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

Abstract 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 Yucatan 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.