Computers Environment and Urban Systems最新文献

An agent-based model for estimating daily face-to-face contact networks in large urban systems 基于智能体的大型城市系统日常面对面接触网络估计模型

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-07-17 DOI: 10.1016/j.compenvurbsys.2025.102321

Ismaïl Saadi , Etienne Côme , Liem Binh Luong Nguyen , Mahdi Zargayouna

{"title":"An agent-based model for estimating daily face-to-face contact networks in large urban systems","authors":"Ismaïl Saadi , Etienne Côme , Liem Binh Luong Nguyen , Mahdi Zargayouna","doi":"10.1016/j.compenvurbsys.2025.102321","DOIUrl":"10.1016/j.compenvurbsys.2025.102321","url":null,"abstract":"<div><div>Detailed contact data is important to model disease transmission in dense urban areas, as human mobility and social interactions significantly impact spread. However, linking mobility, activities, and social contacts in large cities is challenging. Current models often rely on contact surveys and overlook travel behaviors. Here we present a novel modeling framework for estimating large-scale, multi-setting contact networks by leveraging high-resolution synthetic activity-travel data. Our approach introduces a new mathematical formalism to construct multi-setting contact networks from spatiotemporal co-location patterns, enabling constraints based on key statistics (e.g., contact rates per setting, proportions of each contact type), incorporation of location types, and individual activity purposes. Efficient algorithms extract co-presence events, generating validated, individual-based contact networks, from which age-specific contact matrices are derived. The approach is tested using EQASIM, an open and reproducible activity-based travel demand model that relies on publicly available data for France’s Île-de-France region. We also evaluated the spatial effects of work-from-home policies on contact patterns by modifying individuals’ activity-travel diaries. Results show that multi-setting contact networks — representing 12 million individuals distributed across 1,714,920 unique locations — can be generated in minutes while accurately reproducing setting- and age-specific spatial contact patterns.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102321"},"PeriodicalIF":7.1,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144653395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling spatial and temporal urban environmental noise using street view imagery and machine learning 利用街景图像和机器学习建模时空城市环境噪声

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-07-11 DOI: 10.1016/j.compenvurbsys.2025.102327

Devin Yongzhao Wu , Jue Wang

{"title":"Modeling spatial and temporal urban environmental noise using street view imagery and machine learning","authors":"Devin Yongzhao Wu , Jue Wang","doi":"10.1016/j.compenvurbsys.2025.102327","DOIUrl":"10.1016/j.compenvurbsys.2025.102327","url":null,"abstract":"<div><div>This study proposes a framework for modeling environmental noise pollution by integrating land use regression (LUR) with machine learning models and street built environments. Using noise data collected from 128 locations over nine consecutive days in Mississauga, Ontario, Canada, the research demonstrates that incorporating finer-scale street built environment features derived from street view images significantly improves noise prediction accuracy. The model using XGBoost and street view-derived variables significantly outperforms traditional LUR-based models. The results indicate that street-level characteristics, particularly terrain, play a critical role in modeling noise levels, complementing traditional land use and NDVI-based greenness. Furthermore, the research highlights the importance of using non-linear models like XGBoost to capture complex relationships between noise and urban features. This approach offers valuable insights for advancing environmental noise modeling, which further supports future public health studies investigating the impact of noise exposure on population health.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102327"},"PeriodicalIF":7.1,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144595513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Housing segregation in Chinese major cities: A K-nearest neighbor analysis of longitudinal big data 中国主要城市的住房隔离：纵向大数据的k近邻分析

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-07-01 DOI: 10.1016/j.compenvurbsys.2025.102326

Sebastian Kohl , Bo Li , Can Cui

{"title":"Housing segregation in Chinese major cities: A K-nearest neighbor analysis of longitudinal big data","authors":"Sebastian Kohl , Bo Li , Can Cui","doi":"10.1016/j.compenvurbsys.2025.102326","DOIUrl":"10.1016/j.compenvurbsys.2025.102326","url":null,"abstract":"<div><div>Most studies on residential segregation in China have primarily relied on decennial population census data, which lacks the granularity and timeliness needed to capture segregation dynamics with higher frequency. Drawing on georeferenced housing market transaction data between 2012 and 2023 in Shanghai and Beijing, and employing fine-grained spatial segregation analysis techniques, including k-nearest neighbor approaches (<em>k</em>−NN) and modifiable grids, we find that housing segregation by price and size increased between 2012 and 2018, followed by a decline thereafter, particularly in the larger-sized and higher-priced market segments. While segregation levels are generally comparable between the two cities, Shanghai exhibits higher segregation for the top 20 % of apartments, while Beijing shows greater segregation for the bottom 20 %. Segregation is highest for prices, followed by rents, with housing size showing the lowest segregation. Expanding the analysis to 11 major Chinese cities, we suggest that high and rising housing prices are associated with increasing segregation, particularly in cities with lower initial segregation. Methodologically, this paper demonstrates that leveraging big transaction and listing data, alongside utilizing fine-grained spatial analysis, can advance our understanding of urban inequalities.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102326"},"PeriodicalIF":7.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144522231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Social areas revisited through the lens of mobility: A comparative study of the traditional and mobility approaches 通过流动性视角重新审视社会领域：传统方法与流动性方法的比较研究

