Abstract
Abstract. Water depth is an important measure for nautical charts. Accurate methods to provide water depth information are expensive and time costing. For this reason, since late 70’s, it started to be estimate by multispectral sensors with empirical models. In the literature there is no investigation using empirical models partitioned in depth intervals, for this reason, we evaluated the accuracy of partitioned and single bathymetric models. The results have shown that to retrieve depth in from 0 to 15 m the single model provided an RMSE of 3.57 m, with a bias of about −0.83 m; while the RMSE for the partitioned model was 2.29 m with a bias of 0.41 m. For updating nautical charts using multispectral sensors it was concluded that the partitioned model can provide a better result than using a single model.
Highlights
Accurate water depth measurement is an important parameter in aquatic system, since this information could be used e.g to make or update nautical charts to support navigation, explain the amount of deposit sediments, and manage and monitor areas close to water system
The bias in the partitioned models is smaller for all classes while the single model exceeds 1 m in two out of three classes
The major unconformity is shown in the interval between 0-5 m, showing a standard deviation three times bigger in the single model and bias eleven times higher
Summary
Accurate water depth measurement is an important parameter in aquatic system, since this information could be used e.g to make or update nautical charts to support navigation, explain the amount of deposit sediments, and manage and monitor areas close to water system. Nowadays the most common techniques to provide bathymetric information are echosounders and airborne laser bathymetry These methods are accurate, they are expansive and time consuming. For this reason, in the last decades, Remote Sensing techniques have been used to acquire depth in shallow water from multispectral and hyperspectral sensors (Lyzenga,1978; Stumpf et al, 2003, Dierssen et al, 2003; Pacheco et al, 2015; Kerr, Purkis, 2018; Brando et al.,2009). A simpler physical-based approach was created by Lyzenga et al (2006) that can estimate the water depth independently of the ground truth
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