The period of high economic growth in Japan which began in the latter half of the 1950s led to a massive migration of population from rural regions to the Tokyo metropolitan area. This phenomenon brought about rapid urban growth and urban structure changes in this area. Purpose of this study is to establish a constrained CA (Cellular Automata) model with GIS (Geographical Information Systems) to simulate urban growth pattern in the Tokyo metropolitan area towards predicting urban form and landscape for the near future. Urban land-use is classified into multi-categories for interpreting the effect of interaction among land-use categories in the spatial process of urban growth. Driving factors of urban growth pattern, such as land condition, railway network, land-use zoning, random perturbation, and neighborhood interaction and so forth, are explored and integrated into this model. These driving factors are calibrated based on exploratory spatial data analysis (ESDA), spatial statistics, logistic regression, and "trial and error" approach. The simulation is assessed at both macro and micro classification levels in three ways: visual approach; fractal dimension; and spatial metrics. Results indicate that this model provides an effective prototype to simulate and predict urban growth pattern of the Tokyo metropolitan area.

Date Published: 3 November 2008
PDF: 12 pages
Proc. SPIE 7143, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 71431Q (3 November 2008); doi: 10.1117/12.812591

Published in SPIE Proceedings Vol. 7143:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang; Aijun Chen, Editor(s)