Sustainable Cities and Society最新文献

{"title":"Urban cold stress assessment using computational fluid dynamics and universal thermal climate index: A case study of Gwacheon City, South Korea","authors":"Jaekyoung Kim ,&nbsp;Samuel Park ,&nbsp;Seungkwon Jung ,&nbsp;Gunwon Lee","doi":"10.1016/j.scs.2025.106830","DOIUrl":"10.1016/j.scs.2025.106830","url":null,"abstract":"<div><div>This study presents a detailed computational framework to assess outdoor cold stress in urban environments. Considering the increasing climate uncertainty, the frequency and severity of cold-related hazards are projected to increase, particularly in dense urban areas, where the morphology and surface properties exacerbate thermal discomfort. Yet, research on cold stress remains limited compared with heat-related studies. To address this gap, we conducted transient Computational Fluid Dynamics (CFD) simulations across 54 parametric scenarios by varying the radiative properties (emissivity, reflectivity, and transmissivity) of typical urban surface materials, and assessed the pedestrian-level thermal comfort under extremely cold conditions using the Universal Thermal Climate Index (UTCI). The simulation outputs were validated against real-time meteorological observations collected from three urban monitoring stations in Gwacheon, South Korea. Scenario 14, which featured a concrete <span><math><mrow><mi>ε</mi></mrow></math></span> of 0.4 and reflectivity of 0.6, building exterior transmissivity of 0.7, and asphalt <span><math><mrow><mi>ε</mi></mrow></math></span> of 0.7, most accurately replicated the observed temperature patterns (R² &gt; 0.85 across all stations). Spatial UTCI mapping revealed that approximately 886,519 m² experienced strong cold stress (UTCI &lt; –10 °C) at 9:00 on February 8, 2025, particularly in high-rise residential clusters and exposed green zones. These findings highlight the role of surface material configuration and urban form in cold stress distribution. The proposed method offers a robust and physiologically grounded tool for guiding winter climate adaptation strategies in urban planning and design.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106830"},"PeriodicalIF":12.0,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deciphering the spatiotemporal dynamics and driving mechanisms of carbon emissions in China's Greater Bay area: Insights from interpretable machine learning","authors":"Tong Zhang ,&nbsp;Dong Ding ,&nbsp;Guoyang Wang","doi":"10.1016/j.scs.2025.106840","DOIUrl":"10.1016/j.scs.2025.106840","url":null,"abstract":"<div><div>The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) ranks among the four most prominent bay areas globally. Despite comprising less than 0.6% of China`s land area, the GBA generates over 10% of the nation`s economic output. Analyzing the spatiotemporal dynamics of carbon emission (CE) and their drivers is crucial for achieving “dual-carbon” targets and facilitating a green, low-carbon transition in global bay area economies. An XGBoost model, incorporating nighttime light data (NTL) , land surface temperature (LST) , population, and GDP, reconstructs energy-related CE evolution. Spatiotemporal CE dynamics within the GBA were elucidated through multi-dimensional spatial analysis. An XGBoost-SHAP model developed to identify key drivers, revealing nonlinear and interactive effects to inform optimization strategies. The findings show that ((1) Emissions exhibited a two-stage growth pattern: rapid expansion followed by stabilization. (2) Spatially, emissions shifted from a “three-core” model to a “multi-core” model. (3) Spatial agglomeration and heterogeneity coexisted, with a “high-center, low-periphery” distribution. (4) Municipal CE patterns demonstrated significant path dependence and lock-in, though this inertia gradually decreased, accompanied by increased spillover effects from high-emission areas. (5) Population, economic development, and urbanization were primary CE drivers, transitioning from scale-driven to quality-dominated growth. This study elucidates the complex dynamics of circular economy (CE) in rapidly developing regions, such as the GBA, supporting “dual-carbon” goals and sustainable development.