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Critical assessment of vegetation indices from AVHRR in a semi-arid environment
Authors:C LEPRIEUR  Y H KERR  J M PICHON
Affiliation:1. Centre d'Etudes Spatiales de la BIOsphére (CESBIO),—UMR 141 (CNES-CNRS-UPS) , 18. Av. Edouard Belin, Toulouse, F-31055, France;2. Laboratoire de Météorologie Physique, URA 267/CNRS Université Blaise Pascal , Aubière, F-63177, France
Abstract:The most frequently used vegetation index (VI), the Normalized Difference Vegetation Index (NDVI) and its variants introduced recently to correct for atmospheric and soil optical response such as Global Environment Monitoring Index (GEMI) and Modified Soil-Adjusted Vegetation Index (MSAVI) are evaluated over a Sahelian region. The usefulness and limitations of the various vegetation indices are discussed, with special attention to cloud contamination and green vegetation detection from space. The HAPEX Sahel database is used as a test case to compare these indices in arid and semi-arid environments. Selected sites are characterized by sparse vegetation cover and day-to-day variability in atmospheric composition. Simulated indices values behaviour at the surface level shows that these VIs were all sensitive to the presence of green vegetation but were affected differently by changes in soil colour and brightness. We showed that GEMI is less sensitive to atmospheric variations than both NDVI and MSAVI since it exhibits a high atmospheric transmissivity over its entire range for various atmospheric aerosol loadings and water vapour contents. These results were first tested on a vegetation gradient, and secondly evaluated on a transect which encompasses various soils formations. On the vegetation gradient, it was found that GEMI computed from measurements at the top of the atmosphere is invariable from one day to the next. On the bare soils transect, MSAVI calculated at the surface level, has shown a great insensitivity to soil optical responses modifications, while GEMI exhibits from space noticeable variability in this bright soil context. Finally, it was illustrated that GEMI exhibits interesting properties for cloud detection because of the strong decrease of its value on cloudy pixels.
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