Paper
10 October 2011 Validation of the background simulation model MATISSE: comparing results with MODIS satellite images
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Abstract
Generally available satellite images, e. g. from the MODIS sensor, provide data in spectral bands, which are suitable for remote sensing applications and earth surface observations. However, for some applications different bands as well as specific cloud formations for a certain region may be of interest, thus making the simulation of background data essential. Therefore, the software MATISSE ("Advanced Modeling of the Earth for Environment and Scenes Simulation") proved to be the appropriate tool. MATISSE is an infrared background scene generator developed by ONERA for computing natural background spectral radiance images including atmosphere, sea, land and high and low altitude clouds. In order to validate the model, comparisons with MODIS satellite data have been carried out using images in available spectral bands. The investigations comprised selected surface structures like sea, desert, lowland (dry) and highlands (humid). In general, the results on radiance images show a good correlation between MODIS image and the MATISSE-simulation. This paper focuses on comparing results between simulated MATISSE radiance images and the MODIS observations. Based on this, possible sources of error and the limits of the model are discussed.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Caroline Schweitzer, Karin Stein, Norbert Wendelstein, Luc Labarre, Karine Caillault, Sandrine Fauqueux, Claire Malherbe, Antoine Roblin, Bernard Rosier, and Pierre Simoneau "Validation of the background simulation model MATISSE: comparing results with MODIS satellite images", Proc. SPIE 8178, Optics in Atmospheric Propagation and Adaptive Systems XIV, 817805 (10 October 2011); https://doi.org/10.1117/12.901099
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Cited by 7 scholarly publications.
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KEYWORDS
MODIS

Atmospheric modeling

Data modeling

Satellites

Satellite imaging

Clouds

Atmospheric particles

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