NDLI: Simulating urban expansion by coupling a stochastic cellular automata model and socioeconomic indicators

Content Provider	Springer Nature Link
Author	Wu, Daqian Liu, Jian Wang, Shujun Wang, Renqing
Copyright Year	2009
Abstract	Urbanization is one of the most important anthropogenic activities that create extensive environmental implications at both local and global scales. Dynamic urban expansion models are useful tools to understand the urbanization process, project its spatiotemporal dynamics and provide useful information for assessing the environmental implications of urbanization. A hybrid urban expansion model (NNSCA model) was proposed to simulate rapid urban growth in a typical industrial city, Dongying, China, by coupling a artificial-neural-network-based stochastic cellular automata model and several socioeconomic indictors, i.e., the per capita income of the rural population, the per capita income of the urban population, population and gross domestic products of the city. Good conformity between simulated and actual urban patterns suggested that the NNSCA model was able to effectively simulate historic urban growth and to generate realistic urban patterns. A series of scenario analyses suggested that the expanding urban would threaten the ecosystem health of coastal wetlands in the city unless environmental protection actions are taken in the future. The NNSCA model provides abilities to assess future urban growth under various planning and management scenarios, and can be integrated into ecological or environmental process models to evaluate urbanization’s environmental implications.
Starting Page	235
Ending Page	245
Page Count	11
File Format	PDF
ISSN	14363240
Journal	Stochastic Environmental Research and Risk Assessment
Volume Number	24
Issue Number	2
e-ISSN	14363259
Language	English
Publisher	Springer-Verlag
Publisher Date	2009-04-30
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Artificial neural network Cellular automata Dongying Socioeconomic indicator Urban expansion Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution Computational Intelligence Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Mathematical Applications in Earth Sciences Probability Theory and Stochastic Processes Math. Application in Environmental Science
Content Type	Text
Resource Type	Article
Subject	Environmental Chemistry Environmental Engineering Water Science and Technology Safety, Risk, Reliability and Quality

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