Open Streets Research Articles

The impact of the built environment on human mobility patterns during Covid-19: A study of New York City's Open Streets Program

This study uses the Open Streets Program in New York City as a natural experiment to test the effects of change in street use on foot traffic changes during COVID-19. In a two-stage-least-squares (2SLS) design, the Open Streets Program is used as an instrumental variable to isolate the exogenous effect of expanded streets for pedestrians on foot traffic patterns. We then estimate a difference-in-differences model that compares the change in foot traffic to public points-of-interests (POI) in neighborhoods that are part of the Open Streets Program with those that are not “before and after” the start of the city-wide program, in addition to other controls such as street types and weather characteristics to help reduce the error variance of the regression. We find that the Open Streets Program helped increase pedestrian activity at a neighborhood level, even when controlling for street types and other confounding temporal factors such as precipitation and temperature.

The influence of two and three-dimensional spatial characteristics of industrial parks on the emotional well-being of employees: A case study of Shenzhen

Enhancing the emotions of the workers within industrial parks is crucial for achieving the sustainable development goal (SDG). However, evidence on the impact of industrial park environmental layouts on emotions is limited due to the low attention on the workers in the industrial park. Based on a framework of two-dimensional (2D) industrial park morphology indicators and three-dimensional (3D) spatial objective perception, this study aims to compare and analyze the effect of environmental characteristics in Shenzhen's industrial parks on workers' emotions by using emotional geography and social media data. The potential mechanism that environmental characteristic variables influence the positive emotion index (PEI) is also explored. Using the natural language processing (NLP) to analyze the Weibo check-in data, the study captures the daily emotions of workers in industrial parks. By adopting the linear and spatial regression models, this research reveals the complex relationship between the environmental layout of the total 425 industrial parks in Shenzhen city and the corresponding emotions of the workers. The conclusions are as follows: (1) There is a significant correlation between the environmental layout of the industrial parks and the emotions of the workers, with the correlation among 3D variables being higher than that among 2D variables considering spatial effects. (2) There is a certain degree of coordination and contradiction between the morphological indicators of the industrial parks and the spatial objective perception variables, necessitating the planners to consider both macro-scale and micro-perception environmental characteristics to enhance the workers' emotions. (3) In addition to higher accessibility and more public transportation options, the safer, wider, relatively more open streets, more perceivable green spaces, and richer street life can promote the positive emotions among the workers. On the contrary, the enclosed environments, the dense and overwhelming buildings, and the excessive road density may lead to negative emotions. This study contributes to establish the environmental layouts for the industrial parks that foster positive worker emotions and offer insights for the sustainable development of the industrial parks.

Health benefits of Open Streets programmes in Latin America: a quantitative health impact assessment

Health benefits of Open Streets programmes in Latin America: a quantitative health impact assessment

Analyzing the effects of streetscape and land use on urban accidents and predicting future accidents by using machine learning algorithms (case study: Mashhad)

In general, land use and layout of streets can have a significant impact on the behavior of drivers and pedestrians. In particular, streetscape has often been overlooked that recognizing the role of streetscape on street accident in urban areas is important. The aim of this research is to investigate the influence of streetscape and land use on urban accidents that occurred in Mashhad between the years 2017 and 2021. To achieve this objective, the study focused on analyzing accidents in three different urban zones. It also considered the land use types adjacent to both closed and open streets, including residential, commercial, and mixed land uses. The research employed various surveys to gather the necessary data and insights related to the targeted areas. Statistics on accident in three zones show that among the mentioned land uses, commercial areas have experienced the highest number of accidents, with their share being approximately three times that of accidents in residential areas. Additionally, 75 % of all accidents took place in areas with open streetscape, whereas accidents in areas with enclosed view accounted for one third of the number of accidents in open streetscape areas. In this research, analysis and modeling were conducted using machine learning algorithms implemented in the Python programming language. Several models were employed, and the best models were selected based on their performance and accuracy, which include Random Forest Regression (RFR), Multilayer Neural Network Perceptron Regression (MLP) and Extreme Boost Gradient Regression (XGBoost). The accuracy of the machine learning models which successfully predicted future outcomes was as follows: Random Forest Regression (RFR) achieved 85 % accuracy, Extreme Boost Gradient Regression (XGBoost) achieved 81 % accuracy, and finally, Neural Network Multilayer Perceptron Regression (MLP) achieved 75 % accuracy.

