Abstract
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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Acknowledgement
Authors are thankful to USAID-funded Climate-Resilient Ecosystem and Livelihood (CREL) authority for their field support and office accommodations’. Authors are thankful to Sunbeam Rahman and Shariful Islam for technical help where Mr. Sawpon Chandra’s efficient field team helps to collect field data. Authors are also thankful to the different online and offline portals for helping in the technical part of this research work.
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Islam, M.M., Chowdhury, R.M., Mostafa Zaman, A.K.M. et al. Spatiotemporal mapping mangroves of Tengragiri wildlife sanctuary under Barguna district of Bangladesh using freely available satellite imagery. Model. Earth Syst. Environ. 6, 917–927 (2020). https://doi.org/10.1007/s40808-020-00728-7
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DOI: https://doi.org/10.1007/s40808-020-00728-7