torchgeo/torchgeo

Health v2 · maintenance only

Adoption not part of the score

4159 stars · 580 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

TorchGeo is a PyTorch domain library, similar to torchvision, providing datasets, samplers, transforms, and pre-trained models specific to geospatial data. It makes it simple for machine learning experts to work with geospatial data and for remote sensing experts to explore machine learning solutions.

Use cases

• train deep learning models on satellite imagery
• load geospatial datasets in PyTorch
• fine-tune pretrained models on Sentinel-2 multispectral data
• do land cover classification with remote sensing data
• semantic segmentation of aerial imagery
• handle CRS-aligned sampling of geospatial rasters
• work with multispectral bands without RGB workarounds
• benchmark models on earth observation data

When to choose

• you want torchvision-style workflows for satellite or aerial imagery
• you need CRS-aware datasets, samplers, and multispectral transforms out of the box
• you want pretrained remote sensing weights like SeCo, MoCo, MAE, or DOFA
• you use PyTorch or Lightning and need geospatial data pipelines

When to avoid

• your project is not Python/PyTorch based
• you only need GIS processing without machine learning
• you need a general-purpose computer vision library without geospatial metadata support

Facets

library · maturity active

machine-learning deep-learning image-processing data-science machine-learning deep-learning computer-vision python cross-platform pytorch torchvision satellite-imagery remote-sensing earth-observation multispectral pretrained-models lightning crs-aware datasets samplers transforms geospatial gpu

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