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Remote Sens. 2017, 9(8), 814;

Atmospheric Correction of Multi-Spectral Littoral Images Using a PHOTONS/AERONET-Based Regional Aerosol Model

Univ. Bordeaux, UMR 5805, EPOC, Environnements et Paléoenvironnements Océaniques et Continentaux, 33615 Pessac, France
CNES, CNRS, IRD, Univ. Toulouse, UMR 5126, CESBIO, Centre d’Etudes Spatiales de la BIOsphère, 31401 Toulouse, France
Univ. Bourgogne, UMR 6282, Biogéosciences, 21000 Dijon, France
Univ. Littoral Cote d’Opale, Univ. Lille, CNRS, UMR 8187, LOG, Laboratoire d’Océanologie et de Géosciences, 62930 Wimereux, France
Author to whom correspondence should be addressed.
Received: 29 June 2017 / Revised: 1 August 2017 / Accepted: 4 August 2017 / Published: 8 August 2017
(This article belongs to the Special Issue Atmospheric Correction of Remote Sensing Data)
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Spatial resolution is the main instrumental requirement for the multi-spectral optical space missions that address the scientific issues of marine coastal systems. This spatial resolution should be at least decametric. Aquatic color data processing associated with these environments requires specific atmospheric corrections (AC) suitable for the spectral characteristics of high spatial resolution sensors (HRS) as well as the high range of atmospheric and marine optical properties. The objective of the present study is to develop and demonstrate the potential of a ground-based AC approach adaptable to any HRS for regional monitoring and security of littoral systems. The in Situ-based Atmospheric CORrection (SACOR) algorithm is based on simulations provided by a Successive Order of Scattering code (SOS), which is constrained by a simple regional aerosol particle model (RAM). This RAM is defined from the mixture of a standard tropospheric and maritime aerosol type. The RAM is derived from the following two processes. The first process involved the analysis of a 6-year data set composed of aerosol optical and microphysical properties acquired through the ground-based PHOTONS/AERONET network located at Arcachon (France). The second process was related to aerosol climatology using the NOAA hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model. Results show that aerosols have a bimodal particle size distribution regardless of the season and are mainly represented by a mixed coastal continental type. Furthermore, the results indicate that aerosols originate from both the Atlantic Ocean (53.6%) and Continental Europe (46.4%). Based on these results, absorbing biomass burning, urban-industrial and desert dust particles have not been considered although they represent on average 19% of the occurrences. This represents the main current limitation of the RAM. An assessment of the performances of SACOR is then performed by inter-comparing the water-leaving reflectance ( ρ w ) retrievals with three different AC methods (ACOLITE, MACCS and 6SV using three different standard aerosol types) using match-ups (N = 8) composed of Landsat-8/Operational Land Imager (OLI) scenes and field radiometric measurements. Results indicate consistency with the SWIR-based ACOLITE method, which shows the best performance, except in the green channel where SACOR matches well with the in-situ data (relative error of 7%). In conclusion, the study demonstrates the high potential of the SACOR approach for the retrieval of ρ w . In the future, the method could be improved by using an adaptive aerosol model, which may select the most relevant local aerosol model following the origin of the atmospheric air mass, and could be applied to the latest HRS (Sentinel-2/MSI, SPOT6-7, Pleiades 1A-1B). View Full-Text
Keywords: aquatic color radiometry; atmospheric corrections; coastal waters; high spatial resolution; aerosol model; remote sensing aquatic color radiometry; atmospheric corrections; coastal waters; high spatial resolution; aerosol model; remote sensing

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Bru, D.; Lubac, B.; Normandin, C.; Robinet, A.; Leconte, M.; Hagolle, O.; Martiny, N.; Jamet, C. Atmospheric Correction of Multi-Spectral Littoral Images Using a PHOTONS/AERONET-Based Regional Aerosol Model. Remote Sens. 2017, 9, 814.

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