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The main objective of this research is to evaluate the effect of sentinel multispectral images on estimating shallow water depth using linear bathymetry model. Multispectral image data was integrated with available echo sounding and GPS data for the determination of the bathymetry after tide correction in three areas on Delta coast i.e., Kitchiner, Damietta and Rashid. Three visible and one near infrared band (Top of Atmospheric Reflectance level, with 10 m resolution) were used in models derivation. Sentinel image bands were geometrically and atmospherically corrected and sun glint was removed prior to bathymetry models estimation. Three models with ln function were the derivates using Ordinary Least Square (OLS) modeling tool under ArcGIS environment. The results indicated that Adjusted R-Squared for the three estimated bathymetry models were 0.68, 0.62 and 0.72 for Damietta, Rashid and Kitchiner areas respectively. About 75% of the residual values ranged from -1.63 to 1.3 m for Damietta points and 50% of the residual values were between -0.39 to 0.57 m for Rashid and about 65% between -0.76 to 0.97 m for Kitchiner. Hence it can be concluded that these predicted models provide time- and cost-effective solution for Shallow water depths estimation.

Derivation of Bathymetry Models for Shallow Water Using Multispectral Sentinel-2A Images for Delta Coast of Egypt