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Ratih Dewanti -Hariyadi
Departemen Ilmu Dan Teknologi Pangan, Fakultas Teknologi Pertanian, Institut Pertanian Bogor, Kampus IPB, Darmaga, Jl. Lingkar Akademik, Babakan, Kec. Dramaga, Bogor, Jawa Barat 16680
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Journal : Forest and Society

 1 
Estimation and Mapping Above-Ground Mangrove Carbon Stock Using Sentinel-2 Data Derived Vegetation Indices in Benoa Bay of Bali Province, Indonesia Suardana, A. A. Md. Ananda Putra; Anggraini, Nanin; Nandika, Muhammad Rizki; Aziz, Kholifatul; As-syakur, Abd. Rahman; Ulfa, Azura; Wijaya, Agung Dwi; Prasetio, Wiji; Winarso, Gathot; Dewanti, Ratih
Forest and Society Vol. 7 No. 1 (2023): APRIL
Publisher : Forestry Faculty, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24259/fs.v7i1.22062

Abstract

Carbon dioxide (CO2) is one of the greenhouse gases that causes global warming with the highest concentration in the atmosphere. Mangrove forests can absorb CO2 three times higher than terrestrial forests and tropical rainforests. Moreover, mangrove forests can be a source of Indonesian income in the form of a blue economy, therefore an accurate method is needed to investigates mangrove carbon stock. Utilization of remote sensing data with the results of the above-ground carbon (AGC) detection model of mangrove forests based on multispectral imaging and vegetation index, can be a solution to get fast, cheap, and accurate information related to AGC estimation. This study aimed to investigates the best model for estimating the AGC of mangroves using Sentinel-2 imagery in Benoa Bay, Bali Province. The random forest (RF) method was used to classified the difference between mangrove and non-mangrove with the treatment of several parameters. Furthermore, a semi-empirical approach was used to assessed and map the AGC of mangroves. Allometric equations were used to calculated and produced AGC per species. Moreover, the model was built with linear regression equations for one variable x, and multiple regression equations for more than one x variable. Root Mean Square Error (RMSE) was used to assess the validation of the model results. The results of the mangrove forests area detected in the research location around 1134.92 ha, with an Overall Accuracy (OA) of 0.984 and a kappa coefficient of 0.961. This study highlights that the best model was the combination of IRECI and TRVI vegetation indices (RMSE: 11.09 Mg/ha) for a model based on red edge bands. Meanwhile, the best results from the model that does not use the red edge band were the combination of TRVI and DVI vegetation indices (RMSE: 13.63 Mg/ha). The use of red edge and NIR bands is highly recommended in building the AGC model of mangrove forests because they can increase the accuracy value. Thus, the results of this study are highly recommended in estimating the AGC of mangrove forests, because it has been proven to be able to increase the accuracy value of previous studies using optical images.
Co-Authors - Suliantari Abd. Rahman As-syakur Achmad Poernomo Achmad Poernomo Achmad Poernomo Amiroh Amiroh Amiroh Amiroh, Amiroh Arimah Arimah Ayu Intan Sari Aziz, Kholifatul Azura Ulfa, Azura Bambang Trisakti Budi Nurtama C. C. Nurwitri Cahyadi, Muhammad Cynthia Cynthia Cynthia CynthiaCynthia David Yudianto Dedi Fardiaz Ekawati Purwijantiningsih Ekawati Purwijantiningsih, Ekawati Eko Hari Purnomo Endang Tri Rahayu, Endang Tri Ermi Sukasih Estuningsih - Estuningsih - Ety Parwati Fadhina, Maisharah Fenny Larasati Firman Fajar Perdhana Gathot Winarso, Gathot Gino Nemesio Cepeda Hanifaturahmah, Fadiyah Harsi D. Kusumaningrum Hesty Nur Fadia Istiana (alm.) Istiana Istiana, Istiana (alm.) Ita Carolita, Ita Joko Riyanto Karina Nola Sinamo Komala, Kemal Lendrawati Lendrawati Lilis Nuraida Maggy T. Suhartono Maggy Thenawidjaja Suhartono Mala Nurilmala Muhammad Nur Mutaqin, Muhammad Zakki Nandika, Muhammad Rizki Nanin Anggraini, Nanin nFN Setyadjit Ni Gusti Ayu Made Widyatari Asthiti Ni Made Vina Citanirmala Nugroho Indrotristanto Nur Richana Nur Wulandari Nur Wulandari Nuri Andarwulan Nurwitri, C. C. Oryssa Sathalica Pradianti Pawestri, Wari Prasetio, Wiji Pratiwi Yuniarti Martoyo Pratiwi Yuniarti Martoyo Purwiyatno Hariyadi Rahadina Praba Melati Rahmawati Rahmawati Raini Panjaitan Ramadhani Meutia, Yuliasri Ratu Ayu Dewi Sartika Rika Puspitasari MZ Rinto . Sari, Ratna Nurmalita SEDARNAWATI YASNI Shanti Emawati Siti Nurjanah Siti Nurjanah Soegiarto, Salma Rachmanda Sri Estuningsih Sri Harini Suardana, A. A. Md. Ananda Putra Suci Apsari Pebrianti Sudiyono Sudiyono Sukarno Sukarno Supar, Supar Sutrisno Hadi Purnomo Tatik Kartika, Tatik Tri Isti Rahayu Ulfah Amalia Uswatun Hasanah Vanessa Len Cahya Agustine Wati, Ari Kusuma Wijaya, Agung Dwi Wilis, Nabila Sekar Winiati P Rahayu Winiati P Rahayu Winiati P. Rahayu Winiati Pudji Rahayu Wiweka, Toh Jaya Yati Maryati Yati Maryati Yesica M. R. Sinaga Yesica Marcelina Romauli Sinaga Yuli Yanti Yuliasri Ramadhani Meutia Yusma Yennie Yusma Yennie