BATHYMETRY EXTRACTION FROM SPOT 7 SATELLITE IMAGERY USING RANDOM FOREST METHODS

Authors

  • Kuncoro Teguh Setiawan Remote Sensing and Applications Center, Indonesian National Institute of Aeronautics and Space (LAPAN)
  • Nana Suwargana Remote Sensing and Applications Center, Indonesian National Institute of Aeronautics and Space (LAPAN)
  • Devica Natalia BR Ginting Remote Sensing Applications Center, Indonesian National Institute of Aeronautics and Space (LAPAN)
  • Masita Dwi Mandini Manessa Departement of Geography, Indonesia University
  • Nanin Anggraini Remote Sensing Applications Center, Indonesian National Institute of Aeronautics and Space (LAPAN)
  • Syifa Wismayati Adawiah Remote Sensing Applications Center, Indonesian National Institute of Aeronautics and Space (LAPAN)
  • Atriyon Julzarika Remote Sensing Applications Center, Indonesian National Institute of Aeronautics and Space (LAPAN)
  • Surahman Hidrography and Oceanography Center, Indonesia NAVI
  • Syamsu Rosid Departement of Physics, Indonesia University
  • Agustinus Harsono Supardjo Departement of Physics, Indonesia University

DOI:

https://doi.org/10.30536/j.ijreses.2019.v16.a3085

Keywords:

bathymetry, random forest, SPOT 7

Abstract

The scope of this research is the application of the random forest method to SPOT 7 data to produce bathymetry information for shallow waters in Indonesia. The study aimed to analyze the effect of base objects in shallow marine habitats on estimating bathymetry from SPOT 7 satellite imagery. SPOT 7 satellite imagery of the shallow sea waters of Gili Matra, West Nusa Tenggara Province was used in this research. The estimation of bathymetry was carried out using two in-situ depth-data modifications, in the form of a random forest algorithm used both without and with benthic habitats (coral reefs, seagrass, macroalgae, and substrates). For bathymetry estimation from SPOT 7 data, the first modification (without benthic habitats) resulted in a 90.2% coefficient of determination (R2) and 1.57 RMSE, while the second modification (with benthic habitats) resulted in an 85.3% coefficient of determination (R2) and 2.48 RMSE. This research showed that the first modification achieved slightly better results than the second modification; thus, the benthic habitat did not significantly influence bathymetry estimation from SPOT 7 imagery

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Published

2025-11-25

Issue

Vol. 16 No. 1 (2019)

Section

Articles

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