4.7 Article

Simulation of urban expansion and encroachment using cellular automata and multi-agent system model-A case study of Tianjin metropolitan region, China

期刊

ECOLOGICAL INDICATORS
卷 70, 期 -, 页码 439-450

出版社

ELSEVIER
DOI: 10.1016/j.ecolind.2016.06.021

关键词

Cellular automata; Multi-agent system model; Urban expansion; Spatio-temporal patterns; Tianjin metropolitan region

资金

  1. National Basic Research Program of China [2015CB953602]

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The combination model of cellular automata and multi-agent system were used in this paper for simulating spatio-temporal dynamics of urban expansion and its encroachment on other lands at the regional scale. The human system(contain authorities and residents) and their behavior, the landscape system and its behavior as well as the inter actions between them were all simulated in this paper. The behavior of human system is established based on multi-agent system, the authority agent and the resident agent were both regarded as abstract entities. The cellular automata is embedded into the model for simulating the spontaneous urban growth. The impact of neighbor cells were considered so that the expansion of urban lands can be limited near the existed urban lands. Moreover, the rural residential lands have higher probability to convert to urban lands if they were close to the cities or towns. Simulation of urban expansion is undertaken on the time series from 2000 to 2020 for Tianjin metropolitan region, the largest open coastal city in northern China. The results show that Tianjin's urban lands focus on the epitaxial expansion around the central city accompanied with the growing exurb expansion distributing in multiple districts and counties. The croplands are taken the most area of the land-use types, 1764.03 km(2) are converted to urban lands, and more than one fourth of the rural residential lands are changed to urban lands in 2000-2020. The urban development and the cropland protection should be both taken into account to minimize the threats on food security and ecological environment. (C) 2016 Elsevier Ltd. All rights reserved.

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