Journal
GEOCARTO INTERNATIONAL
Volume 31, Issue 6, Pages 612-627Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/10106049.2015.1073365
Keywords
urban growth; simulation; cellular automata; particle swarm optimization (PSO)
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Funding
- CAS-TWAS Project for Drought Monitoring and Assessment [Y3YI2701KB]
- 1-3-5 Innovation Project of RADI_CAS [Y3ZZ15101A]
- Innovation Fund of CEODE [Y2ZZ26101B]
- 100 Talent Program of Chinese Academy of Sciences [Y24002101A]
- CAS Xinjiang Location Cooperation Project [Y423011010A]
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This study presents an optimized algorithm into the cellular automata (CA) models for urban growth simulation in Binhai New Area of Tianjin, China. The optimized CA model by particle swarm optimization (PSO) was compared with the logistic-based cellular automata (LOGIT-CA) model to see the effects of the simulation. The study evaluated the stochastic disturbance in the development of urban growth using the Monte Carlo method; the coefficient d determined the state of urban growth. The validation was conducted by both cross-tabulation test and structural measurements. The results showed that the simulations of PSO-CA were better than LOGIT-CA model, indicating an improvement in the spatio-temporal simulation of urban growth and land use changes in study area. Since the simulations reached their best values when the coefficient was between 1 and 2, the urban growth in the study area was in the period of conversion from spontaneous growth to edge-expansion and infilling growth.
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