geospatial-raster-io
Skill0 starsChanged 2 months agoNo licenceView on GitHub
Read, write, align, and normalize geospatial raster and vector data for ML training. Use when working with GeoTIFF/.tif/.tiff, COG, NetCDF/.nc, HDF5/.h5/.hdf, Zarr, shapefiles/.shp/GeoJSON, or the libraries rasterio, xarray, rioxarray, geopandas, fiona, pyproj, GDAL, gdalwarp. Triggers on tasks like "load this GeoTIFF", "tile a raster into patches", "reproject to EPSG:32633", "why is my normalization broken", "nodata / -9999 / NaN in my imagery", "align my label mask to my image", "rasterize these polygons", "burn shapefile into a label raster", "Sentinel-2 bands / SCL cloud mask / BOA offset", "Landsat Collection 2 scale factor", "QA_PIXEL bitmask", "open_mfdataset time stack", "chunk a NetCDF with dask", "compute per-band mean/std for a satellite dataset", or "install GDAL/rasterio on Windows". Also use when a model trains but predictions have black borders, when class counts don't match the legend, or when two rasters "look aligned" but produce garbage.
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