GRSG has  brought together a collection of powerful, free geospatial software and programming libraries to address a comprehensive remote sensing applications.

These tools support advanced image processing techniques across optical, multispectral, SAR (Synthetic Aperture Radar), and hyperspectral datasets – enabling professionals and researchers to analyse, classify, and visualize Earth observation data with precision.

OSGeo Suite (via OSGeo4W for Windows)

• QGIS
  • EnMAP-box plugin – useful for hyperspectral data (EnMAP, EMIT, PRISMA)
  • Semi-Automatic Classification Plugin (SCP) – for multispectral analysis
• SAGA GIS – Image classification and terrain analysis
• GRASS GIS – Image preprocessing, PCA, classification, and modelling

ESA Toolboxes

• PolSARPro – Radar polarimetry analysis
• SENTINEL Toolbox/SNAP – Processing of multispectral and SAR imagery

Software Requiring Coding

• R Project (R-Studio interface) – Statistical computing with raster/image packages (Remote Sensing with R Guide)
• Scilab – Numerical computing platform (Scilab GitLab)
• Google Earth Engine – Cloud-based satellite image analysis (JavaScript interface, non-commercial use only)
• Python – Extensive geospatial libraries: GDAL, Scikit-learn, SciPy, Numpy, SpectralPy, Pandas (Getting Started with Remote Sensing in Python)