Understanding Urban Cooling of Blue–Green Infrastructure: A Review of Spatial Data and Sustainable Planning Optimization Methods for Mitigating Urban Heat Islands DOI Open Access
Grzegorz Budzik, Marta Sylla, Tomasz Kowalczyk

и другие.

Sustainability, Год журнала: 2024, Номер 17(1), С. 142 - 142

Опубликована: Дек. 27, 2024

Many studies in the literature have assessed blue–green infrastructure (BGI) characteristics that influence its cooling potential for sustainable urban development. Common assessment methods include satellite remote sensing, numerical simulations, and field measurements, each defining different efficiency indicators. This methodological diversity creates uncertainties optimizing BGI management. To address this, a review was conducted using Google Scholar, Web of Science, Scopus, examining how cools space, which spatial data are most effective, differences may affect results, what current research gaps innovative future directions are. The results suggest sensing is ideal large-scale comparisons, simulations local development scenarios, measurements assessing conditions closest to residents. Maximum intensity averages show 4 °C from 3 2 simulations. Differences conclusions arise resolution, model scale, delineation method, range calculation. key object size, vegetation fraction, foliage density, connectivity. Future should prioritize integration methods, shape complexity effectiveness assessment, effects morphology on evaluating characteristics’ effectiveness, explore digital twin technology management optimization. study integrates information BGI’s capabilities, serving as useful resource both practitioners researchers support resilient city

Язык: Английский

Research on the cool island effect of green spaces in megacity cores: A case study of the main urban area of Xi'an, China DOI
Kaili Zhang,

Qiqi Liu,

Bin Fang

и другие.

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106255 - 106255

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

2

Is shading a better way to cool down? Evaluation and comparison of the cooling capacity of blue-green spaces and urban shade DOI Creative Commons
Yu Zou, Jiao Chen, Hua Zong

и другие.

Ecological Indicators, Год журнала: 2024, Номер 167, С. 112688 - 112688

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

4

Optimizing urban park cooling effects requires balancing morphological design and landscape structure DOI Creative Commons
Lin Wang, Wenjia Wang, Fei Tang

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Май 2, 2025

Язык: Английский

Процитировано

0

Quantifying the impact of building material stock and green infrastructure on urban heat island intensity DOI
Yi Bao, Zhou Huang, Ganmin Yin

и другие.

Building and Environment, Год журнала: 2025, Номер unknown, С. 113068 - 113068

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Providing support for urban planning through investigating the cooling influence of park in Northern China: A case study of Xi'an DOI
Kai Xin, Jingyuan Zhao,

Zhaokun Li

и другие.

Urban Climate, Год журнала: 2024, Номер 58, С. 102221 - 102221

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

1

Understanding Urban Cooling of Blue–Green Infrastructure: A Review of Spatial Data and Sustainable Planning Optimization Methods for Mitigating Urban Heat Islands DOI Open Access
Grzegorz Budzik, Marta Sylla, Tomasz Kowalczyk

и другие.

Sustainability, Год журнала: 2024, Номер 17(1), С. 142 - 142

Опубликована: Дек. 27, 2024

Many studies in the literature have assessed blue–green infrastructure (BGI) characteristics that influence its cooling potential for sustainable urban development. Common assessment methods include satellite remote sensing, numerical simulations, and field measurements, each defining different efficiency indicators. This methodological diversity creates uncertainties optimizing BGI management. To address this, a review was conducted using Google Scholar, Web of Science, Scopus, examining how cools space, which spatial data are most effective, differences may affect results, what current research gaps innovative future directions are. The results suggest sensing is ideal large-scale comparisons, simulations local development scenarios, measurements assessing conditions closest to residents. Maximum intensity averages show 4 °C from 3 2 simulations. Differences conclusions arise resolution, model scale, delineation method, range calculation. key object size, vegetation fraction, foliage density, connectivity. Future should prioritize integration methods, shape complexity effectiveness assessment, effects morphology on evaluating characteristics’ effectiveness, explore digital twin technology management optimization. study integrates information BGI’s capabilities, serving as useful resource both practitioners researchers support resilient city

Язык: Английский

Процитировано

1