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Land Use Dynamics: a Cellular Automata
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Abstract
Usually applications of urban growth cellular automata are related to an only one town, with transition rules and constraints a priori defined. This seems to be a severe limits in applications. The paper presented is born to follow a different kind of approach, so to have rules and constraints directly from observed past data. We consider ten European towns and for each one we have data for time series approx. 40 years long. We deduce rules and constraints directly from the data set, solving an inverse problem (in which we have input and output measures and we have to determine a system model).The study aims to define in detail the stochastic or deterministic character of transition rules (in the stochastic case evaluating transition probability). At last the rules are applied to towns maps (by means of ad hoc cellular automaton). With this cellular automaton we try to simulate past dynamics (for a validation of the model) and also to forecast the spatial development of the towns by means of scenarios (based on the past histories of the cities).