Computers Environment and Urban Systems最新文献

{"title":"Adaptive continuity-preserving simplification of street networks","authors":"Martin Fleischmann ,&nbsp;Anastassia Vybornova ,&nbsp;James D. Gaboardi ,&nbsp;Anna Brázdová ,&nbsp;Daniela Dančejová","doi":"10.1016/j.compenvurbsys.2025.102354","DOIUrl":"10.1016/j.compenvurbsys.2025.102354","url":null,"abstract":"<div><div>Street network data is widely used to study human-based activities and urban structure. Often, these data are geared towards transportation applications, which require highly granular, directed graphs that capture the complex relationships of potential traffic patterns. While this level of network detail is critical for certain fine-grained mobility models, it represents a hindrance for studies concerned with the morphology of the street network. For the latter case, street network simplification — the process of converting a highly granular input network into its most simple morphological form — is a necessary, but highly tedious preprocessing step, especially when conducted manually. In this manuscript, we develop and present a novel adaptive algorithm for simplifying street networks that is both fully automated <em>and</em> able to mimic results obtained through a manual simplification routine. The algorithm — available in the <span>neatnet</span> Python package — outperforms current state-of-the-art procedures when comparing those methods to manually, human-simplified data, while preserving network continuity.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"123 ","pages":"Article 102354"},"PeriodicalIF":8.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145418716","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}

{"title":"Prediction of particulate matter (PM) in rural built environments based on Generative Adversarial Network (GAN)","authors":"Liqiang Zhong ,&nbsp;Hao Zheng","doi":"10.1016/j.compenvurbsys.2025.102357","DOIUrl":"10.1016/j.compenvurbsys.2025.102357","url":null,"abstract":"<div><div>Particulate matter (PM) is a key parameter for characterizing outdoor air quality. PM concentration is closely related to features of built environment. Rural built environment elements at block scale, such as building massing, impermeable surfaces, and farmlands, significantly impact the PM concentration. However, current research has focused on large-scale and broad-spectrum forecasting models, which are difficult for guide designers to apply because they lack rapid, detailed forecasting and specific visualization. This study proposes an automated design procedure using the Generative Adversarial Network (GAN) model to perform spatial planning oriented by environmental performance in rural blocks. This study collected and obtained data, including satellite land cover maps and PM concentrations, to construct a prediction model. Then, the model was used to quickly and accurately predict the concentrations of three kinds of particulate matter, PM₁, PM_2.5, and PM₁₀ under different design scenarios. This study found that first, the ratio between industrial and residential buildings (IB:RB) was positively correlated with PM concentration. The buildings with a short-strip configuration exhibited the lowest PM concentration in their environment compared to clusters of buildings in long strips or block-form structures. Second, the ratio between roads and small squares (R:SS) showed a positive correlation with PM concentration. The impervious surfaces characterized by large block configurations demonstrated the lowest PM concentration among the five planar forms evaluated. Third, farmland coverage exhibited a weak negative correlation with PM concentration. Farmlands with small blocks had the lowest PM₁₀ levels among five different planar forms, and small dotted farmlands had the lowest PM₁ and PM_2.5 levels. Finally, the model was used to simulate PM concentration under different design scenarios and suggested interactive strategies for future rural spatial planning design.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"123 ","pages":"Article 102357"},"PeriodicalIF":8.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145247986","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}

{"title":"Exploring climate-induced migration impacts on urban growth","authors":"Thomas Estabrook ,&nbsp;Derek Van Berkel ,&nbsp;Jenna Jorns ,&nbsp;Maria Carmen Lemos","doi":"10.1016/j.compenvurbsys.2025.102368","DOIUrl":"10.1016/j.compenvurbsys.2025.102368","url":null,"abstract":"<div><div>As climate change intensifies, cities may experience stressors like extreme heat and flooding, as well as possibly human in-migration from highly exposed regions facing more extreme climate stressors. This study explores the potential impacts of climate-induced migration on urban development in Grand Rapids, Michigan, and Colorado Springs, Colorado. Using the FUTURES land-change model, we project urban expansion from 2016 to 2045, comparing different policy and planning scenarios to the status quo. These scenarios include urban infill, avoidance of location-specific climate stressors (e.g., fire- and flood-prone areas), and climate migration projections. Our results reveal that while promoting infill development can reduce the loss of green spaces and agricultural land, it has diverging effects on exposure to these climate risks. In Grand Rapids, infill policies led to greater urban expansion in flood-prone areas, while in Colorado Springs, similar policies mitigated development in wildfire-prone zones. Scenarios of climate migration due to sea-level rise suggest minimal urban expansion from migration influxes, largely due to current policies favoring densification in these cities. Uncertainty surrounding climate migration suggests a need to improve population projections by incorporating a broader range of climate stressors (e.g., flooding, wildfires, drought) that are likely to drive resettlement across the United States. Our findings suggest that receiving cities require information on potential impacts to balance the opportunities of climate migration while mitigating related environmental vulnerabilities. Decision support tools like land-use models can be useful for preparing cities to address future demographic and environmental challenges.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"123 ","pages":"Article 102368"},"PeriodicalIF":8.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466734","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}