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-06-29 DOI: 10.1016/j.compenvurbsys.2025.102325

Run Shi , Anthony Gar-On Yeh , Fang Bian

{"title":"Social areas revisited through the lens of mobility: A comparative study of the traditional and mobility approaches","authors":"Run Shi , Anthony Gar-On Yeh , Fang Bian","doi":"10.1016/j.compenvurbsys.2025.102325","DOIUrl":"10.1016/j.compenvurbsys.2025.102325","url":null,"abstract":"<div><div>Social area analysis is a framework for understanding residential social structure as a product of urbanization and economic development. Building on our previous findings that socioeconomically similar residents exhibit different mobility patterns, this study examines urban socio-spatial structure by incorporating commuting patterns from mobile phone data with census in Shenzhen, China. We conduct a comparative analysis to explore differences between the traditional and mobility approaches. Principal Component Analysis (PCA) results reveal that mobility is an essential dimension of socio-spatial differentiation at the aggregated neighborhood committee level. The derived residential social structure explicitly highlights mobility disparities, providing evidence for possible segregation and potential improvements in urban planning. By analyzing the interplays of economic, political, and social forces, we conceptualize mobility as a sub-dimension of social space. The contribution of this study lies in two folds. First, we propose a framework for integrating mobile phone data with census data to capture mobility disparities at the aggregated level with the concept of activity space. Second, we explore the role of mobility in delineating urban socio-spatial structure, providing a novel perspective for examining the internal spatial structure of cities.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102325"},"PeriodicalIF":7.1,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144510637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing transparency in land use change modeling: Leveraging eXplainable AI techniques for urban growth prediction with spatially distributed insights 提高土地利用变化建模的透明度：利用可解释的人工智能技术进行具有空间分布洞察力的城市增长预测

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-06-28 DOI: 10.1016/j.compenvurbsys.2025.102322

Zelin Wang , Tianshu Feng , Abolfazl Safikhani , Emre Tepe

{"title":"Enhancing transparency in land use change modeling: Leveraging eXplainable AI techniques for urban growth prediction with spatially distributed insights","authors":"Zelin Wang , Tianshu Feng , Abolfazl Safikhani , Emre Tepe","doi":"10.1016/j.compenvurbsys.2025.102322","DOIUrl":"10.1016/j.compenvurbsys.2025.102322","url":null,"abstract":"<div><div>Recent applications of machine learning (ML) and deep learning (DL) techniques in land-use change modeling have demonstrated significant success in capturing the intricate dynamics of land development. However, their “black-box” nature restricts their utility in various contexts, such as uncovering the underlying drivers of urban expansion. To mitigate this issue, we propose to utilize eXplainable AI (XAI) techniques in ML/DL methods, which presents a promising solution to this primary constraint. To that end, we introduce DL methods to investigate and predict the non-linear dynamics of land use changes. These methods achieved notably high accuracy scores and were more computationally viable than traditional statistical approaches. Moreover, the proposed approach employed in this study surpassed the parameter interpretation capabilities of statistical methods. More specifically, the proposed XAI approach not only highlights the average effects of features on the outcome but also elucidates the factors influencing specific decisions regarding land use changes, including the number of vacant parcels, the share of single-family parcels, and certain time-lagged neighborhood features. Such analyses provide invaluable insights for researchers, practitioners, and policymakers.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102322"},"PeriodicalIF":7.1,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mapping multidimensional energy deprivation: Socio-spatial inequalities and policy implications in Great Britain 映射多维能源剥夺：社会空间不平等和政策影响在英国

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-06-28 DOI: 10.1016/j.compenvurbsys.2025.102324

