A Distributed Land Cover Classification Of Fp And Cp Sar Observation Using Mapreduce-based Multi-layer Perceptron Algorithm Over The Mumbai Mangrove Region Of India

This article discusses the effects of rapid urbanization, population growth and industrialization on mangrove forests. It highlights the importance of using polarimetric (Pol) synthetic aperture radar (SAR) for remote sensing of the Greater Mumbai area, which is often covered by a quasi-permanent cloud, and for automated land cover classification by neural network models. The article also discusses the utilities of dual-, quad- and full-polarimetric SAR, as well as their advantages in land cover classification.