grass VS tippecanoe

https://grass.osgeo.org/

    GRASS GIS offers powerful raster, vector, and geospatial processing engines in a single integrated software suite. It includes tools for terrain and ecosystem modeling, hydrology, visualization of raster and vector data, management and analysis of geospatial data, and the processing of satellite and aerial imagery. It comes with a temporal framework for advanced time series processing and a Python API for rapid geospatial programming. GRASS GIS has been optimized for performance and large geospatial data analysis.

We haven't looked at integrating GRASS yet, as we're more interested in data display, not deep analysis. Just another example of a C/C++ library with front end bindings for Python. Numbers are crunched in C/C++, results returned to Python.

Anyone have good advice for where to learn how to use GRASS

Access: GRASS GIS

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