Land surface temperature and socioeconomic residential segregation in the Metropolitan Zone of San Luis Potosí, Mexico DOI
Omar Parra Rodríguez, Carlos Alfonso Muñoz Robles, Lourdes Marcela López Mares

и другие.

The Science of The Total Environment, Год журнала: 2024, Номер 957, С. 177753 - 177753

Опубликована: Ноя. 27, 2024

Язык: Английский

Urban heat dynamics in local climate zones (LCZs): A Systematic review DOI Creative Commons

Neshat Rahmani,

Ayyoob Sharifi

Building and Environment, Год журнала: 2024, Номер unknown, С. 112225 - 112225

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

10

Exploration of Influencing Factors of Land Surface Temperature in Cities Within the Beijing–Tianjin–Hebei Region Based on Local Climate Zone Scheme DOI Creative Commons
Zheng Wang, Yifei Peng,

Youfang Li

и другие.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Год журнала: 2024, Номер 17, С. 9728 - 9744

Опубликована: Янв. 1, 2024

Clarifying the factors that influence land surface temperature (LST) is crucial for proposing specific LST mitigation strategies. This study focuses on Beijing-Tianjin-Hebei (BTH) Region and investigates influencing of various local climate zone (LCZ) built types from perspectives urban morphology, cover, human activity. The results suggest areas LCZ vary across cities within BTH Region, attributed to differences in city size Gross Domestic Product (GDP). area Beijing Tianjin, with significantly high sizes GDP, exceeds 2000 km2. In contrast, Qinhuangdao, Zhangjiakou Chengde, which have relatively low this less than 500 However, main same type are highly consistent. Building coverage ratio (BCR), average building height (ABH) pervious fraction (PSF) three most important factors. correlation between BCR mainly concentrated compact high-rise open types, Pearson coefficient (r) ranging 0.2 0.44; ABH high-rise, mid-rise, mid-rise r -0.2 -0.52; PSF almost all -0.56. By integrating these findings features each strategies were further proposed. can help develop context Coordinated Development thereby promoting healthy sustainable development region.

Язык: Английский

Процитировано

8

Assessing Diurnal Land Surface Temperature Variations across Landcover and Local Climate Zones: Implications for Urban Planning and Mitigation Strategies on Socio-Economic Factors DOI Creative Commons
Prathiba A. Palanisamy, Joanna Zawadzka, Kamal Jain

и другие.

Sustainable Cities and Society, Год журнала: 2024, Номер 116, С. 105880 - 105880

Опубликована: Окт. 11, 2024

Язык: Английский

Процитировано

6

The effects of 2-D and 3-D urban landscape metrics on mean radiant temperature in hot-arid Phoenix and Tempe, Arizona, USA DOI Creative Commons
Ahmet Çilek, Müge Ünal, Ariane Middel

и другие.

Sustainable Cities and Society, Год журнала: 2023, Номер 101, С. 105116 - 105116

Опубликована: Дек. 16, 2023

Язык: Английский

Процитировано

16

Research on Characteristics and Influencing Factors of High Temperature Disaster Risk in Wuhan Based on Local Climate Zone DOI Creative Commons
Shujing Guo, Li Zhang