Meixu Chen , Caitlin Robinson , Alex Singleton

{"title":"Mapping multidimensional energy deprivation: Socio-spatial inequalities and policy implications in Great Britain","authors":"Meixu Chen , Caitlin Robinson , Alex Singleton","doi":"10.1016/j.compenvurbsys.2025.102324","DOIUrl":"10.1016/j.compenvurbsys.2025.102324","url":null,"abstract":"<div><div>This work provides a thorough Energy Deprivation Segmentation (EDS) for Great Britain, which aims to address the complex and varied aspects of energy poverty in different small regions. By proposing a reproducible analytical framework, we combine many data sources to provide a comprehensive segmentation that encompasses various dimensions such as energy efficiency, accessibility, demand and supply, housing conditions, and financial vulnerability. The results indicate notable disparities in energy deprivation based on social and spatial factors. We observed higher degrees of deprivation in the peripheral areas of major cities and suburbs in the northern regions of England, southern regions of Wales, and central regions of Scotland. The created EDS identifies six top-level Supergroups and 14 finer Groups and was validated internally and externally to confirm its robustness and applicability. This segmentation offers a more comprehensive insights into the characteristics and distribution of energy-deprived neighbourhoods than traditional measures. This research facilitates policymakers to design targeted strategies and resource allocation to combat specific vulnerabilities within communities and foster sustainable and equitable urban growth. Additionally, a practical tool is provided for monitoring and evaluating the effectiveness of policies aimed at reducing energy poverty.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102324"},"PeriodicalIF":7.1,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Renewable energy adoption in urban residential communities in China: An agent-based model for assessing intervention impact 中国城市居民社区采用可再生能源：基于主体的干预影响评估模型

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-06-19 DOI: 10.1016/j.compenvurbsys.2025.102323

Hua Du , Qi Han , Bauke de Vries , Jun Sun

{"title":"Renewable energy adoption in urban residential communities in China: An agent-based model for assessing intervention impact","authors":"Hua Du , Qi Han , Bauke de Vries , Jun Sun","doi":"10.1016/j.compenvurbsys.2025.102323","DOIUrl":"10.1016/j.compenvurbsys.2025.102323","url":null,"abstract":"<div><div>Designing effective policy interventions is an essential instrument to promote the widespread adoption of photovoltaic (PV) systems in the residential sector. Designing such policies and evaluating their effectiveness requires an approach that allows for simulation in the complex system setting of the built environment. In this study we applied Agent-Based Modelling to evaluate the effectiveness of two policies (i.e., information campaign and demonstration projects) and two community factors (i.e., community size and required agreement rate) to promote the adoption of residential community PV diffusion in Chinese cities. This model is developed based on the empirical results of a previous discrete choice experiment. The results show that lowering the required agreement rate for community decisions contributes to an increase in PV adoption, while community size has little impact on adoption diffusion. We found that combining the two policy interventions or combining them with a community factor (i.e., lowering the required agreement rate) can effectively promote the adoption of community PV. Policy intervention implications and suggestions are presented.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102323"},"PeriodicalIF":7.1,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144312561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Measuring nuanced walkability: Leveraging ChatGPT's vision reasoning with multisource spatial data 测量细微差别的步行性：利用ChatGPT的视觉推理与多源空间数据

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-06-18 DOI: 10.1016/j.compenvurbsys.2025.102319

Donghwan Ki , Hojun Lee , Keundeok Park , Jaehyun Ha , Sugie Lee

{"title":"Measuring nuanced walkability: Leveraging ChatGPT's vision reasoning with multisource spatial data","authors":"Donghwan Ki , Hojun Lee , Keundeok Park , Jaehyun Ha , Sugie Lee","doi":"10.1016/j.compenvurbsys.2025.102319","DOIUrl":"10.1016/j.compenvurbsys.2025.102319","url":null,"abstract":"<div><div>Recent advances in urban analytical tools, particularly street view image (SVI) data and computer vision (CV) algorithms, such as semantic segmentation, have enhanced walkability measurement by enabling the automated assessment of mesoscale features, such as greenery proportions. However, while SVI data contain rich environmental information, off-the-shelf CV models generally struggle to capture microscale features—design details attached to mesoscale elements, such as the quality of greenery or sidewalk maintenance. Moreover, because CV algorithms typically evaluate environmental features in isolation, they often fail to account for spatial arrangements and visual harmony among features, limiting their ability to support a holistic assessment of walkability. Recently, multimodal large language models (MLLMs), particularly ChatGPT, have introduced a transformative approach to image analysis by mimicking human perception. This study proposes a comprehensive walkability measurement framework that leverages ChatGPT's vision reasoning across multiple spatial data, including SVIs and GIS land use and road network maps. To validate this framework, we compare ChatGPT-generated walkability ratings with human assessments and examine their relationship with reported walking behavior data. Furthermore, by comparing ChatGPT-generated outcomes with evaluations from conventional walkability measurement tools, such as GIS and off-the-shelf CV models, we highlight the novel contribution of ChatGPT in walkability assessment. This research advances the literature by introducing a ChatGPT-based framework for a more comprehensive walkability assessment.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102319"},"PeriodicalIF":7.1,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Architecting urban epidemic defense: A hierarchical region-individual control framework for optimizing large-scale individual mobility interventions 构建城市流行病防御：优化大规模个人流动干预的分层区域-个人控制框架