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106840"},"PeriodicalIF":12.0,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applicability of thermoregulation-sensation models and machine learning modelling to simulate dynamic physio-psychological thermal responses during walking in urban continuum","authors":"Jianong Li ,&nbsp;Jianlei Niu ,&nbsp;Cheuk Ming Mak","doi":"10.1016/j.scs.2025.106829","DOIUrl":"10.1016/j.scs.2025.106829","url":null,"abstract":"<div><div>Walkability is an important attribute of a liveable city, and in this era with frequent heat waves the thermal comfort of walking pedestrians can be essential for the microclimate design of walking routes. Upon field tests conducted during summer in urban continuum in Hong Kong, this study examined the applicability of thermoregulation models, including the Gagge 2-node model and multi-node-segment JOS3 model, both of which are updated with a newly obtained convective heat transfer coefficient, for the accurate evaluation of the dynamic physio-psychological responses of walking pedestrians in the urban continuum. Fiala dynamic thermal sensation (DTS) model was assessed for its effectiveness in simulating transient thermal sensations during walking. Moreover, the study utilised the random forest (RF), a machine learning algorithm, to model transient thermal sensations and average thermal acceptance during walking and resting in the urban continuum. The results indicate that the 2-node model, the JOS3 model, and the human body differ in key determinants of mean skin temperature, and the Fiala DTS model underestimates the impacts of skin temperature change rate and thermal pleasure on transient thermal sensations. Body mass index (BMI) is an important factor affecting the dynamic physio-psychological responses, which is not well considered in any of the three models. The developed RF models exhibit high accuracy in simulating dynamic physio-psychological thermal responses and overall thermal acceptance over a period of time.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106829"},"PeriodicalIF":12.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic urban flood risk assessment based on human activity patterns: An IFAHP-EWM-TOPSIS approach","authors":"Weijie He ,&nbsp;Jian Zeng ,&nbsp;Jiahao Zhang ,&nbsp;Aihemaiti Namaiti ,&nbsp;Weihao Shi ,&nbsp;Yuanzhen Song ,&nbsp;Jian Tian","doi":"10.1016/j.scs.2025.106832","DOIUrl":"10.1016/j.scs.2025.106832","url":null,"abstract":"<div><div>Global climate change and accelerated urbanization have significantly increased the frequency and intensity of urban flooding, posing serious threats to urban safety and sustainable development. Traditional flood risk assessments mainly focus on static environmental and infrastructural conditions, often neglecting the dynamic spatiotemporal impacts of human activities. To address this critical gap, this study innovatively integrates dynamic human activity patterns into a traditional flood risk assessment framework, emphasizing the differences between weekdays and weekends. A dynamic flood risk assessment framework was developed, using Nanchang, China, as a case study. Multi-source data were used to identify urban functional zones, and a system of 13 indicators across hazard, exposure, and vulnerability dimensions was constructed. Hazard indicators were derived from an integrated 1D–2D hydrodynamic flood model, while exposure and vulnerability indicators were explicitly linked to human activity patterns. Subjective weights were calculated using the IFAHP method and combined with objective weights from the EWM method. The TOPSIS method was then applied to assess dynamic flood risk. Results show peak risk at midday on weekdays, while weekends exhibit peaks at both midday and late night, with greater variability. Spatially, high-risk zones are concentrated in densely populated, water-adjacent old urban areas. Significant flood risk variations exist among functional zones, with the Business and Office Zone and the Scientific, Educational, and Cultural Services Zone showing the most pronounced intraday fluctuations, while the Industrial and Warehouse Zone and the Green Spaces and Squares Zone exhibit relatively stable risk profiles. This integration of dynamic human activity data represents a substantial advancement over traditional approaches, providing a novel perspective and methodological framework for dynamic urban flood risk assessment and contributing to more refined and adaptive flood management strategies.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106832"},"PeriodicalIF":12.