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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/590

Title: Can human-induced land degradation be distinguished from the effects of rainfall variability? A case study in South Africa
Authors: Wessels, KJ
Prince, SD
Malherbe, J
Small, J
Frost, PE
Van Zyl, D
Keywords: Communal lands
Monitoring
NPP
South Africa
NDVI
AVHRR
Issue Date: Jan-2007
Publisher: Elsevier Science Ltd
Citation: Wessels, KJ, et al. 2007. Can human-induced land degradation be distinguished from the effects of rainfall variability? A case study in South Africa. Journal of Arid Environment, vol. 68(2), pp 271-297
Abstract: Advanced Very High Resolution Radiometer (AVHRR), Normalized Difference Vegetation Index data (NDVI, I km (2), 1985-2003) and modelled net primary production (NPP, 8 km (2), 1981-2000) data were used to estimate vegetation production in South Africa (SA). The linear relationships of Log, Rainfall with NPP and Sigma NDVI were calculated for every pixel. Vegetation production generally had a strong relationship with rainfall over most of SA. Therefore, human-induced land degradation can only be detected if its impacts on vegetation production can be distinguished from the effects of rainfall. Two methods were tested (i) Rain-Use Efficiency (RUE = NPP/Rainfall or Sigma NDVI/ Rainfall) and (ii) Residual Trends (RESTREND), i.e. negative trends in the differences between the observed Sigma NDVI and the Sigma NDVI predicted by the rainfall. Degraded areas mapped by the National Land Cover in north-eastern SA had reduced RUE; however, annual RUE had a very strong negative correlation with rainfall and varied greatly between years. Therefore, RUE was not a reliable indicator of degradation. The RESTREND method showed promising results at a national scale and in the Limpopo Province, where negative trends were often associated with degraded areas in communal lands. Both positive and negative residual trends can, however, result from natural ecological processes, e.g. the carryover effects of rainfall in previous years. Thus, the RESTREND method can only identify potential problem areas at a regional scale, while the cause of negative trends has to be determined by local investigations.
Description: Copyright: 2007 Elsevier Science Ltd
URI: http://hdl.handle.net/10204/590
ISSN: 0140-1963
Appears in Collections:Remote Sensing
General science, engineering & technology

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