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

Remote Sensing

Cheikh Mbow²  Martin Brandt¹  Issa Ouedraogo²  Jan de Leeuw⁴  Michael Marshall²  Arnon Karnieli³  Ioannis Gitas³ 

[1] Institute of Geography, University of Bayreuth, Bayreuth 95440, Germany;World Agroforestry Centre-ICRAF-SD6, United Nations Avenue, Gigiri 00100, Nairobi 30677, Kenya; E-Mails:World Agroforestry Centre-ICRAF-SD6, United Nations Avenue, Gigiri 00100, Nairobi 30677, Kenya;;World Agroforestry Centre-ICRAF, East and Central African Office, Gigiri 00100, Nairobi 30677, Kenya; E-Mail:

关键词: Sahel;    land degradation;    desertification;    remote sensing;    vegetation indices;    drylands;    NDVI;    productivity;   

DOI  :  10.3390/rs70404048

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.