Abstract

There is a gap in bathymetry data in shallow water due to the difficulty in measuring the depth. Meanwhile, to obtain an accurate datum-based coastline, sufficient depth and topography data are required. In the situation in which bathymetry data from the conventional method (sounding measurement) is limited, the bathymetry data resulted from Satellite Derived Bathymetry (SDB) algorithm can be an alternative solution. The SDB is estimated by correlating water depth and the spectral band of images. This research is conducted to develop a method that can be applied for coastline mapping by assessing the capability of SDB. For the integration of all input data, including land elevation and bathymetry data, a gridding method called stacked continuous curvature splines with tension is adopted. Coastline generated from the proposed method was relatively smooth and it was close to the shape of the land feature compared to coastline developed from other data sources such as the national bathymetry data and echo sounding data. From the results, we conclude that the SDB is promising in filling the gap of depth information in shallow water areas. A feasible coastline can be produced since depth information from the SDB model can increase the density of depth information required for generating a coastline model.

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