Assessing urban population exposure risk to extreme heat: Patterns, trends, and implications for climate resilience in China (2000–2020)

Sustainable Cities and Society, Год журнала: 2024, Номер 103, С. 105260 - 105260

Опубликована: Фев. 7, 2024

Язык: Английский

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Spatially explicit assessment of the heat-related health risk in the Yangtze River Delta, China, using multisource remote sensing and socioeconomic data

Sustainable Cities and Society, Год журнала: 2024, Номер 104, С. 105300 - 105300

Опубликована: Фев. 23, 2024

Язык: Английский

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Towards multi-scale and context-specific heat health risk assessment - A systematic review

Sustainable Cities and Society, Год журнала: 2025, Номер 119, С. 106102 - 106102

Опубликована: Янв. 5, 2025

Язык: Английский

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Assessing heat vulnerability in Philadelphia using geographically weighted principal component analysis (GWPCA): A geospatial big data-driven approach

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2024, Номер 127, С. 103653 - 103653

Опубликована: Янв. 16, 2024

The impact of climate change, specifically more intense heat waves, has increased concerns about vulnerability, particularly among high-risk populations. This research utilizes multi-source geospatial big data and employs Geographically Weighted Principal Component Analysis (GWPCA) as well Global (GPCA) to analyze vulnerability in Philadelphia. Using GPCA, four key components are identified Sensitivity, Adaptive Capacity, proxy for Exposure, respectively. subsequent GWPCA analysis reveals localized differences, showing distinct patterns across the city. Notably, Sensitivity factors prominent western southwestern regions, whereas Exposure is dominant central southern parts. study underscores significance considering spatial heterogeneity when assessing vulnerability. It also highlights potential capture subtle disparities within specific areas proposes targeted strategies reduce affected communities. Therefore, incorporation an advanced model enables a comprehensive understanding complex urban environments. progress crucial enhancing resilience adaptation evolving conditions.

Язык: Английский

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Assessing the impact of heat vulnerability on urban public spaces using a fuzzy-based unified computational technique

AI & Society, Год журнала: 2024, Номер unknown

Опубликована: Апрель 2, 2024

Язык: Английский

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Assessing urban surface thermal environment and heat health risk in Chinese cities: A twenty-year study

Urban Climate, Год журнала: 2025, Номер 59, С. 102304 - 102304

Опубликована: Янв. 27, 2025

Язык: Английский

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Analyzing the typology and livability of 15-minute travel at metro stations in high-density cities: A case study of Singapore

Cities, Год журнала: 2025, Номер 158, С. 105727 - 105727

Опубликована: Янв. 17, 2025

Язык: Английский

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Urban heat health risk inequality and its drivers based on Local Climate Zones: A case study of Qingdao, China

Building and Environment, Год журнала: 2025, Номер unknown, С. 112827 - 112827

Опубликована: Март 1, 2025

Язык: Английский

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Spatial heterogeneity of driving factors for urban heat health risk in Chongqing, China: A new identification method and proposal of planning response framework

Ecological Indicators, Год журнала: 2023, Номер 153, С. 110449 - 110449

Опубликована: Июнь 7, 2023

With urban heat challenges increasingly severe, assessing health risk has become crucial for human settlements. Unfortunately, previous studies have not accurately identified the driving factors, posing a significant obstacle to translating assessment results into policymaking. Particularly, potential spatial heterogeneity of factors at indicator-level may exist. Therefore, this study developed systematic method examine in Chongqing. Based on heterogeneity, an integrated framework linking risk, and response strategies was proposed, supporting specific solutions different cities. The indicate that exhibit strong indicator-level. Even within same prevention zone functional areas, maximum differences number combination categories can reach four five, respectively. Moreover, relying solely obtained through traditional methods develop cooling measures is unreasonable. When these are consistent, there still, average, six combinations indicator-level, each includes average 2.9 indicators. higher level zone, more it contains. above moderate 3.9, than 1.1 2 found below levels. Overall, provides reference understanding offers approach assist policymakers formulating guided strategies.

Язык: Английский

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A multiscale examination of heat health risk inequality and its drivers in mega-urban agglomeration: A case study in the Yangtze River Delta, China

Journal of Cleaner Production, Год журнала: 2024, Номер 458, С. 142528 - 142528

Опубликована: Май 9, 2024

Язык: Английский

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