Klasifikasi Habitat Perairan Dangkal Dari Citra Multispasial Di Perairan Pulau Kapota Dan Pulau Kompoone,  Kepulauan Wakatobi

Siregar, Vincentius P.; Sangadji, Muhammad Siddiq; Agus, Syamsul Bahri; Sunuddin, Adriani; Pasaribu, Riza Aitiando; Kurniawati, Esty

doi:10.29244/jitkt.v12i3.32013

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…In comparison to these studies, the accuracy of the maps in this study was found to be similar to those that produced benthic habitat maps with 8 to 9 benthic habitat classes. It is worth noting that the accuracy of the resulting map decreases as the number of classified benthic habitat classes increases (Andréfouët et al 2003;Mastu et al 2018;Siregar et al 2020;Wicaksono et al 2020).…”

Section: Discussionmentioning

confidence: 99%

“…This technology is employed for assessing natural resources in terrestrial sites, such as mangroves (Valderrama-Landeros et al 2018;Hamuna et al 2019b;Ghorbanian et al 2021;Maurya et al 2021) as well underwater resources like coral reefs and seagrass beds (Zhou et al 2018;Wilson et al 2019;Fauzan et al 2021;Lizcano-Sandoval et al 2022;Rosalina et al 2023;Satya et al 2023). The advancement of satellite remote sensing technology has been rapid (Nguyen et al 2021), demonstrated by the development of satellite sensors capable of detecting shallow waters based on specific characteristics (Siregar et al 2020). The development of multi-and hyper-spectral sensors has improved the spatial detail of satellite images, along with the advancements in satellite image data processing.…”

Section: Introductionmentioning

confidence: 99%

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Spatial distribution of benthic habitats in Kapota Atoll (Wakatobi National Park, Indonesia) using remote sensing imagery

HAMUNA,

PUJIYATI,

GAOL

et al. 2023

Biodiversitas

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Abstract. Hamuna B, Pujiyati S, Gaol JL, Hestirianoto T. 2023. Spatial distribution of benthic habitats in Kapota Atoll (Wakatobi National Park, Indonesia) using remote sensing imagery. Biodiversitas 24: 3700-3707. This study aims to classify and map benthic habitats in Kapota Atoll, Wakatobi National Park, using Sentinel-2A satellite imagery, that has undergone both atmospheric and geometric corrections. Sentinel-2A satellite imagery was processed using pixel-based classification method. This study used two machine learning algorithms: support vector machine (SVM) and random forest (RF). This study used nine classified benthic habitat classes, namely five homogeneous benthic classes (sand, live coral, dead coral, rubble, and dense seagrass) and four mixed benthic classes (mixed rubble and sand, mixed sand and rare seagrass, mixed medium seagrass and sand, and a mixture of rubble, dead coral, and seagrass). The RF algorithm produced benthic habitat maps with a higher overall accuracy than the SVM algorithm, which was 65.31% and 63.51%, respectively. These accuracy values have met the standards of accuracy for mapping benthic habitats that apply in Indonesia. The SVM algorithm classification results showed that the benthic habitat of the mixed class of medium seagrass and sand was more dominant than other benthic habitat classes. In contrast, the RF algorithm showed the class dense seagrass was more dominant. The selection of the appropriate algorithm for processing satellite imagery was found to be a significant factor in producing an accurate benthic habitat map.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial distribution of benthic habitats in Kapota Atoll (Wakatobi National Park, Indonesia) using remote sensing imagery

HAMUNA,

PUJIYATI,

GAOL

et al. 2023

Biodiversitas

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Klasifikasi Habitat Bentik Atol Kaledupa Taman Nasional Wakatobi Dengan Algoritma Support Vector Machine

Setiawan¹,

Siregar²,

Susilo³

et al. 2023

J. Ilmu dan Teknologi Kelautan Tropis

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Atol Kaledupa merupakan salah satu kawasan yang dijadikan sebagai zona perlindungan bahari dan zona pemanfaatan lokal di Taman Nasional Wakatobi. Informasi spasial habitat bentik sangat terbatas sehingga penelitian ini diharapkan menjadi pendukung dalam strategi dan upaya pelestarian keanekaragaman hayati laut Atol Kaledupa. Penelitian ini bertujuan untuk memetakan habitat bentik Atol Kaledupa dengan menggunakan metode klasifikasi terbimbing berbasis piksel dan objek/OBIA dengan algoritma support vector machine (SVM). Data yang digunakan adalah citra satelit Sentinel-2 dengan resolusi spasial 10 x10 m yang diakuisisi pada tanggal 4 Nopember 2019. Pengamatan habitat bentik dilakukan secara langsung di lokasi penelitian dengan meletakkan transek kuadran dan mengambil titik pada area habitat yang dominan atau homogen. Transek yang digunakan berukuran 100 x 100 cm2. Klasifikasi citra menggunakan input themathic layer dari data lapangan. Hasil klasifikasi habitat bentik dikelompokan menjadi 6 kelas. Habitat bentik dapat dipetakan menggunakan metode OBIA dengan tingkat akurasi sebesar 78,1% sedangkan klasifikasi berbasis piksel memiliki akurasi keseluruhan 61,8%. Klasifikasi habitat bentik dengan algoritma SVM menggunakan metode OBIA memberikan informasi yang lebih baik dibandingkan dengan metode berbasis piksel.

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Klasifikasi Habitat Perairan Dangkal Dari Citra Multispasial Di Perairan Pulau Kapota Dan Pulau Kompoone, Kepulauan Wakatobi

Cited by 2 publications

References 18 publications

Spatial distribution of benthic habitats in Kapota Atoll (Wakatobi National Park, Indonesia) using remote sensing imagery

Spatial distribution of benthic habitats in Kapota Atoll (Wakatobi National Park, Indonesia) using remote sensing imagery

Klasifikasi Habitat Bentik Atol Kaledupa Taman Nasional Wakatobi Dengan Algoritma Support Vector Machine

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