Analysis of Surface Urban Heat Island in the Guangzhou-Foshan Metropolitan Area Based on Local Climate Zones DOI Creative Commons

Xiaxuan He,

Qifeng Yuan,

Yinghong Qin

и другие.

Land, Год журнала: 2024, Номер 13(10), С. 1626 - 1626

Опубликована: Окт. 7, 2024

Understanding the driving mechanisms behind surface urban heat island (SUHI) effects is essential for mitigating degradation of thermal environments and enhancing livability. However, previous studies have primarily concentrated on central areas, lacking a comprehensive analysis entire metropolitan area over distinct time periods. Additionally, most relied regression models such as ordinary least squares (OLS) or logistic regression, without adequately analyzing spatial heterogeneity factors influencing effects. Therefore, this study aims to explore in Guangzhou-Foshan across different The Local Climate Zones (LCZs) method was employed analyze landscape characteristics structure metropolis years 2013, 2018, 2023. Furthermore, Geographically Weighted Regression (GWR), Multi-scale (MGWR), Geographical Detector (GD) were utilized investigate interactions between (land cover factors, environmental socio-economic factors) Surface Urban Heat Island Intensity (SUHII), maximizing explanation SUHII all Three main findings emerged: First, exhibited significant heterogeneity, with non-linear relationship SUHII. Second, SUHI displayed core-periphery pattern, Large lowrise (LCZ 8) compact 3) areas showing highest levels core zones. Third, land emerged influential metropolis. These results indicate that exhibit notable varying negative can be leveraged mitigate locations. Such offer crucial insights future policy-making.

Язык: Английский

Analytical study of land surface temperature for evaluation of UHI and UHS in the city of Chandigarh India DOI
Ajay Kumar Taloor, Gurnam Parsad,

S Jabeen

и другие.

Remote Sensing Applications Society and Environment, Год журнала: 2024, Номер 35, С. 101206 - 101206

Опубликована: Апрель 25, 2024

Язык: Английский

Процитировано

13
Urban heat dynamics in local climate zones (LCZs): A Systematic review DOI Creative Commons

Noor Rahman Rahmani,

Ayyoob Sharifi

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

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

12
Spatiotemporal Analysis of Land Surface Temperature in Response to Land Use and Land Cover Changes: A Remote Sensing Approach DOI Creative Commons
Gulam Mohiuddin, Jan–Peter Mund

Remote Sensing, Год журнала: 2024, Номер 16(7), С. 1286 - 1286

Опубликована: Апрель 5, 2024

Rapid urbanisation in the global south has often introduced substantial and rapid uncontrolled Land Use Cover (LULC) changes, considerably affecting Surface Temperature (LST) patterns. Understanding relationship between LULC changes LST is essential to mitigate such effects, considering urban heat island (UHI). This study aims elucidate spatiotemporal variations alterations of areas compared changes. The focused on a peripheral area Phnom Penh (Cambodia) undergoing development. Using Landsat images from 2000 2021, analysis employed an exploratory time-series LST. revealed noticeable variability (20 69 °C), which was predominantly influenced by seasonal also provided insights into how varies within different at exact spatial locations. These did not manifest uniformly but displayed site-specific responses accounts for changing land surfaces’ complex physical energy interaction over time. methodology offers replicable model other similarly structured, rapidly urbanised regions utilising novel semi-automatic processing images, potentially inspiring future research various planning monitoring contexts.

Язык: Английский

Процитировано

11
Spatiotemporal analysis of surface Urban Heat Island intensity and the role of vegetation in six major Pakistani cities DOI Creative Commons
Shoaib Ahmad Anees, Kaleem Mehmood, S. K. Raza

и другие.

Ecological Informatics, Год журнала: 2024, Номер unknown, С. 102986 - 102986

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

8
Heterogeneous effects of the availability and spatial configuration of urban green spaces on their cooling effects in China DOI Creative Commons

Qianyuan Huang,

Chao Xu, Dagmar Haase

и другие.

Environment International, Год журнала: 2023, Номер 183, С. 108385 - 108385

Опубликована: Дек. 12, 2023

The impacts of the availability and spatial configuration urban green spaces (UGS) on their cooling effects can vary with background climate conditions. However, large-scale studies that assess potential heterogeneous relationships UGS thermal environment are still lacking. In this study, we investigated land surface temperature (LST) taking 306 cities in China as a case study covering multi-biome-scale. We first calculated surrounding for built-up pixels each city using distance-weighted approach, its was quantified through Gini coefficient. Then, employed various regression models to explore how coefficient LST varies across different quantiles between day- nighttime. results revealed negatively associated both daytime nighttime LST, while showed positive impact solely indicating an adequate equally distributed contributes lower environmental temperatures during daytime. Furthermore, decreased increased quantiles. Whereas only quantile levels, effect remaining almost insignificant night. Our findings provide new insights into environment, offering significant implications infrastructure planning aiming at lowering heat island.

