Does regional cooperation constrain urban sprawl? Evidence from the Guangdong-Hong Kong-Macao Greater Bay Area

Zhang, Xian‐Chun; Chen, Yang; Xu, Yuanshuo; Yue, Wenze; Tang, Chenghui

doi:10.1016/j.landurbplan.2023.104742

Cited by 18 publications

(3 citation statements)

References 64 publications

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“…(c) Transportation facilities. The area of urban roads at the end of the year, and the accessibility of urban transportation is the basis of urban development (Zhang et al2023 [ 41 ]).…”

Section: Methodsmentioning

confidence: 99%

Haze pollution and urban sprawl: An empirical analysis based on panel simultaneous equation model

Huo

2024

PLoS ONE

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Based on the panel data of 227 prefecture-level and above cities in China from 2002 to 2018, a panel linkage equation model is constructed to explore the bidirectional influence relationship between haze pollution and urban sprawl, and the results of the study find that, firstly, there is a bidirectional promotion of causality between haze pollution and urban sprawl. That is, PM2.5 not only has a significant positive effect on urban sprawl, but also urban sprawl has a significant positive correlation with haze pollution, which is further strengthened by adding the air flow coefficient instrumental variable. Second, the heterogeneity analysis yields that haze pollution has different effects on urban sprawl in different regions. Under the sub-regional samples, haze pollution and urban sprawl have a bi-directional significant negative impact relationship in the eastern region, none of the haze pollution and urban sprawl have a bi-directional significant impact relationship in the western region, but both the central region and the northeastern region have a significant positive impact relationship. Under different city sizes, haze pollution and urban sprawl in large, medium and small cities have a bi-directional significant positive impact relationship, and from the numerical size, the degree of influence of haze pollution on urban sprawl in large cities is greater than that in small and medium cities; while the degree of influence of urban sprawl on haze pollution in medium cities is greater than that in large and small cities. Accordingly, it is proposed that urban governance should be adapted to local conditions, focus on innovative technologies to reduce energy consumption, and utilize big data to manage cities.

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“…(c) Transportation facilities. The area of urban roads at the end of the year, and the accessibility of urban transportation is the basis of urban development (Zhang et al2023 [ 41 ]).…”

Section: Methodsmentioning

confidence: 99%

Haze pollution and urban sprawl: An empirical analysis based on panel simultaneous equation model

Huo

2024

PLoS ONE

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“…Analyzing sentiment tones within social media discussions has become a prevalent method for gauging public attitudes and emotions toward urban issues [56]. Researchers utilize this approach to investigate environmental quality, examining how public sentiment on social media platforms like Twitter, Facebook, and Weibo reflects urban environment perceptions [57][58][59][60]. Moreover, sentiment analysis contributes to the reviewing of urban planning theories, providing insights into the effectiveness of different planning strategies and their reception among the public [61][62][63].…”

Section: Social-spatial Dynamic Measurementsmentioning

confidence: 99%

Navigating Post-COVID-19 Social–Spatial Inequity: Unravelling the Nexus between Community Conditions, Social Perception, and Spatial Differentiation

Zhao,

Liu,

Chen

et al. 2024

Land

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The 2023 SDGs report underscores the prolonged disruption of COVID-19 on community living spaces, infrastructure, education, and income equality, exacerbating social and spatial inequality. Against the backdrop of the dual impact of significant events and the emergence of digital technologies, a coherent research trajectory is essential for characterizing social–spatial equity and understanding its influential factors within the urban planning discipline. While prior research emphasized spatial dimensions and mitigated spatial differentiation to ensure urban equity, the complexity of these interconnections necessitates a more comprehensive approach. This study adopts a holistic perspective, focusing on the “social–spatial” dynamics, utilizing social perception (sentiment maps) and spatial differentiation (housing prices index) pre- and post-pandemic to elucidate the interconnected and interactive nature of uneven development at the urban scale. It employs a multi-dimensional methodological framework integrating morphology analysis of housing conditions, GIS analysis of urban amenities, sentiment semantic analysis of public opinion, and multiscale geographically weighted regression (MGWR) analysis of correlation influential factors. Using Suzhou, China, as a pilot study, this research demonstrates how these integrated methods complement each other, exploring how community conditions and resource distribution collectively bolster resilience, thereby maintaining social–spatial equity amidst pandemic disruptions. The findings reveal that uneven resource distribution exacerbates post-pandemic social stratification and spatial differentiation. The proximity of well-maintained ecological environments, such as parks or scenic landmarks, generally exhibits consistency and positive effects on “social–spatial” measurement. Simultaneously, various spatial elements influencing housing prices and social perception show geographic heterogeneity, particularly in areas farther from the central regions of Xiangcheng and Wujiang districts. This study uncovers a bilateral mechanism between social perception and spatial differentiation, aiming to delve into the interdependent relationship between social–spatial equity and built environmental factors. Furthermore, it aspires to provide meaningful references and recommendations for urban planning and regeneration policy formulation in the digital era to sustain social–spatial equity.

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“…Some scholars conceptualize these externalities as "externality fields" [1], "cluster economies" [28], "complex economies" [29], or "urban network externalities" [30]. Although most current research focuses on conceptualizing and measuring the economic externalities in the process of city-regional formation [31,32], few studies paid attention to whether there is spatial heterogeneity in the externalities of city regions and to what a certain extent. In summary, seminal works have examined the various spatial patterns, mechanisms, and heterogeneity of city regions in areas such as migration, industrial redistribution, and urban governance, producing valuable insights and conclusions.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Regional Integration Strategies on the Formation of City Regions and Its Agglomeration Shadow: Evidence from the Yangtze River Delta, China

Zhen

Shi

2023

Land

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Using a sample of 122 county-level units in the Yangtze River Delta (YRD) region from 2000 to 2017, this study employs a difference-in-differences model (DID) to examine the impact of regional integration strategy (RIS) on city-region formation and a difference-in-difference-in-difference model (DDD) to test whether it has spatial heterogeneity. The results indicate that RIS has a significant positive impact on industrial integration while it also displays obvious industrial heterogeneity and spatial heterogeneity. The results of the present study contribute to the following points: First, the implementation of RIS promotes a balanced layout of the secondary industry in the region, yet the tertiary industry tends to agglomerate towards central cities. Furthermore, we found that RIS has a more significant negative effect on the integration of the secondary industry and tertiary industry in cities adjacent to metropolis. Consequently, RIS magnifies the “agglomeration shadow” within city regions in terms of industrial integration. Last, our in-depth fieldwork on Jiaxing unravels the mechanism of the shadow effect of RIS.

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Does regional cooperation constrain urban sprawl? Evidence from the Guangdong-Hong Kong-Macao Greater Bay Area

Cited by 18 publications

References 64 publications

Haze pollution and urban sprawl: An empirical analysis based on panel simultaneous equation model

Haze pollution and urban sprawl: An empirical analysis based on panel simultaneous equation model

Navigating Post-COVID-19 Social–Spatial Inequity: Unravelling the Nexus between Community Conditions, Social Perception, and Spatial Differentiation

The Impact of Regional Integration Strategies on the Formation of City Regions and Its Agglomeration Shadow: Evidence from the Yangtze River Delta, China

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