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GeoJournal

, Volume 61, Issue 4, pp 353–363 | Cite as

Temporal dynamics and spatial scales: Modeling deforestation in the southern Yucatán peninsular region

  • Jacqueline Geoghegan
  • Laura Schneider
  • Colin Vance
Article

Abstract

Two spatially explicit econometric land use change models are presented, focusing on tropical deforestation caused by agricultural expansion in the southern Yucatán peninsula, Mexico. The two models developed are both based on conceptually similar theoretical models of farmer behavior. However, there are different empirical specifications of this theoretical model according to the scale of the analysis as well as the availability of temporal data on the observation of deforestation. For both models, the unit of observation for the dependent variable of deforestation is the TM pixel from satellite data. However, the socio-economic explanatory variables are derived from different sources. The first econometric model links the satellite data for the entire study region with aggregate census data at the village level. This model is estimated using a discrete choice logit model over a single time period. The second econometric model uses individual household survey data for a small random sample of the region, linked to satellite data for the plots of each household over multiple time periods. This model is estimated using a dynamic hazard model that estimates the risk of a specific pixel converting from forest to agricultural use. Both estimated models are used to predict deforestation and the results of the two modeling approaches are compared.

Keywords

econometric models spatially explicit land use change tropical deforestation 

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Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Jacqueline Geoghegan
    • 1
  • Laura Schneider
    • 2
  • Colin Vance
    • 3
  1. 1.Department of Economics and George Perkins Marsh InstituteClark UniversityWorcesterUSA
  2. 2.Department of GeographyRutgers UniversityNew JerseyUSA
  3. 3.German Aerospace CenterInstitute of Transport ResearchBerlinGermany

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