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First Author: |
Jiangfu Liao |
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 3×3 kernel. Parameter sensitivity analysis indicated that there was an optimal large window size in cellular space and a corresponding optimal parameter configuration. |
Contact the author: |
Lina Tang |
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http://authors.elsevier.com/sd/article/S1364815215300724 |
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PubYear: |
2016 |
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Publication Name: |
Environmental Modelling & Software |
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