Cellular Automata for modelling land use change as driven by socio-economic, environmental and policy factors

In this paper we present a decision support framework developed to assist planners and policy makers to analyse a wide range of policies and their associated spatial patterns. The core of this framework consists of dynamic spatial models that operate at both the microand macro-geographical levels. At the macro level, the modelling framework integrates several component sub-models, representing the natural, social, and economic sub-systems typifying the area studied. These are all linked to each other in a network of mutual reciprocal, influence. At the micro level, cellular automata based models determine the fate of individual parcels of land based on their individual institutional and environmental characteristics as well as on the type of activities in their neighbourhoods. Unlike conventional cellular automata, these models are defined with larger neighbourhoods, and more cell-states representing socio-economic land uses and natural land cover. Their overall dynamics are constrained by the models at the macro level. The approach permits the straightforward integration of detailed physical, environmental, and institutional variables, as well as the particulars of the transportation infrastructure. Consequently, they are suited to form the heart of spatial Decision Support Systems developed for integrated land use management or policymaking. In the DSS the models are supplemented with tools enabling the design of policy interventions as well as the analysis and evaluation of their effectiveness in attaining a desirable future for the area studied. Applications to the Island of St. Lucia (West Indies), the coastal zone of South West Sulawesi (Indonesia), the Netherlands, and Mediterranean watersheds will be presented.