Radio Propagation Measurements and Statistical Channel Models for Outdoor Urban Microcells in Open Squares and Streets at 142, 73, and 28 GHz

Radio Propagation Measurements and Statistical Channel Models for Outdoor Urban Microcells in Open Squares and Streets at 142, 73, and 28 GHz

I Open at the Close: A Deep Reinforcement Learning Evaluation of Open Streets Initiatives

The open streets initiative "opens" streets to pedestrians and bicyclists by closing them to cars and trucks. The initiative, adopted by many cities across North America, increases community space in urban environments. But could open streets also make cities safer and less congested? We study this question by framing the choice of which streets to open as a reinforcement learning problem. In order to simulate the impact of opening streets, we first compare models for predicting vehicle collisions given network and temporal data. We find that a recurrent graph neural network, leveraging the graph structure and the short-term temporal dependence of the data, gives the best predictive performance. Then, with the ability to simulate collisions and traffic, we frame a reinforcement learning problem to find which streets to open. We compare the streets in the open streets initiative to those proposed by a Q-learning algorithm. We find that the streets proposed by the Q-learning algorithm have reliably better outcomes, while streets already selected by the open streets initiative have similar outcomes to randomly selected streets. We present our work as a step toward principally choosing which streets to open for safer and less congested cities.

Dreaming a better urban future with Open Streets: ideas from three African cities

Dreaming a better urban future with Open Streets: ideas from three African cities

Bacterial contamination of some fruits sold around wastedumps in Owerri metropolis, Nigeria

Analysis of bacterial contamination of fruits sold near waste dumps in Owerri Metropolis were carried out. The various contamination levels on fruits such as; orange (Citru X sinensis), water melon (Citrullus lanatus), apple (Malus pumila), garden egg (Solanum melongena), groundnut (Arachis hypogeaa), pawpaw (Carica papaya) and carbbage. The fruit samples, each were collected near wastedumps in Owerri metropolis. Fruit samples used as control were collected where there was no wastedump. Each of the samples was packaged into plastic bag and labelled. Sixty fruit samples were collected. (Fifty-four of which were collected near waste dumps while six of the fruit samples were used as the control). Microscopic, physical examination and biochemical test were carried out; five bacterial species were isolated in the fruit samples: Isolate A; Bacillus Subtills, Isolate B; E. coli; Isolate C; Samonella spp, Isolate D; Staphlacocus spp and Isolate E: Klebsiella spp. The results indicate that there were bacterial loads in the fruit samples at each sampling point. The total bacterial loads in the fruits samples ware 1.05x 105 Cfu. This buttress the fact the wastedump maybe contributing to the level of bacterial in the fruit sold around it. The study recommends that Government should stop people from dumping refuse on open market streets rather trucks should be provided to be carrying refuse from various Locations and take them to the approved dumpsites. People selling fruit should be encouraged to display the fruits on a the table and not a the ground where it can be contaminated.

Convective Steady State in Shallow Cloud Fields.

Shallow cloud fields exhibit different patterns, such as closed or open hexagonal cells and cloud streets. These patterns play a key role in determining the cloud fields' radiative effects, thereby affecting the climate. Here, we show that a large subset of shallow cloud fields forms organized, mesoscale-sized, regular patterns that persist for extended times. It emanates from the steady state of the underlying rigid configuration of convection cells. From a climate perspective, in a sea of cloud complexity, the convective steady-state provides an "island of simplicity." The convective steady state can be parametrized in climate models to better capture the feedback of such cloud fields in a warming climate.

