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All Journal Geo Media: Majalah Ilmiah dan Informasi Kegeografian Jurnal Pengembangan Energi Nuklir Majalah Geografi Indonesia Geo-Image Journal JLBG (Jurnal Lingkungan dan Bencana Geologi) (Journal of Environment and Geological Hazards) JURNAL ILMIAH GEOMATIKA MAJALAH ILMIAH GLOBE Jambura Geoscience Review IJEEM - Indonesian Journal of Environmental Education and Management Journal of Applied Geology Environmental and Materials Jurnal Geosains Terapan
Tito Latif Indra
Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Indonesia, Depok
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Physics Social Sciences

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Journal : Environmental and Materials

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Spatial and temporal study of estimating carbon stocks distribution of mangrove forest in coastal area of Teluknaga, Tangerang Yumnaristya, Syefiara Hania; Indra, Tito Latif; Supriatna; Pin, Tjiong Giok; Gracia, Enrico
Environmental and Materials Vol. 1 No. 2: (December) 2023
Publisher : Institute for Advanced Science, Social, and Sustainable Future

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61511/eam.v1i2.2023.270

Abstract

Coastal mangrove forests play a crucial role in balancing carbon emissions in the atmosphere as they are a significant carbon store. Previous studies have shown that mangroves can absorb carbon four times more efficiently than terrestrial tropical forests. Unfortunately, the massive development and land use changes in Teluknaga District's coastal areas threaten these ecosystems' existence. To address this concern, efforts are being made to increase conservation, including estimating carbon stock. The aim of this study is to analyze the spatial distribution of biomass and carbon stock of mangrove forests in Teluknaga between 2016-2022 based on vegetation indices such as ARVI, EVI, and SAVI. Sentinel-2 was calculated into ARVI, EVI, and SAVI vegetation indices to model biomass. Statistical correlation analysis was also used to determine the best vegetation index to model biomass in the coastal area of Teluknaga District. This study found that the ARVI vegetation index had the best correlation (R = 0.60) for modeling biomass, with an RMSE value of 36.67 kg/pixel. Most mangrove forests in the coastal area of Teluknaga District showed an increase in biomass and carbon stock between 2016-2022, with significant growth in Muara and Lemo villages' mangrove forests, which is in line with an increase in the area and density of mangrove forests.
Co-Authors Annisa, Illa Ari Nugroho Asriza Asriza Astuti, Tri Rani Puji Eko Kusratmoko Fadhilah, Raina Arfa Gracia, Enrico Join Wan C. Sigalingging M.H. Dewi Susilowati, M.H. Dewi Muhammad Asrofi, Muhammad Muhammad Dimyati Muhammad Rizqy Septyandy Pin, Tjiong Giok Priyanka Prajna Paramitha R. Syahputra Raldi Hendro Koestoer, Raldi Hendro Randhi Atiqi, Randhi Ratna Saraswati, Ratna Rudy P. Tambunan Sani, Yogie Shidiq, Iqbal Putut Ash Supriatna Supriatna Supriatna Twin Hosea Widodo Kristyanto Wiguna, Dede Prabowo Yumnaristya, Syefiara Hania