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Remote Sens. 2015, 7(4), 4048-4067; doi:10.3390/rs70404048

What Four Decades of Earth Observation Tell Us about Land Degradation in the Sahel?

1
World Agroforestry Centre-ICRAF-SD6,, United Nations Avenue, Gigiri 00100, Nairobi 30677, Kenya
2
Institute of Geography, University of Bayreuth, Bayreuth 95440, Germany
4
World Agroforestry Centre-ICRAF, East and Central African Office, Gigiri 00100, Nairobi 30677, Kenya
3
Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen 1350, Denmark
*
Author to whom correspondence should be addressed.
Academic Editors: Arnon Karnieli, Ioannis Gitas and Prasad S. Thenkabail
Received: 15 December 2014 / Revised: 24 March 2015 / Accepted: 27 March 2015 / Published: 2 April 2015
(This article belongs to the Special Issue Remote Sensing of Land Degradation in Drylands)
View Full-Text   |   Download PDF [813 KB, uploaded 22 April 2015]   |  

Abstract

The assessment of land degradation and the quantification of its effects on land productivity have been both a scientific and political challenge. After four decades of Earth Observation (EO) applications, little agreement has been gained on the magnitude and direction of land degradation in the Sahel. The large number of EO datasets and methods associated with the complex interactions among biophysical and social drivers of ecosystem changes make it difficult to apply aggregated EO indices for these non-linear processes. Hence, while many studies stress that the Sahel is greening, others indicate no trend or browning. The different generations of sensors, the granularity of studies, the study period, the applied indices and the assumptions and/or computational methods impact these trends. Consequently, many uncertainties exist in regression models between rainfall, biomass and various indices that limit the ability of EO science to adequately assess and develop a consistent message on the magnitude of land degradation. We suggest several improvements: (1) harmonize time-series data, (2) promote knowledge networks, (3) improve data-access, (4) fill data gaps, (5) agree on scales and assumptions, (6) set up a denser network of long-term field-surveys and (7) consider local perceptions and social dynamics. To allow multiple perspectives and avoid erroneous interpretations, we underline that EO results should not be interpreted without contextual knowledge. View Full-Text
Keywords: Sahel; land degradation; desertification; remote sensing; vegetation indices; drylands; NDVI; productivity Sahel; land degradation; desertification; remote sensing; vegetation indices; drylands; NDVI; productivity
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Mbow, C.; Brandt, M.; Ouedraogo, I.; de Leeuw, J.; Marshall, M. What Four Decades of Earth Observation Tell Us about Land Degradation in the Sahel? Remote Sens. 2015, 7, 4048-4067.

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