Sundarbans Mangrove Mapping and Above Ground Biomass Estimation Using Earth Observation Techniques
Keywords:Biomass, Deforestation, Forest management, Mangrove mapping, Remote sensing
The Sundarbans, the world's largest mangrove forest, plays a crucial role in Bangladesh's economy and environment. However, overexploitation, anthropogenic activities like tree cutting for development and agriculture, as well as natural disasters, have caused severe damage and changes to the Sundarbans. This research aims to detect changes in the mangrove forest areas and create an above-ground biomass map of the Sundarbans Forest. Previous studies relied on time-consuming and inaccurate traditional methods, while this study seeks to make a significant contribution to mangrove mapping and forest resource management. Landsat 5 and 8 images from 2007 to 2017 were used to generate the mangrove index (including CMRI and MI) for different years. ALOS-PALSAR 2 and JERS images from 1996, 2007, and 2017, with HV+HH polarization, were processed to calculate the backscatter ratio, enabling identification and estimation of vegetation loss and gain over the years. To estimate the above-ground biomass (AGB), tree height was derived from SRTM DEM, and an allometric equation was used to calculate AGB. The results indicate a continuous shrinkage of the mangrove forest. The 2017 maps of the two different indexes reveal significant mangrove vegetation loss compared to 1996 and 2007. Additionally, the study estimates the total above-ground biomass of the Sundarbans mangrove forest to be 329 million tons. The findings can assist relevant authorities in taking necessary action, formulating policies, and implementing plans for sustainable management of the Sundarbans mangrove forest resources.
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