{"title":"VoxCity: A seamless framework for open geospatial data integration, grid-based semantic 3D city model generation, and urban environment simulation","authors":"Kunihiko Fujiwara ,&nbsp;Ryuta Tsurumi ,&nbsp;Tomoki Kiyono ,&nbsp;Zicheng Fan ,&nbsp;Xiucheng Liang ,&nbsp;Binyu Lei ,&nbsp;Winston Yap ,&nbsp;Koichi Ito ,&nbsp;Filip Biljecki","doi":"10.1016/j.compenvurbsys.2025.102366","DOIUrl":"10.1016/j.compenvurbsys.2025.102366","url":null,"abstract":"<div><div>Three-dimensional urban environment simulation is a powerful tool for informed urban planning. However, the intensive manual effort required to prepare input 3D city models has hindered its widespread adoption. To address this challenge, we present VoxCity, an open-source Python package that provides a one-stop solution for grid-based 3D city model generation and urban environment simulation for cities worldwide. VoxCity’s ‘generator’ subpackage automatically downloads building heights, tree canopy heights, land cover, and terrain elevation within a specified target area, and voxelizes buildings, trees, land cover, and terrain to generate an integrated voxel city model. The ‘simulator’ subpackage enables users to conduct environmental simulations, including solar radiation and view index analyses. Users can export the generated models using several file formats compatible with external software, such as ENVI-met (INX), Blender, and Rhino (OBJ). We generated 3D city models for eight global cities, and demonstrated the calculation of solar irradiance, sky view index, and green view index. We also showcased microclimate simulation and 3D rendering visualization through ENVI-met and Rhino, respectively, through the file export function. Additionally, we reviewed openly available geospatial data to create guidelines to help users choose appropriate data sources depending on their target areas and purposes. VoxCity can significantly reduce the effort and time required for 3D city model preparation and promote the utilization of urban environment simulations. This contributes to more informed urban and architectural design that considers environmental impacts, and in turn, fosters sustainable and livable cities. VoxCity is released openly at <span><span>https://github.com/kunifujiwara/VoxCity</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"123 ","pages":"Article 102366"},"PeriodicalIF":8.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466752","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}

{"title":"Decoding human safety perception with eye-tracking systems, street view images, and explainable AI","authors":"Yuhao Kang ,&nbsp;Junda Chen ,&nbsp;Liu Liu ,&nbsp;Kshitij Sharma ,&nbsp;Martina Mazzarello ,&nbsp;Simone Mora ,&nbsp;Fábio Duarte ,&nbsp;Carlo Ratti","doi":"10.1016/j.compenvurbsys.2025.102356","DOIUrl":"10.1016/j.compenvurbsys.2025.102356","url":null,"abstract":"<div><div>The way residents perceive safety plays an important role in how they use public spaces, and it informs city planning and public policy. Recent studies have combined street view images and advanced computer vision techniques to measure human safety perceptions of urban environments. Despite their success, such studies have often overlooked the specific environmental visual factors that draw human attention and trigger people’s feelings of safety perceptions. In this study, we introduce a computational framework that enriches the existing body of literature on place perception by using eye-tracking systems with street view images and explainable AI approaches. Eye-tracking systems measure what users are looking at and how long they engage with specific environmental elements. This allows us to explore the nuance of which visual environmental factors influence human safety perceptions. We conducted our research and recruited volunteers in Helsingborg, Sweden. By examining participants’ focus on specific features using Mean Object Ratio in Highlighted Regions (MoRH) and Mean Object Hue (MoH), we identified key visual elements that attract human attention when perceiving safe environments. For instance, certain urban infrastructure (e.g., stairways and signboards) and public space (flags and chairs) features draw more human attention while the sky is less relevant in influencing safety perceptions. These insights offer a more human-centered understanding of which urban features influence human safety perceptions. Furthermore, we compared the real human attention from eye-tracking systems with attention maps obtained from eXplainable Artificial Intelligence (XAI) results. Several XAI models were tested, and we observed that XGradCAM and EigenCAM most closely align with human safety perceptual patterns. Our framework provides a valuable approach to enhance the interpretability and trustworthiness of XAI models by comparing them with empirically observed human behavior data. This study demonstrates the limitations of previous place perception studies that solely rely on street view images and computer vision techniques, which may not comprehensively capture the nuanced human experiences and behaviors at place. The inclusion of technologies such as eye-tracking not only deepens our comprehension of human subjective experiences, but also contributes to the development of safer environments and communities.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"123 ","pages":"Article 102356"},"PeriodicalIF":8.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145418726","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}

