Aboveground Biomass Estimation of Mangrove Ecosystem in the Anambas Islands Using Remote Sensing Data

Dominikus Yoeli Wilson, Laia and Ronald Raditya Kesatria, Sinaga and Giusti, Ghivarry and Adhera, Sukmawijaya and Wahyudi, Andrito and Andriyatno, Hanif and Rahmat, Irfansyah and Try, Febrianto (2023) Aboveground Biomass Estimation of Mangrove Ecosystem in the Anambas Islands Using Remote Sensing Data. BIO Web of Conferences, 70 (03005). ISSN 22731709

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Abstract

The Anambas Islands is located in the Natuna Sea - the southern part of the South China Sea, encompassing vital marine ecosystems. Among these ecosystems, the mangrove stands out as crucial in the Anambas, playing an important role in providing a range of ecosystem services. However, spatial information regarding the condition of this ecosystem is very limited. In this study, our focus was on estimating and mapping the aboveground biomass (AGB) of mangroves across the Anambas using a combination of field survey and satellite remote sensing data. We employed seven vegetation indices along with five regression methods to determine the most suitable combination for producing an AGB. Our findings revealed that the incorporation of Sentinel-2 remote sensing images and field survey data can be used to model the AGB. The best combination model was the Modified Soil Adjusted Vegetation Index (MSAVI) and polynomial regression, achieving an accuracy of 72.09%. Anambas was estimated to possess a potential AGB of 369,371.47 tonnes and a carbon stock of 173,604.59 tonnes. These findings provide valuable information for regional conservation strategies, including the identification of protected zones, the establishment of a baseline for mangrove conditions, and the assessment of carbon credit in the Anambas.

Item Type: Article
Subjects: S Agriculture > SH Aquaculture. Fisheries. Angling
Divisions: Faculty of Agriculture > Department of Fisheries
Depositing User: Laili Hidayah Hidayah
Date Deposited: 10 Sep 2025 06:47
Last Modified: 10 Sep 2025 06:47
URI: https://ir.lib.ugm.ac.id/id/eprint/20320

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