Mapping Mangrove Surface Carbon Stocks Using Multisensor Imagery in Clungup Mangrove Conservation (Cmc) Malang Regency

Abstract

Mangroves can store carbon effectively with a value of about 1,023 Mg C/Ha and become one of the richest forests that store 4-20 billion tons of blue carbon globally. Remote sensing imagery can be used to map mangrove surface carbon stocks using radar and optical image sensors. Generally, forest carbon on earth is stored in two places, namely above the surface (Above Ground Carbon, AGC) and below the surface (Below Ground Carbon, BGC). This study aims to estimate the surface carbon stock of mangroves using multisensory imagery using the Random Forest method in the Clungup Mangrove Conservation (CMC) area, Malang Regency, East Java. Four vegetation indices (IRECI, NDI45, NDVI, SAVI), single band, and VV VH polarization were used as predictive variables. Estimating the carbon stock mangrove value using Sentinel-1 imagery produced 2,126 tons of C with R² 0.11. Meanwhile, Sentinel-2 produces an estimated carbon value of 2,025 tons C with an R² of 0.22. The estimation model using Sentinel-2 shows a better evaluation value with a Root Mean Squared Error (RMSE) of 0.89 and a Mean Absolute Error (MAE) of 0.75. The IRECI vegetation index is the most important variable in estimating carbon stocks. The results of the mapping accuracy of the Sentinel-1 model show a value of 34.73% and Sentinel-2 35.03%.Keywords: Mangrove, Carbon, Sentinel-1, Sentinel-2, Random Forest