This scientific paper, part of a PhD Thesis currently under execution at the Division for Image Processing of the Brazilian National Institute for Space Research (DPI – INPE), is committed with building up a methodological guideline for modelling urban land use change through GIS, Remote Sensing imagery and Bayesian probabilistic methods. A medium-size town in the west of São Paulo State, Bauru, was adopted as case study. Its urban structure was converted into a 100 x 100 (m) resolution grid, and transition probabilities were calculated for each grid cell by means of the " weights of evidence " statistical method and upon basis of the information related to the technical and social infrastructure of the town. The probabilities therefrom obtained fed a cellular automaton (CA) simulation model – DINAMICA-conceived by the Centre for Remote Sensing of the Federal University of Minas Gerais (CSR-UFMG), based on a multiscale vicinity approach and stochastic transition algorithms. Different simulation outputs for the case study town in the period 1979-1988 were generated, and statistical validation tests were then conducted for the best results, employing a multiple resolution fitting procedure. This modelling experiment revealed the plausibility of adopting Bayesian empirical methods based on the available infrastructure knowledge to simulate urban land use change, what * Third International Symposium -Remote Sensing of Urban Areas, Istambul, Turkey: Istambul Technical University (Turkey), 11th-13th June, 2002. implies their possible further applicability for generating forecasts of growth trends both for Brazilian and worldwide cities.
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