Heat and park attendance: Evidence from “small data” and “big data” in Hong Kong

Hao, Tongping; Chang, Haoliang; Liang, Sisi; Jones, Phil; Chan, P. W.; Li, Lishuai; Huang, Jianxiang

doi:10.1016/j.buildenv.2023.110123

Cited by 10 publications

(6 citation statements)

References 49 publications

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“…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]. Additionally, sentiment analysis aids in managing urban systems and natural areas by providing real-time feedback on public sentiment towards urban developments and environmental conservation efforts [64][65][66].…”

Section: Social-spatial Dynamic Measurementsmentioning

confidence: 99%

“…Through "big data" analysis, community conditions involve quantifying urban spatial elements, such as commercial facilities, public amenities, and park greenery [61,[75][76][77]. Other approaches include examining urban green space (UGS) fairness using MSPA [55], measuring accessibility [16], and evaluating environmental inequality concerning transportation facilities [78], among other aspects of the environment [62,63,70,79].…”

Section: Social-spatial Dynamic Measurementsmentioning

confidence: 99%

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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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Section: Social-spatial Dynamic Measurementsmentioning

confidence: 99%

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

View full text Add to dashboard Cite

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“…High density has both positive and negative effects. Many scholars have presented evidence that higher density in urban areas is associated with a variety of desirable outcomes, including increased use of public transportation, improved financial stability for local governments, walkable and healthy living environments, housing diversity and affordability, enhanced community character, and cultural vitality [9][10][11][12][13][22][23][24][25][26][27][28]. Other scholars, on the contrary, have noted how some high-density neighborhoods produce excessive concentration and congestion, difficult management, and inefficient facilities.…”

Section: The Solution Of High Density For Growing Cities and Sustaina...mentioning

confidence: 99%

Strategies for Sustainable Urban Renewal: Community-Scale GIS-Based Analysis for Densification Decision Making

et al. 2023

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China is gradually shifting towards more sustainable urban development, and the local governments are increasingly promoting social and environmentally sustainable spatial planning practices. This article debates the potential contradiction between the goal of a constantly growing urban population and the limits to the consumption of land planned by this new direction of urban development. The analysis focuses on the wealthy city of Suzhou in the Yangtse River Delta region and explores the opportunities for densification of the residential areas as a possible solution for this contradiction, as already tested by some Chinese cases for land use efficiency. The research applies GIS-based spatial analysis and identifies some of the sites that can be efficiently redeveloped in the resettlement communities for their low floor area ratio (FAR) and obsolescent conditions, which do not correspond to the increasingly middle-class status of the residents in the urban region. The article investigates the different options of a densification strategy in the frame of the policies of urban renewal promoted in China in recent years for improving the quality of the built environment.

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“…Therefore, prediction technologies with low cost were becoming an optional efficient choice [ 8 ]. Hao et al thought that existing studies of outdoor thermal comfort and behavior are limited by the so-called ‘small data’ approach [ 9 ]. Most studies employed site measurement, questionnaires and interviews in the last two decades.…”

Section: Introductionmentioning

confidence: 99%

“…They acquired park attendance data, and captured occupant thermal sensation and comfort using a questionnaire. The performance of biometeorological indicators was compared [ 9 ]. There were some relevant studies of wind environments and urban micro climates.…”

Section: Introductionmentioning

confidence: 99%

Data-mining framework for in-depth quantitative study of influences on low-wind-velocity area from morphological parameters of cuboid-form buildings

Guo,

Song,

Chu

et al. 2024

Heliyon

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Heat and park attendance: Evidence from “small data” and “big data” in Hong Kong

Cited by 10 publications

References 49 publications

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

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

Strategies for Sustainable Urban Renewal: Community-Scale GIS-Based Analysis for Densification Decision Making

Data-mining framework for in-depth quantitative study of influences on low-wind-velocity area from morphological parameters of cuboid-form buildings

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