Abstract
The main focus of this work is to propose a method to depict one vegetation index from free clouds MSG2-SEVIRI (METEOSAT Second Generation 2 - Spining Enhanced in Visible and Infrared Imager) data. The proposed method uses the multi spectral high satellite data frequency (MSG2- SEVIRI image acquisition every 15 minutes), for rapid identification of Normalized Difference Vegetation Index (NDVI), and follow-up of its temporal evolution, to produce an approved monthly scale vegetation chart for a half terrestrial disk scanned by SEVIRI radiometer. To validate our method, we have compared each obtained result with other performed sensor embided on polar SPOT satellite called SPOT Vegetation.
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© 2013 Springer International Publishing Switzerland
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Benkahla, N., Hassini, A. (2013). Identification of Terrestrial Vegetation by MSG-SEVIRI Radiometer and Follow-Up of Its Temporal Evolution. In: Amine, A., Otmane, A., Bellatreche, L. (eds) Modeling Approaches and Algorithms for Advanced Computer Applications. Studies in Computational Intelligence, vol 488. Springer, Cham. https://doi.org/10.1007/978-3-319-00560-7_34
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DOI: https://doi.org/10.1007/978-3-319-00560-7_34
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-00559-1
Online ISBN: 978-3-319-00560-7
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