Urban Agglomerations in China: Characteristics and Influencing Factors of Population Agglomeration

Urban agglomeration(UA)is an advanced spatial economic form formed and developed in the process of rapid industrialization and urbanization,and an important carrier of urbanization and economic development.The economy has developed rapidly in the recent decades of China,and the UAs have also developed rapidly.However,as a large population country,the population distribution and changes of UAs in China has unique characteristics.Using the fifth,sixth and seventh population census data,spatial auto-correlation and spatial econometric models,we analyzed the spatial-temporal evolution characteristics and influencing factors of population agglomeration in China’s UAs.Results revealed that:1)from 2000 to 2020,the population gradually converged into UAs,and the characteristics of population agglomeration in different development degree of UAs differ.The higher the development degree of UA,the higher the population agglomeration degree.Besides,UAs are the main area with the most significant population agglomeration degree,and the spatial autocorrelation show that the cities with similar degree tend to be concentrated in space.The urban population gathering in UAs has a certain positive spillover effect on population size of neighboring cities.2)Economic development and social conditions factors are important factors affecting population agglomeration degree in UAs.The main factors of population gather into UAs are similar with the outside UAs,but the positive promotion of urbanization rate and proportion of tertiary industry in GDP on population agglomeration of UAs in China are enhancing from 2000 to 2020.Meanwhile,the other factors,such as high-quality public services,good urban living environment conditions,high-quality medical and educational resources,are also important factors to promote urban population gather into UAs.This study provides a basis for formulating the development planning of UAs in China,and enriches the relevant theoretical research of population evolution and influencing factors of UAs.

Spatially Heterogeneous Response of Carbon Storage to Land Use Changes in Pearl River Delta Urban Agglomeration, China

Carbon storage of terrestrial ecosystems plays a vital role in advancing carbon neutrality. Better understanding of how land use changes affect carbon storage in urban agglomeration will provide valuable guidance for policymakers in developing effective regional conservation policies. Taking the Pearl River Delta Urban Agglomeration(PRDUA) in China as an example, we examined the heterogeneous response of carbon storage to land use changes in 1990–2018 from a combined view of administrative units and physical entities. The results indicate that the primary change in land use was due to the expansion of construction land(5897.16 km2). The carbon storage in PRDUA decreased from 767.34 Tg C in 1990 to 725.42 Tg C in 2018 with a spatial pattern of high wings and the low middle. The carbon storage loss was largely attributed to construction land expansion(55.74%), followed by forest degradation(54.81%). Changes in carbon storage showed significant divergences in different sized cities and hierarchical boundaries. The coefficients of geographically weighted regression(GWR) reveal that the alteration in carbon storage in Guangzhou City was more responsive to changes in construction land(-0.11) compared to other cities, while that in Shenzhen was mainly affected by the dynamics of forest land(8.32). The change in carbon storage was primarily influenced by the conversion of farmland within urban extent(5.05) and the degradation of forest land in rural areas(5.82). Carbon storage changes were less sensitive to the expansion of construction land in the urban center, urban built-up area, and ex-urban built-up area, with the corresponding GWR coefficients of 0.19, 0.04, and 0.02. This study necessitates the differentiated protection strategies of carbon storage in urban agglomerations.

Spatio-temporal Evolution of Urban Expansion Based on a Novel Adjusted Index and GEE: A Case Study of Central Plains Urban Agglomeration, China

It is crucial to investigate the urban agglomerations spatio-temporal evolution patterns and driving factors for analyzing the urban spatial structure-functional division and promoting the coordinated development of urban agglomerations.In this study,a novel vegetation-building-nighttime light-adjusted index(VBNAI)was established for rapid and effective mapping of urban construction land(UCL)in Central Plains Urban Agglomeration(CPUA),China during 2000–2020 based on Google Earth Engine(GEE)platform.Compared with traditional indices,VBNAI can significantly decrease the blooming effect,Normalized Difference Vegetation Index(NDVI)saturation,and soil background of nighttime light data.In addition,the urban expansion indices and standard deviation ellipse model were synthetically adopted to analyze the spatio-temporal evolution pattern of urban expansion.The gravity model and the geographically weighted regression model were employed to determine the spatial interaction forces and drivers of urban expansion,respectively.The results showed that the VBNAI index has obvious advantages in efficiency and accuracy to extract UCL with the overall accuracy of more than 91%.The UCL of CPUA had increased by 4489.84 km2 during 2000–2020 with the gravity center moving towards southeast continuously.From 2000 to 2010,the urban expansion was in a‘center-hinterland’pattern which had benefit from the favorable effect of the traffic shaft belt.During 2010–2020,the urban network structure had basically established.Urban expansion had been influenced by a variety of socio-economic and demographic factors,and the impact degree varied from region to region.This study could provide scientific references for facilitating the intensive utilization of urban resources and optimizing the spatial development pattern of urban agglomeration.

