Top 18 gdal Open-Source Projects

• rasterio

  6 2,138 8.6 Python

  Rasterio reads and writes geospatial raster datasets

  

Project mention: Building a Dynamic Tile Server Using Cloud Optimized GeoTIFF(COG) with TiTiler | dev.to | 2023-12-21

TiTiler is a dynamic tile server built on FastAPI and Rasterio/GDAL. Its main features include support for Cloud Optimized GeoTIFF(COG), multiple projection methods, various output formats (JPEG, JP2, PNG, WEBP, GTIFF, NumpyTile), WMTS, and virtual mosaic. It also provides Lambda and ECS deployment environments using AWS CDK.

• sf

  17 1,276 9.4 R

  Simple Features for R

  

Project mention: Visualizing shapefiles in R with sf and ggplot2! | dev.to | 2023-08-11

sf

• InfluxDB

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• Fiona

  3 1,124 8.4 Python

  Fiona reads and writes geographic data files

  

Project mention: Friends don't let friends export to CSV | news.ycombinator.com | 2024-03-25

Your issue is that you're using the default (old) binding to GDAL, based on Fiona [0].

You need to use pyogrio [1], its vectorized counterpart, instead. Make sure you use `engine="pyogrio"` when calling `to_file` [2]. Fiona does a loop in Python, while pyogrio is exclusively compiled. So pyogrio is usually about 10-15x faster than fiona. Soon, in pyogrio version 0.8, it will be another ~2-4x faster than pyogrio is now [3].

[0]: https://github.com/Toblerity/Fiona

[1]: https://github.com/geopandas/pyogrio

[2]: https://geopandas.org/en/stable/docs/reference/api/geopandas...

[3]: https://github.com/geopandas/pyogrio/pull/346

• titiler

  6 692 8.9 Python

  Build your own Raster dynamic map tile services

  

• gdal

  3 323 8.7 Rust

  Rust bindings for GDAL (by georust)

  

Project mention: gdal 0.15 is out! | /r/rust | 2023-06-02

gdal 0.15 (repo, docs), a set of Rust bindings for the GDAL library, used for access to geo-spatial data formats, is now out!

• gdal3.js

  4 290 6.3 JavaScript

  Convert raster and vector geospatial data to various formats and coordinate systems entirely in the browser.

• geospatial-wheels

  1 203 4.5

  Geospatial library wheels for Python on Windows

Project mention: Christoph Gohlke's pre-compiled wheels now available on his Github | /r/Python | 2023-05-26

Geospatial library wheels for Python on Windows: GDAL, rasterio, Fiona, etc.

• WorkOS

  workos.com sponsored

  The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  

• geoserver-rest

  1 181 7.7 Python

  Python library for management for geospatial data in GeoServer.

  

• MODIStsp

  1 152 3.9 R

  An "R" package for automatic download and preprocessing of MODIS Land Products Time Series

  

• node-gdal-async

  1 115 8.3 C++

  Node.js bindings for GDAL (Geospatial Data Abstraction Library) with full async support

• gdal-js

  1 114 0.0 C++

  This is an Emscripten port of GDAL, an open source X/MIT licensed translator library for raster and vector geospatial data formats.

• geodot-plugin

  1 95 7.4 C++

  Godot plugin for loading geospatial data

  

Project mention: Geodot - Montar Google Earth en Godot | /r/RafaLagoon | 2023-06-14

Esta librería es opensource: https://github.com/boku-ilen/geodot-plugin

• era5_in_gee

  1 77 2.7 Python

  Functions and Python scripts to ingest ERA5 data into Google Earth Engine

• OpenAthena

  2 61 5.5 Python

  OpenAthena allows common drones to spot precise geodetic locations

  

• GeoPicker

  4 36 8.9 JavaScript

  Geospatial data picker via fast Api Rest interface, not only another simple elevation service.

  

• dsm2dtm

  3 33 0.0 Python

  Generates DTM (Digital Terrain Model) from DSM (Digital Surface Model).

• large_image_wheels

  2 8 6.6 Dockerfile

  manylinux wheel files for girder/large_image dependencies

  

• flood-sim

  1 4 0.0 Python

  This repo simulates water flooding.

• SaaSHub

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• A note from our sponsor - InfluxDB
  www.influxdata.com | 26 Apr 2024

  Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality. Learn more →

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