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.