Yang, Jiawen; Shen, Qing; Shen, Jinzhen; He, Canfei. (2012). Transport Impacts of Clustered Development in Beijing: Compact Development Versus Overconcentration. Urban Studies, 49(6), 1315 – 1331.
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Abstract
This research aims to inform the compact city discussion with a case study of Beijing, where urban planning has emphasised clustered suburban development in the past half-century. It uses three decades of census data to describe Beijing's spatial development trajectory and a household survey to assess its transport impacts. The research reveals an overconcentration of urban activities as a result of the featureless expansion of the central built-up area and the absorption of the suburban clusters; and, a lengthened commuting time stemming from the observed spatial development pattern. Beijing's experience adds to the existing literature by informing the search for good city forms in urban areas of high density. It is essential to differentiate compact development from overconcentration when combating sprawling development. Developing and maintaining suburban nodal characteristics around public transit can reduce travel in high-density urban areas.
Keywords
Jobs-housing Balance; Commuting Patterns; Urban; Growth; City; Towns
Stewart, Orion Theodore; Moudon, Anne Vernez. (2014). Using the Built Environment to Oversample Walk, Transit, and Bicycle Travel. Transportation Research: Part D, 32, 15 – 23.
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Abstract
Characteristics of the built environment (BE) have been associated with walk, transit, and bicycle travel. These BE characteristics can be used by transportation researchers to oversample households from areas where walk, transit, or bicycle travel is more likely, resulting in more observations of these uncommon travel behaviors. Little guidance, however, is available on the effectiveness of such built environment oversampling strategies. This article presents measures that can be used to assess the effectiveness of BE oversampling strategies and inform future efforts to oversample households with uncommon travel behaviors. The measures are sensitivity and specificity, positive likelihood ratio (LR+), and positive predictive value (PPV). To illustrate these measures, they were calculated for 10 BE-defined oversampling strata applied post-hoc to a Seattle area household travel survey. Strata with an average block size of <10 acres within a 1/4 mile of household residences held the single greatest potential for oversampling households that walk, use transit, and/or bicycle. (C) 2014 Elsevier Ltd. All rights reserved.
Keywords
Cycling; Transportation; Observation (scientific Method); Strategic Planning; Public Transit; Land Use; Bicycle; Household Travel Survey; Non-motorized Travel; Sampling; Screening Tests; Transit; Walk; Land-use; North-america; Renaissance; Policies; Choice; Trends
James, Peter; Jankowska, Marta; Marx, Christine; Hart, Jaime E.; Berrigan, David; Kerr, Jacqueline; Hurvitz, Philip M.; Hipp, J. Aaron; Laden, Francine. (2016). Spatial Energetics Integrating Data from GPS, Accelerometry, and GIS to Address Obesity and Inactivity. American Journal Of Preventive Medicine, 51(5), 792 – 800.
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Abstract
To address the current obesity and inactivity epidemics, public health researchers have attempted to identify spatial factors that influence physical inactivity and obesity. Technologic and methodologic developments have led to a revolutionary ability to examine dynamic, high-resolution measures of temporally matched location and behavior data through GPS, accelerometry, and GIS. These advances allow the investigation of spatial energetics, high-spatiotemporal resolution data on location and time-matched energetics, to examine how environmental characteristics, space, and time are linked to activity-related health behaviors with far more robust and detailed data than in previous work. Although the transdisciplinary field of spatial energetics demonstrates promise to provide novel insights on how individuals and populations interact with their environment, there remain significant conceptual, technical, analytical, and ethical challenges stemming from the complex data streams that spatial energetics research generates. First, it is essential to better understand what spatial energetics data represent, the relevant spatial context of analysis for these data, and if spatial energetics can establish causality for development of spatially relevant interventions. Second, there are significant technical problems for analysis of voluminous and complex data that may require development of spatially aware scalable computational infrastructures. Third, the field must come to agreement on appropriate statistical methodologies to account for multiple observations per person. Finally, these challenges must be considered within the context of maintaining participant privacy and security. This article describes gaps in current practice and understanding and suggests solutions to move this promising area of research forward. (C) 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
Keywords
Physical-activity Levels; Built Environment; Activity Monitors; Travel Behavior; Health Research; Neighborhood; Exposure; Validation; Children; Design
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
Moudon, Anne Vernez; Huang, Ruizhu; Stewart, Orion T.; Cohen-Cline, Hannah; Noonan, Carolyn; Hurvitz, Philip M.; Duncan, Glen E. (2019). Probabilistic Walking Models Using Built Environment and Sociodemographic Predictors. Population Health Metrics, 17(1).