Mapping the Multi-Vulnerabilities of Outdoor Places to Enhance the Resilience of Historic Urban Districts: The Case of the Apulian Region Exposed to Slow and Rapid-Onset Disasters

Recent critical events brought attention to the increasing exposure of urban environments to both slow and rapid onset disasters, which arise from both anthropogenic and natural causes. These events have particularly severe effects on historic centres, which are characterized by high levels of vulnerability and valuable assets exposed to risk. To minimize the impact on tangible and intangible cultural heritage values, especially in outdoor public areas such as squares and streets, it is crucial to establish coherent mitigative and adaptive solutions for different types of hazards. This research presents a methodology aimed at defining levels of multi-vulnerabilities in historic districts in the Apulia Region (Italy), considering the recurrent hazards to which the latter is prone. It uses a multi-step process based on structured and non-structured methodologies and tools for single risks, examined in combination, to determine the main properties characterizing the vulnerability assessment. The dataset was analyzed in a GIS environment to evaluate the selected Apulian case study (Molfetta) in Multi-Asynchronous Hazard scenarios, showing the compounded levels of criticalities for open areas and streets. This information is intended to support authority and emergency managers in identifying priority interventions and increasing the resilience of the outdoor public places.

Analysis of urban streets and surface thermal characteristics using thermal imaging camera in residential streets of Gurugram City, India.

The thermal properties of the urban landscape are significantly affected by various human activities such as changing land use patterns, the construction of buildings and other impervious surfaces, and the development of transport systems. Urbanization often leads to the replacement of natural landscapes with impervious surfaces such as concrete and asphalt, which have a higher heat absorption capacity and lower emissivity. The continuous displacement of urban landscapes by impermeable surfaces therefore leads to an increase in urban temperatures, ultimately causing the development of the urban heat island (UHI) phenomenon. The study aims to analyze the thermal properties of physical elements in residential streets of Gurugram City using a thermal imaging camera to investigate the relationship between ambient air temperature and thermal behavior of surface materials. The study shows that the compact streets are 2-4 °C cooler than the open streets due to mutual shading of the buildings. Similarly, the temperature in the light-colored buildings is 1.5-4 °C lower than the dark buildings in the streets. In addition, a simple coat of paint over a plastered wall is much cooler than granite stone wall cladding. The study also showed how shading, whether by mutual shading or vegetative shading, can lower the surface temperature of urban materials. Building codes and design guidelines can therefore use such studies to make urban exteriors more pleasant by recommending lighter colors, plants, and local materials.

Health benefits of Open Streets programmes in Latin America: a quantitative health impact assessment

To improve physical activity in Latin American cities, several interventions have been promoted, such as Open Streets programmes. Our study aims to quantify the health and economic effects of Open Streets-related physical activity in 15 Latin American cities. We used a quantitative health impact assessment approach to estimate annual premature deaths and disease incidence (ischaemic heart disease, ischaemic stroke, type 2 diabetes, colon cancer, breast cancer, and dementia) avoided, the disability-adjusted life-years (DALYs) gained, and the cost saving (from reduced premature mortality) related to increased physical activity from Open Streets programmes in 15 Latin American cities. Input data were obtained from scientific publications, reports, and open street city surveys spanning 2017 to 2019. Physical activity data were converted to metabolic equivalent of the task. Exposure-response relationship functions were applied to estimate relative risk and population-attributable fraction, enabling the assessment of premature deaths and disease incidence. The percentage of male users of the Open Streets programmes ranged from 55% (27 500 of 50 000 in Guatemala) to 75% (2250 of 3000 in El Alto, Bolivia), and female users ranged from 25% (750; El Alto) to 45% (22 500; Guatemala). We estimated that the current Open Streets programmes in the 15 Latin American cities studied could prevent 363 (95% CI 271-494) annual premature deaths due to increased physical activity, with an annual economic impact of US$194·1 million (144·9 million-263·9 million) saved and an annual reduction of 1036·7 DALYs (346·7-1778·3). If one Open Streets event is added per week in each of those cities, the potential benefit could increase to 496 (370 to 677) premature deaths prevented each year. Open Streets programmes in Latin America can provide health and economic benefits related to increased physical activity and can be used as a health promotion and disease prevention tool. EU's Horizon 2020 research and innovation programme.

