مجموعه تزهای شهرسازی

This work is committed to provide methodological guidelines for the simulation of urban land use dynamics. Modeling experiments of urban land use change were conducted for two medium-sized cities (Bauru and Piracicaba) located in the inland of São Paulo State over time series of approximately thirty-five years. Land use transitions were estimated using two different empirical probabilistic methods – the `weights of evidence´ approach, based on Bayes´ theory, and logistic regression. The thereof derived land use change probabilities drove a cellular automata model, built upon basis of stochastic land use allocation algorithms. Socioeconomic and infrastructural factors demonstrated to be the drivers of local land use change, whose logic is explained in light of economic theories of urban development and growth. The simulation outputs

were statistically validated according to a multiple resolution fitting procedure. After the accomplishment of simulations for successive time periods along the whole time series, forecast simulations were carried out for stationary and non-stationary scenarios of transition trends. The former were assessed through the Markov chain, while the latter were obtained from linear regression models relating rates of land use change to demographic data and economic performance indicators. Both types of forecast scenarios were built for the short- and medium-term, respectively 2004 and 2007. And finally, a due attention was drawn to possible extensions of this work throughout