Coupled human-environment system approaches to desertification: Linking people to pixels

Eric F. Lambin, Helmut J Geist, James F. Reynolds, D. Mark Stafford Smith

Research output: Chapter in Book/Report/Conference proceedingChapter

13 Citations (Scopus)


The first part of this paper provides the rationale for approaching desertification by integrating biophysical and socio-economic data. We start with a brief overview of the causes and consequences of land degradation in global drylands, with an emphasis on the interaction between human and natural dimensions of the problem. We then introduce a new paradigm on desertification that accounts for the need to adopt an integrated appraoch to the problem. The second part discusses methodologies to achieve that integration by linking remote sensing data with household survey data. The combination of remote sensing and socio-economic data is increasingly used to better assess land-use changes but little work has been conducted in the context of drylands. Different approaches have been followed: socio-economic surveys to explain or supplement observed patterns of land-cover change; overlay analyses of spatially explicit socio-economic and land-cover data; proximity analyses; interpretations of spatial patterns of land use in terms of land use practices; and joint statistical analyses of spatially explicit household survey and land cover data. After a review of the literature, we propose an eight-step methodology to conduct integrated, place-based research on desertification.
Original languageEnglish
Title of host publicationRecent advances in remote sensing and geoinformation processing for land degradation assessment
EditorsAchim Röder, Joachim Hill
Place of PublicationLeiden, Netherlands
PublisherCRC Press/Balkema
Number of pages11
ISBN (Print)0415397693, 978-0415397698
Publication statusPublished - 22 Apr 2009

Publication series

NameInternational Society for Photogrammetry and Remote Sensing (ISPRS) Book Series
PublisherCRC Press/Balkema


  • Desertification
  • Remote sensing
  • Dahlem paradigm


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