Faster raster processing in R using GRASS GIS
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Updated
Jun 3, 2024 - R
Faster raster processing in R using GRASS GIS
GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.
Python library for management for geospatial data in GeoServer.
GRASS GIS Addons Repository (Manuals: https://grass.osgeo.org/grass-stable/manuals/addons/ | Linux-logs: https://grass.osgeo.org/addons/grass8/logs/ | Windows logs: https://wingrass.fsv.cvut.cz/grass83/addons/grass-8.3.2/logs/)
Geocomputation with R: an open source book
GRASS GIS - free and open-source geospatial processing engine
A python package that extends Google Earth Engine.
🌐 dynamic tile server for visualizing rasters in Jupyter with ipyleaflet or folium
Tools for cartographic production, surveying, digital image processing and spatial analysis.
R package for spatial data handling https://rspatial.github.io/terra/reference/terra-package.html
A list of all the scale and offset parameters for each raster dataset in Google Earth Engine.
Command line interface (CLI) and Rust libraries for the SpatioTemporal Asset Catalog (STAC) specification
Public Fused UDFs. Build any scale workflows with the Fused Python SDK and Workbench webapp, and integrate them into your stack with the Fused Hosted API.
Raster manipulation for the Julia language
Open Data Cube analyses continental scale Earth Observation data through time
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