Way, Thaisa. (2016). The Urban University’s Hybrid Campus. Journal Of Landscape Architecture, 11(1), 42 – 55.
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Abstract
With the growth of urban campuses in the twenty-first century, how can landscape architecture foster the innovation associated with cities and urban neighbourhoods? In Seattle, West Campus at the University of Washington serves as a good urban neighbour while engaging the traditional experiences of a campus. Additionally, the design suggests how an urban campus might generate the culture of an urban innovation district. The contribution of landscapes to innovation districts has rarely been considered in campus design because the focus has been on the architecture of the buildings and the culture of collaboration as social phenomena. This paper explores how the public landscapes of parks, courtyards, and streets shape the experience of an innovation district and contribute to fostering creativity and serendipity. As an extension, the paper suggests the importance of universities in the creation and stewardship of vibrant, creative, and resilient cities.
Keywords
City Planning; Innovation District; Student Residential Planning; University Landscape Design; Urban Campus
Chen, Peng; Hu, Songhua; Shen, Qing; Lin, Hangfei; Xie, Chi. (2019). Estimating Traffic Volume for Local Streets with Imbalanced Data. Transportation Research Record, 2673(3), 598 – 610.
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Abstract
Annual average daily traffic (AADT) is an important measurement used in traffic engineering. Local streets are major components of a road network. However, automatic traffic recorders (ATRs) used to collect AADT are often limited to arterial roads, and such information is, therefore, often unavailable for local streets. Estimating AADT on local streets becomes a necessity as local street traffic continues to grow and the capacity of arterial roads becomes insufficient. A challenge is that an under-represented sample of local street AADT may result in biased estimation. A synthetic minority oversampling technique (SMOTE) is applied to oversample local streets to correct the imbalanced sampling among different road types. A generalized linear mixed model (GLMM) is employed to estimate AADT incorporating various independent variables, including factors of roadway design, socio-demographics, and land use. The model is examined with an AADT dataset from Seattle, WA. Results show that: (1) SMOTE helps to correct imbalanced sampling proportions and improve model performance significantly; (2) the number of lanes and the number of crosswalks are both positively associated with AADT; (3) road segments located in areas with a higher population density or more mixed land use have a higher AADT; (4) distance to the nearest arterial road is negatively correlated with AADT; and (5) AADT creates spatial spillover effects on neighboring road segments. The combination of SMOTE and GLMM improves the estimation accuracy on AADT, which contributes to better data for transportation planning and traffic monitoring, and to cost saving on data collection.
Keywords
Average; Prediction; Network; County
Mooney, Stephen J.; Hurvitz, Philip M.; Moudon, Anne Vernez; Zhou, Chuan; Dalmat, Ronit; Saelens, Brian E. (2020). Residential Neighborhood Features Associated with Objectively Measured Walking Near Home: Revisiting Walkability Using the Automatic Context Measurement Tool (ACMT). Health & Place, 63.
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Abstract
Many distinct characteristics of the social, natural, and built neighborhood environment have been included in walkability measures, and it is unclear which measures best describe the features of a place that support walking. We developed the Automatic Context Measurement Tool, which measures neighborhood environment characteristics from public data for any point location in the United States. We explored these characteristics in home neighborhood environments in relation to walking identified from integrated GPS, accelerometer, and travel log data from 681 residents of King Country, WA. Of 146 neighborhood characteristics, 92 (63%) were associated with walking bout counts after adjustment for individual characteristics and correction for false discovery. The strongest built environment predictor of walking bout count was housing unit count. Models using data-driven and a priori defined walkability measures exhibited similar fit statistics. Walkability measures consisting of different neighborhood characteristic measurements may capture the same underlying variation in neighborhood conditions.
Keywords
Built-environment; Physical-activity; Transit; Density; Obesity; Weight; Time; Gps; American Community Survey; Epa Walkability Index; Neighborhood Environment-wide Association; Study; Walking Bouts
Bogus, Susan M.; Migliaccio, Giovanni C.; Cordova, Arturo A. (2010). Assessment of Data Quality for Evaluations of Manual Pavement Distress. Transportation Research Record, 2170, 1 – 8.
