Pan, Haixiao; Li, Jing; Shen, Qing; Shi, Cheng. (2017). What Determines Rail Transit Passenger Volume? Implications for Transit Oriented Development Planning. Transportation Research: Part D, 57, 52 – 63.
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Abstract
Transit oriented development (TOD) has been an important topic for urban transportation planning research and practice. This paper is aimed at empirically examining the effect of rail transit station-based TOD on daily station passenger volume. Using integrated circuit (IC) card data on metro passenger volumes and cellular signaling data on the spatial distribution of human activities in Shanghai, the research identifies variations in ridership among rail transit stations. Then, regression analysis is performed using passenger volume in each station as the dependent variable. Explanatory variables include station area employment and population, residents' commuting distances, metro network accessibility, status as interchange station, and coupling with commercial activity centers. The main findings are: (1) Passenger volume is positively associated with employment density and residents' commuting distance around station; (2) stations with earlier opening dates and serving as transfer nodes tend to have positive association with passenger volumes; (3) metro stations better integrated with nearby commercial development tend to have larger passenger volumes. Several implications are drawn for TOD planning: (1) TOD planning should be integrated with rail transit network planning; (2) location of metro stations should be coupled with commercial development; (3) high employment densities should be especially encouraged as a key TOD feature; and (4) interchange stations should be more strategically positioned in the planning for rail transit network.
Keywords
Railroad Passenger Traffic; Transportation; Public Transit; Volume Measurements; Smart Cards; Mathematical Models; Accessibility; Density; Rail Transit Passenger Volume; Spatial Coupling Effect; Tod; Land-use; Built Environment; Travel-demand; Mode Choice; Impacts; Distance
Chen, Peng; Sun, Feiyang; Wang, Zhenbo; Gao, Xu; Jiao, Junfeng; Tao, Zhimin. (2018). Built Environment Effects on Bike Crash Frequency and Risk in Beijing. Journal Of Safety Research, 64, 135 – 143.
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Abstract
Introduction: Building a safe biking environment is crucial to encouraging bicycle use. In developed areas with higher density and more mixed land use, the built environment factors that pose a crash risk may vary. This study investigates the connection between biking risk factors and the compact built environment, using data for Beijing. Method: In the context of China, this paper seeks to answer two research questions. First, what types of built environment factors are correlated with bike-automobile crash frequency and risk? Second, how do risk factors vary across different types of bikes? Poisson lognormal random effects models are employed to examine how land use and roadway design factors are associated with the bike-automobile crashes. Results: The main findings are: (1) bike-automobile crashes are more likely to occur in densely developed areas, which is characterized by higher population density, more mixed land use, denser roads and junctions, and more parking lots; (2) areas with greater ground transit are correlated with more bike-automobile crashes and higher risks of involving in collisions; (3) the percentages of wider streets show negative associations with bike crash frequency; (4) built environment factors cannot help explain factors contributing to motorcycle-automobile crashes. Practical Applications: In China's dense urban context, important policy implications for bicycle safety improvement drawn from this study include: prioritizing safety programs in urban centers, applying safety improvements to areas with more ground transit, placing bike-automobile crash countermeasures at road junctions, and improving bicycle safety on narrower streets. (C) 2018 National Safety Council and Elsevier Ltd. All rights
Keywords
Motorcycling Accidents; Built Environment; Motorcycling; Poisson Distribution; Safety; Beijing (china); Bike-automobile Crash; Frequency; Poisson Lognormal Random Effects Model; Risk; Signalized Intersections; Transportation Modes; Urban Intersections; Bicycle Crashes; Motor-vehicle; Riders; Infrastructure; China; Severity; Frequency Distribution; Risk Factors; Bicycles; Fatalities; Collisions; Traffic Accidents; Safety Programs; Urban Environments; Traffic Safety; Population Density; Crashes; Streets; Environmental Effects; Environmental Engineering; Roads; Land Use; Risk Analysis; Urban Areas; Road Design; Construction; Ecological Risk Assessment; Design Factors; Motorcycles; Urban Transportation; Studies; Safety Management; Beijing China
Lee, Wonil; Migliaccio, Giovanni C. (2018). Temporal Effect of Construction Workforce Physical Strain on Diminishing Marginal Productivity at the Task Level. Journal Of Construction Engineering And Management, 144(9).
