Computers Environment and Urban Systems最新文献_第4页

Maximum unobstructed shortest path between multipart-continuous geometries: Enabling novel type of access evaluations for urban safety 多部分连续几何之间的最大无障碍最短路径：为城市安全提供新型通道评估

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-06-03 DOI: 10.1016/j.compenvurbsys.2025.102308

Jiwon Baik, Alan T. Murray

{"title":"Maximum unobstructed shortest path between multipart-continuous geometries: Enabling novel type of access evaluations for urban safety","authors":"Jiwon Baik, Alan T. Murray","doi":"10.1016/j.compenvurbsys.2025.102308","DOIUrl":"10.1016/j.compenvurbsys.2025.102308","url":null,"abstract":"<div><div>In safety planning, preparing for worst-case scenarios is critical. For instance, fire stations are strategically located aiming to respond within four minutes in the worst-case. Similarly, hydrant-to-structure access adheres to this principle. Fire codes require that the furthest projection on a building's exterior must be within a specified distance from fire access roads via an unobstructed route. This ensures that all parts of a building are reachable by a fire hose from parked fire apparatus. This requirement involves a novel spatial optimization problem: the <em>Maximum Generalized Euclidean shortest path problem</em>. The Euclidean shortest path problem is an approach for determining an unobstructed shortest path, however, constrained to single-point representations for origin and destination. This research generalizes this problem to identify unobstructed paths between multipart-continuous geometries, such as road segments and building structures. A novel solution approach is also proposed, expanding the scope of access evaluation and advocating safety planning.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102308"},"PeriodicalIF":7.1,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195481","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

On the power of CNNs to detect slums in Brazil 关于cnn探测巴西贫民窟的力量

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-05-31 DOI: 10.1016/j.compenvurbsys.2025.102306

João P. da Silva , José F. Rodrigues-Jr , João P. de Albuquerque

{"title":"On the power of CNNs to detect slums in Brazil","authors":"João P. da Silva , José F. Rodrigues-Jr , João P. de Albuquerque","doi":"10.1016/j.compenvurbsys.2025.102306","DOIUrl":"10.1016/j.compenvurbsys.2025.102306","url":null,"abstract":"<div><div>The rapid expansion of slums poses a critical challenge for urban planning in Low- and Middle-Income Countries (LMICs), where traditional data collection methods like censuses are often outdated and insufficient. This study examines the transferability and generalization capabilities of deep learning models, specifically Convolutional Neural Networks (CNNs), for automated slum detection across six Brazilian cities with varying urban morphologies: São Paulo, Rio de Janeiro, Belo Horizonte, Brasília, Salvador, and Porto Alegre. Utilizing Very High Resolution (VHR) and High Resolution (HR) satellite imagery, we trained and evaluated models based on the EfficientNetV2L architecture. Our experimental results show that CNN models trained on data from a single city achieved high accuracy within that city (F1 scores exceeding 0.90 with VHR imagery), but their performance significantly decreased when applied to other cities (F1 scores dropping below 0.80), highlighting the impact of regional variations in urban morphology. Conversely, a generalized model trained on combined data from all six cities maintained robust performance across all cities, achieving F1 scores above 0.80 with VHR imagery. These findings indicate that while CNNs are effective for automated slum mapping, regional diversity necessitates training on diverse datasets to ensure generalization. We provide a comprehensive methodology over an openly shared dataset, and code to facilitate future research and applications in urban geoscience. The aim is to enhance the scalability and generalization of remote sensing and deep learning methods for slum identification across diverse urban environments.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102306"},"PeriodicalIF":7.1,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144185952","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

Torque work of origin-destination flows: Quantifying urban place centrality from a physical perspective 起点-终点流的扭矩功：从物理角度量化城市场所中心性

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-05-31 DOI: 10.1016/j.compenvurbsys.2025.102311