No justice, no streets: The complex task of evaluating environmental justice on open streets in three U.S. cities

ABSTRACT In this paper, we study open street initiatives through a holistic definition of environmental justice, shedding light on three potential paradoxes of such initiatives: the engagement, hegemony, and displacement paradoxes. We use a mixed-methods approach integrating interviews and spatial analyses, focusing on three cities with permanent programs: Denver, Oakland, and Seattle. Our findings for the engagement paradox show that cities with existing equity planning relationships were better suited to address procedural justice tensions between the need to act swiftly due to the COVID-19 pandemic and the necessity to adequately engage racially/ethnically minoritized communities in planning open streets. For the hegemony paradox, we find a tension between distributional and recognitional justice, wherein open streets might have been available in minoritized communities but such streets did not meet their needs. In the displacement paradox, respondents suggested that green gentrification concerns were a barrier to the equitable implementation of open streets.

Assessing impacts of objective features and subjective perceptions of street environment on running amount: A case study of Boston

The built environment is found to relate to running behaviors. However, the impacts of the street environment on running were less addressed due to the lack of running data in large geospatial urban regions, while the potential of semi-open data sources like Strava Heatmap for running studies is rarely verified. Moreover, how objective features and the subjective perceptions of the street environment are related to running is still largely unknown. We hypothesize that the eye-level subjective and objective streetscapes may complement the macro-scale built environment factors to better inform running amount prediction. Therefore, we evaluated the associations between running and street attributes by applying multi-sourced data, street view imagery (SVI) and artificial intelligence (AI) technologies, taking Boston as an example. We found that, first, the street environment is significantly correlated with running. Accounting for the spatial effects, the collective strength of street attributes was almost the same as the counterpart of the built environment, validating the value of including subjective and objective streetscapes measures in running studies. Second, street factors can complement built environment factors, indicating the necessity of using both macro-scale and eye-level environmental features to interpret running. Third, in addition to higher accessibility and more public transportation, the safer, wider and relatively open streets with more natural views, street lights, amenities and furniture, could promote running, while the enclosed environment, dense and overwhelming buildings, excessive interruptions on streets might hinder running. Our study provides an important example of using semi-open running data and integrating multi-sourced data and AI to bring new insights into running and urban environment studies. The findings could provide instructive suggestions for the establishment of a running-friendly urban environment and ultimately help to improve public health.

Unintended impacts of the Open Streets program on noise complaints in New York City

BackgroundDuring the COVID-19 pandemic, several cities allocated more public spaces for physical activity and recreation instead of road transport through Open Streets. This policy locally reduces traffic and provides experimental testbeds for healthier cities. However, it may also generate unintended impacts. For instance, Open Streets may impact the levels of exposure to environmental noise but there are no studies assessing these unintended impacts. ObjectivesUsing noise complaints from New York City (NYC) as a proxy of annoyance caused by environmental noise, we estimated associations at the census tract level between same-day proportion of Open Streets in a census tract and noise complaints in NYC. MethodsUsing data from summer 2019 (pre-implementation) and summer 2021 (post-implementation), we fit regressions to estimate the association between census tract-level proportion of Open Streets and daily noise complaints, with random effects to account for within-tract correlation and natural splines to allow non-linearity in the estimated association. We accounted for temporal trends and other potential confounders, such as population density and poverty rate. ResultsIn adjusted analyses, daily street/sidewalk noise complaints were nonlinearly associated with an increasing proportion of Open Streets. Specifically, compared to the mean proportion of Open Streets in a census tract (0.11%), 5% of Open Streets had a 1.09 (95% CI: 0.98, 1.20) and 10% had a 1.21 (95% CI: 1.04, 1.42) times higher rate of street/sidewalk noise complaints. Our results were robust to the choice of data source for identifying Open Streets. ConclusionOur findings suggest that Open Streets in NYC may be linked to an increase in street/sidewalk noise complaints. These results highlight the necessity to reinforce urban policies with a careful analysis for potential unintended impacts to optimize and maximize the benefits of these policies.