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Abstract
Physiological status and environmental stressors are known to influence workforce performance at the individual worker level. A previous study, which conducted a cross-sectional comparison in repetitive material-handling construction activities, suggested that a U-shaped relationship existed between physical strain and productivity at the group level. This research revisits those findings to further investigate the U-curve relationship between physical strain and productivity at the group level and validate the concept of diminishing marginal productivity. Heart rates were measured as an indicator of subjects' physical strain, whereas task productivity was estimated by work sampling. Eighty person-hour data were converted into panel data sets by dividing each subject's 4-h experimental data into 5-min intervals. These data sets were subsequently used to evaluate the effects of time on physical strain and productivity with 5-min lags. The study found a U-curve relationship between physical strain and task-level productivity at the group level while controlling for individual characteristics. The U-shape relationship was constant in the low-performance and high-performance groups, although the degrees of the polynomials differed. Productive workers will remain more productive than low-productive workers with increased physical strain.
Keywords
Construction Industry; Industrial Psychology; Labour Resources; Occupational Health; Polynomials; Productivity; Physiological Status; Environmental Stressors; U-shaped Relationship; Productive Workers; Polynomials Degree; Diminishing Marginal Productivity; Construction Workforce Physical Strain; Labor Productivity; Scientific Management; Shift Work; Performance; Model; Taylorism; Burnout; Design; Impact; Safety; Construction Productivity; Labor And Personal Issue; Work Physiology; Physical Strain
Tenneson, Karis; Patterson, Matthew S.; Mellin, Thomas; Nigrelli, Mark; Joria, Peter; Mitchell, Brent. (2018). Development of a Regional Lidar-Derived Above-Ground Biomass Model with Bayesian Model Averaging for Use in Ponderosa Pine and Mixed Conifer Forests in Arizona and New Mexico, USA. Remote Sensing, 10(3).
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Abstract
Historical forest management practices in the southwestern US have left forests prone to high-severity, stand-replacement fires. Reducing the cost of forest-fire management and reintroducing fire to the landscape without negative impact depends on detailed knowledge of stand composition, in particular, above-ground biomass (AGB). Lidar-based modeling techniques provide opportunities to increase ability of managers to monitor AGB and other forest metrics at reduced cost. We developed a regional lidar-based statistical model to estimate AGB for Ponderosa pine and mixed conifer forest systems of the southwestern USA, using previously collected field data. Model selection was performed using Bayesian model averaging (BMA) to reduce researcher bias, fully explore the model space, and avoid overfitting. The selected model includes measures of canopy height, canopy density, and height distribution. The model selected with BMA explains 71% of the variability in field-estimates of AGB, and the RMSE of the two independent validation data sets are 23.25 and 32.82 Mg/ha. The regional model is structured in accordance with previously described local models, and performs equivalently to these smaller scale models. We have demonstrated the effectiveness of lidar for developing cost-effective, robust regional AGB models for monitoring and planning adaptively at the landscape scale.
Keywords
Laser Scanner Data; Landscape Restoration Program; Canopy Fuel Parameters; Discrete-return Lidar; Western United-states; Wave-form Lidar; Airborne Laser; Tropical Forest; Climate-change; Adaptive Management; Forest Biomass; Aboveground Biomass; Airborne Lidar; Monitoring; Regional Forest Inventory; Variable Selection; Bayesian Model Averaging; Multiple Linear Regression
Di Masso, Andres; Williams, Daniel R.; Raymond, Christopher M.; Buchecker, Matthias; Degenhardt, Barbara; Devine-Wright, Patrick; Hertzog, Alice; Lewicka, Maria; Manzo, Lynne; Shahrad, Azadeh; Stedman, Richard; Verbrugge, Laura; von Wirth, Timo. (2019). Between Fixities and Flows: Navigating Place Attachments in an Increasingly Mobile World. Journal Of Environmental Psychology, 61, 125 – 133.
