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Accuracy of the AVHRR vegetation index as a predictor of biomass, primary productivity and net CO2 flux

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Abstract

The Normalized Difference Vegetation Index (NDVI) or ‘greenness index’, based on the Advanced Very High Resolution Radiometer (AVHRR) aboard the NOAA-7 satellite, has been widely interpreted as a measure of regional to global vegetation patterns. This study provides the first rigorous, quantitative evaluation of global relationships between the NDVI and geographically representative vegetation data-bases, including field metabolic measurements and carbon-balance results from global simulation models. Geographic reliability of the NDVI is judged by comparing NDVI values for different surface types with a general global trend and by statistical analysis of relationships to biomass amounts, net and gross primary productivity, and actual evapotranspiration. NDVI data appear to be relatively reliable predictors of primary productivity except in areas of complex terrain, for seasonal values at high latitudes, and in extreme deserts. The strength of the NDVI-productivity relationship seems comparable to that of earlier climate-based productivity models. Little consistent relationship was found, across different vegetation types, between NDVI and biomass amounts or net biospheric CO2 flux.

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Abbreviations

AET=:

Actual Evapotranspiration

AVHRR=:

Advanced Very High Resolution Radiometer

GPP=:

Gross Primary Production

GVI=:

Global Vegetation Index

NDVI=:

Normalized Difference Vegetation Index

NPP=:

Net Primary Production

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Authors and Affiliations

  1. Geography Department, University of Georgia, 30602, Athens, GA, USA

    Elgene O. Box

  2. National Aeronautics and Space Administration, Goddard Space Flight Center, 20771, Greenbelt, MD, USA

    Brent N. Holben & Virginia Kalb

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  1. Elgene O. Box
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  2. Brent N. Holben
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  3. Virginia Kalb
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Box, E.O., Holben, B.N. & Kalb, V. Accuracy of the AVHRR vegetation index as a predictor of biomass, primary productivity and net CO2 flux. Vegetatio 80, 71–89 (1989). https://doi.org/10.1007/BF00048034

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