MANGROVE CARBON BIOMASS POTENCY THROUGH SATELLITE IMAGE ANALYSIS IN THE EASTERN AREA OF MAUMERE BAY: POTENSI BIOMASSA KARBON EKOSISTEM MANGROVE MELALUI ANALISIS CITRA SATELIT DI KAWASAN TIMUR TELUK MAUMERE

Angelinus Vincentius; Guido Roberto Jerun Parera; Marianus Raymond Roky Woda

doi:10.24319/jtpk.16.370-383

Authors

Angelinus Vincentius Study Program of Aquatic Resources Management, Faculty of Food, Agriculture, and Fisheries Technology, Nusa Nipa University, Jl. Kesehatan No. 3 Maumere, Sikka Regency, East Nusa Tenggara 86111, Indonesia
Guido Roberto Jerun Parera Study Program of Aquatic Resources Management, Faculty of Food, Agriculture, and Fisheries Technology, Nusa Nipa University, Jl. Kesehatan No. 3 Maumere, Sikka Regency, East Nusa Tenggara 86111, Indonesia
Marianus Raymond Roky Woda Study Program of Aquatic Resources Management, Faculty of Food, Agriculture, and Fisheries Technology, Nusa Nipa University, Jl. Kesehatan No. 3 Maumere, Sikka Regency, East Nusa Tenggara 86111, Indonesia

DOI:

https://doi.org/10.24319/jtpk.16.370-383

Keywords:

carbon, mangrove, Maumere Bay, satellite

Abstract

Mangrove ecosystems can store significant amounts of carbon in their standing biomass. The eastern part of Maumere Bay contains mangrove areas that are important because of their economic and ecological value. The amount of carbon stored in the mangroves is unknown due to the lack of inventory data. The objective of this study is to obtain estimated surface carbon biomass stocks in the mangrove forests in the eastern part of Maumere Bay using Sentinel-2A imagery. The study was conducted from June to September 2024. Carbon stock values were obtained using the Normalized Difference Vegetation Index (NDVI) analysis method. Actual carbon stocks in surface biomass were obtained from the allometric equation. A stratified sampling method was applied to determine 18 sample spots, each with a size of 10×10 m². Data was analyzed using accuracy tests and linear, polynomial, and exponential regression. The results of the regression analysis show that the exponential regression equation has the highest coefficient of determination (R²) value, namely 0.8373, with the highest accuracy. Therefore, the exponential regression equation was accepted as a model for estimating surface carbon stocks. The NDVI vegetation index has a strong correlation with carbon stocks of 83.73% (R² = 0.8373). The exponential equation is y = 13.637e^2.0499x, which reflects natural growth patterns where y is the carbon value and x is the NDVI value. The mangrove area covers 527.93 ha. The total aboveground carbon stock amounts to 29,760.52 tons of carbon, with an average value of 56.34 tons of carbon per hectare.

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