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Abstract
Assessment of the conditions of current assets is a task of major relevance in a transportation agency asset management program It not only provides information on the current condition of the asset but also helps the agency make decisions on future maintenance and rehabilitation activities Although low volume roadways represent a large proportion of the total road network in the United States little research on the management of these assets has been done Two major data collection techniques are used for roadway condition assessment manual and automated Although automated techniques have been found to be safer and quicker manual condition surveys have been proven to offer preciseness and cost effectiveness In the case of low volume roadway assessment for which the funds available to asset managers are limited manual condition surveys are often preferred Nevertheless manual condition surveys must address the potential subjectivity of the results Therefore agencies could benefit from a system for ensuring quality on manual condition surveys This paper proposes a framework for assessment of data quality and presents a case study of its implementation in the Northern New Mexico Pavement Evaluation Program The proposed framework is easily implementable and able to identify potential and actual data collection issues The framework can be used as part of an asset management program and could be particularly beneficial in the case of low volume roads
Keywords
Interrater Reliability; Agreement; Ratings
Drewnowski, Adam; Aggarwal, Anju; Hurvitz, Philip M.; Monsivais, Pablo; Moudon, Anne V. (2012). Obesity and Supermarket Access: Proximity or Price? American Journal Of Public Health, 102(8), e74 – e80.
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Abstract
Objectives. We examined whether physical proximity to supermarkets or supermarket price was more strongly associated with obesity risk. Methods. The Seattle Obesity Study (SOS) collected and geocoded data on home addresses and food shopping destinations for a representative sample of adult residents of King County, Washington. Supermarkets were stratified into 3 price levels based on average cost of the market basket. Sociodemographic and health data were obtained from a telephone survey. Modified Poisson regression was used to test the associations between obesity and supermarket variables. Results. Only 1 in 7 respondents reported shopping at the nearest supermarket. The risk of obesity was not associated with street network distances between home and the nearest supermarket or the supermarket that SOS participants reported as their primary food source. The type of supermarket, by price, was found to be inversely and significantly associated with obesity rates, even after adjusting for individual-level sociodemographic and lifestyle variables, and proximity measures (adjusted relative risk = 0.34; 95% confidence interval = 0.19, 0.63) Conclusions. Improving physical access to supermarkets may be one strategy to deal with the obesity epidemic; improving economic access to healthy foods is another. [ABSTRACT FROM AUTHOR]; Copyright of American Journal of Public Health is the property of American Public Health Association 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.)
Keywords
Natural Foods; Obesity Risk Factors; Surveys; Cluster Analysis (statistics); Confidence Intervals; Correlation (statistics); Food Service; Geographic Information Systems; Poisson Distribution; Population Geography; Research Funding; User Charges; Residential Patterns; Socioeconomic Factors; Relative Medical Risk; Statistical Models; Descriptive Statistics; Economics; Washington (state)
Doescher, Mark P.; Lee, Chanam; Berke, Ethan M.; Adachi-mejia, Anna M.; Lee, Chun-kuen; Stewart, Orion; Patterson, Davis G.; Hurvitz, Philip M.; Carlos, Heather A.; Duncan, Glen E.; Moudon, Anne Vernez. (2014). The Built Environment and Utilitarian Walking in Small U.S. Towns. Preventive Medicine, 69, 80 – 86.
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Abstract
Objectives. The role of the built environment on walking in rural United States (U.S.) locations is not well characterized. We examined self-reported and measured built environment correlates of walking for utilitarian purposes among adult residents of small rural towns. Methods. In 2011-12, we collected telephone survey and geographic data from 2152 adults in 9 small towns from three U.S. regions. We performed mixed-effects logistic regression modeling to examine relationships between built environment measures and utilitarian walking (any versus none; high [>= 150 min per week] versus low [<150 min per week]) to retail, employment and public transit destinations. Results. Walking levels were lower than those reported for populations living in larger metropolitan areas. Environmental factors significantly (p < 0.05) associated with higher odds of utilitarian walking in both models included self-reported presence of crosswalks and pedestrian signals and availability of park/natural recreational areas in the neighborhood, and also objectively measured manufacturing land use. Conclusions. Environmental factors associated with utilitarian walking in cities and suburbs were important in small rural towns. Moreover, manufacturing land use was associated with utilitarian walking. Modifying the built environment of small towns could lead to increased walking in a sizeable segment of the U.S. population. (C) 2014 Elsevier Inc. All rights reserved.
