Incorporation of Spatially Heterogeneous Area Partitioning into Vector-Based Cellular Automata for Simulating Urban Land-Use Changes
Jie Zhu,
Mengyao Zhu,
Jiaming Na,
Ziqi Lang,
Yi Lu and
Jing Yang ()
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Jie Zhu: College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China
Mengyao Zhu: College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China
Jiaming Na: College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China
Ziqi Lang: College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China
Yi Lu: Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
Jing Yang: Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
Land, 2023, vol. 12, issue 10, 1-22
Abstract:
In cellular automata (CA) modeling, spatial heterogeneity can be delineated by geographical area partitioning. The dual constrained space clustering method is a prevalent approach for providing an objective and effective representation of differences within urban regions. However, previous studies faced issues by ignoring spatial heterogeneity, which could lead to an over- or under-estimation of the simulation results. Accordingly, this study attempts to incorporate spatially heterogeneous area partitioning into vector-based cellular automata (VCA), producing more accurate and reliable simulations of urban land-use change. First, an area partition strategy with DSC algorithm was employed to generate multiple relatively homogeneous sub-regions, which can effectively capture the spatial heterogeneity in the distribution of land-use change factors. Second, UrbanVCA, a brand-new VCA-based framework, was utilized for simulating land-use changes in distinct urban partitions. Finally, the constructed partitioned VCA model was applied to simulate rapid urban development in Jiangyin city from 2012 to 2017. The results indicated that the combination of DSC clustering and UrbanVCA model could obtain satisfying results as the average FoM values for the partitions and the entire study area exceeded 0.22. Furthermore, a comparative analysis of results from traditional area-partitioned CA models revealed that the proposed area partitioning approach had the potential to yield more accurate simulation outcomes as the FoM values were higher and SHDI and LSI metrics were closer to real-world observations, indicating its good performance in simulating fragmented urban landscapes.
Keywords: urban land-use change simulation; area partitioning; spatial heterogeneity; vector-based cellular automata (VCA); Jiangyin city (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:12:y:2023:i:10:p:1893-:d:1256033
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