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.
Original language | English |
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Journal | Remote Sensing |
Volume | 7 |
Issue number | 4 |
Pages (from-to) | 4048-4067 |
Number of pages | 20 |
ISSN | 2072-4292 |
DOIs | |
Publication status | Published - 1 Apr 2015 |
Keywords
- Desertification, drylands, land degradation, NDVI, Productivity, Remote sensing, Sahel, vegetation indices