The Potential of L-band UAVSAR Data for the Extraction of Mangrove Land Cover using Entropy and Anisotropy based Classification

Mangroves forests serve as an ecosystem stabilizer since they play an important role in providing habitats for many terrestrial and aquatic species along with a huge capability of carbon sequestration and absorbing greenhouse gases. The process of conversion of carbon dioxide into biomass is very rapid in mangrove forests. Mangroves play a crucial role in protecting the human settlement and arresting shoreline erosion by reducing wave height up to a great extent as they form a natural barricade against high sea tides and windstorms. In most cases, human settlement in the vicinity of mangrove forests has affected the eco-system of the forest and placed them in environmental pressure. Since, a continuous mapping, monitoring, and preservation of coastal mangroves may help in climate resilience, therefore a mangrove land cover extraction method using remotely sensed L-band full-pol UAVSAR data (acquired on 25-Feb-2016) based on Entropy (H) and Anisotropy (A) concept has been proposed in this study. The k-Mean clustering has been applied to the subsetted (1-Entropy)*(Anisotropy) image generated by PolSARpro_v5.0 software’s H/A/Alpha Decomposition. The mangrove land cover of the study area was extracted to be 116.07 Km² using k-Mean clustering and validated with the mangrove land cover area provided by Global Mangrove Watch (GMW) data.