Assessing Land Degradation/Recovery in the African Sahel from Long-Term Earth Observation Based Primary Productivity and Precipitation Relationships

Rasmus Fensholt, Kjeld Rasmussen, Per Skougaard Kaspersen, Silvia Huber, Stephanie Horion, Else Swinnen

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    Abstract

    The ‘rain use efficiency’ (RUE) may be defined as the ratio of above-ground net
    primary productivity (ANPP) to annual precipitation, and it is claimed to be a conservative
    property of the vegetation cover in drylands, if the vegetation cover is not subject to
    non-precipitation related land degradation. Consequently, RUE may be regarded as means
    of normalizing ANPP for the impact of annual precipitation, and as an indicator of
    non-precipitation related land degradation. Large scale and long term identification and
    monitoring of land degradation in drylands, such as the Sahel, can only be achieved by use
    of Earth Observation (EO) data. This paper demonstrates that the use of the standard
    EO-based proxy for ANPP, summed normalized difference vegetation index (NDVI)
    (National Oceanic and Atmospheric Administration (NOAA) Advanced Very High
    Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies 3rd
    generation (GIMMS3g)) over the year (ΣNDVI), and the blended EO/rain gauge based
    data-set for annual precipitation (Climate Prediction Center Merged Analysis of
    Precipitation, CMAP) results in RUE-estimates which are highly correlated with precipitation, rendering RUE useless as a means of normalizing for the impact of annual
    precipitation on ANPP. By replacing ΣNDVI by a ‘small NDVI integral’, covering only
    the rainy season and counting only the increase of NDVI relative to some reference level,
    this problem is solved. Using this approach, RUE is calculated for the period 1982–2010.
    The result is that positive RUE-trends dominate in most of the Sahel, indicating that
    non-precipitation related land degradation is not a widespread phenomenon. Furthermore,
    it is argued that two preconditions need to be fulfilled in order to obtain meaningful results
    from the RUE temporal trend analysis: First, there must be a significant positive linear
    correlation between annual precipitation and the ANPP proxy applied. Second, there must
    be a near-zero correlation between RUE and annual precipitation. Thirty-seven percent of
    the pixels in Sahel satisfy these requirements and the paper points to a range of different
    reasons why this may be the case.
    Original languageEnglish
    JournalRemote Sensing
    Volume5
    Pages (from-to)664-686
    ISSN2072-4292
    DOIs
    Publication statusPublished - 2013

    Bibliographical note

    © 2013 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).

    Keywords

    • Rain use efficiency
    • Semi-arid
    • Trend analysis
    • GIMMS3g NDVI
    • CMAP rainfall
    • TIMESAT seasonal parameterization

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