Xiaorui Yan , Tao Pei , Ci Song , Zidong Fang , Xiaohan Liu , Tianyu Liu , Linfeng Jiang , Ying Gao , Guangdong Li , Jie Huang , Yaqin Sun

{"title":"Torque work of origin-destination flows: Quantifying urban place centrality from a physical perspective","authors":"Xiaorui Yan , Tao Pei , Ci Song , Zidong Fang , Xiaohan Liu , Tianyu Liu , Linfeng Jiang , Ying Gao , Guangdong Li , Jie Huang , Yaqin Sun","doi":"10.1016/j.compenvurbsys.2025.102311","DOIUrl":"10.1016/j.compenvurbsys.2025.102311","url":null,"abstract":"<div><div>Quantifying urban place centrality, defined as its relative importance in serving its peripheral areas, provides insights into urban structures, optimizes resource allocation, and supports strategic urban planning. Centrality is shaped by three aspects: service volume, spatial reach, and directional diversity. However, existing measures often assess these factors separately and few integrate them simultaneously. Additionally, centrality analyses often overlook local perspectives and intra-day dynamics. To this end, we propose a novel origin-destination flow-based centrality measure, namely Total Torque Work (TTW), that integrates these three aspects into a single value, conceptualized as “Torque work of flow”, where flow volume, length, and direction correspond to the force magnitude, lever arm, and angular displacement. The effectiveness of the TTW is validated by simulation experiments. We apply this measure to analyze macro- and micro-centralities in Beijing, using taxi and shared bike flow data. Macro-centrality shows a monocentric structure, with higher values near railway stations, airports, and business and commercial centers. Micro-centrality is more polycentric, with subway stations exhibiting higher centrality. Time series clustering identifies three temporal patterns in both macro- and micro-centralities: two “daytime-dominant” patterns linked to multifunctional activities and commuting, and a “nighttime-dominant” pattern in residential areas. The study concludes with several implications for urban planning, emphasizing the importance of incorporating multi-spatiotemporal scales.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102311"},"PeriodicalIF":7.1,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144185936","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

Inclusive Digital Planning – Co-designing a collaborative mapping tool to support the planning of accessible public space for all 包容性数字规划——共同设计一种协作测绘工具，以支持所有人的无障碍公共空间规划

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-05-29 DOI: 10.1016/j.compenvurbsys.2025.102310

Johannes Flacke , Fenna Imara Hoefsloot , Karin Pfeffer

{"title":"Inclusive Digital Planning – Co-designing a collaborative mapping tool to support the planning of accessible public space for all","authors":"Johannes Flacke , Fenna Imara Hoefsloot , Karin Pfeffer","doi":"10.1016/j.compenvurbsys.2025.102310","DOIUrl":"10.1016/j.compenvurbsys.2025.102310","url":null,"abstract":"<div><div>Digital planning is loaded with the expectation to make planning more inclusive. However, digital tools currently used in spatial planning processes to facilitate communication and participation of stakeholders often exclude people with disabilities through their design. Consequently, the research question of this study is how to design digital tools to support inclusive participation in the planning and design of public spaces to make them accessible for all. To answer this question, this research aimed to co-design an inclusive collaborative mapping tool with people with disabilities to enhance their participation in the planning and design of accessible public spaces. Developed in collaboration with eight people with various disabilities from the city of Zwolle in the Netherlands, the open-source mapping tool allows the in-situ registration of accessibility issues and supports collaborative decision-making workshops. The co-design process served to identify barriers and obstacles to the accessibility of public spaces in the city as well as user requirements for the inclusive design of the collaborative mapping tool. The tool was tested and evaluated in a collaborative mapping session with people with disabilities and municipal planners from the case study city. Our findings show that the design of inclusive digital planning tools is not limited to software features but also relates to hardware functionalities and the environment in which a tool is used. Taking the lessons learned from the co-design process, we argue that digital, physical, social and procedural accessibility are key to achieving inclusive digital planning.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"121 ","pages":"Article 102310"},"PeriodicalIF":7.1,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144185953","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

