Assessing benthic habitat distribution in Tunda Island, Banten, Indonesia using Sentinel-2A imagery

Benthic habitats in coastal areas are composed of diverse organisms and substrates such as seaweed, seagrass, algae, hard corals, dead corals, rock, and rubble. Understanding their distribution is essential for effective marine spatial planning and conservation. This study aimed to assess benthic ha...

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Main Authors: Fakhrurrozi, Idris, Rizan Ardiansyah Mohammad Bagus, Muttaqin Andik Dwi, Mauludiyah
Format: Article
Language:English
Published: EDP Sciences 2025-01-01
Series:BIO Web of Conferences
Online Access:https://www.bio-conferences.org/articles/bioconf/pdf/2025/19/bioconf_isoss2024_05014.pdf
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author Fakhrurrozi
Idris
Rizan Ardiansyah Mohammad Bagus
Muttaqin Andik Dwi
Mauludiyah
author_facet Fakhrurrozi
Idris
Rizan Ardiansyah Mohammad Bagus
Muttaqin Andik Dwi
Mauludiyah
author_sort Fakhrurrozi
collection DOAJ
description Benthic habitats in coastal areas are composed of diverse organisms and substrates such as seaweed, seagrass, algae, hard corals, dead corals, rock, and rubble. Understanding their distribution is essential for effective marine spatial planning and conservation. This study aimed to assess benthic habitat distribution around Tunda Island using Sentinel-2A satellite imagery and evaluate the classification accuracy. Field data were collected from March 5 to 7, 2024, using the photo transect method to identify key benthic classes. Image classification was performed using a Random Forest classifier, and accuracy was evaluated through a confusion matrix. The analysis identified four main benthic habitat classes: rock, rubble, seagrass, and hard coral. Habitat distribution generally followed a pattern across all stations—rock and rubble nearshore, transitioning to seagrass and hard coral further offshore. The areal coverage for each class was estimated as rock (31.89 ha), hard coral (31.29 ha), rubble (21.34 ha), and seagrass (11.99 ha). The classification achieved an overall accuracy of 69.86%, indicating that Sentinel-2A imagery combined with Random Forest classification holds promise for mapping benthic habitats in coastal environments like Tunda Island.
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issn 2117-4458
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spelling doaj-art-03f35aa2b5844accbe80eb574f9b3a972025-08-20T03:08:47ZengEDP SciencesBIO Web of Conferences2117-44582025-01-011680501410.1051/bioconf/202516805014bioconf_isoss2024_05014Assessing benthic habitat distribution in Tunda Island, Banten, Indonesia using Sentinel-2A imageryFakhrurrozi0Idris1Rizan Ardiansyah Mohammad Bagus2Muttaqin Andik Dwi3Mauludiyah4Indonesian Coral Reef Foundation (Yayasan TERANGI)Indonesian Coral Reef Foundation (Yayasan TERANGI)Department of Marine Science, Faculty of Science and Technology State Islamic, Universitas Islam Negeri Sunan Ampel SurabayaDepartment of Marine Science, Faculty of Science and Technology State Islamic, Universitas Islam Negeri Sunan Ampel SurabayaDepartment of Marine Science, Faculty of Science and Technology State Islamic, Universitas Islam Negeri Sunan Ampel SurabayaBenthic habitats in coastal areas are composed of diverse organisms and substrates such as seaweed, seagrass, algae, hard corals, dead corals, rock, and rubble. Understanding their distribution is essential for effective marine spatial planning and conservation. This study aimed to assess benthic habitat distribution around Tunda Island using Sentinel-2A satellite imagery and evaluate the classification accuracy. Field data were collected from March 5 to 7, 2024, using the photo transect method to identify key benthic classes. Image classification was performed using a Random Forest classifier, and accuracy was evaluated through a confusion matrix. The analysis identified four main benthic habitat classes: rock, rubble, seagrass, and hard coral. Habitat distribution generally followed a pattern across all stations—rock and rubble nearshore, transitioning to seagrass and hard coral further offshore. The areal coverage for each class was estimated as rock (31.89 ha), hard coral (31.29 ha), rubble (21.34 ha), and seagrass (11.99 ha). The classification achieved an overall accuracy of 69.86%, indicating that Sentinel-2A imagery combined with Random Forest classification holds promise for mapping benthic habitats in coastal environments like Tunda Island.https://www.bio-conferences.org/articles/bioconf/pdf/2025/19/bioconf_isoss2024_05014.pdf
spellingShingle Fakhrurrozi
Idris
Rizan Ardiansyah Mohammad Bagus
Muttaqin Andik Dwi
Mauludiyah
Assessing benthic habitat distribution in Tunda Island, Banten, Indonesia using Sentinel-2A imagery
BIO Web of Conferences
title Assessing benthic habitat distribution in Tunda Island, Banten, Indonesia using Sentinel-2A imagery
title_full Assessing benthic habitat distribution in Tunda Island, Banten, Indonesia using Sentinel-2A imagery
title_fullStr Assessing benthic habitat distribution in Tunda Island, Banten, Indonesia using Sentinel-2A imagery
title_full_unstemmed Assessing benthic habitat distribution in Tunda Island, Banten, Indonesia using Sentinel-2A imagery
title_short Assessing benthic habitat distribution in Tunda Island, Banten, Indonesia using Sentinel-2A imagery
title_sort assessing benthic habitat distribution in tunda island banten indonesia using sentinel 2a imagery
url https://www.bio-conferences.org/articles/bioconf/pdf/2025/19/bioconf_isoss2024_05014.pdf
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