Abstract. Accurate determination of water depth is indispensable in multiple aspects of civil engineering (dock construction, dikes, submarines outfalls, trench control, etc.). To determine the type of atmospheric correction most appropriate for the depth estimation, different accuracies are required. Accuracy in bathymetric information is highly dependent on the atmospheric correction made to the imagery. The reduction of effects such as glint and cross-track illumination in homogeneous shallow-water areas improves the results of the depth estimations. The aim of this work is to assess the best atmospheric correction method for the estimation of depth in shallow waters, considering that reflectance values cannot be greater than 1.5 % because otherwise the background would not be seen. This paper addresses the use of hyperspectral imagery to quantitative bathymetric mapping and explores one of the most common problems when attempting to extract depth information in conditions of variable water types and bottom reflectances. The current work assesses the accuracy of some classical bathymetric algorithms (PolcynLyzenga, Philpot, Benny-Dawson, Hamilton, principal component analysis) when four different atmospheric correction methods are applied and water depth is derived. No atmospheric correction is valid for all type of coastal waters, but in heterogeneous shallow water the model of atmospheric correction 6S offers good results.

Remote sensing has been used since the 1980s to study parameters in relation with coastal zones. It was not until the beginning of the twenty-first century that it started to acquire imagery with good temporal and spectral resolution. This has encouraged the development of reliable imagery acquisition systems that consider remote sensing as a water management tool. Nevertheless, the spatial resolution that it provides is not adapted to carry out coastal studies. This article introduces a new methodology for estimating the most fundamental physical property of intertidal sediment, the grain size, in coastal zones. The study combines hyperspectral information (CASI-2 flight), robust statistic, and simultaneous field work (chemical and radiometric sampling), performed over Santander Bay, Spain. Field data acquisition was used to build a spectral library in order to study different atmospheric correction algorithms for CASI-2 data and to develop algorithms to estimate grain size in an estuary. Two robust estimation techniques (MVE and MCD multivariate M-estimators of location and scale) were applied to CASI-2 imagery, and the results showed that robust adjustments give acceptable and meaningful algorithms. These adjustments have given the following R(2) estimated results: 0.93 in the case of sandy loam contribution, 0.94 for the silty loam, and 0.67 for clay loam. The robust statistic is a powerful tool for large dataset.

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Abstract. Abstract. Accurate determination of water depth is indispensable in multiple aspects of civil engineering (dock construction, dikes, submarines outfalls, trench control, etc.). According to the final objective, different accuracies will be required. Accuracy in bathymetric information is highly dependent on the atmospheric correction made to the imagery. The reduction of effects such as glint and cross track illumination in shallow-water areas with homogeneous improves the results of the depth estimations. The aim of this work is to assess the best atmospheric correction method for the estimation of depth in shallow waters. This paper addresses the use of hyperspectral imagery to quantitative bathymetric mapping, and explores one of the most common problems when attempting to extract depth information in conditions of variable water types and bottom reflectances. The current work assesses the accuracy of some classical bathymetric algorithms (Polcyn-Lyzenga, Philpot, Benny-Dawson, Hamilton, Principal Component Analysis) when four different atmospheric correction methods are applied and water depth is derived. This work shows the importance of atmospheric correction in order to depth estimation in shallow waters. None atmospheric correction is valid for all type of coastal waters but in heterogeneous shallow water, the model of atmospheric correction 6S offers good results.