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An integrated framework for assessing solar photovoltaic potential of building surfaces at city scale using parametric simulation and optimized machine learning models","authors":"Fuming Lei ,&nbsp;Zengfeng Yan ,&nbsp;Pingan Ni ,&nbsp;Yingjun Yue ,&nbsp;Shanshan Yao ,&nbsp;Jingpeng Fu ,&nbsp;Liuhui Meng ,&nbsp;Guojin Qin","doi":"10.1016/j.scs.2025.106836","DOIUrl":"10.1016/j.scs.2025.106836","url":null,"abstract":"<div><div>Efficient utilization of building-integrated photovoltaics is an important pathway for achieving sustainable urban development. However, existing methods for assessing solar photovoltaic potential of large urban building surfaces suffer from issues such as coarse modeling, low prediction accuracy, and incomplete assessments. To address these challenges, this study proposes a novel solar photovoltaic potential assessment method for large cities, which builds a high-accuracy NSGA-II-ANN predictive model using Ladybug Tools and Machine Learning techniques to predict and optimize photovoltaic panel parameters. Taking Xi'an, China, as an example, the study calculates and evaluates solar photovoltaic potential of building surfaces from multiple dimensions. The main findings are as follows: (1) The solar photovoltaic potential of building surfaces in Xi'an is significant, with all roof shading rates below 15 %, and the average solar radiation intensity reaching 1020.42 kWh/m², offering great utilization value. (2) The NSGA-II-ANN predictive model constructed for photovoltaic panel parameters has R² values greater than 0.960, MSE values less than 0.04, and the loss curve demonstrates clear convergence characteristics. (3) After optimization, the maximum solar radiation potential of rooftop photovoltaic systems in Xi'an can reach 59.398 TWh, with 25.534 TWh in summer and 14.055 TWh in winter. (4) The maximum photovoltaic generation capacity for building surfaces in Xi'an ranges from 18.27 to 22.84 TWh, potentially meeting 46.88 % of the city's annual electricity demand or up to 175.99 % of residential electricity consumption. This research framework and findings provide a more practical assessment of solar photovoltaic potential in large cities, offering recommendations and strategies for urban photovoltaic utilization.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106836"},"PeriodicalIF":12.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Building form optimization for renewable energy-economic utility of flexible solar cells as building integrated photovoltaics","authors":"Jitao Bai ,&nbsp;Zhonghao Chen ,&nbsp;Simiao Zhang ,&nbsp;Jiahe Liang","doi":"10.1016/j.scs.2025.106819","DOIUrl":"10.1016/j.scs.2025.106819","url":null,"abstract":"<div><div>Buildings are responsible for considerable amounts of global energy consumption, and promoting renewable energy in buildings is conducive to sustainable development of modern society. In this paper, flexible solar cells (FSCs) were proposed to be used as building integrated photovoltaics (BIPVs) on free-form building surfaces, and the building form was optimized so that the renewable energy utility (REU) and economic utility (ECU) of FSCs could be enhanced. Both the REU and ECU were characterized by solar radiation calculated from a previously proposed analytical model, and the building geometry was controlled through control node method. A penalty strategy-based constrained differential evolution (PS-CDE) algorithm was developed for building form optimization, which was conducted in four cities at different latitude and climate zones. Results demonstrate that PS-CDE is effective. Both the building forms with maximum REU and minimum ECU show a frustum-of-cone geometry, while those with minimum REU and maximum ECU can be well described with a hyperbolic model. For a given height-radius ratio, the optimal building forms under the same objective are parallel, with the ECU remaining constant and REU proportional to the square of the height ratio. As the height-radius ratio increases, the maximum REU increases linearly, while the maximum ECU decreases in a hyperbolic mode. The optimal building form for REU-ECU trade-off is roughly consistent with that of the dominant objective, suggesting amplitude-variation of REU and ECU across the design domain. Based on the findings, an empirical framework was established for efficient FSC-oriented building form design, which exhibits good robustness (0.2 % ∼ 0.6 % for discretization-related error) and reliability (around 10 % difference in simulation validation). The study is expected to offer a systematic approach for building form design with enhanced performance of the next-generation FSC-based BIPVs.