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This paper explores the enduring impact of freeway construction on urban neighborhoods and communities, focusing on Los Angeles. The legacy of freeways in Los Angeles, often and purposefully constructed through marginalized communities during the mid-20th century for the benefit of white suburbanites, is reflected in significant social, economic, and environmental symptoms today. This paper also examines de-freeway methods to reconnect these divided communities, assessing their need and effectiveness through data analysis and case studies.The case studies presented in this paper offer a diverse range of solutions. They include the capping of I-5 for Freeway Park in Seattle, the tunneling of the Central Artery for Boston's Big Dig, the activation of I-5 underpasses for Chicano Park in San Diego, and the creation of the Ricardo Lara embankment park along the I-105 freeway in Lynnwood. These examples provide valuable insights into the processes, challenges, and successes of de-freeway and community reconnection efforts, showcasing the adaptability of these solutions in different urban contexts.The paper introduces three design proposals for freeway sites across six communities in Los Angeles. These proposals are guided by urban reformation around freeways and incorporating urban design principles prioritizing social equity, environmental sustainability, and economic revitalization for the most vulnerable and impacted communities. The proposed designs aim to restore community cohesion and foster resilient urban ecosystems.This study contributes to the ongoing discourse on sustainable urban transformation and the reclamation of public spaces for community benefit by providing a comprehensive analysis of historical impacts and contemporary solutions. The paper's findings should help inform and guide urban planning and policy advocates and professionals inspired by the reconnecting communities movement, underscoring the need for innovative approaches to mending bifurcated and ecologically disadvantaged communities.

Press coverage of the Sheffield street tree dispute showed images of protestors and yellow ribbons on trees threatened with felling as part of a highly charged and public argument between the council and some of its citizens. However, a closer analysis of the highways management programme shows that it was not simply a case of two parties in conflict. This paper pulls on a wide range of secondary data sources to explore Sheffield's street tree dispute by examining the urban management approach taken by the local authority. Using the place-keeping concept as an analytical framework, the paper will demonstrate how the Sheffield case reflects "business as usual" maintenance practices undertaken by local authorities when contracting out management work. The analysis also provides evidence showing how the Sheffield case demonstrates poor contract design, governance processes, evaluation and communication practices that had ramifications for the city that went beyond its street trees. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering (17264073) is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Urban regeneration is one of the most important public administration issues facing modern cities. While abundant studies have focused on the state-led or market-based governance modes of large urban regeneration projects, relatively fewer studies investigate the collaborative governance mode, especially on the numerous street-level small-scale regeneration projects. Street-level small-scale regeneration projects directly touch on citizens' life and impact governance effectiveness at grassroot level. This paper studies dynamics of collaborative governance of a street-level regeneration that can balance multiple regeneration objectives and successfully address conflicts and tensions inherent in such projects. Our findings are significant in confirming the applicability of the basic tenets of collaborative governance in grassroot level and pointing out some key differences between large-scale collaborative governance projects and street-level small-scale projects in how governance effectiveness could be achieved through different stakeholders' interactions in urban regeneration. [ABSTRACT FROM AUTHOR]

Historic cities serve as a crucial historical–cultural cornerstone within urban settings, and fostering its sustainable vitality has emerged as a focal point in urban research. Multisource data have advanced large-scale vitality research. Despite keen interest in the nexus between urban vitality and the built environment, the spatiotemporal intricacies influencing street vitality in smaller urban settings like ancient city are underexplored. To fill this gap, we use Chaozhou ancient cities as a case study to examine the relationship between street vitality and the built environment. Leveraging Jacobs' urban vitality theory and the 5D system, this study develops initial tools to understand ancient city vitality, focusing on density, diversity, accessibility, and the streets' spatial characteristics. Subsequently, employing a geographically and temporally weighted regression model, we delve into the spatiotemporal heterogeneity of vitality and the built environment. The research findings indicate that: (1) the association between street vitality and the built environment in historic cities exhibits dynamic variations over time and space. The impact of different built environment indicators on the vitality of the streets varies in intensity across different periods and areas. (2) Density and diversity play contrasting multifaceted and limited roles in enhancing the vitality of ancient cities. Accessibility's role in traffic attraction and navigability significantly sways vitality. The temporal nonstationary of street space characteristics is particularly pronounced. (3) The density of aged buildings, diversity of building ages, sky view ratio, and green view ratio generally show a negative correlation with the vitality of ancient cities across time and space. [ABSTRACT FROM AUTHOR]

Streets and buildings that become inactive within the historical texture of cities can be restored to the district through rehabilitation projects and color designs, which encourage urbanites to use them more actively. Such spaces are especially important for urban memory, yet they risk losing their integrity over time due to uncontrolled development. Therefore, making them available for urban use is important for socio‐cultural and economic development. This study involves the application, under a rehabilitation project, of a holistic approach to façade color design for buildings located on two streets in the center of Adana, a city in southern Turkey that dates back to the Common Era. The study began with collecting color samples from the area as part of environmental color analyses, after which the colors of the samples were measured. In line with the environmental characteristics that affect color perception, a range of colors with Munsell's equivalent value and hue contrast was considered appropriate for application to the facades of buildings in the Kayalıbağ neighborhood. In the color design, five different hues with high‐value (light) and low chroma were selected to increase the attractiveness of the historically and archeologically highly significant district. The aim of the color design was to increase the livability and attractiveness of the district, while not overshadowing the cultural qualities of the urban environment. [ABSTRACT FROM AUTHOR]

