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Geospatial Data Science

This repository contains Jupyter notebooks with Python code about geoscience and remote sensing. Many notebooks come from the book Geoprocessing with Python by Chris Garrard, others are my experiments with open geospatial datasets. The topics of the notebooks follows those in the book plus others common in geostatistics.

The notebooks are based on the following open source software packages

  • GDAL/OGR for raster to vector and vector to raster transformations
  • GeoPandas to handle vector data
  • Rasterio for raster data
  • Shapely for spatial relations
  • PROJ for coordinates transformations
  • Cartopy for geospatial data visualization
  • Folium for map visualization
  • Xarray for multidimensional array processing
  • SciPy, interpolation, linear algebra, numerical integration, optimization
  • PyKRIGE, geostatistics, kriging
  • GeoStat, geostatistics, kriging, random field generation, variogram estimation
  • pyGIMLi, inversion for geophysics
  • xESMF, regridding
  • FiPy, partial differential equations solver
  • scikit-image for digital image processing
  • RasterVision for ML and DL
  • TorchGeo for ML and DL
  • PyTorch for ML and DL
  • GeoWombat geospatial and time series at scale
  • rio-mucho windowed parallel processing wrapper for rasterio
  • The Generic Mapping Tools Earth science data manipulation and visualization
  • HoloViz high-level tools for visualization
  • PySAL, spatial analysis

Other tools used for testing and satellite imagery analysis and processing

Geoscience tools

Geospatial Datasets

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