Healthy transportation - healthy communities: developing objective measures of built-environment using GIS and testing significance of pedestrian variables on walking to transit

Walking to transit stations is proposed as one of the strategies to increase the use of transit. Urban planners, transportation planners, environmentalists, and health professionals encourage and support environmental interventions that can reduce the use of cars for all kinds of trips and use alter...

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Main Author: Maghelal, Praveen Kumar
Other Authors: Ellis, Christopher
Format: Others
Language:en_US
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/1969.1/ETD-TAMU-1685
http://hdl.handle.net/1969.1/ETD-TAMU-1685
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spelling ndltd-tamu.edu-oai-repository.tamu.edu-1969.1-ETD-TAMU-16852013-01-08T10:40:41ZHealthy transportation - healthy communities: developing objective measures of built-environment using GIS and testing significance of pedestrian variables on walking to transitMaghelal, Praveen KumarPedestrianwalkabilitytransit-oriented developmentnon-motorized transportationWalking to transit stations is proposed as one of the strategies to increase the use of transit. Urban planners, transportation planners, environmentalists, and health professionals encourage and support environmental interventions that can reduce the use of cars for all kinds of trips and use alternative modes of travel such as walking, biking, and mass-transit. This study investigates the influence of the built-environment on walking to transit stations. Transit-oriented communities at quarter and half-mile distances from the Dallas Area Rapid Transit (DART) station in Dallas, Texas, were analyzed to identify the relation of various constructs of built-environment on walking to the DART stations. Twenty-one pedestrian indices were reviewed to develop a comprehensive list of 73 built-environment variables used to measure the suitability to walk. This study aims to objectively measure built-environment using spatial data. Based on this criterion the total number of variables was narrowed to 32. Walking to transit, calculated as a percentage of transit users who walk to the DART LRT stations, was used as the dependent variable. The number of stations in operation and used for analysis in this study is 20(n). Therefore, bootstrapping was used to perform the statistical analysis for this study. The final pattern of variable grouping for the quarter-mile and the half-mile analysis revealed four principal components: Vehicle-Oriented Design, Density, Diversity, and Walking-Oriented Design. Bootstrap regression revealed that density ( = -0.767) was the only principal component that significantly (p<0.05) explained walking to transit station at quarter-mile distance from the station. At half-mile distance built-environment variables did not report any significant relation to walking to transit. The present study revealed that mere increase of density should not be taken as a proxy of increase in walking. Environmental interventions that can promote walking should be identified even at locations with high density. Further studies should use advanced statistical techniques such as Hierarchical Linear Modeling or Structural Equation Modeling to test the relationship of both the principal components and the individual variables that define the principal component to clearly understand the relationship of built-environment with walking to transit station.Ellis, ChristopherKweon, Byoung-Suk2010-01-14T23:55:30Z2010-01-16T02:03:20Z2010-01-14T23:55:30Z2010-01-16T02:03:20Z2007-082009-05-15BookThesisElectronic Dissertationtextelectronicapplication/pdfborn digitalhttp://hdl.handle.net/1969.1/ETD-TAMU-1685http://hdl.handle.net/1969.1/ETD-TAMU-1685en_US
collection NDLTD
language en_US
format Others
sources NDLTD
topic Pedestrian
walkability
transit-oriented development
non-motorized transportation
spellingShingle Pedestrian
walkability
transit-oriented development
non-motorized transportation
Maghelal, Praveen Kumar
Healthy transportation - healthy communities: developing objective measures of built-environment using GIS and testing significance of pedestrian variables on walking to transit
description Walking to transit stations is proposed as one of the strategies to increase the use of transit. Urban planners, transportation planners, environmentalists, and health professionals encourage and support environmental interventions that can reduce the use of cars for all kinds of trips and use alternative modes of travel such as walking, biking, and mass-transit. This study investigates the influence of the built-environment on walking to transit stations. Transit-oriented communities at quarter and half-mile distances from the Dallas Area Rapid Transit (DART) station in Dallas, Texas, were analyzed to identify the relation of various constructs of built-environment on walking to the DART stations. Twenty-one pedestrian indices were reviewed to develop a comprehensive list of 73 built-environment variables used to measure the suitability to walk. This study aims to objectively measure built-environment using spatial data. Based on this criterion the total number of variables was narrowed to 32. Walking to transit, calculated as a percentage of transit users who walk to the DART LRT stations, was used as the dependent variable. The number of stations in operation and used for analysis in this study is 20(n). Therefore, bootstrapping was used to perform the statistical analysis for this study. The final pattern of variable grouping for the quarter-mile and the half-mile analysis revealed four principal components: Vehicle-Oriented Design, Density, Diversity, and Walking-Oriented Design. Bootstrap regression revealed that density ( = -0.767) was the only principal component that significantly (p<0.05) explained walking to transit station at quarter-mile distance from the station. At half-mile distance built-environment variables did not report any significant relation to walking to transit. The present study revealed that mere increase of density should not be taken as a proxy of increase in walking. Environmental interventions that can promote walking should be identified even at locations with high density. Further studies should use advanced statistical techniques such as Hierarchical Linear Modeling or Structural Equation Modeling to test the relationship of both the principal components and the individual variables that define the principal component to clearly understand the relationship of built-environment with walking to transit station.
author2 Ellis, Christopher
author_facet Ellis, Christopher
Maghelal, Praveen Kumar
author Maghelal, Praveen Kumar
author_sort Maghelal, Praveen Kumar
title Healthy transportation - healthy communities: developing objective measures of built-environment using GIS and testing significance of pedestrian variables on walking to transit
title_short Healthy transportation - healthy communities: developing objective measures of built-environment using GIS and testing significance of pedestrian variables on walking to transit
title_full Healthy transportation - healthy communities: developing objective measures of built-environment using GIS and testing significance of pedestrian variables on walking to transit
title_fullStr Healthy transportation - healthy communities: developing objective measures of built-environment using GIS and testing significance of pedestrian variables on walking to transit
title_full_unstemmed Healthy transportation - healthy communities: developing objective measures of built-environment using GIS and testing significance of pedestrian variables on walking to transit
title_sort healthy transportation - healthy communities: developing objective measures of built-environment using gis and testing significance of pedestrian variables on walking to transit
publishDate 2010
url http://hdl.handle.net/1969.1/ETD-TAMU-1685
http://hdl.handle.net/1969.1/ETD-TAMU-1685
work_keys_str_mv AT maghelalpraveenkumar healthytransportationhealthycommunitiesdevelopingobjectivemeasuresofbuiltenvironmentusinggisandtestingsignificanceofpedestrianvariablesonwalkingtotransit
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