We introduce University of Texas - GLObal Building heights for Urban Studies (UT-GLOBUS), a dataset providing building heights and urban canopy parameters (UCPs) for more than 1200 city or locales worldwide. UT-GLOBUS combines open-source spaceborne altimetry (ICESat-2 and GEDI) and coarse-resolution urban canopy elevation data with a machine-learning model to estimate building-level information. Validation using LiDAR data from six U.S. cities showed UT-GLOBUS-derived building heights had a root mean squared error (RMSE) of 9.1 meters. Validation of mean building heights within 1-km2 grid cells, including data from Hamburg and Sydney, resulted in an RMSE of 7.8 meters. Testing the UCPs in the urban Weather Research and Forecasting (WRF-Urban) model resulted in a significant improvement (55% in RMSE) in intra-urban air temperature representation compared to the existing table-based local climate zone approach in Houston, TX. Additionally, we demonstrated the dataset's utility for simulating heat mitigation strategies and building energy consumption using WRF-Urban, with test cases in Chicago, IL, and Austin, TX. Street-scale mean radiant temperature simulations using the SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model, incorporating UT-GLOBUS and LiDAR-derived building heights, confirmed the dataset's effectiveness in modeling human thermal comfort in Baltimore, MD (daytime RMSE = 2.85°C). Thus, UT-GLOBUS can be used for modeling urban hazards with significant socioeconomic and biometeorological risks, enabling finer scale urban climate simulations and overcoming previous limitations due to the lack of building information. [ABSTRACT FROM AUTHOR]

AbstractProblem, research strategy, and findingsTakeaway for practiceWe predicted the amount, share, and value of land dedicated to roadways within and across 316 U.S. primary metropolitan statistical areas. Despite the amount and value of land dedicated to roadways, our study provides the first such estimate across a broad range of metropolitan areas. Our basic approach was to estimate roadway widths using a 10% sample of widths provided by the Highway Performance Monitoring System and apply our estimates to the rest of the roadway system. Multiplying estimated widths by segment length and netting out double counting at intersections provided estimates of land area. We also matched roadway segments and areas to existing land value estimates and satellite-based measures of urbanized land. We found that a little less than a quarter of urbanized land—roughly the size of West Virginia—was dedicated to roadway. This land was worth around $4.1 trillion in 2016 and had an annualized value that was higher than the total variable costs of the trucking sector and the total annual federal, state, and local expenditures on roadways. Conducting a back-of-the-envelope cost–benefit analysis, we found that the country likely has too much land dedicated to urban roads.Federal, state, and local agencies dedicate substantial time, money, and resources to providing roadways. Even with relatively generous assumptions and no external costs from driving, however, we estimated that the average cost of expanding roadways exceeded the benefits by a factor of nearly three when accounting for land value. Policymakers should question policies focused on roadway expansion and consider options to reduce the amount of space dedicated to roadway in favor of more housing, offices, and other land uses. In addition to our findings, we provide a novel data set that academics and policymakers can use to draw their own conclusions about the state of America’s urban roadways. [ABSTRACT FROM AUTHOR]

The role of restorativeness in attracting and retaining people on commercial streets has been under-researched. To examine this topic, this convergent parallel mixed methods study was conducted on four commercial streets in Brazil. It included a quantitative evaluation of correlations between a set of microscale aspects of commercial streets and liveliness, and a qualitative thematic analysis of users' experiences informed by the Attention Restoration Theory. The results showed restorativeness as one pathway linking microscale aspects of commercial streets to liveliness. The perceived restorative potential of microscale aspects of commercial streets should be considered when adopting fine-grained approaches to enhance their liveliness. [ABSTRACT FROM AUTHOR]

Urban street trees (USTs) have a range of values – some of which are easier to quantify than others. Focusing specifically on the UK context and using the Sheffield Tree Protests (2012–) as a case study, whilst confirming existing research as to the variety of values associated with their specifically 'cultural' services, the article argues that USTs have an additional potential form – what I call 'civic-transformative value'. This form of value has at least three key characteristics. Firstly, it is place-based and communal; second, its form is 'relational'; and finally, as intrinsically contingent, it is pluralistic in the sense that its civic-transformative potential is dependent on successfully integrating a range of other values. The article emphasises both the possibility and necessity of 'convergence' – that is, a pluralistic and pragmatic alliance of values which might help protect not only USTs, but other embattled sites of nature. [ABSTRACT FROM AUTHOR]

Rapid urbanization increases psychological stress among pedestrians, potentially heightening mental health disorders. This study examines the role of street walls' visual and textural characteristics in stress recovery, using Qingdao as a case study. Virtual reality is employed to simulate five distinct street walls: yellow mortar, brown stone, red brick, green plant, and white mortar. The stress recovery effectiveness of these walls was evaluated through psychological and physiological indicators from 48 young college students. Results indicated that street walls with warm tones, particularly brown stone, significantly aid stress recovery. Psychologically, Restorative Components Scale was highest for brown stone at 1.13. Physiologically, it was linked with notable reductions in diastolic and pulse pressure (decreases of 2.95 mmHg and 2.27 mmHg, respectively), and enhanced parasympathetic activity, as evidenced by the fastest decrease in low frequency/high frequency ratio (LF/HF), and increases in pNN50 and RR (0.14–2.01% and 1.57–11.81 ms, respectively). For urban design, the incorporation of warm-toned materials and natural elements like stone is recommended for their superior restorative benefits. [ABSTRACT FROM AUTHOR]

Evaluating arterial operational performance plays a pivotal role in arterial system management and enhancement. As a fundamental reference guide for traffic engineers, the Highway Capacity Manual (HCM) provides a series of analysis methodologies for evaluating multimodal operations on urban streets, highways, freeways, and off-street pathways. However, the efficient use of the performance evaluation methodology of urban street facilities for motorized vehicles in the HCM can be restricted by a large amount of traffic volume collections at signalized and access point intersections, roadway segment geometric data inputs, and complicated calculation procedures on urban street segments. Further, the use of alternative tools, such as vehicle trajectory data, remains to be explored to supplement the urban street facility calculation framework in the HCM. To bridge the gap, this research utilizes vehicle trajectory data as an alternative tool and proposes a combined vehicle trajectory data and HCM calculation framework to implement and assess the existing performance evaluation methodology of urban street facilities for motorized vehicles in the HCM 7th Edition. A case study was carried out on three major signalized arterials in Sparks, Nevada, for HCM methodology implementation and performance evaluation. Based on evaluation results, it was found that vehicle trajectory data can be utilized as an alternative tool to implement the performance evaluation methodology of urban street facilities for motorized vehicles in the HCM 7th Edition. It is recommended to combine arterial through-vehicle trajectories, the time-space diagram, arterial level of service (LOS), and the poorest segment LOS for arterial operational performance evaluation and further enhancement. The proposed automobile traveler perception score (ATPS) in the HCM was found to be insensitive to reflecting traveler’s perception of service quality. Additional traveler perception-based factors are recommended to be included for further ATPS development and enhancement. [ABSTRACT FROM AUTHOR]

