Incorporating spatial heterogeneity to model spontaneous and self-organized urban growth

被引:4
作者
Zhang, Bin [1 ,2 ,3 ]
Hu, Shougeng [1 ,2 ]
Wang, Haijun [4 ]
Yang, Jianxin [1 ,2 ]
Wang, Zhenzhen [1 ,2 ]
机构
[1] China Univ Geosci, Sch Publ Adm, Wuhan, Peoples R China
[2] Key Lab Minist Nat Resources Res Rule Law, Wuhan, Peoples R China
[3] Guangdong Hong Kong Macau Joint Lab Smart Cities, Shenzhen, Peoples R China
[4] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China
基金
中国国家自然科学基金;
关键词
Urban growth; Cellular automata; Spatial heterogeneity; Spontaneous; Self-organized; CELLULAR-AUTOMATA MODEL; LAND-USE; LOGISTIC-REGRESSION; SIMULATION; URBANIZATION; EXPANSION; DYNAMICS; REGION; ACCESSIBILITY; DETERMINANTS;
D O I
10.1016/j.apgeog.2024.103196
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
Contemporary investigations into cellular automata (CA) modeling often neglect the considerable influence of spatial heterogeneity on both spontaneous and self -organized processes of urban growth. In this research, we combined a partitioned quantity control strategy, the geographically weighted artificial neural network (GWANN), and a neighborhood size -adaptive approach to formulate a CA framework for simulating spatially heterogeneous spontaneous and self -organized urban growth (SHSS-CA). We examined the simulation performance of SHSS-CA in Beijing, Shanghai, and the Pearl River Delta during 2000-2010 for calibration and 2010-2020 for validation. The findings demonstrate that incorporating spatial heterogeneity enhances CA performance in approximately 90% of regions. Introducing spatially heterogenous spontaneous or self -organized urban growth rules alone can improve the simulation performance of CA. Furthermore, their integration leverages the strengths of both rules and makes SHSS-CA the optimal choice, resulting in a notable improvement in the figure of merit (FoM)-approximately 9% during calibration and around 5% during validation-when compared with ANN -CA. This study contributes new methodologies for developing urban growth simulation rules and has the capacity to effectively help urban planners understand and analyze the complicated urban growth processes.
引用
收藏
页数:14
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