@InProceedings{Almeida:2004:SiPrUr,
author = "Almeida, Cl{\'a}udia Maria de",
affiliation = "Instituto Nacional de Pesquisas Espaciais, Divis{\~a}o de
Sensoriamento Remoto (INPE, DSR)",
title = "Simulation and prediction of urban land use change as a tool for
better planning",
booktitle = "Proceedings...",
year = "2004",
organization = "International Symposium on Urbanization Worldwide: Trends and
Challenges in the 21st Century.",
keywords = "PLANEJAMENTO URBANO, gest{\~a}o ambiental, uso da terra, urban
modelling, cellular automata, town planning, land use change,
Bayes theorem.",
abstract = "This scientific paper 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 S{\~a}o 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 implies their
possible further applicability for generating forecasts of growth
trends both for Brazilian and worldwide.",
conference-location = "Stuttgart",
conference-year = "2004",
copyholder = "SID/SCD",
language = "en",
targetfile = "mso167.pdf",
urlaccessdate = "11 maio 2024"
}