Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6962746 | Environmental Modelling & Software | 2016 | 13 Pages |
Abstract
Urban cellular automata (CA) models are broadly used in quantitative analyses and predictions of urban land-use dynamics. However, most urban CA developed with neighborhood rules consider only a small neighborhood scope under a specific spatial resolution. Here, we quantify neighborhood effects in a relatively large cellular space and analyze their role in the performance of an urban land use model. The extracted neighborhood rules were integrated into a commonly used logistic regression urban CA model (Logistic-CA), resulting in a large neighborhood urban land use model (Logistic-LNCA). Land-use simulations with both models were evaluated with urban expansion data in Xiamen City, China. Simulations with the Logistic-LNCA model raised the accuracies of built-up land by 3.0%-3.9% in two simulation periods compared with the Logistic-CA model with a 3Â ÃÂ 3 kernel. Parameter sensitivity analysis indicated that there was an optimal large window size in cellular space and a corresponding optimal parameter configuration.
Related Topics
Physical Sciences and Engineering
Computer Science
Software
Authors
Jiangfu Liao, Lina Tang, Guofan Shao, Xiaodan Su, Dingkai Chen, Tong Xu,