Recent developments of remote sensing techniques which can capture both the structure and function of the ecosystem provide a more representative view of the landscape. These unique Earth observations were used to help improve traditional forestry surveys by providing species-specific land cover classes for mangrove forests in the Sundarbans East Wildlife Sanctuary. By combining optical data from WorldView2 (WV2; 2 m pixel) and a canopy height model derived using radar data from TanDEM-X (TDX; 12 m pixel), we identified nine mangrove and five non-mangrove classes by following an Iterative Self-Organizing Data Analysis Algorithm. Three dominant mangrove species accounted for nearly 50% of the sanctuary. Heritieria fomes disproportionately covered the largest area at 43%, overturning previous field-based estimates of Excoecaria agallocha dominance. E. agallocha and Sonneratia apetala, covered 3% and 1.47% of the sanctuary, respectively. Four mixed species classes were also identified with clear vegetation zonation patterns that trended toward species homogeneity with increasing distance from shore. The overall land cover accuracy (WV2: 89.33%; WV2-TDX: 89.89%), the Kappa Coefficient (WV2: 0.88; WV2-TDX: 0.89) and change statistics between WV2 and WV2-TDX land cover classifications indicate that the WV2 imagery can separate mangrove community types without structural data. The combination of the land cover classifications and the canopy height model indicated that H. fomes were not only the most dominant forest but also, on average, the tallest (12.3 m) among the other eight mangrove types. Our large-scale mapping with high resolution optical and radar platforms can capture subtle changes in mangrove vegetation and canopy structural gradients more accurately and be used to monitor biodiversity changes and Aichi Biodiversity Targets and Indicators, which would contribute to biodiversity policy updating.
1.Kyoto Univ, Grad Sch Agr, Sakyo Ku, Kyoto 6068502, Japan 2.Univ Maryland, Dept Geog Sci, 2181 Samuel J LeFrak Hall,7251 Preinkert Dr, College Pk, MD 20742 USA 3.NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA 4.Bana Bhaban, Bangladesh Forest Dept, Plot E-8,B-2, Dhaka 1207, Bangladesh
Recommended Citation:
Rahman, Md Mizanur,Lagomasino, David,Lee, SeungKuk,et al. Improved assessment of mangrove forests in Sundarbans East Wildlife Sanctuary using WorldView 2 and TanDEM-X high resolution imagery[J]. REMOTE SENSING IN ECOLOGY AND CONSERVATION,2019-01-01,5(2):136-149