GIS and Remote Sensing

Classification of Remote Sensing Data

Classification of Remote Sensing Data

Classification is one the classical remote sensing applications used for land cover mapping and monitoring. We used single or multi-sensor remote sensing data for land cover classification and mojor tasks include but not limited to;

  • Land cover classification for map generation
  • Discrimationing different ground targets
  • Object based image segmentation


  • Supervised classification (SVM, Random forest, Decision tree, Extreemly randomized tree, etc)
  • Unsupervised classification (K-mean and the ISODATA clustering algorithm)
  • Hybried methods


Python, IDL, C/C++, Matlab, R, ArcPy, machine learning libraries