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"133 ","pages":"Article 106819"},"PeriodicalIF":12.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Socio-demographic disparities of heat exposure in affluent, aging, and diverse Swiss society","authors":"Yuyang Chang ,&nbsp;Gabriele Manoli ,&nbsp;Jaboury Ghazoul ,&nbsp;Fritz Kleinschroth","doi":"10.1016/j.scs.2025.106813","DOIUrl":"10.1016/j.scs.2025.106813","url":null,"abstract":"<div><div>As climate change intensifies, disparities in people’s heat exposure are emerging as a critical public health concern, including in wealthy countries like Switzerland. This study investigates spatial and socio-demographic differences in outdoor heat exposure across 1625 Swiss municipalities, using satellite data and predicted air temperature data within a multi-dimensional heat exposure framework encompassing a composite heat exposure index (CHEI) combining heat intensity, heatwave duration, and historical heatwave probability. Using stepwise weighted least squares (WLS) regression models, we first model socio-demographic predictors, then add topography, and finally incorporate urban-form variables to assess heat exposure disparities associated with economic status, age structure, immigration background, social assistance, and living conditions. We further use geographically weighted regression (GWR) to capture spatial heterogeneity and classify municipalities as overexposed, underexposed, or showing no significant disparity. Our findings reveal that high-income municipalities tend to experience higher heat exposure. At the same time, municipalities with larger shares of non-EU foreigners and residents receiving social assistance are also more exposed than others, underscoring the intersection of heat risk with socially marginalized and affluent communities in larger cities. Yet many of these associations weaken after controlling for elevation and urbanization, highlighting the critical role of physical geography in the Swiss context. For age structure, regression models suggest weak or negative associations between elderly concentration and heat exposure after accounting for physical factors; however, quartile analyses reveal that municipalities with higher shares of residents aged over 80 still face higher exposure in certain regions. Our findings emphasize the need to address socio-demographic heat disparities in affluent societies with diverse population structures, large aging population, where topography and degree of urbanisation can amplify local heat burdens. Integrating social vulnerability with geographic and morphological drivers is therefore essential for designing targeted adaptation measures and reducing unequal heat risks.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"132 ","pages":"Article 106813"},"PeriodicalIF":12.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of clean heating on urban climate risk: Empirical analysis with double machine learning method","authors":"Kai Chen ,&nbsp;Yutian Xu ,&nbsp;Peilin Chen","doi":"10.1016/j.scs.2025.106822","DOIUrl":"10.1016/j.scs.2025.106822","url":null,"abstract":"<div><div>The effective management of urban climate risks is a pressing challenge for China and the global community, and the Plan for Cleaner Winter Heating in the Northern Region (NCH) is expected to play a pivotal role in addressing it. Against this background, based on panel data of 285 Chinese cities from 2011 to 2022, this research uses a double machine learning (DML) model to examine the impacts and action mechanisms of the NCH policy on urban climate risk levels. The findings indicate that: (1) The NCH policy significantly reduces urban climate risk levels, and this conclusion holds under multiple robustness tests. (2) The NCH policy reduces urban climate risk levels by promoting enterprise green technological innovation, increasing government environmental regulation, and enhancing public environmental concern. (3) The impacts of the NCH policy on urban climate risk levels exhibit significant heterogeneity. The policy is effective in old industrial base cities, non-resource-based cities, coastal cities, and cities with lower implementation challenges. These findings provide a scientific basis for enhancing the implementation of the NCH policy and reducing urban climate risk levels.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"132 ","pages":"Article 106822"},"PeriodicalIF":12.