Please use this identifier to cite or link to this item: http://repository.ipb.ac.id/handle/123456789/166461
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dc.contributor.advisorSiregar, Vincentius P.-
dc.contributor.advisorAgus, Syamsul Bahri-
dc.contributor.authorWulandari, Wahyu-
dc.date.accessioned2025-08-01T23:44:22Z-
dc.date.available2025-08-01T23:44:22Z-
dc.date.issued2025-
dc.identifier.urihttp://repository.ipb.ac.id/handle/123456789/166461-
dc.description.abstractPerairan dangkal merupakan ekosistem dinamis yang memegang peranan penting dalam ekologi wilayah pesisir. Ketersediaan data akurat mengenai karakteristik dasar perairan dangkal menjadi faktor penting dalam pengelolaan dan pengembangan kawasan pesisir serta pulau-pulau kecil. Sebagai negara kepulauan dengan karakteristik perairan dangkal yang beragam, Indonesia membutuhkan metode efisien untuk memperoleh data secara cepat dengan cakupan wilayah yang luas. Dalam konteks ini, teknologi penginderaan jauh muncul sebagai solusi alternatif yang menjanjikan. Perkembangan pesat teknologi penginderaan jauh, khususnya sistem pesawat tanpa awak (Unmanned Aerial Vehicle/UAV) berbasis drone multispektral. Studi ini bertujuan mengevaluasi potensi pemanfaatan citra drone multispektral untuk estimasi kedalaman perairan dan pemetaan struktur geomorfologi perairan dangkal. Penelitian ini dilaksanakan pada tanggal 19 – 23 Mei 2024 di perairan dangkal Pulau Panggang, Kabupaten Kepulauan Seribu, DKI Jakarta. Alat yang digunakan berupa DJI Phantom 4 Multispektral, GPS RTK, Gun Sounder, Go Pro Camera, DroneDeploy, AgiSoft Metashape, ArcGIS, QGIS, Global Mapper, MATLAB, dan Microsoft Excel. Klasifikasi struktur geomorfologi perairan dangkal, menggunakan data batimetri dengan pendekatan BTM yang terintegrasi pada ArcGIS. Estimasi kedalaman maksimum pada perairan laut dangkal Pulau Panggang adalah 16 meter dengan menggunakan algoritma SVM dengan memiliki koefisien determinasi (R2) 0,91. Sehingga data hasil SVM digunakan sebagai data input pada aplikasi BTM. Kombinasi scale factor yang digunakan pada lokasi penelitian yakni Fine BPI 20 dan Broad BPI 79 dengan nilai slope 84,94°. Terdapat 13 kelas struktur geomorfologi yang didapatkan pada Pulau Panggang dengan hasil analisis BTM. Kelas struktur geomorfologi dengan variasi yang tinggi didapatkan pada wilayah Pulau Panggang. Struktur kelas geomorfologi di daerah penelitian didapatkan kelas terluas hingga terkecil mulai dari flat plains, steep slope, broad slope, rock outcrop, flat ridges, current scoured, local ridges, narrow depression, local depression, scarp, dan crevices.-
dc.description.abstractShallow waters represented dynamic ecosystems that played a crucial role in coastal ecology. Accurate data on the characteristics of shallow seabeds were essential for the management and development of coastal areas and small islands. As an archipelagic nation with diverse shallow-water characteristics, Indonesia required efficient methods to rapidly obtain data across extensive areas. In this context, remote sensing technology emerged as a promising alternative solution. The rapid advancement of remote sensing technology, particularly Unmanned Aerial Vehicle (UAV)-based multispectral drones, opened new opportunities for marine research. This study aimed to evaluate the potential of multispectral drone imagery for water depth estimation and the mapping of benthic habitat geomorphological structures. The research was conducted from May 19–23, 2024, in the shallow waters of Panggang Island, Thousand Islands Regency, Jakarta. The equipment employed consisted of hardware such as a DJI Phantom 4 Multispectral drone, RTK GPS, gun sounder, GoPro camera, and software including DroneDeploy, Agisoft Metashape, ArcGIS, QGIS, Global Mapper, MATLAB, and Microsoft Excel. The classification of shallow-water geomorphological structures was performed using bathymetric data integrated with field data through a Benthic Terrain Modeler (BTM) approach in ArcGIS. The maximum estimated depth in the shallow waters of Panggang Island was 16 meters, derived using an SVM algorithm with a coefficient of determination (R²) of 0.91. The SVM regression output was used as input for BTM analysis. The scale factors applied in the study were Fine BPI (20), Broad BPI (79), and slopes (84.94°). BTM analysis identified 13 geomorphological structures on Panggang Island, with high variability observed across the study area. The geomorphological classes, ranked by coverage from largest to smallest, included flat plains, steep slopes, broad slopes, rock outcrops, flat ridges, current-scoured areas, local ridges, narrow depressions, local depressions, scarps, and crevices.-
dc.description.sponsorshipnull-
dc.language.isoid-
dc.publisherIPB Universityid
dc.titleKajian Geomorfologi Perairan Dangkal dengan Pendekatan Benthic Terrain Modeler (BTM) Menggunakan Drone Multispektralid
dc.title.alternativeGeomorphological Study of Shallow Waters Using Multispectral Drones with Analysis Approach of Benthic Terrain Modeler (BTM)-
dc.typeTesis-
dc.subject.keywordBatimetriid
dc.subject.keywordDrone Multispektralid
dc.subject.keywordgeomorfologiid
dc.subject.keywordBenthic Terrain Modelid
dc.subject.keywordsupport vector machineid
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