Evaluating arterial operational performance plays a pivotal role in arterial system management and enhancement. As a fundamental reference guide for traffic engineers, the Highway Capacity Manual (HCM) provides a series of analysis methodologies for evaluating multimodal operations on urban streets, highways, freeways, and off-street pathways. However, the efficient use of the performance evaluation methodology of urban street facilities for motorized vehicles in the HCM can be restricted by a large amount of traffic volume collections at signalized and access point intersections, roadway segment geometric data inputs, and complicated calculation procedures on urban street segments. Further, the use of alternative tools, such as vehicle trajectory data, remains to be explored to supplement the urban street facility calculation framework in the HCM. To bridge the gap, this research utilizes vehicle trajectory data as an alternative tool and proposes a combined vehicle trajectory data and HCM calculation framework to implement and assess the existing performance evaluation methodology of urban street facilities for motorized vehicles in the HCM 7th Edition. A case study was carried out on three major signalized arterials in Sparks, Nevada, for HCM methodology implementation and performance evaluation. Based on evaluation results, it was found that vehicle trajectory data can be utilized as an alternative tool to implement the performance evaluation methodology of urban street facilities for motorized vehicles in the HCM 7th Edition. It is recommended to combine arterial through-vehicle trajectories, the time-space diagram, arterial level of service (LOS), and the poorest segment LOS for arterial operational performance evaluation and further enhancement. The proposed automobile traveler perception score (ATPS) in the HCM was found to be insensitive to reflecting traveler’s perception of service quality. Additional traveler perception-based factors are recommended to be included for further ATPS development and enhancement. [ABSTRACT FROM AUTHOR]

The effects of the physical environment on people's active behaviour have been a central topic over the last decade, particularly in urban design, public health, and transportation. Research on the impact of the built environment attributes on walkability still needs to be completed in developing countries. Literature on walkability demonstrated the effectiveness of the studies, which consider micro-scale elements when evaluating pedestrian street environments. We are interested in assessing urban design qualities at the micro-scale level, which would give more evidence on the walking conditions of a developing country. This study explores whether the typo-morphological aspect of selected routes in a medium-sized African city is associated with urban design qualities related to walkability and compares the combined scores of urban design qualities with other cities. According to our findings, the typo-morphological aspect of urban routes correlates with the evaluated urban design qualities. The results revealed a significant difference in these qualities between the old colonial and the post-independence fabrics, with imageability and complexity appearing to be the most influential qualities. The results showed that urban design qualities related to walkability in a mediumsized African city scored lower than in other urban contexts. This study has several implications for city planners and decision-makers looking to improve the walking environment of the city. [ABSTRACT FROM AUTHOR]

A review of roadway planning and design practices since the early-20th century demonstrates that engineers have increasingly prioritized building and designing roads that are adapted to their surrounding context. Roadbuilding in the early-20th century focused on delivering road facilities able to operate in all weather conditions, accommodate automobiles, and facilitate personal travel and commerce. The growth in automobile ownership required engineers to work towards alleviating congestion and thus resulting in constructing sprawling infrastructure networks that connect urban and suburban areas -- sometimes at the expense of marginalized communities and neighborhood cultures. The late-1990s and early-2000s saw transportation agencies, AASHTO, and NCHRP embrace performance-based approaches to road design that are more sensitive to context. This trend continues today, with novel tools being devised to help engineers carry out a flexible, multimodal, performance-based, and context-sensitive design process built upon the context classification system introduced in A Policy of Geometric Design for Highways and Streets (7th Edition) and expanded through a series of NCHRP research documents. Using W. Broadway Avenue in Louisville, Kentucky, as a case study, this paper illustrates the application of the new context classification system and associated Transportation Expectations to road design. Making use of the latest tools and concepts, the case study shows, will improve project delivery so planners and engineers may also address issues related to public health, community and transportation equity, local cultures, and community needs when crafting design solutions. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Arquitectura (1657-0308) is the property of Universidad Catolica de Columbia, Facultad de Arquitectura and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As the aspirational Complete Streets movement sweeps North America with multimodal transportation policies and plans, communities need practice-ready tools that reinforce social inclusion and sustainable development through the movement's implementation. Here we present two such tools: (1) gender analysis, which considers gendered experiences and roles in the context of Complete Streets so as to benefit diverse travelers with improved safety, transportation choices, support for caregivers, and more; and (2) an approach called SDG 360 Thinking, a holistic analysis of Complete Streets policy co-benefits, unintended harms, and trade-offs using the UN Sustainable Development Goals. We piloted these tools in workshops with community members and technical experts. Workshop participants gained new insights, made connections across sectors, took more inclusive and diverse perspectives, and made recommendations about Complete Streets policies. These tools are practical, easy to understand, and could be broadly impactful for communities. [ABSTRACT FROM AUTHOR]

