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L'article du mois ( novembre 2017)

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

Bru D., Lubac B., Normandin C., Robinet A., Leconte M., Hagolle O., Martiny N. and Jamet C. Remote Sensing 2017, 9, 814

 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 spatialresolution 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 regardlessoftheseasonandaremainlyrepresentedbyamixedcoastalcontinentaltype. 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 (ρw) 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 ρw. 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).

Présentation rapide

Le Centre de Recherches de Climatologie (CRC) est une équipe de recherche de l'UMR6282 Biogéosciences (CNRS / Université de Bourgogne). Le CRC travaille sur la détection, l'attribution et la prévision du signal climatique et de ses impacts dans l'actuel et le futur. Ses activités sont centrées autour de la régionalisation du climat observé et simulé.

Le CRC est structuré en deux axes thématiques qui mettent en œuvre des méthodes permettant de passer de l'information large échelle (objet des travaux de l'équipe « Dynamique du Climat ») à une information d'échelle plus fine permettant d'évaluer les impacts (équipe « Impacts Climatiques »). Cette méthodologie relève de la statistique (méthodes statistico-dynamiques sur les sorties de modèles; statistiques spatiales;  désagrégation), de l'analyse spatiale (SIG opérateurs d'analyse spatiale vecteur et raster; interpolation spatiale mécaniste ou statistique), ou de la modélisation numérique du climat (modèles régionaux MM5 et WRF, modèle global Arpege-Climat).

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