Modeling urban land use changes in Lanzhou based on artificial neural network and cellular automata

Xibao Xu; Jianming Zhang; Xiaojian Zhou

doi:10.1117/12.812574

3 November 2008 Modeling urban land use changes in Lanzhou based on artificial neural network and cellular automata

Xibao Xu, Jianming Zhang, Xiaojian Zhou

Proceedings Volume 7143, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments; 71431A (2008) https://doi.org/10.1117/12.812574
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

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.

Citation Download Citation

Xibao Xu, Jianming Zhang, and Xiaojian Zhou "Modeling urban land use changes in Lanzhou based on artificial neural network and cellular automata", Proc. SPIE 7143, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 71431A (3 November 2008); https://doi.org/10.1117/12.812574

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