Higher concentrations of air pollutants, such as nitrogen dioxide (NO 2 ) and particulate matter (PM), are observed in streets compared to the urban background. These concentrations could be predominantly attributed to road traffic, which remains an important source despite relentless efforts. In this study, performed over the Paris area, the impacts of the evolution of the fleet composition on urban air quality down to the street scale is assessed with two scenarios assuming the introduction of very-low-emission vehicles. Exhaust emission factors for these vehicles are based on the improvement of engine and after-treatment technologies, leading to factors lower than those proposed for the European emission standard Euro 7. Using the year 2014 as the baseline, very-low-emission vehicles are introduced up to the year 2030 for the Paris region. NO 2 emissions are thus reduced by 68 % in streets, and concentrations by 53 %. However, PM concentration reduction is limited to 18 % in streets as non-exhaust emissions from tyre and brake wear and road abrasion are preponderant. PM emissions from non-exhaust sources represent 59 % of the total road-traffic emission of PM in 2014 and 89 % in 2030. Non-regulated pollutant concentrations are also reduced, by 42 % for black carbon and 30 % for organic matter. Considering only very-low-emission and electric vehicles in the fleet further reduce NO 2 emissions and concentrations by 99.5 % and 80 % respectively. PM concentrations are only reduced by 22 %. This study highlights the high reduction potential of NO 2 concentrations with very-low-emission and electric vehicles, because of reduction of exhaust emissions. However, difficulties remain to reduce PM concentrations in urban areas, with the large majority of PM traffic emissions coming from non-exhaust sources. [ABSTRACT FROM AUTHOR]

To meet the requirement of mega low earth orbit (LEO) constellation design in non-terrestrial network (NTN), a geometric configuration design method of Walker constellation applicable to arbitrary latitude range coverage multiple and satellite quantity scale is proposed. First, a Walker configuration representation based on the streets of coverage (SoC) characteristic parameters is proposed. Then, satellite quantity required for coverage and the SoC parameters are estimated by calculating the width and adjacent spacing of SoC, which can improve the enumeration efficiency. Finally, by adjusting the phase and quantity of the satellite on the SoC, the constellation configuration with optimal comprehensive performances is selected from multiple groups of results. To demonstrate the effectiveness of the proposed design method, the performance comparisons among the existing mega LEO constellation systems are conducted. Compared with the existing configurations, the configuration calculated by the proposed method can efficiently reduce the satellite quantity required for coverage by about 20%, and can also satisfy the comprehensive demands including coverage performance, inter-satellite link, configuration redundancy and collision avoidance by reasonably selecting configuration parameters. • The streets-of-coverage characteristics are directly related to coverage performance. • Variability of coverage street widths of nonplanar satellites widens design space. • Continuous solution space improves enumeration and coverage judging efficiency. • Adjusting configuration parameters and satellite quantity can meet various demands. [ABSTRACT FROM AUTHOR]

The idling of automobiles at street intersections can lead to pollutant accumulation which impacts the health of residents in street-facing buildings. Previous research focused on pollutant dispersion within street canyons and did not consider the coupling of indoor and outdoor pollutants. This paper employs the computational fluid dynamics (CFD) method to simulate the dispersion characteristics of vehicle emission pollutants in street canyons, primarily investigating the indoor and outdoor pollutant dispersion patterns under various window opening configurations (single-sided ventilation, corner ventilation, and different positions of the glass under corner ventilation). Additionally, the study considers the impacts of the aspect ratio and ambient wind speed. Studies have shown that corner ventilation is effective in reducing indoor pollutant levels. When the two window glass positions are far away from the center of the intersection, the average CO mass fraction in the single-sided ventilation room is reduced by 87.1%. The average indoor CO mass fraction on the leeward side decreases with the increasing wind speed and aspect ratio. At a wind speed of 8 m/s, the average indoor CO mass fraction on the leeward side decreases to 2.45 × 10−8. At an aspect ratio of 2, the indoor CO mass fraction on the leeward side decreases with increasing floors before stabilizing at approximately 4.77 × 10−9. This study suggests optimal window opening strategies to reduce indoor pollutant levels in street-facing buildings at street intersections, offering guidance to indoor residents on window ventilation practices. [ABSTRACT FROM AUTHOR]

The dynamics of spin–orbit-coupled Bose–Einstein condensate with parity-time symmetry through a moving obstacle potential is simulated numerically. In the miscible two-component condensate, the formation of the Kármán vortex street is observed in one component, while 'the half-quantum vortex street' is observed in the other component. Other patterns of vortex shedding, such as oblique vortex dipoles, V-shaped vortex pairs, irregular turbulence, and combined modes of various wakes, can also be found. The ratio of inter-vortex spacing in one row to the distance between vortex rows is approximately 0.18, which is less than the stability condition 0.28 of classical fluid. The drag force acting on the obstacle potential is simulated. The parametric regions of Kármán vortex street and other vortex patterns are calculated. The range of Kármán vortex street is surrounded by the region of combined modes. In addition, spin–orbit coupling disrupts the symmetry of the system and the gain-loss affects the local particle distribution of the system, which leads to the local symmetry breaking of the system, and finally influences the stability of the Kármán vortex street. Finally, we propose an experimental protocol to realize the Kármán vortex street in a system. [ABSTRACT FROM AUTHOR]

In 2015, the Zimbabwean government announced that street vendors had one week to clear the streets or the national army would be deployed against them. This was part of a long-standing campaign of disavowing and displacing vendors. Yet street vendors are integral to economic life in Zimbabwe. In this paper, I examine vending and its policing. I draw on ethnographic fieldwork I conducted in Zimbabwe to ask what underlies the vitriol and violence targeted at vendors. I propose that vending is more than a constellation of individual traders and that its politics extend beyond the conceptions of (il)legality that often characterize debates around street trade. Rather, vending has weaved itself into an infrastructure of economic life in Zimbabwe, facilitating vital flows and undergirding an economy rocked by economic turmoil. Yet vending operates as an infrastructure of disavowal at the nexus of citizenry and spatial politics, as "unwanted" persons operate in unauthorized spaces. Recognizing vending as infrastructural opens up consideration of a decolonial approach to infrastructure and urban governance in African cities. [ABSTRACT FROM AUTHOR]

