Estimation of Biomass and Carbon Stock Using NDVI from Multispectral Camera in the Revegetation Area of PT Berau Coal - Pasmika Sima; Filsa Bioresita (International Journal of Marine Engineering Innovation and Research, 2024)
PT Berau Coal is a company that has held the Coal Mining Work Agreement (PKP2B) since 1983, with an area of approximately 243,146.60 hectares located in Berau Regency, East Kalimantan Province. As a mining industry, the company must play a role in maintaining hydro-orological functions and protecting flora and fauna. The restoration of forest functions is crucial for providing environmental services, including efforts to act as a carbon (C) producing area and absorbing carbon dioxide (CO2). PT Berau Coal has carried out reclamation and revegetation in its post-mining areas, but until now, no research has been conducted in the revegetation areas of PT Berau Coal. Therefore, this study aims to determine the distribution of biomass and carbon stock in the revegetation areas and planting years at the Binungan site of PT Berau Coal from 2015 to 2022. The method used to calculate carbon stock and biomass involves field sampling and remote sensing using MicaSense multispectral aerial photos. Biomass and carbon stock estimation with aerial photos is conducted by calculating the plant greenness index using NDVI, followed by regression with field biomass. The regression model used includes four types: linear, quadratic, cubic, and exponential. These models are evaluated to find the best fit model with accuracy tests using Root Mean Square Error (RMSe), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) to determine the modeling accuracy. The results show that the best model for estimating biomass and carbon stock is the exponential regression model with a correlation value of 0.84. This correlation value falls into the category of a fairly high correlation. The RMSe produced in the accuracy test is 15.65, with an accuracy rate of 73%. The estimated carbon stock value for each planting year is 70,817,156.852 Kg/Ha (2015), 79,837,036.531 Kg/Ha (2016), 49,654,443.503 Kg/Ha (2017), 47,047,989.557 Kg/Ha (2018), 35,219,578.867 Kg/Ha (2019), 19,693,198.417 Kg/Ha (2020), 31,335,533.541 Kg/Ha (2021), and 31,335,533.541 Kg/Ha (2022). The modeling results indicate that the older the plants, the higher their NDVI, resulting in greater biomass and carbon stock in the area.