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Abstract
This paper develops a theoretical argument for how place attachments are forged and become dynamically linked to increasingly common mobility practices. First, we argue that mobilities, rather than negating the importance of place, shift our understanding of place and the habitual ways we relate to and bond with places as distinct from a conception of place attachment premised on fixity and stability. Second, we document how the body of research on place attachment has both reinforced and contested 'sedentaristic' assumptions criticized within the so-called 'mobilities turn' in the social sciences. Third, we present a conceptual framework, built around different modes of interrelation between fixity and flow, as a way to re-theorize, link and balance the various studies of place attachment that have grappled with mobility. Finally, we sketch out the main research implications of this framework for advancing our understanding of place attachment in a mobile world.
Keywords
Sense; Identity; Dimensions; Mobilities; Home; Cosmopolitan; Environment; Migration; Community; Benefits; Flow; Fixity; Place Attachment; Human Settlements; Psychology; Social Environment
Lin, Xiongbin; Maclachlan, Ian; Ren, Ting; Sun, Feiyang. (2019). Quantifying Economic Effects of Transportation Investment Considering Spatiotemporal Heterogeneity in China: A Spatial Panel Data Model Perspective. The Annals Of Regional Science, 63(3), 437 – 459.
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Abstract
Transportation investment plays a significant role in promoting economic development. However, in what scenario and to what extent transportation investment can stimulate economic growth still remains debatable. For developing countries undergoing rapid urbanization, answering these questions is necessary for evaluating proposals and determining investment plans, especially considering the heterogeneity of spatiotemporal conditions. Current literature lacks systematical research to consider the impacts of panel data and spatial correlation issue in examining the economic effects of transportation investment. To fill this gap, this study collects provincial panel data in China from 1997 to 2015 to evaluate multi-level temporal and spatial effects of transportation investment on economic growth by using spatial panel data analysis. Results show that transportation investment leads to significant and positive effects on growth and spatial concentration of economic activities, but these results vary significantly depending on the temporal and spatial characteristics of each province. The economic impacts of transportation investment are quite positive even considering the time lag effects. This study suggests that both central and local governments should carefully evaluate the multifaceted economic effects of transportation investment, such as a balanced transportation investment and economic development between growing and lagging regions, and considering the spatiotemporal heterogeneity of the economic environment.
Keywords
High-speed Rail; Infrastructure Investment; Causal Relationship; Empirical-analysis; Growth; Impact; Productivity; Efficiency; Spillover; Agglomeration; C33; R40; R58; Spatial Analysis; Time Lag; Urbanization; Transportation; Heterogeneity; Economic Growth; Economic Models; Economic Impact; Data Analysis; Spatial Data; Panel Data; Economic Development; Developing Countries--ldcs; Investments; Economic Analysis; Investment; Local Government; China
Scully, Jason Y.; Moudon, Anne Vernez; Hurvitz, Philip M.; Aggarwal, Anju; Drewnowski, Adam. (2019). A Time-Based Objective Measure of Exposure to the Food Environment. International Journal Of Environmental Research And Public Health, 16(7).
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Abstract
Exposure to food environments has mainly been limited to counting food outlets near participants' homes. This study considers food environment exposures in time and space using global positioning systems (GPS) records and fast food restaurants (FFRs) as the environment of interest. Data came from 412 participants (median participant age of 45) in the Seattle Obesity Study II who completed a survey, wore GPS receivers, and filled out travel logs for seven days. FFR locations were obtained from Public Health Seattle King County and geocoded. Exposure was conceptualized as contact between stressors (FFRs) and receptors (participants' mobility records from GPS data) using four proximities: 21 m, 100 m, 500 m, and 1/2 mile. Measures included count of proximal FFRs, time duration in proximity to 1 FFR, and time duration in proximity to FFRs weighted by FFR counts. Self-reported exposures (FFR visits) were excluded from these measures. Logistic regressions tested associations between one or more reported FFR visits and the three exposure measures at the four proximities. Time spent in proximity to an FFR was associated with significantly higher odds of FFR visits at all proximities. Weighted duration also showed positive associations with FFR visits at 21-m and 100-m proximities. FFR counts were not associated with FFR visits. Duration of exposure helps measure the relationship between the food environment, mobility patterns, and health behaviors. The stronger associations between exposure and outcome found at closer proximities (<100 m) need further research.