{"title":"Exploring the inequality of the particulate matter exposure level of public bicycle scheme users using an agent-based model","authors":"Suyeon Hwang ,&nbsp;Heesoo Rhim ,&nbsp;Jeon-Young Kang ,&nbsp;Jinmu Choi","doi":"10.1016/j.compenvurbsys.2025.102367","DOIUrl":"10.1016/j.compenvurbsys.2025.102367","url":null,"abstract":"<div><div>Air pollution negatively affects human health and understanding its relationship with mobility is crucial for assessing these effects. Although previous studies have relied on individual GPS trajectories, employing data gathered at the individual level frequently results in ecological fallacies. This study constructed a spatially explicit agent-based model (ABM) to illustrate the uneven interactions between the mobility patterns of bicycle users and their exposure to particulate matter (PM). We found that bicycle users who visited specific rental stations were exposed to higher PM levels. We conducted scenario analyses that included the closure of rental stations with higher average PM exposure levels or the introduction of detour routes to evaluate the influence of rental station utilization on exposure levels. When rental stations were completely closed and users were directed to detour to nearby accessible stations for both departure and arrival, they were observed to explore new mobility behaviors. During this process, users increased their exposure levels by selecting routes characterized by high PM concentrations and longer travel times. Conversely, when implementing a temporary closure that restricted only departures, the measured exposure levels showed a significant reduction compared with both the baseline and complete closure scenarios. The scenario analyses verified that individuals' exposure to PM was significantly affected by mobility patterns. The spatially explicit ABM can aid in identifying inequality in individuals' PM exposure levels by considering their mobility and can provide insights for improving urban transportation system management.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"123 ","pages":"Article 102367"},"PeriodicalIF":8.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145418717","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}

{"title":"Reassessing air pollution exposure: How daily mobility and activities shape individual risk in greater Paris","authors":"Taos Benoussaïd ,&nbsp;Isabelle Coll ,&nbsp;Hélène Charreire ,&nbsp;Inès Makni ,&nbsp;Malo Costes ,&nbsp;Arthur Elessa Etuman","doi":"10.1016/j.compenvurbsys.2025.102340","DOIUrl":"10.1016/j.compenvurbsys.2025.102340","url":null,"abstract":"<div><div>Understanding individual exposure to air pollution is essential for tackling environmental inequalities and informing public policies aimed at reducing disparities. Traditional approaches often focus on residential locations, but exposure is intrinsically linked to daily mobility, activities and socio-economic profiles. This study presents new results based on a dynamic exposure modelling approach that takes these dimensions into account, offering a more realistic assessment of air pollution risk. By integrating high-resolution air quality data with detailed information on individual mobility, activities and socio-economic characteristics, we quantify the exposure of 400,000 individuals in the Île-de-France region. Our approach takes into account all the environments that individuals visit during the day and the time spent in each of them, going beyond static exposure assessments based on residential location. We compare this dynamic model with traditional exposure calculations, revealing significant differences in the spatial distributions of PM10 and NO2 exposure. Our analysis highlights how mobility patterns and daily activities contribute to total exposure, demonstrating that place of residence is only one part of reality. For example, commuting, workplaces and leisure activities play a key role in determining individual exposure levels. The results of our study show that dynamic exposure calculation provides a better understanding of exposure factors and offers a framework for understanding environmental inequalities. By shifting the focus from home-based to person-based exposure, our approach makes it possible to identify levers for action to reduce disparities and support targeted public health action. Our study redefines the way in which we assess the risks associated with air pollution, by highlighting the need to take into account mobility behaviour and individual trajectories.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"122 ","pages":"Article 102340"},"PeriodicalIF":8.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144894924","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}