Our biggest social problems tend to manifest themselves in small ways--on the streets where they affect people's daily lives. Local governments, who govern the streets and thereby are closest to the people, often find themselves on the front lines of combatting those problems. Accordingly, local governments are now promoting reforms to address climate change and homelessness, to reinvent education and transportation, and to remedy ingrained inequities. Any government instituting change can and will face headwinds, which, in America perhaps inevitably, will at some point assume the form of lawsuits. But for various legal and functional reasons, city action is even more susceptible to litigation than federal or state action. Moreover, cities are particularly vulnerable to litigation instigated by the economically and politically powerful, who choose litigation when they fail to get their way from the political process. Consequently, suing cities has become a tool to stop local progress in its tracks. This Article is the first to call attention to these trends. It shows how, with little scholarly analysis or legal pushback, American law has come to accord special standing rights to private plaintiffs suing local governments. It also demonstrates how this regime systemically exacerbates existing inequalities and unjustifiably interferes with local democratic governance. But all is not lost. This Article identifies potential changes to the law that could rebalance the relationship between private plaintiffs and local governments. These changes will channel anticity litigation toward more socially beneficial uses, while discouraging the kinds of litigation that are, almost by nature, obstacles to progress. Current law famously makes it hard to sue federal and state governments. Much less famously, it makes it easy to sue local governments. By recognizing the problems each of the extremes portends, we can hopefully move closer to a democratically sound regime for suing governments. [ABSTRACT FROM AUTHOR]

This paper presents a novel method to compute various measures of effectiveness (MOEs) at a signalized intersection using vehicle trajectory data collected by flying drones. Specifically, this study investigates the use of drone raw data at a busy three-way signalized intersection in Athens, Greece, and builds on the open data initiative of the pNEUMA experiment. Using a microscopic approach and shockwave analysis on data extracted from real-time videos, we estimated the maximum queue length, whether, when, and where a spillback occurred, vehicle stops, vehicle travel time and delay, crash rates, and fuel consumption. The results of the various MOEs were found to be promising. We also demonstrated that estimating MOEs in real-time is achievable using drone data. Such models can track individual vehicle movements within street networks and thus allow the modeler to consider any traffic conditions, ranging from highly under-saturated to highly over-saturated conditions. [ABSTRACT FROM AUTHOR]

Computer vision research involving street and road detection methods usually focuses on driving assistance and autonomous vehicle systems. In this context, street segmentation occurs in real-time, based on images centered on the street. This work, on the other hand, uses street segmentation for urban planning research to classify pavement types of a city or region, which is particularly important for developing countries. For this application, it is needed a dataset with images from various locations for each street. These images are not necessarily centered on the street and include challenges that are not common in street segmentation datasets, such as mixed pavement types and the presence of faults and holes on the street. We implemented a multi-class version of a state-of-the-art segmentation algorithm and adapted it to perform street pavement classification, handling navigation along streets and angle variation to increase the accuracy of the classification. A data augmentation approach is also proposed to use preliminary results from the test instances as new ground truth and increase the amount of training data. A dataset with more than 300,000 images from 773 streets from a Brazilian city was built. Our approach achieved a precision of 0.93, showing the feasibility of the proposed application. [ABSTRACT FROM AUTHOR]

The transport sector is considered the largest contributor of air pollutants in urban areas, mainly on-road vehicles, affecting the environment and human health. Bahía Blanca is a medium-sized Latin American city, with high levels of traffic in the downtown area during peak hours. In this regard, it is necessary to analyze air pollution using an air quality model considering that there are no air pollutant measurements in the central area. Furthermore, this type of study has not been carried out in the region and since the city is expected to grow, it is necessary to evaluate the current situation in order to make effective future decisions. In this sense, the AERMOD model (US-EPA version) and the RLINE source type were used in this work. This study analyzes the variations of pollutant concentrations coming from mobile sources in Bahía Blanca's downtown area, particularly carbon monoxide (CO) and nitrogen oxides (NOx) during the period Jul-2020 to Jun-2022. It is interesting to note the results show the maximum concentration values detected are not directly associated with maximum levels of vehicle flow or emission rates, which highlights the importance of meteorological parameters in the modeling. In addition, alternative scenarios are proposed and analyzed from a sustainable approach. Regarding the scenario analysis, it can be concluded that diesel vehicles have a large influence on NOx emissions. Moreover, restrictions as strict as those proposed for a Low Emission Zone would be less applicable in the city than alternative temporary measures that modify traffic at peak hours. [ABSTRACT FROM AUTHOR]

This paper takes the central area of Shenzhen as an example to explore the correlation and differences between 2D and 3D green spaces on urban roads during the summer of 2023. By collecting street view image data and using convolutional neural networks for image semantic segmentation, the Green View Index (GVI) was calculated and combined with the Normalized Difference Vegetation Index (NDVI) for analysis. The results show that the road greening levels in Nanshan District, Futian District, and Luohu District of Shenzhen are relatively high, with GVI exceeding 25%. The Pearson correlation coefficient between the 2D and 3D greening data is 0.5818, indicating a moderate correlation. By analyzing four typical greening scenarios (high NDVI and high GVI, high NDVI and low GVI, low NDVI and high GVI, and low NDVI and low GVI), the study found specific reasons for the differences in green data in different dimensions; the analysis revealed that factors such as building height, density, and elevated transportation facilities significantly affect the accuracy of NDVI in urban spaces. The study suggests that in urban greening assessments, the complementarity and differences between street view data and remote sensing data should be comprehensively considered to improve the accuracy and comprehensiveness of the analysis. [ABSTRACT FROM AUTHOR]

