Journal
GLOBAL AND PLANETARY CHANGE
Volume 92-93, Issue -, Pages 71-81Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.gloplacha.2012.05.003
Keywords
NDVI; long-term biomass productivity trend; land degradation; soil erosion; multi-scale approach; Volta basin; West Africa
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Separating human-induced land degradation from that caused by natural processes in the world of global climate and atmospheric change is a challenging task, but important for developing mitigation strategies. Current remote-sensing data and spatio-temporal analyses allow the distinction of climate and human-induced land degradation on a sub-continental scale, but the underlying processes cannot be discerned at this scale. This study is conducted at a river-basin scale to (1) identify land degradation hotspots in a basin or sub-basin, and (2) assess the correspondence and divergence of land degradation assessed by NDVI shifts with and without accounting for atmospheric fertilization with that based on soil erosion assessment at a sub-basin scale. Long-term remote sensing (NDVI) and rainfall data were used to identify human-induced land degradation hotspot areas in the Volta basin. The results were compared with the critical zone of soil loss in the White Volta sub-basin derived from a spatially distributed soil erosion model, validated by field-measured data. A spatial comparison of the above studies revealed that the biomass productivity (NDVI)-based land degradation assessment grossly underestimated the extent to which soil is being lost, unless a correction was included to account for atmospheric fertilization. Based on inter-annual NDVI signals land degradation was evident in about 8% of the Volta basin's landmass, but when accounting for atmospheric fertilization, as much as 65% of the land is losing some of its vital attributes such as soil quality or vegetation productivity. The study demonstrates the need for using a multi-pronged assessment strategy in land degradation assessment that offers an insight of the processes involved in land degradation. (C) 2012 Elsevier B.V. All rights reserved.
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