python - the Go program is faster and more production ready at this point. I imagine if folders are working for you the quantity of tiles doesn't number into the millions, so the Python program might be sufficient.

Feel free to open an issue.

PMTiles

For the next revision of the JS decoder I'm including `fflate` as a dependency so clients can decompress gzipped tile data using JavaScript.

https://github.com/protomaps/PMTiles/blob/master/js/package....

This is awesome. Such a great use case for nix.

I do a lot of geospatial processing in the cloud and I've been using Tippecanoe a lot to create vector tiles. It pairs well with PM Tiles for storing on the cloud. It seriously increases the web app performance for massive data sets. I queue these up with ECS tasks to process our json/csv/parquet input and create optimize vector tile outputs.

https://github.com/felt/tippecanoe

https://github.com/protomaps/PMTiles

Tippecanoe would be a great addition to your nix packages. I've been thinking more and more about how Nix could fit into this pipeline.

Great work!

I'm the author of a few of the tools mentioned in this post!

A convenient new development is instead of using tippecanoe -> go-pmtiles to create PMTiles archives, you can now output .pmtiles directly:

tippecanoe -o bks2.pmtiles mainroad.geojson ...

This is available in Tippecanoe (https://github.com/felt/tippecanoe) v2.17 and later.

Thanks to Felt (https://felt.com) for supporting this open source work.

tippecanoe

Things I have tried so far: - Just using native vector tile conversion as it involves feature simplification. Doesn't work since smallest feature just disappear, resulting in blank regions instead of "averaged" regions. - Using tippecanoe's built in features to drop/merge in densest zones. Results are disappointing because of unexpected (and too big) differences between each zoom level. - Rasterizing the map, sieving, then vectorizing with smoothing. Doesn't work because pixel information are mixed. I would need a way to rasterize while preserving the land-cover category (with some kind of majority filter ?), but haven't find a way to do this with any QGis built-in or plugin feature.

Take a look at Tippecanoe, which is under active development again[0]. The original developer, Erica Fischer (who is wonderful to work with), has a fork[1] where new work is happening.

[0] https://felt.com/blog/erica-fischer-tippecanoe-at-felt

[1] https://github.com/felt/tippecanoe

https://felt.com/blog/erica-fischer-tippecanoe-at-felt