GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.
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Updated
Jun 4, 2024 - C++
GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.
Geocomputation with R: an open source book
🍂🗺️ The most powerful leaflet plugin for drawing and editing geometry layers
A curated list of awesome tools, tutorials, code, projects, links, stuff about Earth Observation, Geospatial Satellite Imagery
THREDDS Data Server v4.6
Tutorial on geospatial data manipulation with Python
Repository for Digital Earth Australia Jupyter Notebooks: tools and workflows for geospatial analysis with Open Data Cube and Xarray
Transform, query, and download geospatial data on the web.
A Python package develop for transportation spatio-temporal big data processing, analysis and visualization.
Community Datasets added by users and made available for use at large
Discover how Matplotlib and Seaborn can help clearly communicate and present your newly acquired insight
Introduction to Geospatial Raster and Vector Data with R
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.
Course materials for: Geospatial Data Science
A node-friendly typescript port of https://github.com/awslabs/dynamodb-geo
High-level geospatial data visualization library for Python.
Satellite imagery for dummies.
OSM in memory
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