opengeos/geoai
GeoAI: Artificial Intelligence for Geospatial Data
This tool helps geospatial researchers, environmental scientists, and urban planners use AI to analyze satellite imagery, aerial photographs, and other geographic data. You can input various geospatial datasets like GeoTIFFs or Shapefiles, train AI models for tasks like land cover classification or building detection, and get maps or classified images as output. It streamlines complex AI workflows for practitioners who need to extract insights from spatial information.
2,656 stars. Actively maintained with 52 commits in the last 30 days.
Use this if you need to apply AI models for tasks like segmenting features from satellite imagery, classifying land use, or detecting changes over time without deep machine learning expertise.
Not ideal if your primary need is general-purpose GIS operations without any AI component or if you only work with non-geospatial data.
Stars
2,656
Forks
376
Language
Python
License
MIT
Category
Last pushed
Mar 11, 2026
Commits (30d)
52
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/opengeos/geoai"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related frameworks
torchgeo/torchgeo
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
terrastackai/terratorch
A Python toolkit for fine-tuning Geospatial Foundation Models (GFMs).
DataverseLabs/pyinterpolate
Kriging | Poisson Kriging | Variogram Analysis
OSGeo/grass
GRASS - free and open-source geospatial processing engine
sentinel-hub/eo-learn
Earth observation processing framework for machine learning in Python