Spatiotemporal Variations and Regional Transport of Air Pollutants in Two Urban Agglomerations in Northeast China Plain

Characteristics of air pollution in Northeast China(NEC) received less research attention in the past comparing to other heavily polluted regions in China.Spatiotemporal variations of six criteria air pollutants(PM10, PM2.5, SO2, NO2, O3 and CO) in Central Liaoning Urban Agglomeration(CLUA) and Harbin-Changchun Urban Agglomeration(HCUA) in NEC Plain were analyzed in this study based on three-year hourly observations of air pollutants and meteorological variables from 2015 to 2017.The results indicated that the annual mean concentrations of air pollutants are generally higher in the middle and southern regions in NEC Plain and lower in the northern region.Megacities such as Shenyang, Harbin and Changchun experience severe air pollution, with a three-year averaged air quality index(AQI) larger than 80, far exceeding the daily AQI standard at the first-level of 50 in China.The annual mean PM and SO2 concentrations decrease most significantly in NEC urban agglomerations from 2015 to 2017, followed by CO and NO2, while O3 shows a slight increasing trend.All the six pollutants exhibit obvious seasonal and diurnal variations, and these variations are dictated by local emission and meteorological conditions.PM2.5 and O3 concentrations in NEC urban agglomerations strongly depend on wind conditions.High O3 concentrations at different cities usually occur in presence of strong winds but are independent on wind direction(WD), while high PM2.5 is usually accompanied by weak winds and poor dispersion condition, and sometimes also occur when the northerly or southerly winds are strong.Regional transport of air pollutants between NEC urban agglomerations is common.A severe haze event on November 1–4, 2017 is examined to demonstrate the role of regional transport on pollution.

Size structure of urban agglomerations in China:rationality evaluation,patterns, and implications

This paper establishes a diagnostic model for assessing the rationality of size structure of urban agglomerations(UAs) in China. The model is designed to determine from a three-dimensional index including size distribution index(SDI), size compactness index(SCI), and size efficiency index(SEI). The spatio-temporal pattern of size structure involving the studied 19 UAs and its implications are explored. The results indicate that size structure of China's UAs advanced from a low rationality development stage to a moderate rationality development stage in 1995-2015.Among them, the SDI and SEI were reasonably high, and the SCI was relatively low. Spatially, the high rationality UAs were distributed across eastern China, while the low rationality UAs were located in western China. UAs with positive size structure possessed typically a dual-or multicenter urban structure, while UAs with negative size structure usually presented as a single-center structure. The evolutionary trajectories of rationality of size structure of UAs can be summarized as four different stages. Our findings suggest that, in addition to consolidating the status of national-level UAs, the development of regional-level UAs should be promoted. Also, the fostering focus and direction should be oriented toward an UA with dual-or multicenter spatial structure.

The Effect of Urban Agglomeration Expansion on PM_(2.5) Concentrations: Evidence from a Quasi-natural Experiment

This study constructs a quasi-natural experiment based on the expansion of the Yangtze River Delta urban agglomeration(YRDUA) of China in 2010 to investigate the impact and inner mechanism of urban agglomeration expansion on fine particulate matter(PM_(2.5)) concentrations through propensity scores in difference-in-differences models(PSM-DID) using panel data from 286 prefecturelevel cities in China from 2003 to 2016. The results show that 1) urban agglomeration expansion contributes to an overall decrease in PM_(2.5)concentration, which is mainly achieved from the original cities. For the new cities, on the other hand, the expansion significantly increases the local PM_(2.5)concentration. 2) In the long term, the significant influence of urban agglomeration expansion on PM_(2.5)concentration lasts for three years and gradually decreases. A series of robustness tests confirm the applicability of the PSM-DID model.3) Cities with weaker government regulation, a better educated population and higher per capita income present stronger PM_(2.5)reduction effects. 4) Urban agglomeration expansion affects the PM_(2.5)concentration mainly through industrial transfer and population migration, which cause a decrease in the PM_(2.5)concentration in the original cities and an increase in the PM_(2.5)concentration in the new cities.Corresponding policy suggestions are proposed based on the conclusions.

