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Abstract
The strong systematic change in solar zenith angles (SZA) due to annual orbital drift of the NOAA satellites has raised the suspicion of the influence of residual illumination on the calibrated normalized difference vegetation index (NDVI) derived from the Pathfinder AVHRR Land (PAL) database. The aim of this work is to analyse if trends in AVHRR NDVI from 1982 to 2000 over the Sahel region in Africa depend on variations in SZA.
The analysis uses both ordinary least squares regression and cointegration to analyse possible linear dependencies between NDVI and SZA on a per satellite basis. Tests for integration and cointegration fail to find any significant evidence for either. This, together with the ability of simple deterministic models to explain primarily SZA constitutes evidence against integration and cointegration, indicating that linear relationships can be examined using ordinary linear regression. Regression gives no consistent relationship between NDVI and SZA and the explanatory power (R 2) of the regression is low (on average 0.08).
However there is some evidence for downward bias in NDVI due to nonlinear interactions between NDVI and SZA when SZA is large (80°) leading to the conclusion that PAL data from the year 2000 should not be used for analyses in these environments.
Acknowledgment
J. Lindström, J. Holst, and U. Holst have been partially funded by the Swedish Foundation for Strategic Research under grant A3 02 : 125, Spatial statistics and image analysis for environment and medicine.
L. Eklundh was financed through a grant from the Swedish National Space Board (SNSB).
Data used by the authors in this study include data produced through funding from the Earth Observing System Pathfinder Program of NASA's Mission to Planet Earth in cooperation with National Oceanic and Atmospheric Administration. The data were provided by the Earth Observing System Data and Information System (EOSDIS), Distributed Active Archive Center at Goddard Space Flight Center which archives, manages, and distributes this dataset.