Keywords
Cities & Towns -- Environmental Conditions; Walking; Telephone Surveys; Logistic Regression Analysis; Public Transit; Cities & Towns; Rural Conditions; United States; Exercise/physical Activity; Health Promotion; Physical Environment; Prevention; Rural Health; Social Environment; Physical-activity; Postmenopausal Women; Adults; Health; Risk; Transportation; Associations; Neighborhood; Travel; Determinants
Kang, Bumjoon; Scully, Jason Y.; Stewart, Orion; Hurvitz, Philip M.; Moudon, Anne V. (2015). Split-Match-Aggregate (SMA) Algorithm: Integrating Sidewalk Data with Transportation Network Data in GIS. International Journal Of Geographical Information Science, 29(3), 440 – 453.
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Abstract
Sidewalk geodata are essential to understand walking behavior. However, such geodata are scarce, only available at the local jurisdiction and not at the regional level. If they exist, the data are stored in geometric representational formats without network characteristics such as sidewalk connectivity and completeness. This article presents the Split-Match-Aggregate (SMA) algorithm, which automatically conflates sidewalk information from secondary geometric sidewalk data to existing street network data. The algorithm uses three parameters to determine geometric relationships between sidewalk and street segments: the distance between streets and sidewalk segments; the angle between sidewalk and street segments; and the difference between the lengths of matched sidewalk and street segments. The SMA algorithm was applied in urban King County, WA, to 13 jurisdictions' secondary sidewalk geodata. Parameter values were determined based on agreement rates between results obtained from 72 pre-specified parameter combinations and those of a trained geographic information systems (GIS) analyst using a randomly selected 5% of the 79,928 street segments as a parameter-development sample. The algorithm performed best when the distances between sidewalk and street segments were 12m or less, their angles were 25 degrees or less, and the tolerance was set to 18m, showing an excellent agreement rate of 96.5%. The SMA algorithm was applied to classify sidewalks in the entire study area and it successfully updated sidewalk coverage information on the existing regional-level street network data. The algorithm can be applied for conflating attributes between associated, but geometrically misaligned line data sets in GIS.
Keywords
Geodatabases; Sidewalks; Algorithms; Pedestrians; Digital Mapping; Algorithm; Gis; Pedestrian Network Data; Polyline Conflation; Sidewalk; Built Environment; Physical-activity; Mode Choice; Urban Form; Land-use; Travel; Generation; Walking
Yang, Liya; Shen, Qing; Li, Zhibin. (2016). Comparing Travel Mode and Trip Chain Choices Between Holidays and Weekdays. Transportation Research Part A: Policy & Practice, 91, 273 – 285.
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Abstract
Choices of travel mode and trip chain as well as their interplays have long drawn the interests of researchers. However, few studies have examined the differences in the travel behaviors between holidays and weekdays. This paper compares the choice of travel mode and trip chain between holidays and weekdays tours using travel survey data from Beijing, China. Nested Logit (NL) models with alternative nesting structures are estimated to analyze the decision process of travelers. Results show that there are at least three differences between commuting-based tours on weekdays and non-commuting tours on holidays. First, the decision structures in weekday and holiday tours are opposite. In weekday tours people prefer to decide on trip chain pattern prior to choosing travel mode, whereas in holiday tours travel mode is chosen first. Second, holiday tours show stronger dependency on cars than weekday tours. Third, travelers on holidays are more sensitive to changes in tour time than to the changes in tour cost, while commuters on weekdays are more sensitive to tour cost. Findings are helpful for improving travel activity modeling and designing differential transportation system management strategies for weekdays and holidays. (C) 2016 Elsevier Ltd. All rights reserved.
Keywords
Choice Of Transportation; Transportation Management; Voyages & Travels; Travel Costs; Travel Time (traffic Engineering); Decision Structure; Nested Logit Model; Policy; Travel Behavior; Patterns; Behavior; Time
Chen, Peng; Shen, Qing. (2019). Identifying High-risk Built Environments for Severe Bicycling Injuries. Journal of Safety Research, 68, 1 – 7.