Transforming Streets into Public Spaces Using Menged Le Sew as a Driver

Addis Ababa, the traffic-choked capital of Ethiopia with an ever-growing population, faces an urban crisis regarding road safety and mobility in recent years. To tackle these challenges, the government of Ethiopia and collaborative stakeholders launched a movement called Menged Le Sew (Streets for People), which takes place once a month since December 2018 in Addis Ababa and a few other cities in Ethiopia. The government's strategy to restrict cars once a month gives people an opportunity to reclaim public spaces. Residents of the cities use the open streets for different activities such as, participating in various sports, exercising, health campaigns, active mobility, and serving as a playground for children. To further promote the campaign nationwide and increase its longevity and aimed at serving as a guidebook for stakeholders organizing similar Menged Le Sew events, a toolkit was recently developed and launched by the Addis Ababa Traffic Management Agency and the World Resources Institute, Africa. However, the complexity of urban mobility, rising urbanization, and cross-sectoral interdependence necessitate a management strategy that blends new forms of governance and cooperation while emphasizing public participation to find and execute strategies to promote systemic change. Even though the movement has already started bearing fruit, to make the gains more sustainable and to race with the extremely growing mobility and urbanization challenges, this paper suggests a new framework and strategies of street experiments, taking the already existing and widely accepted movement (Menged Le Sew) as a potential ground. The study introduces the urbanization and mobility crisis in the country, then discusses the context of car-free days as a pathway for the sociotechnical transition towards sustainable mobility and proposes a framework for the actualization of this transition.

Measuring the perceptual features of coastal streets: a case study in Qingdao, China

The coastal streets are the most attractive urban space, improving spatial quality and public perception of coastal streets is an important work of urban regeneration. The study used machine learning semantic segmentation, GIS and Semantic difference (SD) etc methods to obtain the spatial data and perceptual evaluation of coastal streets in Qingdao. Each of the six perceptual features, imageability, enclosure, human scale, transparency, complexity and nature, was taken as dependent variables and the corresponding physical features was taken as independent variables. The six regression models were established and the influence rules of spatial parameters on public perception were obtained. Meanwhile, based on the results of perceptual features evaluation, the overall coastal streets are divided into three types, open streets, mixed streets and biophilic streets. In all the three types coastal streets, the nature was the most significant perceptual feature due to the high greenness; the complexity was the lowest perceptual feature because of the low landscape diversity. The research results provided theoretical and technical support for the urban regeneration and spatial quality improvement of coastal streets in Qingdao.

