tippecanoe
openmaptiles
tippecanoe | openmaptiles | |
---|---|---|
7 | 8 | |
772 | 2,294 | |
5.2% | 1.4% | |
8.0 | 8.1 | |
24 days ago | 8 days ago | |
C++ | PLpgSQL | |
BSD 2-clause "Simplified" License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tippecanoe
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Geospatial Nix β create, use and deploy today
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!
- Protomaps β A free and open source map of the world
- How The Post is replacing Mapbox with open source solutions
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Self-Hosted Vector Tiles
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.
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COMTiles (Cloud Optimized Map Tiles) hosted on Amazon S3 and Visualized with MapLibre GL JS
tippecanoe
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How would you generalize a very high density vector map for various zoom levels ?
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.
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OpenStreepMap 2012 vs. 2022
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
openmaptiles
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Fedora 38 Known issues
Openmaptiles uses docker-compose for its work. It fails flat on its face with podman.
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COMTiles (Cloud Optimized Map Tiles) hosted on Amazon S3 and Visualized with MapLibre GL JS
OpenMapTiles
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Headway is a self-hosted alternative to Google Maps which supports 200+ cities across the globe
What is the advantage of this project over something like openmaptiles https://github.com/openmaptiles/openmaptiles
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Show HN: Flatmap β a new tool to create vector tiles from OpenStreetMap data
Flatmap calls into user-defined profiles in 2 places: first when processing each input element to map it to a vector tile feature, then a second time right before emitting all vector features in a layer.
That second call lets you manipulate vector features on each tile using JTS geometry utilities (i.e. merge nearby polygons or lines with the same tags). PostGIS uses GEOS which is ported from JTS so you have access to pretty much the same geometry utilities - often with the same name.
It's definitely not as flexible as a PostGIS based solution - especially if you join faraway features that don't appear on the same tile, but in practice it was enough to port the entire OpenMapTiles schema.
See the basemap layers package: https://github.com/onthegomap/flatmap/tree/main/flatmap-base...
For example see the landcover layer: https://github.com/onthegomap/flatmap/blob/main/flatmap-base...
Which was ported from the SQL contained in: https://github.com/openmaptiles/openmaptiles/tree/master/lay...
Also, this OpenMapTiles PR might help improve your pipeline after it gets merged: https://github.com/openmaptiles/openmaptiles-tools/pull/383
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GraphHopper Routing Engine - Open Source Route Planning
To fully self-host a route planner (e.g. a "Google Maps" equivalent) you need GraphHopper for the routing and two other parts: you also need some visualization aka "maps" (e.g. with OpenMapTiles) and you need the address search (e.g. with Photon).
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parsing Openstreet map layers in python
Probably not the answer you're looking for, but I have been using openmaptiles to pull osm into postgres (in docker using quickstart.sh). If you can talk postgres in python then maybe that is for you?
- A new way to make maps with OpenStreetMap
What are some alternatives?
planetiler - Flexible tool to build planet-scale vector tilesets from OpenStreetMap data fast
tilemaker - Make OpenStreetMap vector tiles without the stack
tippecanoe - Build vector tilesets from large collections of GeoJSON features.
go-pmtiles - Single-file executable tool for working with PMTiles archives
Leaflet - π JavaScript library for mobile-friendly interactive maps πΊπ¦
maputnik - An open source visual editor for the 'MapLibre Style Specification'
TileMaker - A terrain tile mask generator for 3x3 terrain tile sections for game engines.
osmium-tool - Command line tool for working with OpenStreetMap data based on the Osmium library.
photon - an open source geocoder for openstreetmap data