Al Farisi, Rinal (2019) Pemetaan Habitat Perairan Dangkal Menggunakan Citra Satelit Sentinel-2 (Studi Kasus: Gugusan Pulau Pari, Kepulauan Seribu). Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Perkembangan teknologi penginderaan jauh telah banyak diterapkan untuk berbagai keperluan, seperti penerapan pada deteksi habitat perairan dangkal. Perairan dangkal laut tropis memiliki beberapa macam ekosistem antara lain yaitu terumbu karang, padang lamun, pasir, lumpur, dan hutan mangrove, dimana ekosistem-ekosistem tersebut saling berinteraksi satu sama lain. Ekosistem terumbu karang dan lamun berada di lingkungan perairan dangkal. Tipe habitat dasar di perairan dangkal dapat menjadi salah satu parameter yang mempengaruhi penentuan kawasan konservasi laut, karena merupakan tempat biota-biota laut hidup. Penelitian ini bertujuan untuk melakukan pemetaan dan klasifikasi habitat perairan dangkal di Gugusan Pulau Pari, Kepulauan Seribu menggunakan citra satelit Sentinel-2. Proses koreksi pada citra dilakukan sebanyak tiga tahap, meliputi koreksi radiometrik, Sun-Glint, dan Lyzenga. Klasifikasi dilakukan dengan metode supervised dan diuji ketelitiannya menggunakan matrix confusion. Hasil penelitian membagi habitat perairan dangkal menjadi lima kelas, berupa : (1) terumbu karang, (2) makro alga, (3) lamun sedang, (4) lamun tinggi dan (5) substrat dasar. Nilai overall accuracy hasil penelitian sebesar 86,2% dengan koefisien kappa sebesar 0,85, dimana hasil tersebut telah memenuhi syarat minimum ketelitian klasifikasi citra Sentinel-2. Hasil dari penelitian menunjukkan Gugusan Pulau Pari didominasi oleh habitat lamun, dimana terdapat 33,1% yang kebanyakan tersebar di utara dan selatan Pulau Pari. Sedangkan terumbu karang umumnya tersebar di sekitar Pulau Tengah dan memiliki presentase 30,8% dari keseluruhan habitat. =================================================================================================================================
The development of remote sensing technology has been applied for various purposes, such as the application of shallow habitat detection. The shallow waters of tropical seas have a variety of ecosystems including coral reefs, seagrass beds, sand, mud, and mangrove forests, while ecosystem ecosystems are interrelated. Coral reef ecosystems and environments in shallow crossing environments. Basic habitat types in shallow water can be one of the parameters that affect marine conservation areas, because it is a place for living marine biota. This study aims to map and classify shallow habitats in the Pari Island Cluster, Seribu Islands using Sentinel-2 satellite imagery. The image correction process is done in three, radiometric correction, Sun-Glint, and Lyzenga. Classification is done by a method that is supervised and submitted to its accuracy using a confusion matrix. The results of the study divided shallow habitats into five classes, consisting of: (1) coral reefs, (2) macro algae, (3) medium seagrass, (4) high seagrass and (5) basic substrate. The overall value of the accuracy of the results of the study is 86.2% with a kappa coefficient of 0.85, while this result must meet the minimum requirements. Accuracy of Sentinel-2 image classification. The results showed that the Pari Island cluster was estimated by seagrass habitat, which constituted 33.1% distributed in the north and south of Pari Island. While coral reefs are scattered around Central Island and have a percentage of 30.8% of the total habitat.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSG 621.367 8 Alf p-1 2019 |
| Uncontrolled Keywords: | Shallow Aquatic Habitat, Sentinel-2, Matrix Confusion, Supervised Classification. |
| Subjects: | G Geography. Anthropology. Recreation > G Geography (General) > G109.5 Global Positioning System G Geography. Anthropology. Recreation > G Geography (General) > G70.212 ArcGIS. Geographic information systems. G Geography. Anthropology. Recreation > G Geography (General) > G70.217 Geospatial data G Geography. Anthropology. Recreation > G Geography (General) > G70.5.I4 Remote sensing S Agriculture > SH Aquaculture. Fisheries. Angling |
| Divisions: | Faculty of Civil Engineering and Planning > Geomatics Engineering > 29202-(S1) Undergraduate Thesis |
| Depositing User: | Rinal Al Farisi |
| Date Deposited: | 10 Jan 2024 06:54 |
| Last Modified: | 10 Jan 2024 06:54 |
| URI: | http://repository.its.ac.id/id/eprint/64659 |
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