Язык: Английский

Процитировано

12
Modeling urban air temperature using satellite-derived surface temperature, meteorological data, and local climate zone pattern—a case study in Szeged, Hungary DOI Creative Commons
Yuchen Guo, János Unger,

Almaskhan Khabibolla

и другие.

Theoretical and Applied Climatology, Год журнала: 2024, Номер 155(5), С. 3841 - 3859

Опубликована: Фев. 5, 2024

Abstract Urban air temperature is a crucial variable for many urban issues. However, the availability of often limited due to deficiency meteorological stations, especially in areas with heterogeneous land cover. Many studies have developed different methods estimate temperature. variables and local climate zone (LCZ) been less used this topic. Our study new method canopy layer during clear sky days by integrating surface (LST) from MODIS, based on reanalysis data, LCZ data Szeged, Hungary. Random forest algorithms were developing estimation model. We focused four seasons distinguished between daytime nighttime situations. The cross-validation results showed that our can effectively temperature, average root mean square error (RMSE) 0.5 ℃ ( R 2 = 0.99) 0.9 0.95), respectively. test dataset 2018 2019 indicated optimal model selected had best performance summer, time-synchronous RMSE 2.1 0.6, daytime) 2.2 0.86, nighttime) seasonal 1.5 0.34, 1.2 0.74, nighttime). In addition, we found was more important at night, while contributed daytime, which revealed temporal mechanisms effect these two estimation. provides novel reliable tool explore thermal environment researchers.

Язык: Английский

Процитировано

5
Investigating the cooling effects of land cover and landscape patterns surrounding rivers: Insights from the subtropical city of Changsha, China DOI

Jie Tan,

Wenjun Kuang,

De Yu

и другие.

Urban Climate, Год журнала: 2024, Номер 55, С. 101975 - 101975

Опубликована: Май 1, 2024

Язык: Английский

Процитировано

5
Detecting the air-cooling effect of urban green spaces in a hot climate town relative to land surface temperature on Landsat-9 thermal imagery DOI

C. Munyati

Advances in Space Research, Год журнала: 2024, Номер 74(10), С. 4598 - 4615

Опубликована: Июль 14, 2024

Язык: Английский

Процитировано

5
A cross-scale indicator framework for the study of annual stability of land surface temperature in different land uses DOI
Shuyang Zhang, Chao Yuan, Taihan Chen

и другие.

Sustainable Cities and Society, Год журнала: 2024, Номер unknown, С. 105936 - 105936

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

5
Research on the Spatial-Temporal Evolution of Changsha’s Surface Urban Heat Island from the Perspective of Local Climate Zones DOI Creative Commons

Yanfen Xiang,

Bohong Zheng,

Ji-ren Wang

и другие.

Land, Год журнала: 2024, Номер 13(9), С. 1479 - 1479

Опубликована: Сен. 12, 2024

Optimizing urban spatial morphology is one of the most effective methods for improving thermal environment. Some studies have used local climate zones (LCZ) classification system to examine relationship between and Surface Urban Heat Islands (SUHIs). However, these often rely on single-time-point data, failing consider changes in space time-series LCZ mapping relationships. This study utilized remote sensing data from Landsat 5, 7, 8–9 retrieve land surface temperatures Changsha 2005 2020 using Mono-Window Algorithm. The spatial-temporal evolution Island Intensity (SUHII) was then examined analyzed. aims (1) propose a localized, long-time method, (2) investigate SUHII, (3) develop more convenient SUHI assessment method planning design. results showed that reflects sequence expansion. In terms quantity, number built-type LCZs maintaining their original types low, with each undergoing at least type change. open increased most, followed by sparse composite LCZs. Spatially, experience reverse transitions due expansion quality improvements central areas. Seasonal vary, differences not only among but also building heights within same type. relative importance parameters differs seasons. model constructed Boosted Regression Trees (BRT) demonstrated high predictive accuracy, R2 values 0.911 summer 0.777 winter. practical case validation, explained 97.86% 96.77% provides evidence-based recommendations mitigate heat create comfortable built

Язык: Английский

Процитировано

3