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Simulation of urban expansion using geographical similarity transition rules and neighbourhood sizes

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Most existing cellular automata(CA)models impose strict requirements on the number and spatial distribution of samples.This makes it a challenge to capture spatial het-erogeneity in urban dynamics and meet the modeling needs of large and complex geographic areas.This paper presents a CA model based on geographically optimal similarity(GOS)transition rules and similarly sized neighborhoods(SSN).By comparing the similarity in geo-graphical configuration between samples and predicted points,the model enables a com-prehensive characterization of the driving mechanism behind urban expansion and its self-organizing scope.This helps to mitigate the impact of sample selection and assumptions about spatial stationarity on simulation results.The performance of GOS-SSN-CA simulation was tested by taking the urban expansion in the Changsha-Zhuzhou-Xiangtan urban ag-glomeration in China as an example.The results show that GOS can derive more accurate and reliable urban transition rules with fewer samples,thereby significantly reducing spatial prediction errors compared with logistic regression.Moreover,SSN selects different neigh-borhood sizes to represent the difference between the local self-organizing range and sur-rounding cells,thus further improving the simulation accuracy and restricting urban expansion morphology.Overall,GOS-SSN-CA effectively characterizes the geographical similarity of urban expansion,improves simulation accuracy while constraining the urban expansion form,and enhances the practical application value of CA.

urban growthcellular automatageographic similaritymodel optimizationspatial nonstationarity

LI Yinqi、AN Yue、ZHOU Zhou、REN Hui、TAN Xuelan

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College of Resources,Hunan Agricultural University,Changsha 410128,China

College of Geographical Sciences,Hunan Normal University,Changsha 410081,China

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNatural Science Foundation of Hunan ProvinceKey Project of Philosophy and Social Science Foundation of Hunan ProvinceGraduate Science and Innovation Project of Hunan Province

41971219415711682020JJ437218ZDB015CX20230719

2024

10.1007/s11442-024-2253-8

地理学报(英文版)
中国地理学会,中国科学院地理科学与资源研究所

地理学报(英文版)

CSTPCD
影响因子：1.307
ISSN：1009-637X
年,卷(期)：2024.34(7)
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