Abstract
PlanetScope has a multispectral sensor that can identify and map various land cover types, which play an important role in carbon storage. The purpose of this study was to map the estimated mangrove carbon stock spatially. The research method used was a remote sensing approach using the Difference Vegetation Index (DVI) vegetation index and regression analysis between field carbon values and vegetation index values to produce an estimate of the carbon stock above the mangrove surface. In this study, the dominant species found included Rizophora apiculata and Sonneratia alba with an average tree diameter of 10.84 cm for the Sonneratia alba species, and a tree diameter of 38.82 cm for the Rhizophora apiculata species. The total biomass value at the study location was 147,752 tons/ha with the lowest biomass value of 0.386 tons/ha in the dominant species Sonneratia alba, and the highest being 25.943 tons/ha in the dominant species Rhizophora apiculata. The total value of field carbon stock is 69.443 tons/ha with the lowest carbon value of 0.182 tons/ha and the highest of 12.193 tons/ha from the calculation results using species-based allometry. In comparison, the total estimated value of carbon stock from imagery is 0.080 tons/ha. This study produced an error of 3.163 tons/ha which means it has a good accuracy value. A better level of accuracy is indicated by the lower value obtained from the standard error estimate. Research using remote sensing data can better understand the important role of mangroves in carbon storage and climate change mitigation efforts, as well as support the sustainability of ecosystems that provide many benefits to the environment and society. Mapping mangrove carbon stocks using remote sensing methods not only provides accurate and comprehensive data but also increases our capacity to manage and conserve mangrove ecosystems.