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Abstract
BackgroundIndividual sociodemographic and home neighborhood built environment (BE) factors influence the probability of engaging in health-enhancing levels of walking or moderate-to-vigorous physical activity (MVPA). Methods are needed to parsimoniously model the associations.MethodsParticipants included 2392 adults drawn from a community-based twin registry living in the Seattle region. Objective BE measures from four domains (regional context, neighborhood composition, destinations, transportation) were taken for neighborhood sizes of 833 and 1666 road network meters from home. Hosmer and Lemeshow's methods served to fit logistic regression models of walking and MVPA outcomes using sociodemographic and BE predictors. Backward elimination identified variables included in final models, and comparison of receiver operating characteristic (ROC) curves determined model fit improvements.ResultsBuilt environment variables associated with physical activity were reduced from 86 to 5 or fewer. Sociodemographic and BE variables from all four BE domains were associated with activity outcomes but differed by activity type and neighborhood size. For the study population, ROC comparisons indicated that adding BE variables to a base model of sociodemographic factors did not improve the ability to predict walking or MVPA.ConclusionsUsing sociodemographic and built environment factors, the proposed approach can guide the estimation of activity prediction models for different activity types, neighborhood sizes, and discrete BE characteristics. Variables associated with walking and MVPA are population and neighborhood BE-specific.
Keywords
Walking; Confidence Intervals; Research Funding; Transportation; Logistic Regression Analysis; Built Environment; Socioeconomic Factors; Predictive Validity; Receiver Operating Characteristic Curves; Data Analysis Software; Descriptive Statistics; Psychology; Washington (state); Active Travel; Home Neighborhood Domains; Physical Activity; Physical-activity; United-states; Life Stage; Adults; Attributes; Health; Associations; Destination; Pitfalls
Jung, Meen Chel; Dyson, Karen; Alberti, Marina. (2021). Urban Landscape Heterogeneity Influences the Relationship Between Tree Canopy and Land Surface Temperature. Urban Forestry & Urban Greening, 57.
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Abstract
Urban trees play a key role in alleviating elevated summertime land surface temperatures in cities. However, urban landscape influences the capacity of urban trees to mitigate higher temperatures. We propose that both developed land characteristics and tree cover should be considered to accurately estimate the mitigation effects of canopy cover. We subclassified original land cover based on the canopy cover ratio to capture the within-land cover heterogeneity. We selected two coastal cities with different summertime climatic conditions: Seattle, Washington, USA, and Baltimore, Maryland, USA. We used Landsat-based grid cells (30 m x 30 m) as our spatial analytical unit, with corresponding land surface temperature, canopy area, canopy compactness, population size, and National Land Cover Database (NLCD)-based land cover group. We first used grouped boxplots, Kruskal-Wallis H tests, and post-hoc multiple comparison tests to detect the distribution of land surface temperatures by the land cover group. We then introduced statistical models to test the group effects on the relationship between land surface temperatures and canopy cover variables. We found: (1) land surface temperature increases with level of development, (2) land surface temperature decreases with canopy cover level, (3) the magnitude of the mitigation effects from canopy area differs based on development level and current canopy cover, (4) the differing efficacies of canopy area in decreasing land surface temperature follows a nonlinear threshold relationship, and (5) compactness of canopy cover was not significant in reducing the land surface temperature. These findings suggest the importance of considering heterogeneous canopy cover within developed land cover classes in urban heat island research. Tree planting strategies need to consider the nonlinear relationships between tree canopy cover and land surface temperature alongside environmental equity concerns.
