publication . Article . 2003

Stochastic cellular automata modeling of urban land use dynamics: empirical development and estimation

Almeida, Claudia; Batty, Michael; Monteiro, Miguel; Camara, Gilberto; Soares-Filho, Britaldo; Cerqueira, Gustavo; Pennachin, Cassio;
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  • Published: 01 Sep 2003 Journal: Computers, Environment and Urban Systems, volume 27, pages 481-509 (issn: 0198-9715, Copyright policy)
  • Publisher: Elsevier BV
Abstract
An increasing number of models for predicting land use change in rapidly urbanizing regions are being proposed and built using ideas from cellular automata (CA). Calibrating such models to real situations is highly problematic and to date, serious attention has not been focused on the estimation problem. In this paper, we propose a structure for simulating urban change based on estimating land use transitions using elementary probabilistic methods which draw their inspiration from Bayes’ theory and the related ‘weights of evidence’ approach. These land use change probabilities drive a CA model based on eight cell Moore neighborhoods implemented through empirical...
Subjects
free text keywords: Land use change, Transition probabilities, Bayesian methods, Cellular automata, Urban growth, Urban planning, Stochastic cellular automaton, Machine learning, computer.software_genre, computer, Cellular automaton, Geography, Bayes' theorem, Land use, Urban planning, Probabilistic method, Data mining, Bayesian probability, Artificial intelligence, business.industry, business, Operations research, Land use, land-use change and forestry
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