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Cloud Screening Methodology for MERIS/AATSR Synergy Products

Luis Gomez-Chova(1), Gustavo Camps-Valls(1), Jordi Muñoz-Mari(1), Javier Calpe(1) and Jose Moreno(1)

(1) University of Valencia, Dr Moliner 50, 46100 Burjasot (Valencia), Spain


This paper describes a cloud-screening method that exploits the combined information of both AATSR and MERIS instruments on board ENVISAT to improve current cloud masking products for both sensors. An accurate automatic detection of clouds is a key issue for a wide range of remote sensing applications. With no accurate cloud masking, undetected clouds are one of the most significant sources of error in both sea and land cover biophysical parameter retrieval.

The MERIS and AATSR instruments provide similar spatial resolution and swath but complementary information, encompassing different spectral domains and viewing geometries. The objective of this research is to explore synergistic use of both instruments in order to increase cloud detection accuracy. For this purpose, the method exploits the combined information of AATSR and MERIS instruments, such as the high spectral and radiometric resolutions of MERIS, the oxygen absorption feature on MERIS, the water vapour absorptions, and SWIR and thermal information from AATSR.

The cloud-screening scheme relies on the extraction of meaningful physical features (e.g. brightness, whiteness, temperature) that are combined with atmospheric absorption features at specific spectral band locations (oxygen and water vapour absorptions). The cloud-screening algorithm is capable of detecting clouds accurately, but also and very importantly, it provides a cloudiness index per pixel rather than a flag. This added value product allows the user to apply an adjustable cloud mask depending on the further processing stages and final use of the image. To attain this objective, the first part of the work is based on simulated data generated from coupled surface and atmospheric radiative transfer models. In particular, many simulated situations covering a wide range of real scenarios will be used for developing supervised cloud classifiers. Finally, the AATSR/MERIS cloud-screening algorithm is being implemented as an independent module in the BEAM toolbox in order to demonstrate how to identify the location and abundance of clouds present in AATSR/MERIS synergy products.

This work is being developed in the frame of the “MERIS/AATSR Synergy Algorithms for Cloud Screening, Aerosol Retrieval, and Atmospheric Correction” ESA project. The current status and results of the cloud-screening algorithm will be shown at the time of the conference.


Workshop presentation

Keywords: ESA European Space Agency - Agence spatiale europeenne, observation de la terre, earth observation, satellite remote sensing, teledetection, geophysique, altimetrie, radar, chimique atmospherique, geophysics, altimetry, radar, atmospheric chemistry