Using remote sensing tools to assess land use transitions in unsustainable arid agro-ecosystems

Jose Raul Romo-Leon*, Willem J.D. van Leeuwen, Alejandro Castellanos-Villegas

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


This research investigates the human impact on land-cover dynamics in arid agro-ecosystems. Our study area was La Costa de Hermosillo (northwestern Mexico), where the unregulated use of water resources has resulted in the abandonment of irrigated agricultural fields and a shift to new economic activities. Using remote sensing and ancillary datasets combined with classification and regression tree (CART) models, we mapped land-cover class distributions over 22 years (1988-2009) to characterize agricultural changes following management decisions. Our land-cover classification maps had an overall accuracy of over 80%. Using these maps, we were able to show the decrease in agriculture from approximately 115,066 to 66,044ha between 1988 and 2009 and the conversion to alternative economic activities, with aquaculture increasing from 0 to 10,083ha during the same period. Our analyses also show the temporal-spatial dynamics of land-use management practices, which suggest that implementation of the remote sensing methods developed in this manuscript may contribute to bridging the gap of knowledge between ecological effects and unsustainable management practices and decrease the time required to inform and make policy decisions in arid agro-ecosystems.

Original languageEnglish
Pages (from-to)27-35
Number of pages9
JournalJournal of Arid Environments
StatePublished - Jul 2014

Bibliographical note

Funding Information:
The authors wish to thank the support for this research provided by the Arizona Remote Sensing Center , University of Arizona, Tucson, AZ, USA. JRRL wishes to acknowledge support from CONACYT in the form of a PhD scholarship and to recognize the assistance with the field work provided by the CONAFOR-CONACYT grant ( 10644 ) to AECV. Landsat TM data were obtained through the online USGS/Earth Resources Observation and Science (EROS) Earth Explorer website .


  • Desert succession
  • Land-cover change
  • Remote sensing
  • Sonoran Desert
  • Sustainable management policies


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