GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.
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Updated
Mar 7, 2023 - C++
GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.
Satellite imagery for dummies.
Open source book: Geocomputation with R
High-level geospatial data visualization library for Python.
A curated list of awesome tools, tutorials, code, projects, links, stuff about Earth Observation, Geospatial Satellite Imagery
Community Datasets added by users and made available for use at large
A list of open geospatial datasets available on AWS, Earth Engine, Planetary Computer, NASA CMR, and STAC Index
Tutorial on geospatial data manipulation with Python
Distributed version-control for geospatial and tabular data
Course materials for: Geospatial Data Science
A Python package develop for transportation spatio-temporal big data processing, analysis and visualization.
Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.
THREDDS Data Server v4.6
OSM in memory
A node-friendly typescript port of https://github.com/awslabs/dynamodb-geo
Python based framework to retreive Global Database of Events, Language, and Tone (GDELT) version 1.0 and version 2.0 data.
(Spatial) data harmonisation with hale studio (formerly HUMBOLDT Alignment Editor)
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