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging or dividing? The Matthew effect of climate-resilient built environments on community walkability in cold cities","authors":"Shiwei Yu ,&nbsp;Jianfei Chen ,&nbsp;Gong Jue ,&nbsp;Liu Jingyi ,&nbsp;Wang Jiaqi","doi":"10.1016/j.scs.2025.106824","DOIUrl":"10.1016/j.scs.2025.106824","url":null,"abstract":"<div><div>Climate-resilient built environments are vital for promoting walkability in cold cities, which face challenges from seasonal variations. This study develops a comprehensive framework integrating multi-source data and advanced modeling to investigate the nonlinear and spatially heterogeneous relationships between the built environment and community walkability (CW) in Harbin, China. Key findings reveal: (1) CW exhibits strong and significant spatial clustering (Global Moran’s <em>I</em> &gt; 0.6, <em>p</em> &lt; 0.001), with the aggregation intensity markedly stronger in winter, confirming a pronounced “Matthew Effect”exacerbated by cold conditions; (2) factors influencing CW exhibit significant seasonal and spatial specificity, with density-related elements like road and population density remaining consistently important yet exhibiting threshold effects; (3) nonlinear thresholds were identified—for instance, population density beyond 13,000 people/km² and subway station distance exceeding 0.8 km negatively impact winter walkability; (4) complex interaction effects are critical, revealing synergistic effects between land-use mix and road density in core areas, and antagonistic effects between high population density and poor transit accessibility; (5) most importantly, the drivers of walkability follow a distinct core-periphery divergence: urban core areas are primarily driven by macro-level factors (e.g., metro accessibility, green space), whereas peripheral areas are more sensitive to micro-level community design (e.g., internal greening, winter facilities), necessitating diametrically opposed planning interventions. This research translates these spatial patterns and nonlinear mechanisms into actionable, evidence-based strategies for targeted planning to enhance climate resilience and spatial equity in cold-climate cities.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"132 ","pages":"Article 106824"},"PeriodicalIF":12.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145119132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term dynamics of urban heat island and hot spots in Wrocław: A 25-year satellite-based analysis using machine learning","authors":"Melika Tasan ,&nbsp;Jolanta Dąbrowska ,&nbsp;Krystyna Michałowska ,&nbsp;Anna Uciechowska-Grakowicz","doi":"10.1016/j.scs.2025.106797","DOIUrl":"10.1016/j.scs.2025.106797","url":null,"abstract":"<div><div>Urban areas are increasingly vulnerable to rising temperatures due to rapid land cover transformation, which intensifies the Urban Heat Island (UHI) effect, promotes the emergence of thermal hot spots, and contributes to growing thermal discomfort. Understanding long-term urban thermal dynamics is crucial for climate-responsive urban planning. While many existing studies rely on short-term analyses, single-source thermal indicators, and a single Land Use/Land Cover (LULC) classification method, this study offers a 25-year assessment (1999–2023) of UHI patterns and thermal hot spots in Wrocław, one of Poland’s largest and most urbanized cities, using an optimal LULC classification technique and an integrated composite thermal index. Landsat satellite imagery was used to derive LULC classifications and Land Surface Temperature (LST) maps. To ensure classification accuracy, four methods were evaluated: Maximum Likelihood (MaxL), Minimum Distance (MD), Support Vector Machine (SVM), and Artificial Neural Network (ANN), with ANN yielding the highest performance. A key innovation of this study is the integration of UHI and Urban Thermal Field Variance Index (UTFVI) maps to generate composite thermal stress maps, which reveal more nuanced spatial patterns of urban heat exposure than single-indicator approaches. Results indicate that 32.9% of the number of identified thermal hot spots emerged after 2010, 21.7% disappeared, and 45.4% remained stable throughout the study period. These findings underscore the critical influence of LULC changes on urban thermal environments and provide valuable insights for sustainable urban development and environmental policy-making.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"132 ","pages":"Article 106797"},"PeriodicalIF":12.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}