Abstract
Most of the studies dealing with seabed mapping from hyperspectral images have been carried out using airborne data although hyperspectral satellite sensors have already been or are planned to be launched for the near future (hyperspectral imager for the coastal ocean (HICO) environmental mapping and analysis program (ENMAP) or BIODIVERSITY). The objective of this study is to evaluate the benefit of a BIODIVERSITY-like sensor to determine the bio-optical properties of the water column, namely the Chlorophyll-a concentration, the suspended particulate matter (SPM) concentration, the absorption coefficient of the colored dissolved organic matter (CDOM), the bathymetry and the composition of the seabed, according to its spatial resolution and spectral resolution and its signal to noise ratio. For this purpose, radiative transfer simulations are analyzed together with remote sensing hyperspectral airborne data acquired above the Porquerolles Island (France). The retrieval performance of all in-water and seabed parameters derived from the inversion of BIODIVERSITY-like data is compared with the performance obtained using ENMAP and HICO spatial and radiometric specifications. It is shown that a BIODIVERSITY-like sensor significantly improves the estimation performance of the water column parameters. Furthermore, BIODIVERSITY-like sensor is highly appropriate for seabed mapping when bottom pixels are composed of pure material (e.g., Sand or Posidonia ) in shallow waters when seabed depth is less than 10 m. Conversely, the performance of the inversion deteriorates when seabed pixels are composed of mixed materials (e.g., Sand mixed with Posidonia ). It is also shown that the concentration of chlorophyll, SPM and CDOM absorption are less sensitive to noise level than depth and seabed abundance.
Highlights
T HERE is a growing interest in the use of hyperspectral imagery, in the field of ocean optics along with the deployment of new hyperspectral satellites [1]
The relative error decreases with the seabed depth because of the stronger influence of the water column relative to the influence of the seabed, which leads to an improvement in the performance of the suspended particulate matter (SPM) retrieval
Note that the absolute error is low for Chl, SPM, and colored dissolved organic matter (CDOM), while the relative error is high because their concentrations are weak not significantly influencing the reflectance; the retrieval performance of these variables with a high degree of accuracy remains challenging using semi-analytical model inversion
Summary
T HERE is a growing interest in the use of hyperspectral imagery, in the field of ocean optics along with the deployment of new hyperspectral satellites [1]. Hyperspectral imagery offers numerous advantages including the spectroscopic techniques for analyzing the remote signal which allows a better understanding of water optical properties even in turbid waters [2]. The recent interest in hyperspectral imagery is amplified by the fact that it allows estimations of geophysical products over different geographic sites, in open as in coastal waters, without needing to have previously chosen the location of bands [5]. This is in conjugation with the growing scientific interest in differentiating certain phytoplankton species/groups and characterizing seabed composition. Further studies in the field of hyperspectral imagery are necessary [6]
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