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Uji Akurasi Metode Berbasis Citra Satelit untuk Ekstraksi Data Batimetri

*Ayu Nur Safi'i  -  Badan Informasi Geospasial, Indonesia
Ratna Sari Dewi  -  Badan Informasi Geospasial, Indonesia
Open Access Copyright (c) 2020 TEKNIK

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Abstract

Citra penginderaan jauh memungkinkan pengumpulan data batimetri dengan cakupan luas, sehingga dapat diintegrasikan dengan informasi terestrial untuk pemodelan wilayah pesisir dan pemodelan garis pantai. Data batimetri berbasis citra satelit cukup menjanjikan karena kemampuannya untuk mengisi kesenjangan data kedalaman yang diperoleh dari survei hidrografi. Tujuan dari penelitian ini difokuskan untuk mengevaluasi tiga model dalam memperoleh informasi kedalaman. Model-model tersebut dibuat dengan mengintegrasikan data citra penginderaan jauh dan data pengukuran in-situ (pemeruman) untuk menyediakan dan mengisi data kedalaman di perairan dangkal kawasan pesisir antara permukaan laut dan batas awal data pemeruman. Tiga model yang dievaluasi yaitu: Random Forest (RF), Multi Linear Regression (MLR) dan Generalized Additive Model (GAM). Secara statistik (hasil RMSE), GAM lebih unggul dibandingkan MLR dan RF dalam memperoleh informasi kedalaman. Nilai RMSE masing-masing adalah 0,16, 0,32 dan 0,64 untuk GAM, MLR dan RF. Namun, dari hasil visualisasi, model SDB dengan menggunakan GAM sangat ‘smooth’. Sementara jika dilihat dari penggunaan data, RF sangat tergantung pada jumlah data training. Dalam hal ini, MLR cukup menjanjikan untuk digunakan dalam memperoleh informasi kedalaman karena memiliki akurasi model SDB yang baik dan memiliki pola kedalaman yang lebih andal/reliable. Selain itu, MLR tidak terlalu tergantung pada jumlah data training.

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Keywords: kedalaman; batimetri; batimetri berbasis citra; perairan dangkal, penginderaan jauh, SBES

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