Development of cloud, snow, and shadow masking algorithms for VEGETATION imagery

Author

Lisens, G. ; Kempencers, P. ; Fierens, F. ; Van Rensbergen, J.

Author_Institution

Centre of Remote Sensing & Atmos. Processes, Vito, Belgium, Germany

Volume

2

fYear

2000

fDate

2000

Firstpage

834

Abstract

Cloud detection is an essential part of the preprocessing chain for various products of the VEGETATION sensor aboard the SPOT satellite. State of the art techniques have been developed to construct a 3 level cloud mask and a binary snow mask. A genetic algorithm has been developed to optimize thresholds on the VEGETATION spectral bands. The increase in performance is dramatic, and improves the quality of VEGETATION products (atmospheric correction, synthesis...). Clouds also cast shadows on the Earth´s surface. This can lead up to a 40% bias of the true reflectance of the underlying terrain element. A new and fully automated technique has been developed to provide a cloud shadow mask, based on geometry and radiometry

Keywords

genetic algorithms; geophysical signal processing; geophysical techniques; image processing; remote sensing; terrain mapping; vegetation mapping; SPOT; VEGETATION imagery; VEGETATION sensor; binary snow mask; cloud; cloud mask; genetic algorithm; geophysical measurement technique; image processing; land surface; multispectral remote sensing; preprocessing; satellite remote sensing; shadow masking algorithm; snow; spectral band; terrain mapping; vegetation mapping; Clouds; Earth; Genetic algorithms; Geometry; Lead; Radiometry; Reflectivity; Satellite broadcasting; Snow; Vegetation mapping;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-6359-0

Type

conf

DOI

10.1109/IGARSS.2000.861719

Filename

861719