Simulation of Urban Land Expansion Under Ecological Constraints in Harbin-Changchun Urban Agglomeration,China

Under the demand of urban expansion and the constraints of China’s’National Main Functional Area Planning’policy,urban agglomerations are facing with a huge contradiction between land utilization and ecological protection,especially for HarbinChangchun urban agglomeration who owns a large number of land used for the protection of agricultural production and ecological function.To alleviate this contradiction and provide insight into future land use patterns under different ecological constraints’scenarios,we introduced the patch-based land use simulation(PLUS)model and simulated urban expansion of the Harbin-Changchun urban agglomeration.After verifying the accuracy of the simulation result in 2018,we predicted future urban expansion under the constraints of three different ecological scenarios in 2026.The morphological spatial pattern analysis(MSPA)method and minimum cumulative resistance(MCR)model were also introduced to identify different levels of ecological security pattern(ESP)as ecological constraints.The predicted result of the optimal protection(OP)scenario showed less proportion of water and forest than those of natural expansion(NE)and basic protection(BP)scenarios in 2026.The conclusions are that the PLUS model can improve the simulation accuracy at urban agglomeration scale compared with other cellular automata(CA)models,and the future urban expansion under OP scenario has the least threat to the ecosystem,while the expansion under the natural expansion(NE)scenario poses the greatest threat to the ecosystem.Combined with the MSPA and MCR methods,PLUS model can also be used in other spatial simulations of urban agglomerations under ecological constraints.

Stability of Spatial Structure of Urban Agglomeration in China Based on Central Place Theory

This paper brings forward the concept of stability of the spatial structure of urban agglomeration(UA)based on Central Place Theory by introducing centrality index and fractal theory.Before assessment,K=4 is selected as parameter to calculate centrality index and fractal dimension(K represents the quantitive relationship between city and the counties in Central Place Theory),and then found the number of nodes,the type of spatial structure,the spatial allocation of nodes with different hierarchy affecting the stability of spatial structure.According to spatial contact direction and the level of stability,UAs in China are classified into five types.Finally,it is posed as a further question that how to use hierarchical relation K=6 and K=7 in central place system to coordinate with the assessment of stability of soatial structure is brought forward.

Spatial Pattern Evolution and Casual Analysis of County Level Economy in Changsha-Zhuzhou-Xiangtan Urban Agglomeration, China

In order to evaluate whether or not the county units′ economy in the Changsha-Zhuzhou-Xiangtan(Chang-Zhu-Tan) Urban Agglomeration was growing as expected, this study analyzed the spatial economy pattern at county-level by using the Exploratory Spatial Data Analysis(ESDA) method. In this process, the global Moran′s I and local Getis-Ord G*i indexes were employed to analyze indicators including per capita GDP and three industrials(i.e. primary, secondary and tertiary industry) from 2000 to 2010. The results show that: 1) the county units′ economy in the Chang-Zhu-Tan Urban Agglomeration has exhibited a strong spatial autocorrelation and an accelerated integration trend since 2008(Moran′ s I increased from 0.26 to 0.56); 2) there is a significant difference in economy development between the northern and southern county units in the Chang-Zhu-Tan Urban Agglomeration: the hotspot zone with high economic level was formed among the northern county units whereas the coldspot zone with low economic level was located in the southern areas. This difference was caused primarily by the increasingly prominent economic radiation effect of Changsha ′upheaval′; 3) town density, secondary industry, and the integration policy are the major contributors driving the evolution of the spatial economy pattern in the Chang-Zhu-Tan Urban Agglomeration.

