Estimating carbon storage using remote sensing in the Selo Resort forest area of Mount Merbabu National Park, Central Java, Indonesia

Abstract

Abstract. Sulton MN, Putri NRA, Nugraheni RS, Afifah RN, Fadilah RN, Indrawan M, Kusumaningrum L, Sutarno, Sunarto, Sugiyarto, Pradhan P, Setyawan AD. 2023. Estimating carbon storage using remote sensing in the Selo Resort forest area of Mount Merbabu National Park, Central Java, Indonesia. Biodiversitas 24: 6264-6270. This study is of paramount importance for long-term climate change mitigation efforts, as it aims to estimate carbon storage and assess land cover density in Selo Resort forest area of Mount Merbabu National Park (MMbNP), Central Java, Indonesia, utilizing remote sensing techniques. Sentinel 2A satellite imagery, acquired on May 28, 2023, serves as the foundational dataset for this research. Employing ArcGIS 10.5, the satellite imagery was processed to derive the Normalized Difference Vegetation Index (NDVI), a critical parameter in this analysis. The NDVI values were subsequently employed to categorize land cover density, leading to the classification of land into five distinct classes: non-vegetation, shrubs, low density, medium density, and high density. This classification process enabled the determination of land cover density. The calculated values for each density class, namely low, medium, and high-density land cover, revealed substantial carbon storage potentials: 12,357.99 tons C, 92,871.04 tons C, and 73,542.06 tons C, respectively. Moreover, the computed areas for low, medium, and high-density cover were 202.59 ha, 364.93 ha, and 348.26 ha, respectively. This study underscores the need for ongoing monitoring to detect changes in land cover and to implement afforestation initiatives in areas with low-density vegetation. Such efforts are crucial for the preservation of land cover and the associated carbon storage benefits, thereby contributing to broader climate change mitigation strategies.