@InProceedings{AlmeidaGler:2005:CeAuNe,
author = "Almeida, Cl{\'a}udia Maria de and Gleriani, Jos{\'e} Marinaldo",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and
{Universidade Federal de Vi{\c{c}}osa (UFV)}",
title = "Cellular automata and neural networks as a modelling framework for
the simulation of urban land use change",
booktitle = "Anais...",
year = "2005",
editor = "Epiphanio, Jos{\'e} Carlos Neves and Fonseca, Leila Maria
Garcia",
pages = "3697--3706",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 12. (SBSR)",
publisher = "INPE",
address = "S{\~a}o Jos{\'e} dos Campos",
keywords = "urban modelling, land use dynamics, neural networks, cellular
automata, town planning.",
abstract = "Empirical models designed to simulate and predict urban land use
change are generally based on the utilisation of statistical
techniques to reckon 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 urban land use change in which a supervised
back-propagation neural network has been employed in the
parameterisation of the simulation model. The thereof estimated
spatial land use transition probabilities 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 S{\~a}o Paulo State, Piracicaba. A series of
simulation outputs for the case study town in the period 1985-1999
were produced, and statistical validation tests were then
conducted for the best results, upon basis of a multiple
resolution fitting procedure.",
conference-location = "Goi{\^a}nia",
conference-year = "16-21 abr. 2005",
isbn = "85-17-00018-8",
language = "Ingl{\^e}s",
organisation = "Instituto Nacional de Pesquisas Espaciais",
ibi = "ltid.inpe.br/sbsr/2004/11.22.22.31",
url = "http://urlib.net/ibi/ltid.inpe.br/sbsr/2004/11.22.22.31",
targetfile = "3697.pdf",
type = "Planejamento Urbano e Regional",
urlaccessdate = "2024, May 05"
}