Analysis of Carbon Stock Estimation in Mangroves with Climate Variability in West Java 2019-2023

Abstract

Mangrove ecosystems are important in carbon sequestration and climate regulation and contribute to climate change mitigation. However, carbon stock estimation is still mostly done manually, which is less efficient. This study utilizes remote sensing to investigate the correlation between mangrove carbon stocks and climate variability in West Java from 2019 to 2023. Mangrove land cover classification was performed using the Random Forest algorithm with NDVI and NDWI indices, while the relationship between carbon stock and climate factors was analyzed using linear regression. The results showed that increased precipitation was associated with higher carbon stocks (R2=0.5514), while carbon stocks had a negative correlation with 2-meter temperature (R2=0.8242) and sea surface temperature (SST) (R2=0.7111). This study enhances our understanding of mangrove-climate interactions and provides valuable insights for developing remote sensing-based climate resilience and coastal ecosystem management policies.