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

Methods

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

Tools

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