Critical assessment of vegetation indices from AVHRR in a semi-arid environment

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 MS...

[1]  G. Dedieu,et al.  SMAC: a simplified method for the atmospheric correction of satellite measurements in the solar spectrum , 1994 .

[2]  R. Myneni,et al.  Atmospheric effects and spectral vegetation indices , 1994 .

[3]  J.-P. Goutorbe,et al.  HAPEX-Sahel: a large-scale study of land-atmosphere interactions in the semi-arid tropics , 1994 .

[4]  R. M. Mitchell,et al.  Atmospheric and viewing angle correction of vegetation indices and grassland fuel moisture content derived from NOAA/AVHRR , 1990 .

[5]  Garik Gutman,et al.  Vegetation indices from AVHRR: An update and future prospects , 1991 .

[6]  Bernard Pinty,et al.  Evaluation of the performance of various vegetation indices to retrieve vegetation cover from AVHRR data , 1994 .

[7]  R. Escadafal,et al.  Remote sensing of soil color: Principles and applications , 1993 .

[8]  Bernard Pinty,et al.  Towards a quantitative interpretation of vegetation indices Part 1: Biophysical canopy properties and classical indices , 1993 .

[9]  J. Leonard,et al.  The Vegetation of Africa , 1984 .

[10]  J. Clevers.  The Derivation of a Simplified Reflectance Model for the Estimation of Leaf Area Index , 1988 .

[11]  B. Pinty,et al.  The potential contribution of satellite remote sensing to the understanding of arid lands processes , 1991 .

[12]  A. J. Richardsons,et al.  DISTINGUISHING VEGETATION FROM SOIL BACKGROUND INFORMATION , 1977 .

[13]  Gérard Dedieu,et al.  Use of a meteorology model to correct atmospheric effects inNOAA-AVHRR data , 1994 .

[14]  Michel Desbois,et al.  Rainfall estimation in the Sahel: the EPSAT-NIGER experiment , 1992 .

[15]  Y. Kerr,et al.  On current compositing algorithms , 1997 .

[16]  P. Deschamps,et al.  Description of a computer code to simulate the satellite signal in the solar spectrum : the 5S code , 1990 .

[17]  Yoram J. Kaufman,et al.  Atmospheric correction against algorithm for NOAA-AVHRR products: theory and application , 1992, IEEE Trans. Geosci. Remote. Sens..

[18]  Yann Kerr,et al.  Geographical, biological and remote sensing aspects of the hydrologic atmospheric pilot experiment in the sahel (HAPEX-Sahel) , 1995 .

[19]  A. Huete.  A soil-adjusted vegetation index (SAVI) , 1988 .