Convolutional neural networks for predicting the perceived density of large urban fabrics 用于预测大型城市结构感知密度的卷积神经网络

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-05-22 DOI: 10.1016/j.compenvurbsys.2025.102304

Guy Austern , Roei Yosifof , Tomer Michaeli , Shahar Yadin , Dafna Fisher-Gewirtzman

{"title":"Convolutional neural networks for predicting the perceived density of large urban fabrics","authors":"Guy Austern , Roei Yosifof , Tomer Michaeli , Shahar Yadin , Dafna Fisher-Gewirtzman","doi":"10.1016/j.compenvurbsys.2025.102304","DOIUrl":"10.1016/j.compenvurbsys.2025.102304","url":null,"abstract":"<div><div>Urban density, along with the associated urban morphology and topology, significantly influences human perception, emotions, and behavior, ultimately affecting our overall well-being. Over the past decades, experts have developed spatial analysis models and tools which evaluate how planning and design impact urban residents and the functionality of cities. One such spatial analyses model is the Urban Spatial Openness Index (USOI) which utilizes ray-casting to conduct 3D visibility analysis predicting the perceived density of entire cities on a macro-scale, represented as 2D heatmaps. In the urban scale, ray-casting analysis is computationally intense and requires significant resources, which hinders its effective application. In this paper, we use a Convolutional Neural Network (CNN) to train a model to predict perceived density in urban fabrics based on 2D heatmap images. The processes described in this paper include creating a dataset of corresponding USOI images and height images from several different cities, training a CNN model, and evaluating the model's performance. The model predicts USOI with a mean absolute error of 1.92 %, which is considered highly accurate for visual perception on the urban scale. This study showcases the capability of CNN models to predict perceived density as measured by the USOI. The use of a predictive model can significantly reduce the processing time of 3D visibility analysis on the urban scale.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"120 ","pages":"Article 102304"},"PeriodicalIF":7.1,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144114848","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

Deciphering Urban Soundscapes: A study of sensory experiences at Hong Kong Victoria harbour waterfronts using social media 解读城市声景：利用社会媒体在香港维多利亚港海滨进行感官体验研究

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-05-16 DOI: 10.1016/j.compenvurbsys.2025.102307

Haotian Wang, Zidong Yu, Xintao Liu

{"title":"Deciphering Urban Soundscapes: A study of sensory experiences at Hong Kong Victoria harbour waterfronts using social media","authors":"Haotian Wang, Zidong Yu, Xintao Liu","doi":"10.1016/j.compenvurbsys.2025.102307","DOIUrl":"10.1016/j.compenvurbsys.2025.102307","url":null,"abstract":"<div><div>The impact of sensory experiences on physical and mental health in urban environments has gained significant attention, particularly the influence of soundscapes in waterfronts development. This study employed social media data from Twitter to quantitatively analyse the soundscape of Hong Kong Victoria Harbour waterfronts, offering a novel perspective in urban sensory research. Through comparative analysis between tourists and residents, it uncovered how different groups perceive soundscapes in these specific urban waterfronts setting. Utilizing a two-step analytical approach—initially applying rank-size distribution and mean difference index—this study mapped the spatial distribution of soundscapes and used global and local regression models to explore their correlations with key urban features such as building density, population density, and ethnic diversity. The findings revealed distinct spatial patterns in how soundscapes are experienced by tourists and residents at the Victoria Harbour waterfronts, influenced significantly by the built environment. For instance, while residents experience negative auditory sensory in high building density areas, tourists perceive these areas positively. Furthermore, this research underscored the differing correlations of population density on soundscape experience among these groups. Residents enjoy positive soundscape connections in bustling areas, whereas tourists prefer quieter environments. Moreover, the research also found the differences in how residents and tourists accept multicultural soundscapes. This study not only contributed theoretically by linking soundscapes to urban and socio-economic variables but also demonstrated the potential of social media data as a tool for studying urban sensory. The study findings could offer insights that are relevant to planning and design of urban waterfronts.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"120 ","pages":"Article 102307"},"PeriodicalIF":7.1,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071157","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