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-06-14 DOI: 10.1016/j.compenvurbsys.2025.102312

Yuxiao Luo , Ling Yin , Kemin Zhu , Kang Liu

{"title":"Architecting urban epidemic defense: A hierarchical region-individual control framework for optimizing large-scale individual mobility interventions","authors":"Yuxiao Luo , Ling Yin , Kemin Zhu , Kang Liu","doi":"10.1016/j.compenvurbsys.2025.102312","DOIUrl":"10.1016/j.compenvurbsys.2025.102312","url":null,"abstract":"<div><div>In urban areas, high population density and extensive mobility can foster rapid transmission of emerging infectious diseases, particularly acute respiratory infections, which could lead to significant public health challenges and widespread social impact. EPidemic Control (EPC) strategies like mobility interventions tailored for each individual effectively mitigate these risks, balancing the safeguarding of public health with the socio-economic impacts. However, a large number of urban residents (e.g., millions) with complex spatiotemporal activities in modern cities pose a large-scale challenge of optimizing mobility interventions at an individual-level. To address this issue, this study introduces a framework of Hierarchical Region-Individual Control for Epidemic (Hi-RICE) to dynamically adapt specific interventions to large-scale individuals in complex urban epidemic scenarios with given control objectives. Hi-RICE initially assesses the dynamic infectious risk and contact risk for each individual according to their spatiotemporal behaviors. Subsequently, regional control agents, utilizing multi-agent reinforcement learning, optimize the appropriate intervention intensity for each region. Finally, specific mobility interventions are applied to high-risk individuals in each region according to their optimized control intensities. Utilizing Shenzhen, China, as a case of a megacity, simulations validate the proposed framework’s effectiveness and adaptability across various epidemic conditions, demonstrating its capacity to optimally balance epidemic control and socio-economic sustainability.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102312"},"PeriodicalIF":7.1,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144280291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing urban green space spatial patterns for thermal environment improvement: A multi-objective approach in the context of urban renewal 基于热环境改善的城市绿地空间格局优化：城市更新背景下的多目标方法

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-06-12 DOI: 10.1016/j.compenvurbsys.2025.102320

Liangguo Lin , Yaolong Zhao , Juchao Zhao

{"title":"Optimizing urban green space spatial patterns for thermal environment improvement: A multi-objective approach in the context of urban renewal","authors":"Liangguo Lin , Yaolong Zhao , Juchao Zhao","doi":"10.1016/j.compenvurbsys.2025.102320","DOIUrl":"10.1016/j.compenvurbsys.2025.102320","url":null,"abstract":"<div><div>The rapid and inevitable trend of urbanization has amplified urban thermal challenges, intensifying the urban heat island (UHI) effect. Given the constraints of limited urban land resources, optimizing the spatial patterns of urban green space (UGS) to maximize their cooling potential is essential for mitigating urban thermal environments and supporting effective urban renewal planning. This research integrates the XGBoost model with the NSGA-II algorithm to propose a multi-objective approach to optimize UGS spatial patterns for thermal environment improvement, using the central urban area of Guangzhou, China, as a case study in the context of urban renewal. To further assess the effectiveness of optimization, the Shapley additive explanation (SHAP) model was employed to examine how landscape pattern metrics, which characterize UGS spatial patterns, influence LST before and after optimization. The results demonstrate that optimized UGS spatial patterns, achieved through a controlled expansion of UGS area, significantly alleviated thermal stress by reducing the total LST by 2,799.82 °C and lowering its standard deviation by 0.04. Industrial zones, densely populated areas, and commercial districts exhibited the most pronounced LST reductions that spatially corresponded to changes in UGS spatial patterns. In addition, post-optimization analysis revealed notable changes in key landscape pattern metrics: patch cohesion index (COHESION), patch density (PD), landscape shape index (LSI), and percent of landscape (PLAND). Compared to pre-optimization conditions, their positive contributions to LST were weakened, while their cooling effects were enhanced. This research provides a “space-for-time” planning paradigm that offers intuitive and actionable decision-making support for urban renewal planners and policymakers.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102320"},"PeriodicalIF":7.1,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0