Agent-based modeling and genetic programming for modeling land change in the Southern Yucatán Peninsular Region of Mexico

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161 Scopus citations


Land-use and land-cover change research increasingly takes the form of integrated land-change science, the explicit joining of ecological, social and information sciences. Traditional interdisciplinary methods are buttressed by new ones stemming from computational intelligence research and the complexity sciences. Several of these - genetic programming, cellular modeling and agent-based modeling - are applied to land change in the Southern Yucatán Peninsular Region (SYPR) of Mexico through the SYPR Integrated Assessment (SYPRIA). This work illustrates how computational intelligence techniques, such as genetic programming, can be used to model decision making in the context of human-environment relationships. This application also contributes to methodological innovations in multicriteria evaluation and modeling of coupled human-environment systems. This effort also demonstrates the importance of considering both social and environmental drivers of land change, particularly with respect to the decision making of change agents within the context of key socioeconomic and political drivers, particularly as channelled through market institutions and land tenure, and ecological factors, especially characteristics of land-use and land-cover such as state, history and fragmentation. SYPRIA demonstrates the utility of modeling methods based in computational intelligence and the complexity sciences in helping understand the decision making of land-change agents as a function of both social and environment drivers.

Original languageEnglish (US)
Pages (from-to)47-62
Number of pages16
JournalAgriculture, Ecosystems and Environment
Issue number1-4
StatePublished - Dec 1 2005

Bibliographical note

Funding Information:
This work is supported by the National Aeronautics and Space Administration (NASA) Earth System Science Fellowship program (ESS 99-0000-0008) and a National Science Foundation Doctoral Dissertation Improvement grant (NSF 99-07952). It is also supported by NASA's Land-Cover and Land-Use Change program through the Southern Yucatán Peninsular Region project (NAG 56406 and NAG 511134) and the Center for Integrated Studies of Global Environmental Change, Carnegie Mellon University (NSF-SBR 95-21914). The author gratefully acknowledges the assistance of SYPR project personnel. Responsibility for the opinions expressed herein is solely that of the author.


  • Agent-based model
  • Genetic program
  • Land-use and land-cover change
  • Multicriteria evaluation
  • Symbolic regression


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