Digital twins and AI for healthy and sustainable cities 数字孪生和人工智能为健康和可持续发展的城市服务

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-05-12 DOI: 10.1016/j.compenvurbsys.2025.102305

Mark Birkin , Patrick Ballantyne , Seth Bullock , Alison Heppenstall , Heeseo Kwon , Nick Malleson , Jing Yao , Anna Zanchetta

{"title":"Digital twins and AI for healthy and sustainable cities","authors":"Mark Birkin , Patrick Ballantyne , Seth Bullock , Alison Heppenstall , Heeseo Kwon , Nick Malleson , Jing Yao , Anna Zanchetta","doi":"10.1016/j.compenvurbsys.2025.102305","DOIUrl":"10.1016/j.compenvurbsys.2025.102305","url":null,"abstract":"<div><div>The paper discusses the relevance of the latest advances in data science and artificial intelligence for urban systems research. It has a particular focus on the importance of recent innovations in the context of ‘wicked’ urban problems which continue to confront decision-makers within practical policy settings. It is argued that the latest advances in AI such as large language models offer the potential for transformative research, but only if properly specified within the unique and distinctive context of geographical space. The idea of a digital twin requires careful articulation to support the management of expectations and appropriate alignment within a social setting. At the end of the day, AI is not a panacea for the problems of cities, nor is it a substitute for imaginative policy design or interventions through consensus and good government. However in a world which is characterised by vast riches of data alongside enormous complexity of process, the investment in new tools and methods is a social and intellectual imperative in driving human understanding to new levels.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"120 ","pages":"Article 102305"},"PeriodicalIF":7.1,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936557","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

So close, yet so far: A new method for identification of high-impact missing links in pedestrian networks 如此接近，却又如此遥远：一种识别行人网络中高影响缺失环节的新方法

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-05-12 DOI: 10.1016/j.compenvurbsys.2025.102290

Matthew Wigginton Bhagat-Conway , Audrey Compiano , E. Irene Ivie

{"title":"So close, yet so far: A new method for identification of high-impact missing links in pedestrian networks","authors":"Matthew Wigginton Bhagat-Conway , Audrey Compiano , E. Irene Ivie","doi":"10.1016/j.compenvurbsys.2025.102290","DOIUrl":"10.1016/j.compenvurbsys.2025.102290","url":null,"abstract":"<div><div>Post-war suburban development is often characterized by a disconnected pod-and-collector street pattern. This creates significant barriers to active travel, forcing even short trips to take roundabout routes on busy arterial roads. However, it also creates a network of low-stress neighborhood streets. We hypothesize that there are many opportunities to add short, low-cost pedestrian and bicycle links to these street networks to increase connectivity.</div><div>A key challenge is identifying these links. While planners have a good idea of where major infrastructure investments are beneficial, they are unlikely to be familiar with every neighborhood street and potential connections between them. We introduce an algorithm to automatically and efficiently identify potential new links based only on existing network topology, with no need to prespecify potential projects. We score these links based on their contribution to accessibility. We apply this algorithm to the pedestrian network of Charlotte, North Carolina, USA, and find opportunities to improve connectivity through new links and safe crossings of major roads.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"120 ","pages":"Article 102290"},"PeriodicalIF":7.1,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936556","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

Quantifying seasonal bias in street view imagery for urban form assessment: A global analysis of 40 cities 量化城市形态评估中街景图像的季节偏差：对40个城市的全球分析

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-05-09 DOI: 10.1016/j.compenvurbsys.2025.102302

Tianhong Zhao , Xiucheng Liang , Filip Biljecki , Wei Tu , Jinzhou Cao , Xiaojiang Li , Shengao Yi

