geomaster
Provides geospatial and Earth observation workflows using GeoPandas, Rasterio, GDAL, Xarray, Shapely, Laspy, PDAL, Google Earth Engine, and STAC/Planetary Computer, covering Sentinel, Landsat, MODIS, SAR and hyperspectral imagery, spectral indices, terrain and network analysis, point clouds, COGs, CRS handling, and spatial ML, with code in Python, R, Julia, JavaScript, C++, Java, Go, and Rust. Use when computing NDVI or other indices from satellite imagery, when running vector overlays, reprojection, or spatial statistics on shapefiles, GeoJSON, or GeoPackage data, when searching STAC catalogs and reading cloud-optimized GeoTIFFs, when classifying land cover or training ML models on Earth observation data, or when doing terrain, hydrology, or point cloud analysis. Not for general non-spatial data analysis or tabular ML.
- Version
- 1.3
- License
- MIT
Pinned to revision df088027ff23, so it is the text this page describes rather than whatever the author pushed since.
Files
- skills/geomaster/SKILL.md
- skills/geomaster/README.md
- skills/geomaster/references/advanced-gis.md
- skills/geomaster/references/big-data.md
- skills/geomaster/references/code-examples.md
- skills/geomaster/references/coordinate-systems.md
- skills/geomaster/references/core-libraries.md
- skills/geomaster/references/data-sources.md
- skills/geomaster/references/gis-software.md
- skills/geomaster/references/industry-applications.md
- skills/geomaster/references/machine-learning.md
- skills/geomaster/references/programming-languages.md
- skills/geomaster/references/remote-sensing.md
- skills/geomaster/references/scientific-domains.md
- skills/geomaster/references/specialized-topics.md
- skills/geomaster/references/troubleshooting.md
Every link opens the file at its source, pinned to the revision this page describes.