The designed and the ad hoc: dynamic remakings of street space in New York City

Most people in the United States began to alter their decisions and actions beginning in March 2020 due to the Covid-19 pandemic, when the closures and ‘pause’ on most work were established. Studying the transforming urban conditions in New York City specifically presents a lens through which to understand how we quickly adapted to new spatial conditions as measures were put in place for keeping people healthy and encouraging businesses to stay open and approachable. Immediately, the need for social distancing asked us to consider how to navigate exposure as we moved beyond the home. Necessities for businesses to survive became a priority for the city and coalesced with people’s desire for seeking ways to do things outdoors. A focus on using city streets as urban public spaces resulted. Policies such as Open Restaurants and Open Streets were developed by the Department of Transportation to mitigate pandemic circumstances and to stir dynamic and optimistic possibilities for street use. Open Restaurants called for food/drink establishments to quickly reimagine their adjacent pavement or available street space. Open Streets initiated new ways for creating pedestrian zones in previously trafficked areas. This article highlights fieldwork documentation comparing a Cluster and Line of food/drink establishments with a newly pedestrian Avenue, in connected Brooklyn neighbourhoods. Diagrams, photographs and maps document the ingenious street constructions and the observed and felt psychological or phenomenal transformations taking place. An urban interiorism grew out of the imposed formalisation of rules for movement patterns and compact constructions, while the ad hoc or serendipitous conditions allowed for other intimate conditions. Notions of ‘village cafés’ or ‘urban beaches’ evolved through myriad forms and materials inviting unusual seating configurations and interactions. Speculations on what these internal/external spatial experiences, changing identities and continued urban freedoms are teaching us are also explored through a multidisciplinary set of voices.

Unintended impacts of the Open Streets program on noise complaints in New York City

Background and Aim: Exposure to high levels of environmental noise and noise annoyance have been associated with detrimental health outcomes. In 2012, a campaign in New York City (NYC) measured noise levels frequently exceeding recommended standards. Noise complaints have been used as a proxy of noise annoyance and exposure. NYC has been opening parts of its street network to recreation and physical activity through the Open Streets program. We aim to describe the citywide distribution of noise complaints by census tract percentage of Open Streets. Methods: We conducted analyses at the census tract level from 2019 to 2021 across NYC. We used noise complaints from 311 calls for specific locations and times, which we aggregated to daily census tract counts of noise complaints. We focused on two categories of noise complaints that may be impacted by Open Streets: vehicle and street/sidewalk noise complaints. We used a mixed-effects model with random intercepts for census tracts to estimate the association between changes in noise complaints and area covered by Open Streets (%) given tract-level socioeconomic status and street geometry. We allowed for nonlinear exposure–outcome relationships using natural splines. We also carried out sensitivity analyses using data from a citizen’s survey on Open Streets implementation levels gathered by Transportation Alternatives (TA) to assess its impact on model results. Results: Census tracts with increasing use of street space as Open Streets (i.e. higher than 5%) reported more daily street/sidewalk noise complaints. For vehicle noise complaints, 5 to 10% of area covered by Open Streets showed increasing noise complaints but estimates plateaued at higher percentages. The sensitivity analyses using TA implementation data showed that our estimates were fairly robust. Conclusions: Our preliminary results suggest that Open Streets were associated with increases in street/sidewalk noise complaints. Keywords (2-6): Policy, Noise annoyance, Open Streets, Urban planning, Cities

Reconsidering the regulation of facial recognition in public spaces.

This paper contributes to the discussion on effective regulation of facial recognition technologies (FRT) in public spaces. In response to the growing universalization of FRT in the United States and Europe as merely intrusive technology, we propose to distinguish scenarios in which the ethical and social risks of using FRT are unattainable from other scenarios in which FRT can be adjusted to improve our everyday lives. We suggest that the general ban of FRT technologies in public spaces is not an inevitable solution. Instead, we advocate for a risk-based approach with emphasis on different use-cases that weighs moral risks and identifies appropriate countermeasures. We introduce four use-cases that focus on presence of FRT on entrances to public spaces (1) Checking identities in airports (2) Authorisation to enter office buildings (3) Checking visitors in stadiums (4) Monitoring passers-by on open streets, to illustrate the diverse ethical and social concerns and possible responses to them. Based on the different levels of ethical and societal risks and applicability of respective countermeasures, we call for a distinction of public spaces between semi-open public spaces and open public spaces. We suggest that this distinction of public spaces could not only be helpful in more effective regulation and assessment of FRT in public spaces, but also that the knowledge of different risks and countermeasures will lead to better transparency and public awareness of FRT in diverse scenarios.