In developing countries such as India, Bengaluru city has experienced extraordinary growth in vehicle traffic on arterial roads, causing intersections to operate over capacity under mixed traffic conditions. The speed on urban streets in central business district areas is lower than 15 kmph during peak hours. One of the main routes connecting the airport to the central business district is also vulnerable to this problem. Therefore, providing an alternative route to divert traffic from the mainstream is critical. This study's main goal is to identify alternate routes from Majestic to the airport using remote sensing and a geographic information system, and then evaluate those alternates using the Fuzzy‐TOPSIS approach. This study has used the GIS Arc software application to select the alternative while taking numerous factors such as time, speed, distance, environmental impact, and economic feasibility into consideration. The video graphic and moving car observer methods have been used for the extraction of data for the inventory of the existing route, while the geo image processing tool has been used to analyze alternative routes in the Bengaluru metropolitan area (BMA). The analysis has shown that the alternative route has a lesser travel time of 2 h 30 min in public transit and 1 h 30 min in private mode. The future scope of the study is to compare the alternative and the most suitable routes to divert traffic. Another public transport route network could be developed to minimize the external incoming vehicles in BMA, particularly to reach the airport on urban roads under heterogeneous traffic conditions. [ABSTRACT FROM AUTHOR]

Pedestrian vitality in commercial streets is influenced by various factors, among which the spatial form of the street and the resulting thermal environment have a significant impact. This study, from the perspective of thermal comfort, combines thermal comfort simulation with pedestrian simulation to establish an optimization model based on pedestrian vitality. The model aims to analyze and quantify the impact of street spatial form on thermal comfort and pedestrian vitality, providing a comprehensive evaluation of optimization schemes for commercial street spaces. Firstly, the study identifies the levels of spatial design parameters for commercial streets and generates optimized design scenarios for commercial street spaces. Using the simulation platforms Rhino 7 Grasshopper and MATLAB R2023a, a pedestrian simulation model guided by thermal comfort is constructed and validated against empirical data. Next, the influence of commercial street spatial design parameters on store visitations is assessed, identifying the most critical design parameters. Finally, design strategies for commercial streets are proposed based on vitality-oriented layouts. The results indicate that the spatial form of the street significantly affects store visitations, with the street width-to-height ratio being the most influential factor, followed by street orientation and interface form. NW-SE-oriented streets show a 47.2% higher Total Store Visitations (TSV) value compared to E-W-oriented streets, while E-W streets exhibit a Differential Store Visitation (DSV) value 4.47 times that of NW-SE streets. Streets with a W/H ratio of 0.25 have a 54.9% higher Total Store Visitations value than those with a W/H ratio of 0.9, and streets with a W/H ratio of 0.65 exhibit a Differential Store Visitations value 1.21 times that of streets with a W/H ratio of 0.25. Considering overall street vitality, the study recommends NW-SE- and NE-SW-oriented streets, with a width-to-height ratio between 0.25 and 0.4. The study also proposes strategies for the modification and expansion of streets in different orientations, providing the scientific basis and optimization recommendations for the planning and renovation of commercial streets in cold regions during summer. [ABSTRACT FROM AUTHOR]

There is a potential to allocate road space dynamically over time when demands are complementary or disputed. A workshop with experts was performed to discuss the practicability of implementing dynamic solutions in urban areas. The workshop aimed to identify possible dynamic solutions, select streets for intervention, and systematize and rank street-level criteria for different dynamic road space allocation solutions. The results suggest that street-level site selection criteria can be classified into three typologies (functional, geometric, and layout) and vary across solutions. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Beijing University of Civil Engineering & Architecture is the property of Journal of Beijing University of Civil Engineering & Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The built environment's impact on human activities has been a hot issue in urban research. Compared to motorized spaces, the built environment of pedestrian and cycling street spaces dramatically influences people's travel experience and travel mode choice. The streets' built environment data play a vital role in urban design and management. However, the multi-source, heterogeneous, and massive data acquisition methods and tools for the built environment have become obstacles for urban design and management. To better realize the data acquisition and for deeper understanding of the urban built environment, this study develops a new portable, low-cost Arduino-based multi-sensor array integrated into a single portable unit for built environment measurements of street cycling spaces. The system consists of five sensors and an Arduino Mega board, aimed at measuring the characteristics of the street cycling space. It takes air quality, human sensation, road quality, and greenery as the detection objects. An integrated particulate matter laser sensor, a light intensity sensor, a temperature and humidity sensor, noise sensors, and an 8K panoramic camera are used for multi-source data acquisition in the street. The device has a mobile power supply display and a secure digital card to improve its portability. The study took Beijing as a sample case. A total of 127.97 G of video data and 4794 Kb of txt records were acquired in 36 working hours using the street built environment data acquisition device. The efficiency rose to 8474.21% compared to last year. As an alternative to conventional hardware used for this similar purpose, the device avoids the need to carry multiple types and models of sensing devices, making it possible to target multi-sensor data-based street built environment research. Second, the device's power and storage capabilities make it portable, independent, and scalable, accelerating self-motivated development. Third, it dramatically reduces the cost. The device provides a methodological and technological basis for conceptualizing new research scenarios and potential applications. [ABSTRACT FROM AUTHOR]

The living vegetation volume (LVV) can accurately describe the spatial structure of greening trees and quantitatively represent the relationship between this greening and its environment. Because of the mostly line shape distribution and the complex species of street trees, as well as interference from artificial objects, current LVV survey methods are normally limited in their efficiency and accuracy. In this study, we propose an improved methodology based on vehicle-mounted LiDAR data to estimate the LVV of urban street trees. First, a point-cloud-based CSP (comparative shortest-path) algorithm was used to segment the individual tree point clouds, and an artificial objects and low shrubs identification algorithm was developed to extract the street trees. Second, a DBSCAN (density-based spatial clustering of applications with noise) algorithm was utilized to remove the branch point clouds, and a bottom-up slicing method combined with the random sampling consistency iterative method algorithm (RANSAC) was employed to calculate the diameters of the tree trunks and obtain the canopy by comparing the variation in trunk diameters in the vertical direction. Finally, an envelope was fitted to the canopy point cloud using the adaptive AlphaShape algorithm to calculate the LVVs and their ecological benefits (e.g., O2 production and CO2 absorption). The results show that the CSP algorithm had a relatively high overall accuracy in segmenting individual trees (overall accuracy = 95.8%). The accuracies of the tree height and DBH extraction based on vehicle-mounted LiDAR point clouds were 1.66~3.92% (rRMSE) and 4.23~15.37% (rRMSE), respectively. For the plots on Zijin Mountain, the LVV contribution by the maple poplar was the highest (1049.667 m3), followed by the sycamore tree species (557.907 m3), and privet's was the lowest (16.681 m3). [ABSTRACT FROM AUTHOR]