{"title":"Quantifying seasonal bias in street view imagery for urban form assessment: A global analysis of 40 cities","authors":"Tianhong Zhao , Xiucheng Liang , Filip Biljecki , Wei Tu , Jinzhou Cao , Xiaojiang Li , Shengao Yi","doi":"10.1016/j.compenvurbsys.2025.102302","DOIUrl":"10.1016/j.compenvurbsys.2025.102302","url":null,"abstract":"<div><div>Street view imagery (SVI), with its rich visual information, is increasingly recognized as a valuable data source for urban research. Particularly, by leveraging computer vision techniques, SVI can be used to calculate various urban form indices (e.g., Green View Index, GVI), providing a new approach for large-scale quantitative assessments of urban environments. However, SVI data collected at the same location in different seasons can yield varying urban form indices due to phenological changes, even when the urban form remains constant. Numerous studies overlook this kind of seasonal bias. To address this gap, we propose a systematic analytical framework for quantifying and evaluating seasonal bias in SVI, drawing on more than 262,000 images from 40 cities worldwide. This framework encompasses three aspects: seasonal bias within urban areas, seasonal bias across cities on a global scale, and the impact of seasonal bias in practical applications. The results reveal that (1) seasonal bias is evident, with an average mean absolute percentage error (MAPE) of 54 % for GVI across all sampled cities, and it is particularly pronounced in areas with significant seasonal bias; (2) seasonal bias is strongly correlated with geographic location, with greater bias observed in cities with lower average rainfall and temperatures; and (3) in practical applications, ignoring seasonal bias may result in analytical errors (e.g., an ARI of 0.35 in clustering). By identifying and quantifying seasonal bias in SVI, this study contributes to improving the accuracy of urban environmental assessments based on street view data and provides new theoretical support for the broader application of such data on a global scale.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"120 ","pages":"Article 102302"},"PeriodicalIF":7.1,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143923716","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

Incorporating environmental considerations into infrastructure inequality evaluation using interpretable machine learning 使用可解释机器学习将环境因素纳入基础设施不平等评估

IF 7.1 1区地球科学

Computers Environment and Urban Systems Pub Date : 2025-05-03 DOI: 10.1016/j.compenvurbsys.2025.102301

Bo Li, Ali Mostafavi

{"title":"Incorporating environmental considerations into infrastructure inequality evaluation using interpretable machine learning","authors":"Bo Li, Ali Mostafavi","doi":"10.1016/j.compenvurbsys.2025.102301","DOIUrl":"10.1016/j.compenvurbsys.2025.102301","url":null,"abstract":"<div><div>A growing body of literature has recognized the importance of characterizing infrastructure inequality in cities and provided quantified metrics to inform urban development plans. However, the majority of existing approaches suffered from two limitations. First, prior research has provided empirical evidence of negative environmental impacts that infrastructure can incur, while infrastructure provision inequality assessment has not taken those environmental concerns into consideration. Second, comprehensive provision assessment for multi-infrastructure system calls for a proper weight assignment, while current studies either determine the infrastructure components as equal weights or rely on subjective methods (e.g. AHP), which may be affected by potential biases. This study proposes a novel approach for incorporating environmental considerations into quantifying and assessing infrastructure provision in cities based on a data-driven method. We applied an interpretable machine learning method (XGBoost + SHAP) to capture the relationship between infrastructure features and environmental hazards (i.e., air pollution and urban heat), and then determined feature weights as their relative contributions towards environmental hazards when calculating infrastructure provision. The implementation of the model in five metropolitan areas in the U.S. demonstrates the capability of the proposed approach in characterizing inequality in infrastructure. Further the study reveals both spatial and income inequality regarding infrastructure provision. Environmentally integrated infrastructure provision proposed in this study can better capture the intersection of infrastructure development and environmental justice in measuring and characterizing infrastructure inequality in cities. This study could be used effectively to inform integrated urban design strategies to promote infrastructure equity and environmental justice based on data-driven and machine learning-based insights.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"120 ","pages":"Article 102301"},"PeriodicalIF":7.1,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143901960","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