Measurement and Spatial Distribution of Urban Agglomeration Industrial Compactness in China

Urban agglomeration (UA) compactness means spatial concentration degree of physical entities, such as cities (towns), industries, resources, funds, traffic and technologies, whose concentration is formed according to specified economic and technologic association in the process of UA formation and development. The UA industrial compactness means the concentration degree of industry and industry clusters with reference to the industrial, technologi- cal and economic relations among the cities in the UA in the process of rational industrial division and with the exten- sion of industrial chain. After analyzing the researches on compactness, this paper finds that the relevant measurement coefficient and methods reflecting industrial geographical concentration fail to link industries spatial concentration with urban spatial concentration. Taking 23 UAs as samples and classifying them by development degree, this paper probes into UA compactness and spatial distribution characteristics from the perspective of industry by adopting UA index systems of industry and measurement models. The research finds out: 1) there is obvious positive correlation between UA industrial compactness and UA development degree; 2) the spatial distribution difference of UA industrial compactness is relatively great; and 3) UA industrial compactness shows a gradually decreasing tendency from the eastern part, the middle part to the western part of China. From the research thoughts and approaches, this article suggests that studies on the UA integrated compactness measurement should be enhanced from a multidimensional perspective involving space, traffic, population density and so on.

Spatial pattern and drivers of urbanization in China's mid-level developing urban agglomeration:A case study of Chang-Zhu-Tan

Urban agglomeration has become the main form of regional spatial organization in China.While most of the existing studies of urban agglomeration in China have focused on the eastern coastal areas,urban agglomeration with mid-level development in the rest of the country has been overlooke1.To better understand the urbanization process of the mid-level developing urban agglomeration,this study investigated the clustering pattern and the drivers of both urban population and firm dynamics during 2005-2015 in the Changsha-Zhuzhou-Xiangtan(Chang-Zhu-Tan)urban agglomeration of China using the methods ofkernel density estimation and geographic detection.Our results show that centralization was obvious,although decentralization also occurred in Chang-Zhu-Tan,and that the spatial agglomeration was promoted by several factors,such as administrative resources,location advantage,labor cost,and consumption capacity.Some problems hindering the development of this region were also discovered:administrative resources played a critical role in urbanization because small towns and villages did not receive enough attention,and the effect of local policy was not as beneficial as expected.These findings partly explain the relatively slow development of mid-level developing urban agglomerations and have important implications for promoting healthier urbanization.

Influential Intensity of Urban Agglomeration on Evolution of Ecoenvironmental Pressure:A Case Study of Changchun,China

In this paper,we study the interactive relationship between the agglomeration of urban elements and the evolution of eco-environmental pressure.We build an index system for evaluating the agglomeration of urban elements and eco-environmental pressure.Using the entropy method and response intensity model,we analyze how urban elements agglomeration influenced eco-environmental pressure in Changchun from 1990 to 2012,eliciting the changing features and influential factors.Ultimately,we conclude there is a significant interactive relationship between the agglomeration of urban elements and the evolution of eco-environmental pressure in Changchun.This is inferred from the degree of this agglomeration in Changchun having increased since 1990,with the degree of eco-environmental pressure first decreasing and then increasing.Alongside this,the impact of urban elements agglomeration on eco-environmental pressure has changed from negative to positive.The main reasons behind this shift are arguably the rapid growth of urban investment and ongoing urbanization.

Spatiotemporal Characteristics of Typical Ecosystem Services and Their Spatial Responses to Driving Factors in Ecologically Fragile Areas in Upper Yellow River,China

The identification of dominant driving factors for different ecosystem services(ESs)is crucial for ecological conservation and sustainable development.However,the spatial heterogeneity of the dominant driving factors affecting various ESs has not been adequately elucidated,particularly in ecologically fragile regions.This study employed the integrated valuation of ESs and trade-offs(InVEST)model to evaluate four ESs,namely,water yield(WY),soil conservation(SC),habitat quality(HQ),and carbon storage(CS),and then to identify the dominant driving factors of spatiotemporal differentiation of ES and further to characterize the spatial heterogeneity characteristics of the dominant driving factors in the eco-fragile areas of the upper Yellow River,China from 2000 to 2020.The results demonstrated that WY exhibited northeast-high and northwest-low patterns in the upper Yellow River region,while high values of SC and CS were distributed in central forested areas and a high value of HQ was distributed in vast grassland areas.The CS,WY,and SC exhibited decreasing trends over time.The most critical factors affecting WY,SC,HQ,and CS were the actual evapotranspiration,precipitation,slope,and normalized difference vegetation index,respectively.In addition,the effects of different factors on various ESs exhibited spatial heterogeneity.These results could provide spatial decision support for eco-protection and rehabilitation in ecologically fragile areas.

