首页|顾及建设用地聚集与排斥性的城市扩张模拟:以义乌市为例

顾及建设用地聚集与排斥性的城市扩张模拟:以义乌市为例

Urban expansion simulation considering spatial aggregation and exclusion of construction land:A case study in Yiwu,China

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建设用地在空间上存在相互聚集或排斥的特性,并可能影响到城市扩张格局.本文在厘清建设用地内部以及不同类型建设用地之间聚集与排斥性的基础上,将其纳入到元胞自动机(CA)模型的发展适宜性与邻域影响因子计算中,以此构建顾及建设用地聚集与排斥性的CA-SAE模型,并将其应用于义乌城市扩张模拟的实证分析.结果表明:CA-SAE模型能够有效模拟不同类型建设用地的扩张状况,且模拟精度要优于传统CA模型.同时,多情景的模拟结果也证实了建设用地聚集与排斥性会影响到不同类型建设用地的空间分布及城市扩张形态.本文构建的CA-SAE模型创新性地将建设用地聚集与排斥性纳入到CA模型中,为开展面向不同类型建设用地的城市扩张模拟提供了思路与方法.
The spatial distribution of construction land exhibits characteristics of aggregation or exclusion,potentially influencing the urban expansion pattern.However,existing studies on urban expansion simulation often overlook the aggregation and exclusion of construction land.Therefore,based on clarifying the aggregation and exclusion within construction land and among different types of construction land,this study incorporates them into calculating the developmental suitability and neighborhood impact factors of a Cellular Automaton(CA).Then,the CA-SAE(CA model considering spatial aggregation and exclusion of construction land)model is developed.Specifically,firstly,integrating spatial impact factors and influence forces of spatial factors for different construction land expansions,we calculate the suitability for potential development land units to develop into different types of construction land.Secondly,in combination of the aggregation and exclusion coefficients of construction land,the neighborhood impact factor for potential development land units to develop into different types of construction land is computed.Furthermore,by incorporating the constraints and random disturbance factors from the traditional CA model,the probability for potential development land units to develop into different types of construction land is calculated,and the land type with the highest probability is selected as the expected transformed construction land type.Finally,these units are grouped based on the expected transformed construction land type for potential development land units in the study area.Within each group,transformations occur sequentially from high to low probability,and the simulation terminates when the number of transformations reaches the constraints of various types of construction land planning indicators.To verify the scientific and effective nature of the CA-SAE model,we apply it to the empirical analysis of the urban expansion simulation in Yiwu.The results show that:(1)The CA-SAE model can effectively simulate the expansion of different types of construction land,with results more closely aligning with reality.(2)The simulation accuracy of the CA-SAE model surpasses that of traditional CA models.The overall accuracy of the CA-SAE model is 0.9063,the Kappa coefficient is 0.7688,and the FoM is 0.1509.(3)Multi-scenario simulation results confirm that construction land aggregation and exclusion affect the spatial distribution of different types of construction land and the form of urban expansion.When the aggregation of construction land is strong,it tends to cluster,and the fragmentation decreases.Conversely,when the exclusion of construction land is strong,the aggregation of industrial land increases,and the fragmentation decreases,with expansion occurring away from residential and commercial land.The CA-SAE model developed in this study innovatively incorporates the aggregation and exclusion of construction land into the CA model.This model provides new ideas and methods for simulating urban expansion,focusing on different types of construction land.Additionally,the simulation results based on this model can offer references for the spatial layout of different types of construction land in territorial spatial planning.

urban expansion simulationconstruction landspatial aggregationspatial exclusioncellular automata

田宇、熊昌盛

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海南大学国际旅游与公共管理学院,海口 570100

城市扩张模拟 建设用地 聚集性 排斥性 元胞自动机

国家自然科学基金国家自然科学基金教育部哲学社会科学研究重大课题攻关项目教育部人文社会科学研究一般项目海南省研究生创新科研项目

720040494236103920JZD01320XJCZH009Qhys2021-194

2024

地理研究
中国科学院地理科学与资源研究所

地理研究

CSTPCDCSSCICHSSCD北大核心
影响因子:2.214
ISSN:1000-0585
年,卷(期):2024.43(4)
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