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作者

Jinyao Lin;Xia Li;Youyue Wen;Peiting He

来源

CITIES,Vol.133,Issue1,Article 103906

语言

英文

关键字

Landscape pattern;Cellular automata;Urban land-use change;Land-use patch

作者单位

School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, PR China;Key Lab. of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, PR China;South China Institute of Environmental Science, Ministry of Ecology and Environment, NO.18 Ruihe RD., Guangzhou 510535, PR China;National Key Laboratory of Urban Ecological Environment Simulation and Protection, Guangzhou 510535, PR China;School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, PR China;Key Lab. of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, PR China;South China Institute of Environmental Science, Ministry of Ecology and Environment, NO.18 Ruihe RD., Guangzhou 510535, PR China;National Key Laboratory of Urban Ecological Environment Simulation and Protection, Guangzhou 510535, PR China

摘要

Cellular automaton (CA) is a widely-used tool for modeling land-use changes that can enhance our understanding of past and future urban development. Previous studies have demonstrated that patch-based CA models are superior to cell-based CA because the spatial homogeneity of urban growth at local scales can be considered. However, there still exists a major limitation that traditional patch-based CA did not incorporate any information about landscape pattern into land-use change modeling. To alleviate this issue, we present a novel landscape-driven patch-based CA (LP-CA) model that can simultaneously consider landscape similarity and cell-by-cell agreement. We have examined this new model by simulating and predicting the urban expansion in a fast-growing city. Results indicate that our method performs better than stand-alone traditional patch-based CA and landscape-driven cell-based CA in terms of the combined error. The capability to characterize and replicate landscape pattern is greatly important for urban planners to explore the potential influences of urban expansion under different land-use planning scenarios. Therefore, this proposed model has the potential to provide valuable support for urban land-use planning and policy-making processes.