Individual skill

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.

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Nov 6, 2026
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# GeoMaster

Comprehensive geospatial science skill covering GIS, remote sensing, spatial analysis, and ML for Earth observation across 70+ topics with 500+ code examples in 8 programming languages.

## Installation

```bash
# Core Python stack (conda recommended)
conda install -c conda-forge gdal rasterio fiona shapely pyproj geopandas

# Remote sensing & ML (rsgislib is conda-forge only, not on PyPI)
conda install -c conda-forge rsgislib
uv pip install torchgeo earthengine-api
uv pip install scikit-learn xgboost torch-geometric