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Proceedings Paper

Modeling urban land use changes in Lanzhou based on artificial neural network and cellular automata
Author(s): Xibao Xu; Jianming Zhang; Xiaojian Zhou
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Paper Abstract

This paper presented a model to simulate urban land use changes based on artificial neural network (ANN) and cellular automata (CA). The model was scaled down at the intra-urban level with subtle land use categorization, developed with Matlab 7.2 and loosely coupled with GIS. Urban land use system is a very complicated non-linear social system influenced by many factors. In this paper, four aspects of a totality 17 factors, including physical, social-economic, neighborhoods and policy, were considered synthetically. ANN was proposed as a solution of CA model calibration through its training to acquire the multitudinous parameters as a substitute for the complex transition rules. A stochastic perturbation parameter v was added into the model, and five different scenarios with different values of v and the threshold were designed for simulations and predictions to explore their effects on urban land use changes. Simulations of 2005 and predictions of 2015 under the five different scenarios were made and evaluated. Finally, the advantages and disadvantages of the model were discussed.

Paper Details

Date Published: 3 November 2008
PDF: 10 pages
Proc. SPIE 7143, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 71431A (3 November 2008); doi: 10.1117/12.812574
Show Author Affiliations
Xibao Xu, Nanjing Institute of Geography and Limnology (China)
Jianming Zhang, Lanzhou Univ. (China)
Xiaojian Zhou, Nantong Univ. (China)


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)

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