Details

Autor(en) / Beteiligte

• Liao, Jiangfu
• Tang, Lina
• Shao, Guofan
• Su, Xiaodan
• Chen, Dingkai
• Xu, Tong

Titel

Incorporation of extended neighborhood mechanisms and its impact on urban land-use cellular automata simulations

Ist Teil von

• Environmental modelling & software : with environment data news, 2016-01, Vol.75, p.163-175

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2016

Link zum Volltext

Quelle

Elsevier ScienceDirect Journals Complete

Beschreibungen/Notizen

• 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. •Extended neighborhood effects and their influence on urban dynamics were addressed in this study.•A logistic regression urban CA model incorporating the extracted neighborhood rules, Logistic-LNCA, was developed.•The Logistic-LNCA model achieved higher simulation accuracy than the Logistic-CA model with a 3 × 3 kernel.•The simulation accuracy and the Kappa coefficient varied with window sizes and radius intervals.•There is an optimal window size in cellular space and corresponding optimal parameter configurations.