Critical Evaluation of the Spatiotemporal Behavior of UHI, through Correlation Analyses based on Multi-City Heterogeneous Dataset

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 110, P. 105576 - 105576

Published: June 5, 2024

Language: Английский

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Data-driven analysis of Urban Heat Island phenomenon based on street typology

Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 101, P. 105170 - 105170

Published: Dec. 29, 2023

This study explores the intricate relationship between diverse street types and urban heat island (UHI) phenomenon - a major issue where regions are warmer than their rural counterparts due to anthropogenic release absorption by structures. UHI leads increased energy consumption, diminished air quality, potential health hazards. research posits that sample of representative streets (i.e., few from each type street) will be sufficient capture model in an context, accurately reflecting behavior other streets. To do so, were classified into unique typologies based on (1) socio-economic morphological attributes (2) temperature profiles, utilizing two clustering methodologies. The first approach employed K-Prototypes categorize according similarities. second utilized Time Series Clustering K-Means, focusing profiles. findings indicate models retain strong performance levels, with R-Squared values 0,85 0,80 MAE ranging 0,22 0,84°C for CUHI SUHI respectively, while data collection efforts can reduced 50 70%. highlights value typology interpreting mechanisms. also stresses need consider aspects temporal variations its drivers when formulating mitigation strategies, thereby providing new insights understanding alleviating effects at local scale.

Language: Английский

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Impacts of spatial explanatory variables on surface urban heat island intensity between urban and suburban regions in China

International Journal of Digital Earth, Journal Year: 2024, Volume and Issue: 17(1)

Published: Jan. 16, 2024

The intensified thermal environment in suburban areas is raising wide concerns for human society and public health due to rapid urbanization. Although the satellite-derived surface urban heat island intensity (SUHII) a commonly used indicator, it still needs be determined SUHII between challenges delineating their boundaries with changes. Thus, comprehensive analysis of spatial explanatory variables (SEVs) among highly needed. Here, using long-term satellite observations, we analyzed spatiotemporal patterns different temporal intervals (i.e. seasonal diurnal) contribution SEVs areas. Our results indicate that shows predominantly increasing trend from 2012–2021 cities China. Despite trends increasing/decreasing) being relatively consistent both suburban, latter higher proportion regarding various SEVs. Besides, partial least squares regression (PLSR) model major contributors are landscape shape index (LSI), patch density (PD), digital elevation (DEM), while areas, those critical LSI, normalized difference built-up (NDBI), DEM. These findings can facilitate sustainable design planning nature-based solution.

Language: Английский

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Greenspace coverage vs. enhanced vegetation index: Correlations with surface urban heat island intensity in different climate zones

Urban Climate, Journal Year: 2024, Volume and Issue: 58, P. 102140 - 102140

Published: Sept. 28, 2024

Language: Английский

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Exploring air temperature variability and socio-demographic inequalities in heat exposure through machine learning: A case study of Maricopa County, Arizona

Urban Climate, Journal Year: 2025, Volume and Issue: 59, P. 102276 - 102276

Published: Jan. 9, 2025

Language: Английский

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