Depth estimation model of shallow-tropical seawaters based on remote sensing data and BatNas Available to Purchase

Seawaters depth monitoring has many uses for environmental management, development planning, fisheries, and transportation. In general, depth measurement uses acoustic methods that rely on sound waves. For shallow waters we can use multispectral satellite imagery. This study aims to develop a depth algorithm of shallow-tropical seawaters based on Landsat imagery and National Bathymetry (BatNas) data. This model takes an area of interest in West Kalimantan, Indonesia. We tested the model with echo sounding data from 294 observation points. Model validation and accuracy refers to r-square, central tendency, RMSE, MSE, and MAE. This study indicates that our model has determination of 81 percent with p-value of less than 0.01. In terms of accuracy, this algorithm has RMSE 1.07, MSE 3.41, and MAE 1.76. Our algorithm can estimate depths of up to 35 meters with an error of up to 1.94 meters. The actual depth pattern from echo sounding and the model have similar patterns to describe subsurface conditions. Although Indonesia has had a national scale bathymetric data, our algorithm could be useful for monitoring the depth of the shallow-tropical seawaters on a regular basis that is effective, efficient, and low-cost, but needs annual or seasonal updates.