Utilisation of Sentinel-2A Imagery for Estimation of Mangrove Carbon Stock in Mamminasata Area, South Sulawesi

Abstract

Population growth and land conversion have led to the degradation of mangrove forests on the southern coast of South Sulawesi, especially the Mamminasata area. Reduced mangroves increase carbon dioxide in the atmosphere. However, data on the potential carbon absorption of mangroves is still lacking. To overcome this, remote sensing is used to estimate carbon reserves. This reseach utilises Sentinel-2A imagery to estimate mangrove carbon stocks in Mamminasata. The image processing process includes radiometric correction, atmospheric correction, image classification, and extraction of NDVI values. The NDVI value is used to classify the density of mangroves into sparse, medium, and dense, covering 1,244.75 hectares. Field data collection was carried out through a survey of forest stand measurements. The results of NDVI transformation show a value range of 0.2 to 0.8 for mangrove objects in the Mamminasata area. The NDVI data on the analysed images were then made into three density classes. The rare density class has a carbon value of 3.56 – 21.16 Ton C/ha, the medium density class is between 21.17 – 31.49 Ton C/ha, and the dense density class is between 31.50 – 39.18 Ton C/ha. Regression analysis shows a strong correlation between NDVI and carbon stock (R² = 0.7134). This study confirms the effectiveness of remote sensing in environmental monitoring and mangrove conservation. These findings support conservation efforts and sustainable management policies by highlighting areas with high carbon sequestration potential.