Civil & Environmental Engineering
Permanent URI for this communityhttp://hdl.handle.net/1903/2221
Browse
2 results
Search Results
Item THE IMPACT OF MULTIPLE SPATIAL LEVELS OF THE BUILT ENVIRONMENT ON NONMOTORIZED TRAVEL BEHAVIOR AND HEALTH(2019) Mahmoudi, Jina; Zhang, Lei; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Over the past several decades, the primacy of the automobile in American travel culture has led to rising congestion and energy consumption levels, rampant air pollution, sprawled urban designs, pervasiveness of sedentary behaviors and lifestyles, and prevalence of many health problems. Nonmotorized modes of travel such as walking and bicycling are sustainable alternatives to the automobile and suitable remedies to the adverse environmental, economic, and health effects of automobile dependency. As research continues to reveal the many benefits of nonmotorized travel modes, identification of the factors that influence people’s levels of walking and bicycling has become essential in developing transportation planning policies and urban designs that nurture these activities, and thereby promote public health. Among such factors are the built environment characteristics of the place of residence. To date, research on the impact of the built environment on nonmotorized travel behavior has been focused on neighborhood-level factors. Nonetheless, people do not stay within their neighborhoods; they live and work at a regional scale and travel to different places and distances each day to access various destinations. Little is known, however, about the impact of built environment factors at larger scales including those representing the overall built environment of metropolitan areas on nonmotorized travel behavior and health status of residents. Guided by the principles of the ecological model of behavior, this dissertation systematically tests the impact of the built environment at hierarchical spatial scales on nonmotorized travel behavior and health outcomes. Advanced statistical techniques have been employed to develop integrated models allowing comprehensive examination of the complex interrelationships between the built environment, nonmotorized travel, and health. Through inclusion of built environment factors from larger spatial scales, this research sheds light on the overlooked impact of the macro-level built environment on nonmotorized travel and health. The findings indicate that built environment factors at various spatial scales—including the metropolitan area—can influence nonmotorized travel behavior and health outcomes of residents. Thus, to promote walking and bicycling and public health, more effective policies are those that include multilevel built environment and land use interventions and consider the overall physical form of urban areas.Item Exploring Linkages between Travel Behavior and Health with Person-Level Data from Smartphone Applications(2013) Vemulapati, Sapeksha Virinchi; Zhang, Lei; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In the past, scholars have explored different variables and linked them with the individual's travel behavior. This study explores the linkages between an individual's health and his/her everyday travel behavior. In order to capture accurate and comprehensive travel behavior information, a smartphone application is developed that can track user location for long periods without the need of user intervention. Focus is placed on designing the application to have minimum respondent burden and long-standing battery life of the smart device. Subjects are recruited through a web survey designed to collect information about the individual's healthy living habits. Data from the application is regressed against the health measure data acquired from the survey. Results show that active modes of travel are positively associated with the person's general health measures. The feasibility of this platform as a data collection method is highlighted while explaining the limitations due to the sample distribution and size.