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Loose-coupling a cellular automaton model and GIS: Long-term urban growth prediction for San Francisco and Washington/Baltimore

International Journal of Geographical Information Science
By:  and 
https://doi.org/10.1080/136588198241617

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Abstract

Prior research developed a cellular automaton model, that was calibrated by using historical digital maps of urban areas and can be used to predict the future extent of an urban area. The model has now been applied to two rapidly growing, but remarkably different urban areas: the San Francisco Bay region in California and the Washington/Baltimore corridor in the Eastern United States. This paper presents the calibration and prediction results for both regions, reviews their data requirements, compares the differences in the initial configurations and control parameters for the model in the two settings, and discusses the role of GIS in the applications. The model has generated some long term predictions that appear useful for urban planning and are consistent with results from other models and observations of growth. Although the GIS was only loosely coupled with the model, the model's provision of future urban patterns as data layers for GIS description and analysis is an important outcome of this type of calculation.

Publication type Article
Publication Subtype Journal Article
Title Loose-coupling a cellular automaton model and GIS: Long-term urban growth prediction for San Francisco and Washington/Baltimore
Series title International Journal of Geographical Information Science
DOI 10.1080/136588198241617
Volume 12
Issue 7
Year Published 1998
Language English
Publisher Taylor & Francis
Contributing office(s) Earth Resources Observation and Science (EROS) Center, Western Geographic Science Center
Description 16 p.
First page 699
Last page 714
Country United States
State California, Maryland
City Baltimore, San Francisco, Washington D.C.
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