Incorporation of extended neighborhood mechanisms and its impact on urban land-use cellular automata simulations |
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Affiliation: | 1. Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China;2. Computer Engineering College, Jimei University, Xiamen, 361021, China;3. Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN 47907, USA |
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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. |
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Keywords: | Urban expansion Cellular automata Extended enrichment factors Neighborhood effects Neighborhood rules |
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