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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A Novel Urban Heat Vulnerability Analysis: Integrating Machine Learning and Remote Sensing for Enhanced Insights

Remote Sensing, Год журнала: 2024, Номер 16(16), С. 3032 - 3032

Опубликована: Авг. 18, 2024

Rapid urbanization and climate change exacerbate the urban heat island effect, increasing vulnerability of residents to extreme heat. Although many studies have assessed vulnerability, there is a significant lack standardized criteria references for selecting indicators, building models, validating those models. Many existing approaches do not adequately meet planning needs due insufficient spatial resolution, temporal coverage, accuracy. To address this gap, paper introduces U-HEAT framework, conceptual model analyzing vulnerability. The primary objective outline theoretical foundations potential applications U-HEAT, emphasizing its nature. This framework integrates machine learning (ML) with remote sensing (RS) identify at both long-term detailed levels. It combines retrospective forward-looking mapping continuous monitoring assessment, providing essential data developing comprehensive strategies. With active capacity, enables refinement evaluation policy impacts. presented in offers sustainable approach, aiming enhance practical analysis tools. highlights importance interdisciplinary research bolstering resilience stresses need ecosystems capable addressing complex challenges posed by increased study provides valuable insights researchers, administrators, planners effectively combat challenges.

Язык: Английский

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Spatiotemporal dynamic mapping of heat exposure risk for different populations in city based on hourly multi-source data

Sustainable Cities and Society, Год журнала: 2024, Номер 107, С. 105454 - 105454

Опубликована: Апрель 18, 2024

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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A multiscale examination of heat risk spatiotemporal dynamics in Chinese urban agglomerations: A hierarchical assessment method and planning framework

International Journal of Disaster Risk Reduction, Год журнала: 2025, Номер 117, С. 105198 - 105198

Опубликована: Янв. 10, 2025

Язык: Английский

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Exploring intra-urban thermal stress vulnerability within 15-minute city concept: Example of heat waves 2021 in Moscow

Sustainable Cities and Society, Год журнала: 2024, Номер 114, С. 105729 - 105729

Опубликована: Авг. 4, 2024

Язык: Английский

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Spatio-temporal Variations of Heat Extremes across the Yangtze River Delta during 2001-2023 Based on Remotely Sensed Seamless Air Temperature

Environmental Research, Год журнала: 2025, Номер unknown, С. 120824 - 120824

Опубликована: Янв. 1, 2025

Язык: Английский

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Adapting to Heatwaves: Optimizing Urban Green Spaces in Beijing to Reduce Heat Health Risks

Опубликована: Янв. 1, 2025

Язык: Английский

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From scenarios to strategies. Integrated methodology addressing urban heat vulnerability in uncertain future

Sustainable Cities and Society, Год журнала: 2025, Номер 121, С. 106202 - 106202

Опубликована: Фев. 6, 2025

Язык: Английский

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Research on the Spatial Differentiation Pattern of High-Temperature Disaster Resilience and Strategies for Enhancing Resilience: A Case Study of Hangzhou, China

Sustainability, Год журнала: 2025, Номер 17(6), С. 2338 - 2338

Опубликована: Март 7, 2025

With the intensification of climate change and urbanization, impact high-temperature disasters on urban resilience has become increasingly significant. Based “Pressure-State-Response” (PSR) model, this study proposes a novel assessment method for disaster resilience. Through 15 evaluation indicators across 3 categories, we quantified level in Hangzhou constructed SOM-K-means second-order clustering algorithm to classify area into different zones, exploring spatial differentiation characteristics The research results indicate following: (1) exhibits relatively low resilience, with distribution pattern showing radial decrease from main city at center, followed by slight increase far periphery area. (2) was divided four distinct demonstrating significant characteristics. This innovatively integrates PSR model method, providing new perspective quantitative zoning findings offer valuable decision-making support enhancing

Язык: Английский

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