Land Use Dynamics and Ecosystem Service Value Changes in the Yangtze River Delta Urban Agglomeration Under Different Scenarios

Urban agglomerations,serving as pivotal centers of human activity,undergo swift alterations in ecosystem services prompted by shifts in land utilization.Strengthening the monitoring of ecosystem services in present and future urban agglomerations contributes to the rational planning of these areas and enhances the well-being of their inhabitants.Here,we analyzed land use conversion in the Yangtze River Delta(YRD)urban agglomeration during 1990-2020 and discussed the spatiotemporal response and main drivers of changes in ecosystem service value(ESV).By considering the different development strategic directions described in land use planning policies,we predicted land use conversion and its impact on ESV using the Future Land Use Simulation(FLUS)model in three scenari-os in 2025 and 2030.Results show that:1)from 1990 to 2020,land use change is mainly manifested as the continuous expansion of con-struction land to cultivated land.Among the reduced cultivated land,82.2%were occupied by construction land.2)The land use types conversion caused a loss of 21.85 billion yuan(RMB)in ESV during 1990-2020.Moreover,the large reduction of cultivated land area led to the continuous decline of food production value,accounting for 13%of the total ESV loss.3)From 2020 to 2030,land use change will mainly focus on Yangzhou and Zhenjiang in central Jiangsu Province and Taizhou in southern Zhejiang Province.Under the BAU(natural development)and ED(cultivated land protection)scenarios,construction land expansion remains dominant.In contrast,under the EP(ecological protection)scenario,the areas of water bodies and forest land increase significantly.Among the different scenarios,ESV is highest in the EP scenario,making it the optimal solution for sustainable land use.It can be seen that the space use conflict among urban,agriculture and ecology is a key factor leading to ESV change in the urban agglomeration of Yangtze River Delta.There-fore,it is crucial to maintain spatial land use coordination.Our findings provide suggestions for scientific and rational land use planning for the urban agglomeration.

The Structure and Pattern of Urban Network in the Lanzhou-Xining Urban Agglomeration

In this paper,we use factor analysis to evaluate the urban comprehensive quality of each city in the Lanzhou-Xining(Lan-Xi)urban agglomeration.The time distance was obtained by using GIS spatial analysis,and the structure and pattern of the spatial network were analyzed by using the gravity model and social network analysis method.The results show that:1)The scale effect of the Lan-Xi urban agglomeration is gradually emerging,and it is gradually forming the urban agglomeration with Lanzhou and Xining as the core,the Lan-Xi high-speed railway as the axis,and a high-dense connection.2)Lanzhou and Xining are at the core of the Lan-Xi urban agglomeration,which has a strong attraction and spreads to neighboring cities.3)In the network structure of the Lan-Xi urban agglomeration,Lanzhou,Baiyin,Gaolan,Yuzhong,Yongdeng,Dingxi,Lintao,Xining,Ledu,Huangzhong,Ping’an,Minhe and Datong are located in the network core position,which have the superiority position and lead to the entire regional communication enhancement and the regional integration development.4)This urban agglomeration has significant subgroups,eight tertiary subgroups and four secondary subgroup;the tertiary subgroups which compose secondary subgroup have a close connection and mutually influence each other.5)The Lanzhou Metropolitan Area and the Xining Metropolitan Area have an important impact on the surrounding cities,and the peripheral cities are basically controlled by the central city.The Dingxi subgroup,Lintao-Linxia subgroup,Gonghe subgroup have more structural holes than the subgroups within the Lanzhou Metropolitan Area and the Xining Metropolitan Area,so the peripheral cities of these subgroups have relatively less connection with surrounding cities.

Network analysis and spatial agglomeration of China’s high-speed rail: A dual network approach

China has the largest high-speed railway(HSR) system in the world, and it has gradually reshaped the urban network.The HSR system can be represented as different types of networks in terms of the nodes and various relationships(i.e.,linkages) between them. In this paper, we first introduce a general dual network model, including a physical network(PN)and a logical network(LN) to provide a comparative analysis for China’s high-speed rail network via complex network theory. The PN represents a layout of stations and rail tracks, and forms the basis for operating all trains. The LN is a network composed of the origin and destination stations of each high-speed train and the train flows between them. China’s high-speed railway(CHSR) has different topological structures and link strengths for PN in comparison with the LN. In the study, the community detection is used to analyze China’s high-speed rail networks and several communities are found to be similar to the layout of planned urban agglomerations in China. Furthermore, the hierarchies of urban agglomerations are different from each other according to the strength of inter-regional interaction and intra-regional interaction, which are respectively related to location and spatial development strategies. Moreover, a case study of the Yangtze River Delta shows that the hub stations have different resource divisions and are major contributors to the gap between train departure and arrival flows.

