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Remote Sens. 2014, 6(10), 9552-9575; doi:10.3390/rs6109552

Assessing Land Degradation and Desertification Using Vegetation Index Data: Current Frameworks and Future Directions

School of Science and the Environment, Manchester Metropolitan University, Chester Street, Manchester, M1 5GD, UK
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Received: 6 August 2014 / Revised: 12 September 2014 / Accepted: 23 September 2014 / Published: 10 October 2014
(This article belongs to the Special Issue Remote Sensing of Land Degradation in Drylands)
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Abstract

Land degradation and desertification has been ranked as a major environmental and social issue for the coming decades. Thus, the observation and early detection of degradation is a primary objective for a number of scientific and policy organisations, with remote sensing methods being a candidate choice for the development of monitoring systems. This paper reviews the statistical and ecological frameworks of assessing land degradation and desertification using vegetation index data. The development of multi-temporal analysis as a desertification assessment technique is reviewed, with a focus on how current practice has been shaped by controversy and dispute within the literature. The statistical techniques commonly employed are examined from both a statistical as well as ecological point of view, and recommendations are made for future research directions. The scientific requirements for degradation and desertification monitoring systems identified here are: (I) the validation of methodologies in a robust and comparable manner; and (II) the detection of degradation at minor intensities and magnitudes. It is also established that the multi-temporal analysis of vegetation index data can provide a sophisticated measure of ecosystem health and variation, and that, over the last 30 years, considerable progress has been made in the respective research. View Full-Text
Keywords: land degradation; desertification; NDVI; NPP; multi-temporal; trend analysis; RESTREND; RUE; UNCCD land degradation; desertification; NDVI; NPP; multi-temporal; trend analysis; RESTREND; RUE; UNCCD
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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

Higginbottom, T.P.; Symeonakis, E. Assessing Land Degradation and Desertification Using Vegetation Index Data: Current Frameworks and Future Directions. Remote Sens. 2014, 6, 9552-9575.

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