BATHYMETRY EXTRACTION FROM SPOT 7 SATELLITE IMAGERY USING RANDOM FOREST METHODS

Kuncoro Teguh Setiawan, Nana Suwargana, Devica Natalia Br. Ginting, Masita Dwi Mandini Manessa, Nanin Anggraini, Syifa Wismayati Adawiah, Atriyon Julzarika, Surahman Surahman, Syamsu Rosid, Agustinus Harsono Supardjo

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.

Keywords

bathymetry; random forest; SPOT 7

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DOI: http://dx.doi.org/10.30536/j.ijreses.2019.v16.a3085

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