Landscape Architecture, Год журнала: 2025, Номер 32(1), С. 105 - 113

Опубликована: Янв. 1, 2025

Objective Against the background of rapid urbanization and global warming, Wuhan is frequently hit by extreme heat events, which not only poses a serious threat to health status local residents, but also brings great losses socio-economic development. Mapping high temperature disaster risk in urban development area analyzing influencing factors thereof at scale can provide an important basis for prevention disasters city. Methods Based on "hazard – exposure vulnerability" assessment framework proposed Intergovernmental Panel Climate Change, this research constructed system utilizing multi-source data, then pre-processes all relevant indicators make them dimensionless. Then, combination analytic hierarchy process principal component analysis adopted assign weights indicators, with such being finally superimposed obtain hazard map, map vulnerability respectively. On basis, synthesized identify distribution characteristics area. Then Landsat 8 remote sensing images are processed SAGA GIS software, Google Earth Pro Random Forest algorithm classify into 17 climate zone (LCZ) types based image classification method World Urban Database Access Portal Tools (WUDAPT). With 70% random samples used drawing 30% checking, LCZ maps that meet requirements accuracy obtained analyzed site identification scale. The local-scale risk, analyze degree each type differences between different types, explore reasons differences. Finally, eight landscape pattern indices preliminarily selected levels, optimal size using moving window Fragstats 4.2 software. Furthermore, highly correlated screened out under size, multicollinearity examined those excluded. geographically weighted regression (GWR) models effect patterns spatial heterogeneity risk. Results district do differ much, overall presentation center gradually decreases from low, high-risk areas mainly located south-central part Caidian District, west north Jiangxia dense industrial parks south Dongxihu Iron Steel Factory Qingshan Tianhe Airport Huangpi low-risk watershed part. Jianghan, Qiaokou, districts have relatively average value due population density or buildings, while Wuchang Hongshan low presence large water green therein. Overlaying normalized maps, it be seen that, among building sparse built-up (LCZ 9) has lowest significantly higher than other low-rise buildings 8) heavy 10), plants zones Among natural environment G) indicates effectively mitigate disaster; bare rock E), exposed sand F), construction H) outdoor, they typically values solar radiation long time. As indices, percentage (PLAND) influence aggregation index (AI). Conclusion results above, strategies cope proposed. First, vegetation should increased. Secondly, layout rationally planned. Meanwhile, anthropogenic source emissions controlled. service facilities improved enhance city's coping ability.

Язык: Английский

Процитировано

0

Inter- and intra-LCZ thermal heterogeneity: The dominant role of external environments in shaping local land surface temperature DOI
Xinlu Lin, Xu Lin, Chao Yan

и другие.

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106188 - 106188

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

The Impact of Spatiotemporal Effect and Relevant Factors on the Urban Thermal Environment Through the XGBoost-SHAP Model DOI Creative Commons

Junqing Wei,

Yonghua Li,

Liqi Jia

и другие.

Land, Год журнала: 2025, Номер 14(2), С. 394 - 394

Опубликована: Фев. 13, 2025

The urban thermal environment is a critical topic in contemporary studies. However, the mechanisms driving relationships between influencing factors and across different spatial scales temporal dimensions remain unclear, particularly as most of these exhibit nonlinearity. This study utilizes XGBoost SHAP models, combined with partial dependency plot, to analyze influence population activities, built environment, topography, ecological climatic conditions, landscape pattern on diurnal nocturnal land surface temperature (LST) changes rural areas Hangzhou throughout year. results indicate that during daytime, topography exerts strong LST both Hangzhou. At nighttime, activities becomes more pronounced. Meanwhile, patterns show no significant impact either or areas, regardless daytime nighttime. Additionally, we analyzed specific nonlinear LST. Finally, our findings suggest can interact synergistically pairs affect LST, this mechanism being prominent areas. Overall, categorizes examines contributing from perspectives, providing insights for developing planning strategies mitigate heat issues future.

Язык: Английский

Процитировано

0

How landscape characteristics impact land surface temperature in the context of urban spatial heterogeneity: A case study from Beijing, China DOI
Wei Chen, Jianjun Zhang,

Chenyan Huang

и другие.

Urban Climate, Год журнала: 2025, Номер 60, С. 102366 - 102366

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Exploring the heat balance characteristics in Shanghai by using the WRF model coupled with LCZ scheme DOI
Zheng Wang, Yasuyuki Ishida, Yifei Peng

и другие.

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106295 - 106295

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Advances in urban mapping of local climate zones for heat mitigation: A systematic review DOI
Gladys Adriana Acosta-Fernández, K.E. Martínez-Torres, M.E. González-Trevizo

и другие.

Land Use Policy, Год журнала: 2025, Номер 153, С. 107540 - 107540

Опубликована: Апрель 9, 2025

Язык: Английский

Процитировано

0