Keywords
Global Positioning Systems; Physical-activity; Health Research; Land-use; Neighborhood; Gps; Obesity; Tracking; Validity; Mobility; Fast Food; Spatio-temporal Exposure; Mobility Patterns; Selective Mobility Bias
Acolin, Arthur. (2020). Owning vs. Renting: The Benefits of Residential Stability? Housing Studies, 37(4), 644-647.
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Abstract
In housing research, owning, as compared to renting, is generally depicted as more desirable and associated with better outcomes. This paper explores differences in outcomes between owners and renters in 25 European countries and whether these differences are systematically smaller in countries in which owners and renters have more similar levels of residential stability (smaller tenure length gap). The results indicate that the direction of the relationship between tenure type and the selected outcomes is largely similar across countries. Owners generally exhibit more desirable outcomes (including life satisfaction, civic participation, educational outcomes for children, and physical and mental health). However, when looking at the relationship between outcomes and country level differences in tenure length gap, findings suggest that renters have outcomes that are more similar to owners in countries in which tenure length gaps are smaller. These results point to the potential benefits of policies that would increase residential stability, particularly for renters.
Keywords
European Union; Homeownership Benefits; Length Of Residence; Tenure; Home-ownership; Homeownership
Hess, Chris; Colburn, Gregg; Crowder, Kyle; Allen, Ryan. (2020). Racial Disparity in Exposure to Housing Cost Burden in the United States: 1980-2017. Housing Studies.
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Abstract
This article uses the Panel Study of Income Dynamics to analyse Black-White differences in housing cost burden exposure among renter households in the USA from 1980 to 2017, expanding understanding of this phenomenon in two respects. Specifically, we document how much this racial disparity changed among renters over almost four decades and identify how much factors associated with income or housing costs explain Black-White inequality in exposure to housing cost burden. For White households, the net contribution of household, neighbourhood and metropolitan covariates accounts for much of the change in the probability of housing cost burden over time. For Black households, however, the probability of experiencing housing cost burden continued to rise throughout the period of this study, even after controlling for household, neighbourhood and metropolitan covariates. This suggests that unobserved variables like racial discrimination, social networks or employment quality might explain the increasing disparity in cost burden among for Black and White households in the USA.
Keywords
Cost Burden; Housing Cost; Racial Inequality; Income Inequality; Rent Burden; Affordability; Neighborhoods; Segregation; Dynamics; Hardship; Prices; Market; Poor
Liu, Yue; Colburn, Alex; Inanici, Mehlika. (2020). Deep Neural Network Approach for Annual Luminance Simulations. Journal Of Building Performance Simulation, 13(5), 532 – 554.
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Abstract
Annual luminance maps provide meaningful evaluations for occupants' visual comfort and perception. This paper presents a novel data-driven approach for predicting annual luminance maps from a limited number of point-in-time high-dynamic-range imagery by utilizing a deep neural network. A sensitivity analysis is performed to develop guidelines for determining the minimum and optimum data collection periods for generating accurate maps. The proposed model can faithfully predict high-quality annual panoramic luminance maps from one of the three options within 30 min training time: (i) point-in-time luminance imagery spanning 5% of the year, when evenly distributed during daylight hours, (ii) one-month hourly imagery generated during daylight hours around the equinoxes; or (iii) 9 days of hourly data collected around the spring equinox, summer and winter solstices (2.5% of the year) all suffice to predict the luminance maps for the rest of the year. The DNN predicted high-quality panoramas are validated against Radiance renderings.
Keywords
Scattering Distribution-functions; Daylight Performance; Glare; Model; Prediction; Daylighting Simulation; Luminance Maps; Machine Learning; Neural Networks; Hdr Imagery; Panoramic View