Abstract
Abstract. Hyperspectral imaging provides quantitative remote sensing of ocean colour by the high spectral resolution of the water features. The HICO™ (Hyperspectral Imager for the Coastal Ocean) is suitable for coastal studies and monitoring. The accurate retrieval of hyperspectral water-leaving reflectance from HICO™ data is still a challenge. The aim of this work is to retrieve the water-leaving reflectance from HICO™ data with a physically based algorithm, using the local microphysical properties of the aerosol in order to overcome the limitations of the standard aerosol types commonly used in atmospheric correction processing. The water-leaving reflectance was obtained using the HICO@CRI (HICO ATmospherically Corrected Reflectance Imagery) atmospheric correction algorithm by adapting the vector version of the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) radiative transfer code. The HICO@CRI algorithm was applied on to six HICO™ images acquired in the northern Mediterranean basin, using the microphysical properties measured by the Acqua Alta Oceanographic Tower (AAOT) AERONET site. The HICO@CRI results obtained with AERONET products were validated with in situ measurements showing an accuracy expressed by r2 = 0.98. Additional runs of HICO@CRI on the six images were performed using maritime, continental and urban standard aerosol types to perform the accuracy assessment when standard aerosol types implemented in 6SV are used. The results highlight that the microphysical properties of the aerosol improve the accuracy of the atmospheric correction compared to standard aerosol types. The normalized root mean square (NRMSE) and the similar spectral value (SSV) of the water-leaving reflectance show reduced accuracy in atmospheric correction results when there is an increase in aerosol loading. This is mainly when the standard aerosol type used is characterized with different optical properties compared to the local aerosol. The results suggest that if a water quality analysis is needed the microphysical properties of the aerosol need to be taken into consideration in the atmospheric correction of hyperspectral data over coastal environments, because aerosols influence the accuracy of the retrieved water-leaving reflectance.
Highlights
Hyperspectral imaging is well suited to investigating water quality in coastal environments where a local scale is required in the case of optically complex coastal waters (Amin et al, 2014; Gitelson et al, 2011; Gao et al, 2009)
The the HICO@CRI algorithm results obtained considering the local microphysical properties of the aerosol as provided by the Alta Oceanographic Tower (AAOT) site at the HICOTM acquisition time were validated using in situ data
This study has highlighted the impact of the microphysical properties of aerosol on the accuracy of the results of the physically based atmospheric correction of hyperspectral data acquired over coastal water with clear improvement on the simplification typical of the aerosol standard types (Zibordi et al, 2009a; Gordon and Wang, 1994)
Summary
Hyperspectral imaging is well suited to investigating water quality in coastal environments where a local scale is required in the case of optically complex coastal waters (Amin et al, 2014; Gitelson et al, 2011; Gao et al, 2009). For these applications, the water-leaving reflectance has to be obtained by accurate atmospheric modelling because only 10 % of the total radiance received by sensor come from the water target (Antoine and Morel, 1999). Retrieving the water-leaving reflectance involves the removal of the sea surface contribution due to sun, view geometry and wind speed (McClain, 2009; Morel and Gentili, 1996, 1991; Gordon and Wang, 1992) in addition to removing the atmospheric contribution from the total sensor signal
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