Keywords
Extreme Heat Events; Climate-change; Cover Data; Island; Pattern; Cities; Vegetation; Mortality; Phoenix; Impact; Canopy Cover; Environmental Equity; Land Cover; Land Surface Temperature; Mitigation Effect; Area; Canopy; Cells; Climatic Factors; Databases; Heat Island; Landscapes; Multiple Comparison Test; Planting; Population Size; Research; Statistical Models; Summer; Surface Temperature; Testing; Trees; Urban Forestry; Maryland
Cuo, Lan; Beyene, Tazebe K.; Voisin, Nathalie; Su, Fengge; Lettenmaier, Dennis P.; Alberti, Marina; Richey, Jeffrey E. (2011). Effects of Mid-Twenty-first Century Climate and Land Cover Change on the Hydrology Of the Puget Sound Basin, Washington. Hydrological Processes, 25(11), 1729 – 1753.
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Abstract
The distributed hydrology-soil-vegetation model (DHSVM) was used to study the potential impacts of projected future land cover and climate change on the hydrology of the Puget Sound basin, Washington, in the mid-twenty-first century. A 60-year climate model output, archived for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4), was statistically downscaled and used as input to DHSVM. From the DHSVM output, we extracted multi-decadal averages of seasonal streamflow, annual maximum flow, snow water equivalent (SWE), and evapotranspiration centred around 2030 and 2050. Future land cover was represented by a 2027 projection, which was extended to 2050, and DHSVM was run (with current climate) for these future land cover projections. In general, the climate change signal alone on sub-basin streamflow was evidenced primarily through changes in the timing of winter and spring runoff, and slight increases in the annual runoff. Runoff changes in the uplands were attributable both to climate (increased winter precipitation, less snow) and land cover change (mostly reduced vegetation maturity). The most climatically sensitive parts of the uplands were in areas where the current winter precipitation is in the rain-snow transition zone. Changes in land cover were generally more important than climate change in the lowlands, where a substantial change to more urbanized land use and increased runoff was predicted. Both the annual total and seasonal distribution of freshwater flux to Puget Sound are more sensitive to climate change impacts than to land cover change, primarily because most of the runoff originates in the uplands. Both climate and land cover change slightly increase the annual freshwater flux to Puget Sound. Changes in the seasonal distribution of freshwater flux are mostly related to climate change, and consist of double-digit increases in winter flows and decreases in summer and fall flows. Copyright (C) 2010 John Wiley & Sons, Ltd.
Keywords
Joaquin River-basin; Water-resources; Change Impacts; Model; Sensitivity; Temperature; Prediction; Streamflow; Forecasts; Humidity; Hydrologic Prediction; Climate Change Impacts; Land Cover Change Impacts
Kang, Bumjoon; Moudon, Anne V.; Hurvitz, Philip M.; Reichley, Lucas; Saelens, Brian E. (2013). Walking Objectively Measured: Classifying Accelerometer Data with GPS and Travel Diaries. Medicine & Science In Sports & Exercise, 45(7), 1419 – 1428.