There are two standard methods in instance segmentation: top-down and bottom-up. The top-down approach performs object detection to generate candidate proposals and then performs pixel-level segmentation for each proposal. It is accurate and flexible, capable of handling objects of different sizes and shapes. However, it is computationally complex and relies on object detection accuracy. The bottom-up approach first performs pixel-level clustering or segmentation and then combines candidate instances to obtain the final segmentation result. It can handle overlapping cases and has lower computational complexity, but it may need to localize accurately, and segment instances, and the segmentation granularity is coarser. In this paper, the Urban Street Scene Instance Segmentation (UISNet) algorithm is proposed. Firstly, the feature extraction network is the foundation of UISNet, which uses EfficientNet as the backbone network. Secondly, MPAFPN is the feature pyramid network part of UISNet, used for multi-scale feature fusion. By using EfficientNet and MPAFPN as the backbone network and bottleneck layers, the accuracy of UISNet is improved by 4% compared to ResNet and FPN. In the inference phase, this paper introduces an innovative dual-branch design that combines top-down and bottom-up strategies. One branch is the bounding box aggregation branch, which generates highdimensional information such as the shape and orientation of bounding boxes based on the FCOS Head. The other branch is the mask decoding branch, which creates mask prediction results. These two branches are fused using the Mask FCN Header to obtain the final instance segmentation result. With this dual-branch design, the model can effectively utilize the information from both top-down and bottom-up approaches, thereby improving the accuracy and robustness of instance segmentation. Through experimental comparisons, the proposed network model in this paper achieves the best performance in terms of accuracy compared to other instance segmentation networks, with an accuracy of 36.28%. Moreover, the proposed model performs better in urban street scenes, enhancing object detection and segmentation and offering more reliable and efficient solutions for applications such as autonomous driving and intelligent transportation. [ABSTRACT FROM AUTHOR]

This study investigates the efficacy of an open vocabulary, multi-modal, foundation model for the semantic segmentation of images from complex urban street scenes. Unlike traditional models reliant on predefined category sets, Grounded SAM uses arbitrary textual inputs for category definition, offering enhanced flexibility and adaptability. The model's performance was evaluated across single and multiple category tasks using the benchmark datasets Cityscapes, BDD100K, GTA5, and KITTI. The study focused on the impact of textual input refinement and the challenges of classifying visually similar categories. Results indicate strong performance in single-category segmentation but highlighted difficulties in multi-category scenarios, particularly with categories bearing close textual or visual resemblances. Adjustments in textual prompts significantly improved detection accuracy, though challenges persisted in distinguishing between visually similar objects such as buses and trains. Comparative analysis with state-of-the-art models revealed Grounded SAM's competitive performance, particularly notable given its direct inference capability without extensive dataset-specific training. This feature is advantageous for resource-limited applications. The study concludes that while open vocabulary models such as Grounded SAM mark a significant advancement in semantic segmentation, further improvements in integrating image and text processing are essential for better performance in complex scenarios. [ABSTRACT FROM AUTHOR]

As one of the classic tasks in information retrieval, the core of image retrieval is to identify the images sharing similar features with a query image, aiming to enable users to find the required information from a large number of images conveniently. Street view image retrieval, in particular, finds extensive applications in many fields, such as improvements to navigation and mapping services, formulation of urban development planning scheme, and analysis of historical evolution of buildings. However, the intricate foreground and background details in street view images, coupled with a lack of attribute annotations, render it among the most challenging issues in practical applications. Current image retrieval research mainly uses the visual model that is completely dependent on the image visual features, and the multimodal learning model that necessitates additional data sources (e.g., annotated text). Yet, creating annotated datasets is expensive, and street view images, which contain a large amount of scene texts themselves, are often unannotated. Therefore, this paper proposes a deep unsupervised learning algorithm that combines visual and text features from image data for improving the accuracy of street view image retrieval. Specifically, we employ text detection algorithms to identify scene text, utilize the Pyramidal Histogram of Characters encoding predictor model to extract text information from images, deploy deep convolutional neural networks for visual feature extraction, and incorporate a contrastive learning module for image retrieval. Upon testing across three street view image datasets, the results demonstrate that our model holds certain advantages over the state‐of‐the‐art multimodal models pre‐trained on extensive datasets, characterized by fewer parameters and lower floating point operations. Code and data are available at https://github.com/nwuSY/svtRetrieval. [ABSTRACT FROM AUTHOR]

Graph theory effectively explains urban structures via street--street connectivity. However, systematic comparisons of street structures across cities remain challenging. This study employs graph convolutional networks (GCNs) to analyze street network structures. A two-branch GCN was used as the backbone to extract comparable features among street networks. The proposed approach was used to examine the structures of different urban road networks in a case study of polycentricity prediction across 298 Chinese cities. The model transformed approximately 4.5-million street segments into natural streets to create urban street graphs, which were subsequently analyzed to extract local and global embeddings. The extracted embeddings -- with a portion labeled with a known urban polycentricity score -- were used to predict the score for each city through a single-layer perceptron (SLP) model. Our results show consistency between the predicted polycentricity scores based on the derived street embeddings and those based on the population. Thus, the proposed GCN-based method can effectively predict the complexity and interconnection of street networks in different cities. This innovative integration of GCNs into urban studies demonstrates that deep learning techniques can analyze and comprehend the intricate patterns of street networks on a large scale. [ABSTRACT FROM AUTHOR]

