| Abstrakt: |
Naturally grown mangrove forest is the south coastal community’s green barrier from any type of hydro-meteorological hazard and disasters. South-western coastal area of Bangladesh is covered by the Sundarbans, and mid-central zone is covered by Tengragiri wildlife sanctuary which is taken as a protected area in this recent era but not mapped properly with considering different species diversification and temporal changes pattern which is required for successful co-management of this mangrove forest. This study identifies species composition, plant diseases, degradation of the mangrove forests and further focuses on mapping mangroves by conducting plotting-based primary field visit, variability analysis using different indices and cross-matching with secondary databases. Existing mangrove forest boundary’s 200 m buffering with three-time series satellite imagery 2000, 2010 and 2017 is considered for further analysis. Including all buffering zone, this protected area considered 9 major classes that included four subclasses for presenting result like Baen (Avicennia officinalis), Gewa-Goran (Excoecaria agallocha, Ceriops decandra), Keora (Sonneratia apetala), Sundri (Heritiera fomes), Plantation trees Samanea Saman(Raintree), agriculture-grassland (agri-grass) and homestead settlement, sandbar and waterbody. Mapping accuracy assessment purpose automatically generated 996 points cross-matched with previously mangrove species level detailed survey results and found highest accuracy in Sundri species (70%) and all others above 50%. During 2000–2017, the Keora area showed the highest increase 129% over 2000 and increasing rate 13.17 ha/yr. About 26% Sundri and Baen–Passur increased around 13.45 ha/yr. In case of Sundri, 70% area coverage remained intact during 2000–2017, while other 25% classified in 2017 as Avicennia officinalis, Gewa-Goran classes. Furthermore, using refracted electromagnetic energy from various physical characteristics of plants application, four indices (NDVI, DVI, MSAVI-2, RVI) are usable where single-species-level crop density analysis has limitations, but identification of Sundri and Keora by MSAVI-2 and NDVI found significant and alternately lower accuracy values from RVI. Identification of dominant mangrove species groups as well as area gains and losses over 2000–2017 is a robust biophysical baseline for management of the sanctuary. Natural hearts of this area and working as first-step warriors against natural disasters originated from Indian Ocean and Bay of Bengal; so far, it is very much required to save this forest and the coastal communities as well. The results of the study and maps will be helpful for the scientific community, planners, government-international bodies and the activists, Forest Department and the local community in effective planning, monitoring the effectiveness of co-management in conservation of the sanctuary. |
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