Geospatialml
geospatialml.com
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Overview
GeoSpatial ML is a weekly blog on geospatial machine learning — remote sensing, earth observation, foundation models, and applied ML for understanding our planet. Authors Isaac Corley — Director of Research at Taylor Geospatial focused on geospatial AI and remote sensing.
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GeoSpatial ML is a weekly blog on geospatial machine learning - remote sensing, earth observation, foundation models, and applied ML for understanding our planet. Produced and edited by Isaac Corley & Caleb Robinson. Click to read Geospatial ML, a Substac
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Q&A from the slop trenches
Between the two of us, we reviewed 22 paper submissions this summer, spread across NeurIPS, WACV, and TerraBytes (a geospatial workshop at ECCV). Fifteen of the 22 (68%) contained entirely fabricated citations, fabricated author lists for existing papers,
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Sentinel-2 Paint: Recreate Any Image from Real Satellite Imagery
What colors does the Earth actually come in? We built Sentinel-2 Paint to find out: a script that scours the Sentinel-2 archive for patches of every color the planet shows, and a browser app for playing with the results. Upload a photo and the app rebuild
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Similar but Different: A Benchmark for Measuring Whether Models Actually Use Multispectral Bands
The broad availability of multispectral data is one thing that separates satellite-based machine learning from mainstream computer vision. Sentinel-2 L2A data has 12 surface-reflectance bands, which include visible bands (RGB), red edge, near-infrared (NI
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Running a U-Net Inside the GDAL CLI (Because Why Not)
Disclaimer: nobody should deploy a neural network this way. This post is for the geospatial developer who has, at some point, said the words "I just want a single static binary", "Python is not a real deployment target", or "why isn't this a GDAL subcomma
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