A cold island connectivity and network perspective to mitigate the urban heat island effect

Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 94, P. 104525 - 104525

Published: March 25, 2023

Language: Английский

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Influence of non-urban reference delineation on trend estimate of surface urban heat island intensity: A comparison of seven methods

Remote Sensing of Environment, Journal Year: 2023, Volume and Issue: 296, P. 113735 - 113735

Published: July 27, 2023

Language: Английский

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Drivers of global surface urban heat islands: Surface property, climate background, and 2D/3D urban morphologies

Building and Environment, Journal Year: 2023, Volume and Issue: 242, P. 110581 - 110581

Published: July 4, 2023

Language: Английский

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A quantitative review of nature-based solutions for urban sustainability (2016–2022): From science to implementation

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 927, P. 172219 - 172219

Published: April 4, 2024

Language: Английский

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Characteristics of surface urban heat islands in global cities of different scales: Trends and drivers

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 107, P. 105483 - 105483

Published: April 28, 2024

Language: Английский

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Spatio-temporal assessment of heat health risk in Chinese metropolitan cities based on the modified multi-indicators coupled risk framework

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 108, P. 105451 - 105451

Published: April 20, 2024

Language: Английский

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Analysis of urban heat island and human thermal comfort in a Mediterranean city: A case study of Lecce (Italy)

Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 98, P. 104849 - 104849

Published: Aug. 6, 2023

Language: Английский

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A comprehensive generalizability assessment of data-driven Urban Heat Island (UHI) models

Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 96, P. 104701 - 104701

Published: June 7, 2023

Data-driven models serve as valuable tools for understanding and tackling the UHI phenomenon that can provide user-friendly platforms urban planners incorporating considerations in their decisions. This study aims to assess generalizability of data-driven at street-level resolution, particularly considering various similarity degrees contexts between training testing cities. Five cities from three countries were selected encompass a diverse range similarities this comparative study. Random Forest developed. The lowest-performing model has an R2 value 0.56 MAE 0.07, highest-performing 0.71 0.05. While these proved be accurate they trained for, cross-validation different revealed low capabilities, irrespective degree datasets. Small changes feature importance resulted significant variation derivation mechanisms behavior, which contributes models’ generalizability. findings research indicate universal mitigation strategies may not yield consistent outcomes worldwide, one-size-fits-all approach inefficient addressing UHI. Hence, it's vital tackle locally.

Language: Английский

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Advantages of modeling the urban heat island intensity: A tool for implementing nature-based solutions

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 102, P. 105204 - 105204

Published: Jan. 13, 2024

Language: Английский

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Trends and attributions of the long-term thermal comfort across the urban–rural gradient in major Chinese cities

Applied Geography, Journal Year: 2024, Volume and Issue: 164, P. 103221 - 103221

Published: Feb. 6, 2024

Language: Английский

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