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Abstract
Introduction: This study is aimed at filling part of the knowledge gap on bicycling safety in the built environment by addressing two questions. First, are built environment features and bicyclist injury severity correlated; and if so, what built environment factors most significantly relate to severe bicyclist injuries? Second, are the identified associations varied substantially among cities with different levels of bicycling and different built environments? Methods: The generalized ordered logit model is employed to examine the relationship between built environment features and bicyclist injury severity. Results: Bicyclist injury severity is coded into four types, including no injury (NI), possible injury (PI), evident injury (El), and severe injury and fatality (SIF). The findings include: (a) higher percentages of residential land and green space, and office or mixed use land are correlated with lower probabilities of El and SIF; (b) land use mixture is negatively correlated with El and SIF; (c) steep slopes are positively associated with bicyclist injury severity; (d) in areas with more transit routes, bicyclist injury is less likely to be severe; (e) a higher speed limit is more likely to correlate with SIF; and (f) wearing a helmet is negatively associated with SIF, but positively related to PI and El. Practical applications: To improve bicycle safety, urban planners and policymakers should encourage mixed land use, promote dense street networks, place new bike lanes in residential neighborhoods and green spaces, and office districts, while avoiding steep slopes. To promote bicycling, a process of evaluating the risk of bicyclists involving severe injuries in the local environment should be implemented before encouraging bicycle activities. (C) 2018 National Safety Council and Elsevier Ltd. All rights reserved.
Keywords
Motor Vehicle; Land-use; Crashes; Severities; Facilities; Frameworks; Frequency; Cyclists; Bike; Bicyclist Injury Severity; Built Environments; Generalized Ordered Logit Model; Us Cities; Bicycles; Urban Environments; Injuries; Neighborhoods; Land Use; Urban Areas; Paths; Protective Equipment; Bicycling; Fatalities; Correlation; Residential Areas; Traffic Accidents & Safety; Safety; Logit Models; Ecological Risk Assessment; Slopes; Health Risks; Urban Transportation; Studies; Environments
Berrigan, David; Dannenberg, Andrew L.; Lee, Michelle; Rodgers, Kelly; Wojcik, Janet R.; Wali, Behram; Tribby, Calvin P.; Buehler, Ralph; Sallis, James F.; Roberts, Jennifer D.; Steedly, Ann; Peng, Binbin; Eisenberg, Yochai; Rodriguez, Daniel A. (2021). The 2019 Conference on Health and Active Transportation: Research Needs and Opportunities. International Journal Of Environmental Research And Public Health, 18(22).
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Abstract
Active transportation (AT) is widely viewed as an important target for increasing participation in aerobic physical activity and improving health, while simultaneously addressing pollution and climate change through reductions in motor vehicular emissions. In recent years, progress in increasing AT has stalled in some countries and, furthermore, the coronavirus (COVID-19) pandemic has created new AT opportunities while also exposing the barriers and health inequities related to AT for some populations. This paper describes the results of the December 2019 Conference on Health and Active Transportation (CHAT) which brought together leaders from the transportation and health disciplines. Attendees charted a course for the future around three themes: Reflecting on Innovative Practices, Building Strategic Institutional Relationships, and Identifying Research Needs and Opportunities. This paper focuses on conclusions of the Research Needs and Opportunities theme. We present a conceptual model derived from the conference sessions that considers how economic and systems analysis, evaluation of emerging technologies and policies, efforts to address inclusivity, disparities and equity along with renewed attention to messaging and communication could contribute to overcoming barriers to development and use of AT infrastructure. Specific research gaps concerning these themes are presented. We further discuss the relevance of these themes considering the pandemic. Renewed efforts at research, dissemination and implementation are needed to achieve the potential health and environmental benefits of AT and to preserve positive changes associated with the pandemic while mitigating negative ones.
Keywords
Improving Arterial Roads; Physical-activity; Cost-effectiveness; Built Environment; Autonomous Vehicles; Walking; Behavior; Impact; Active Transportation; Covid-19; Climate Change; Physical Activity; Public Health; Pandemics; Public Transportation; Collaboration; Transportation; Economic Models; Environmental Impact; Outdoor Air Quality; Vehicle Emissions; Coronaviruses; Hispanic Americans; Fatalities; Systems Analysis; African Americans; Infrastructure; Medical Research; Committees; Land Use; Economic Analysis; New Technology; United States--us