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| Titel: |
Using neural networks and cellular automata for modelling intra-urban land-use dynamics |
| Auteur: |
Almeida, C. M. Gleriani, J. M. Castejon, E. F. Soares-Filho, B. S. |
| Verschenen in: |
International journal of geographical information science |
| Paginering: | Jaargang 22 (2008) nr. 9 pagina's 943-963 |
| Jaar: |
2008 |
| Inhoud: |
Empirical models designed to simulate and predict urban land-use change in real situations are generally based on the utilization of statistical techniques to compute the land-use change probabilities. In contrast to these methods, artificial neural networks arise as an alternative to assess such probabilities by means of non-parametric approaches. This work introduces a simulation experiment on intra-urban land-use change in which a supervised back-propagation neural network has been employed in the parameterization of several biophysical and infrastructure variables considered in the simulation model. The spatial land-use transition probabilities estimated thereof feed a cellular automaton (CA) simulation model, based on stochastic transition rules. The model has been tested in a medium-sized town in the Midwest of Sao Paulo State, Piracicaba. A series of simulation outputs for the case study town in the period 1985-1999 were generated, and statistical validation tests were then conducted for the best results, based on fuzzy similarity measures. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 8 van 8 gevonden artikelen
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