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
modelling 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 modelling 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.
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