Analysis on Ecological Footprint of the Urban Agglomeration in Pearl River Delta

[Objective] The research aimed to calculate and analyze ecological footprint of the urban agglomeration in Pearl River Delta in 2009. [Method] 9 cities in Pearl River Delta as research zone, by using calculation model of the ecological footprint, ecological footprint and security of the urban agglomeration in Pearl River Delta were calculated. Current situation and sustainable development condition of the ecological environment in Pearl River Delta were conducted quantitative analysis. [Result] Except construction land and woodland, other 4 kinds of lands were all in ecological deficit states in Pearl River Delta. Especially arable land and fossil fuel land had obvious ecological deficit. [Conclusion] Biological resource consumption level and energy consumption level in Pearl River Delta were higher. We ought to take a variety of measures to reduce ecological deficit, making development manner turn toward sustainable direction.

数字基础设施建设对城市绿色创新效率的影响——基于“宽带中国”战略试点政策的准自然实验

本文基于我国280个地级及以上城市2006~2021年的面板数据,利用多期双重差分模型考察“宽带中国”战略试点政策实施对城市绿色创新效率的影响效应、内在机制及异质性表现。研究发现:(1)“宽带中国”战略试点政策实施对城市绿色创新效率具有显著的提升作用,并且在一系列稳健性检验后结果依然稳健;(2)劳动力流动和生产性服务业集聚是“宽带中国”战略试点政策实施提高城市绿色创新效率的两种机制;(3)“宽带中国”战略试点政策实施对城市绿色创新效率的促进作用在东部城市、大规模城市、非资源型城市中更强;(4)正式环境规制和非正式环境规制正向调节“宽带中国”战略试点政策实施对城市绿色创新效率的驱动作用。本文为推动数字基础设施建设以及城市绿色创新效率的提升提供了重要政策启示。

中国三大城市群生态经济效率的时空演变及收敛性分析

基于2006—2020年中国三大城市群48个地级市数据,综合运用Super-SBM模型、Malmquist指数及收敛模型,系统考察中国三大城市群生态经济效率的时空演变和收敛特征。结果表明:(1)京津冀城市群生态经济效率水平呈上升趋势,长三角城市群趋于平稳,珠三角城市群呈下降态势;三大城市群生态经济效率的空间演变存在差异,主要表现为珠三角城市群呈现由“面”向“点”转变的趋势、长三角城市群呈“三点”分布状并逐步向外发散、京津冀城市群则以北京市为起点并逐步向南发展。(2)京津冀与长三角城市群存在σ收敛特征,珠三角城市群不存在σ收敛;三大城市群均存在绝对β收敛和条件β收敛,但收敛速度不一。

SSP-RCP情景下京津冀城市群夏季热环境空间网络识别与评估

全球气候变化加剧和城市高温热浪频发,严重影响人居环境健康和社会可持续发展。该文综合GIS、形态学空间格局分析、电路理论和图论法等理论与技术,基于共享社会经济路径(SharedSocio-economicPathways,SSPs)与典型浓度路径(Representative Concentration Pathways,RCPs)联合情景框架的未来气候数据,定量识别2021-2100年低辐射强迫情景(SSP1-RCP2.6)、中等辐射强迫情景(SSP2-RCP4.5)和高辐射强迫情景(SSP5-RCP8.5)下京津冀城市群夏季热岛斑块时空格局并评估热环境空间网络时空演变过程和结构特征。结果表明:①2021-2100年京津冀城市群夏季热岛斑块类型以核心型和边缘型为主导,热环境源地数量、面积以及廊道数量、总长度和电流密度随时间和情景强迫性提升呈增加趋势,其中源地和廊道集中增长区域由南向北迁移,而廊道高密度区域始终位于城市群东南部;②京津冀城市群热环境空间网络的电流密度之和、夹点稳定性、网络闭合度、节点连接率和网络连接度与情景强迫性呈正相关,城市群发展的时空不均衡性是影响城市群热环境空间网络结构特征变化的重要原因。研究结果可为未来情景城市群热环境空间网络分析提供技术范式,也可为城市群空间协同发展主动应对气候变化风险提供理论参考。