Skripsi

ANALISIS PEMANFAATAN SATELLITE DERIVED BATHYMETRY UNTUK EKSTRAKSI DATA KEDALAMAN PERAIRAN DANGKAL DI PERAIRAN TAMAN NASIONAL KARIMUNJAWA MENGGUNAKAN CITRA SATELIT LANDSAT-8 DAN SENTINEL-2A

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Penilaian

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Remote sensing technology for depth data extraction, known as Satellite Derived Bathymetry (SDB), can support and facilitate bathymetric data collection, particularly in shallow waters, by utilizing satellite image data to obtain water depth information. This research aims to analyze the comparison between Landsat 8 and Sentinel-2A images in acquiring shallow water depth information in the waters of the Karimunjawa National Park. The algorithm model employed is the Stumpf algorithm, which utilizes the relationship between image values and field survey data at Anora Beach, Ambar Beach, and Batu Lawang Beach. The optimal method is determined based on the values of root mean square error (RMSE), correlation coefficients, and the use of a reduced training dataset. The statistical results of this study indicate that Landsat 8 images produce better RMSE values, ranging from 0.197 to 1.338 meters, at all three research locations, while the RMSE values derived from Sentinel-2A images range from 0.364 to 1.926 meters. In addition to yielding superior RMSE values, Landsat 8 images provide deeper water depth values compared to the depth model derived from Sentinel-2A images. Overall, both images are capable of detecting depth in shallow waters. The maximum detectable depth for both Landsat 8 and Sentinel-2A images is 18 meters. The depth values obtained from the Stumpf model using both types of images are highly influenced by the depth values derived from the bathymetric survey data used as training data.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307002246	T110593	T1105932023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1105932023

Publisher

Inderalaya : Jurusan Ilmu Kelautan, Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Sriwijaya., 2023

Collation

xxiv, 110 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

577.607

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Jurusan Ilmu Kelautan
Ekologi Perairan dan Ekologi Air Tawar

Specific Detail Info

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Statement of Responsibility

SEPTA

Other version/related

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