Spatial and temporal study of estimating carbon stocks distribution of mangrove forest in coastal area of Teluknaga, Tangerang
DOI:
https://doi.org/10.61511/eam.v1i2.2023.270Keywords:
biomass, carbon stock, mangrove, sentinel-2, vegetation indicesAbstract
Coastal mangrove forests play a crucial role in balancing carbon emissions in the atmosphere as they are a significant carbon store. Previous studies have shown that mangroves can absorb carbon four times more efficiently than terrestrial tropical forests. Unfortunately, the massive development and land use changes in Teluknaga District's coastal areas threaten these ecosystems' existence. To address this concern, efforts are being made to increase conservation, including estimating carbon stock. The aim of this study is to analyze the spatial distribution of biomass and carbon stock of mangrove forests in Teluknaga between 2016-2022 based on vegetation indices such as ARVI, EVI, and SAVI. Sentinel-2 was calculated into ARVI, EVI, and SAVI vegetation indices to model biomass. Statistical correlation analysis was also used to determine the best vegetation index to model biomass in the coastal area of Teluknaga District. This study found that the ARVI vegetation index had the best correlation (R = 0.60) for modeling biomass, with an RMSE value of 36.67 kg/pixel. Most mangrove forests in the coastal area of Teluknaga District showed an increase in biomass and carbon stock between 2016-2022, with significant growth in Muara and Lemo villages' mangrove forests, which is in line with an increase in the area and density of mangrove forests.
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