{"title":"Walking smart in the heat: A dynamic shade-oriented pathfinding approach to enhance pedestrian comfort in arid cities","authors":"Jianxiu Wen ,&nbsp;Diaa Addeen Abuhani ,&nbsp;Martina Mazzarello ,&nbsp;Fabio Duarte ,&nbsp;Leslie Norford ,&nbsp;Ruohan Xu ,&nbsp;Nyuk Hien Wong ,&nbsp;Carlo Ratti","doi":"10.1016/j.compenvurbsys.2025.102337","DOIUrl":"10.1016/j.compenvurbsys.2025.102337","url":null,"abstract":"<div><div>In recent decades, rapid population growth in Middle Eastern cities has led to increased motorization and rising carbon emissions, particularly in car-oriented, high-density urban environments like Dubai. In response, cities are expanding their public transportation systems and promoting walking and cycling. However, scorching temperatures make the choice of active mobility challenging. This study presents a methodology to evaluate pedestrian walking environments by comparing the alignment between the shortest and optimal shadiest paths around metro stations in Dubai. Unlike existing models that apply a constant shade reward, we develop an optimal shadiest path method that assigns dynamic rewards to buildings, trees, and indoor shade, which better reflects real-world conditions. Additionally, we highlight the often-overlooked role of indoor paths in enhancing pedestrian thermal comfort, particularly in arid cities. To quantify both the shortcut effect and the shade improvement of indoor paths, we introduce the Indoor Contribution Index (ICI), a metric that assesses the role of indoor routes in improving pedestrian thermal comfort and walking efficiency. The results reveal that, on average, the optimal shadiest path is 1.3% longer than the shortest path, with an 8.9% increase in building shade and an 8.8% decrease in sun exposure compared to the shortest path. Additionally, both temporal factors and spatial characteristics significantly influence the utility of indoor routes in enhancing thermal walking comfort. Our findings highlight the need for further research into smart pathfinding algorithms that can guide pedestrians through hot environments, as well as the integration of indoor networks into urban mobility systems, particularly in Middle Eastern cities and other regions with harsh outdoor conditions.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"122 ","pages":"Article 102337"},"PeriodicalIF":8.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049430","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}

{"title":"Encoding experience: Quantifying multisensory perception of urban form through a systematic review","authors":"Korawich Kavee,&nbsp;Katherine A. Flanigan","doi":"10.1016/j.compenvurbsys.2025.102349","DOIUrl":"10.1016/j.compenvurbsys.2025.102349","url":null,"abstract":"<div><div>As cities become increasingly measurable and modeled, a new design paradigm is emerging — one that places human perception, emotion, and sensory experience at the center of urban analysis. Yet most planning frameworks and computational models continue to emphasize visual and spatial configuration alone, leaving out the full spectrum of how people engage with and feel in the built environment. This paper addresses that gap by systematically mapping how five sensory modalities — sight, sound, smell, touch, and taste — relate to urban form. A key innovation lies in reinterpreting Lynch’s seminal taxonomy of urban elements as a scaffold for organizing and analyzing multisensory perception. We synthesize findings across disciplines and identify sensing technologies capable of capturing the submodalities of each sensory domain, enabling a more complete understanding of how the built environment is experienced. While walkability serves as a representative domain throughout, the insights extend to broader efforts in urban design, infrastructure management, and experience-driven planning. By linking subjective human experience to objective spatial features, this work lays the foundation for new computational tools and humanistic metrics that can inform how cities are designed, maintained, and adapted.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"122 ","pages":"Article 102349"},"PeriodicalIF":8.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144932758","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}

{"title":"Digital planning for sustainable urban future","authors":"Yanliu Lin ,&nbsp;Stan Geertman ,&nbsp;Patrick Witte ,&nbsp;Nuno Pinto","doi":"10.1016/j.compenvurbsys.2025.102334","DOIUrl":"10.1016/j.compenvurbsys.2025.102334","url":null,"abstract":"","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"122 ","pages":"Article 102334"},"PeriodicalIF":8.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265536","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}