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Abstract
Purpose: This study developed and tested an algorithm to classify accelerometer data as walking or nonwalking using either GPS or travel diary data within a large sample of adults under free-living conditions. Methods: Participants wore an accelerometer and a GPS unit and concurrently completed a travel diary for seven consecutive days. Physical activity (PA) bouts were identified using accelerometry count sequences. PA bouts were then classified as walking or nonwalking based on a decision-tree algorithm consisting of seven classification scenarios. Algorithm reliability was examined relative to two independent analysts' classification of a 100-bout verification sample. The algorithm was then applied to the entire set of PA bouts. Results: The 706 participants' (mean age = 51 yr, 62% female, 80% non-Hispanic white, 70% college graduate or higher) yielded 4702 person-days of data and had a total of 13,971 PA bouts. The algorithm showed a mean agreement of 95% with the independent analysts. It classified PA into 8170 walking bouts (58.5 %) and 5337 nonwalking bouts (38.2%); 464 bouts (3.3%) were not classified for lack of GPS and diary data. Nearly 70% of the walking bouts and 68% of the nonwalking bouts were classified using only the objective accelerometer and GPS data. Travel diary data helped classify 30% of all bouts with no GPS data. The mean + SD duration of PA bouts classified as walking was 15.2 + 12.9 min. On average, participants had 1.7 walking bouts and 25.4 total walking minutes per day. Conclusions: GPS and travel diary information can be helpful in classifying most accelerometer-derived PA bouts into walking or nonwalking behavior.
Keywords
Walking; Algorithms; Decision Trees; Geographic Information Systems; Research Funding; Travel; Accelerometry; Diary (literary Form); Descriptive Statistics; Algorithm; Classification; Physical Activity; Walk Trip; Global Positioning Systems; Physical-activity; Environment; Behaviors; Validity; Location
Wang, X.; Liu, C.; Kostyniuk, L.; Shen, Q.; Bao, S. (2014). The Influence of Street Environments on Fuel Efficiency: Insights from Naturalistic Driving. International Journal Of Environmental Science And Technology, 11(8), 2291 – 2306.
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Abstract
Fuel consumption and greenhouse gas emissions in the transportation sector are a result of a three-legged stool: fuel types, vehicle fuel efficiency, and vehicle miles travelled (VMT). While there is a substantial body of literature that examines the connection between the built environment and total VMT, few studies have focused on the impacts of the street environment on fuel consumption rate. Our research applied structural equation modeling to examine how driving behaviors and fuel efficiency respond to different street environments. We used a rich naturalistic driving dataset that recorded detailed driving patterns of 108 drivers randomly selected from the Southeast Michigan region. The results show that, some features of compact streets such as lower speed limit, higher intersection density, and higher employment density are associated with lower driving speed, more speed changes, and lower fuel efficiency; however, other features such as higher population density and higher density of pedestrian-scale retails improve fuel efficiency. The aim of our study is to gain further understanding of energy and environmental outcomes of the urban areas and the roadway infrastructure we plan, design, and build and to better inform policy decisions concerned with sustainable transportation.
Keywords
Travel; Consumption; Emissions; Cities; Energy; Street Environments; Fuel Efficiency; Structural Equation Modeling; Naturalistic Driving
Oshima, Ken Tadashi. (2016). Rediscovering Japanese Urban Space in a World Context. Journal Of Urban History, 42(3), 623 – 633.
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Abstract
Counter to the rise of the modern metropolis in Japan in the era of high-speed growth following World War II, a movement to embrace elements of traditional townscapes that had been lost as rational urban planning took hold from the mid-1950s to the mid-1970s. During this period, the realities of large-scale urban development and increasing urban problems would eventually expose the limitations of functional planning and the need to preserve traditional structures and townscapes. While architects like Bruno Taut had praised the virtues of the farmhouse villages at Shirakawago in the 1930s and Yoshida Tetsur presented traditional Japanese architecture to an international audience as contemporary design before World War II, among others, the discourse subsequently shifted from Japanese objects and structures to urban space in the postwar period. This discourse on Japanese urban space would lead to the publication of Nihon no toshi kukan (Japanese Urban Space) in 1963 (1968 as a book) that presented the work of the Toshi dezain kenkyutai (Urban Design Research Group) including Isozaki Arata (1931-) and architectural historian It Teiji (1922-2010). This article analyzes the origins and implications of this work through a plethora of subsequent design surveys throughout Japan and other trajectories of research and design of Japanese urban space from the 1960s to the present.
Keywords
Japanese Urban Space; Urban Landscape; Serial Vision; Imageability; Design Survey