Copyright of New Architecture is the property of New Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A limited number of meteorological stations and sparse data challenge microclimate assessment in urban areas. Therefore, it is necessary to complement these data with additional measurements to achieve a denser spatial coverage, enabling a detailed representation of the city's microclimatic features. In this study, conducted in Zagreb, Croatia, mobile air temperature measurements were utilized and compared with satellite-derived land surface temperature (LST). Here, air temperature measurements were carried out using bicycles and an instrument with a GPS receiver and temperature probe during a heat wave in June 2021, capturing the spatial pattern of air temperature to highlight the city's microclimate characteristics (i.e. urban heat load; UHL) in extremely hot weather conditions. Simultaneously, remotely sensed LST was retrieved from the Landsat-8 satellite. Air temperature measurements were compared to city-specific street type classification, while neighbourhood heat load characteristics were analysed based on local climate zones (LCZ) and LST. Results indicated significant thermal differences between surface types and urban forms and between street types and LCZs. Air temperatures reached up to 35 °C, while LST exceeded 40 °C. City parks, tree-lined streets and areas near blue infrastructure were 1.5–3 °C cooler than densely built areas. Temperature contrasts between LCZs in terms of median LST were more emphasised and reached 9 °C between some classes. These findings highlight the importance of preserving green areas to reduce UHL and enhance urban resilience. Here, exemplified by the city of Zagreb, it has been demonstrated that the use of multiple datasets allows a comprehensive understanding of temperature patterns and their implications for urban climate research. [ABSTRACT FROM AUTHOR]

The original Cerdà plan (Pla Cerdà) of 1855 for the extension of Barcelona is famous for its grid array of large blocks and wide streets to promote circulation. Each block was originally intended to have an area of open space in the center to provide for the needs of residents. Already by the 1920s, however, the center of the blocks had been filled with buildings. Barcelona currently suffers from a chronic lack of open space, excess noise, and air pollution that exceeds European Union law. This article aims to trace the agency of play as a dynamic process in urban planning to provide new sources of open space through Superblocks (aka Superillas and Supermanzanas). We begin with a brief history of their implementation in the city of Barcelona and the evolution of their justification from the 1990s onward. We then explain the capacity for urban transformation that Superblocks have and how they can modify the urban mobility model and the public space model. We then analyze the role of different forms of play that are used in the area of Poblenou to suggest how play can be used to increase the legitimacy of public participation. Finally, we observe the contingent role of play within urban socialization and in motivating and shaping the urban planning processes of implementing Superblocks. [ABSTRACT FROM AUTHOR]

Cities are complex spaces of contesting infrastructures, media, humans and more-than-human interactions. They are places that house multiple visible and invisible cartographies that draw on multisensorial ways of being in the world. In the city, our senses are amplified and intensified in ways that reorient our processes of worlding. Cities have, more recently, been defined and approached as spaces for play. In this article, we explore how understanding the city as a playground—or through the activity of playgrounding—can invite new ways of designing urban games and playful interventions that acknowledge the uneven and multisensorial ways we inhabit the world. We reflect upon dominant, innovative, and interventionist ideas of playgrounds and notions such as the playful or playable city. We then reflect on findings from a placemaking game workshop designed around the Spanish Superillas (superblocks) in Barcelona. Superillas are playgrounds designed into street intersections that have transformed specific sections of the city in a playground. What does it mean to think about the city as a playground? Can this speculation/ provocation help us rethink the city in more inclusive and sensorial ways? [ABSTRACT FROM AUTHOR]

Commercial pedestrian streets significantly enhance urban life. Previous research often depends on limited survey data or subjective evaluations, which fail to fully capture the impact of street elements on spatial vitality under diverse spatiotemporal conditions. This study, conducted in Beijing's Sanlitun commercial district, analyzes pedestrian data from six branch roads collected via WiFi detection to determine how various spatial elements influence the vibrancy of commercial pedestrian streets. The results show a positive correlation between street width, ranging from 5.88 to 10.83 m, and vitality. Furthermore, the influence of different street elements on vitality varies notably. During the daytime, street width is the most effective element for enhancing vitality, with a maximum standardized coefficient of 1.717. However, at night, the associations between advertising area, store type, and vitality diminish. The street recording the highest nighttime vitality peaked at a pedestrian count of 91.7831. The contribution of street width to enhancing nighttime vitality is 2.49 times greater than at noon on non-working days, 2.01 times more than on working days, and 2.92 times higher than the impact of tables and chairs. Therefore, street design should prioritize street width, ground floor interface permeability, number of tables and chairs, store density, advertising area, and store type. [ABSTRACT FROM AUTHOR]

Morphological structures of urban streets in Baghdad have been deciphered by using practical methodologies inclusive of data collection, digitization, and identification processes. This paper uses street pattern morphological analysis in a typical Middle Eastern city, in this case, Baghdad, from organic configurations to modern metropolitan sprawl. It is based on historical maps and satellite images, supported by field surveys. Six distinct street patterns have been identified that have influenced the formation of Baghdad’s urban development and continuity, focusing attention on the ancient city configuration and current planning principles. Of great interest is the fact that there are calls for the retention of the urbanism historical fabric in the cities with new growth at the same time there are calls for methodologies that are responsive to the sociocultural energy characteristic of the cities in the Middle East. This study adds to the general body of literature on urban morphology and further provides detailed insight into the morphology of streets in Baghdad and other similar towns. The research, therefore, shows evidence of the need for recognizing street morphology roles in the form and function of urban landscapes and will advocate for environments reflective of historical context in line with the needs that modern urban life requires. Results will demonstrate how streets change based on influences from culture and socio-economic factors. They conclude that streets developed in the light of cumulative processes, directions, and scales of development. This research is taken up to comprehend urban morphology leading towards sustainable and culturally responsive designs.