With gas prices rising rapidly, many people have started to believe that it has become imperative to reduce their vehicle miles travelled. Land use patterns have been found culpable of contributing to the extra VMT driven by the average. As such, urban planners have employed many strategies to attempt to reduce this portion of VMT. For example, research shows that smart growth in the form of mixed-use compact development results in a better match of jobs and housing since it brings trip origins and destinations closer, thereby making work trips shorter. This research uses spatial modeling in GIS and Multiple Linear regression/ANOVA in SPSS to analyze the link between job-housing (J/H) mismatch, land use mix and worker commute flows. The study examines J/H imbalance within a travel catchment area using a 7-mile buffer from the centroid of each census tract in Dallas County, Texas. Moreover, it uses jobs, workers local economic and community data in the form of Local Employment Dynamics, Longitudinal Employer-Household Dynamics and Quarterly Workforce Indicators provided by the US Census Bureau to carry out area profile, area comparison, distance/direction, destination, inflow/outflow and paired area analysis for workers place of work and residential distributions in Dallas county. This analysis is linked in Geographical Information Systems to the land use map, which is classified as an entropy index. The GIS results present a spatial picture of labor- shed, commute-shed, job-housing balanced and imbalanced areas by relating the land use mix and commute flows of workers in Dallas County. Moreover, MLR regression model in SPSS shows that Land use mix, Job/housing balance and housing affordability are significant predictors of mean travel time to work. This strategic tool developed through Target Area Analysis and Hot Spot Analysis will act as a guideline for land use planners to understand the regional growth complexities related to work flows. The analytical model developed can also be deployed to direct land development patterns, which will ultimately improve the quality of life, halt urban sprawl, lower costs to businesses and commuters and produce related positive externalities.

Land use grain is a commonly-used measure of the mixture of land uses in the urban environment in transportation planning and public health, but there is no standard measurement practice in place. This thesis examines the meaning and common measurements of land use grain in these subfields. The entropy-based equation, the jobs-to-housing ratio, and the Herfindahl-Hirschman Index (HHI) are among the most common measures of land use grain, but results from these metrics differ depending upon how researchers choose a sample area and upon how land use categories are defined. All three metrics are performed, in a single context with varying assumptions, using the neighborhoods of Roxbury and Dorchester in Boston, MA. The entropy-based equation was deemed the most appropriate measure in a general context, with the HHI and the jobs-to-housing ratio potentially appropriate in specific contexts.

Certains chercheurs veulent que les gouvernements modifient les déterminants de l’environnement urbain du transport actif dans des régions à bas statut socioéconomique pour réduire les inégalités en activité physique et santé. Mais, des individus de différents sousgroupes de la population pourraient réagir différemment à l’environnement urbain. Plusieurs chercheurs ont examiné si l’influence d’un environnement urbain propice aux piétons sur le transport actif diffère entre les personnes ayant un statut socioéconomique de quartier différent et ont obtenu des résultats mixtes. Ces résultats équivoques pourraient être dus à la façon dont les mesures de l’environnement urbain étaient déterminées. Plus spécifiquement, la plupart des études ont examiné l’effet de la propicité à la marche des lieux résidentiels et n’ont pas pris en compte les destinations non-résidentielles dans leurs mesures. Cette étude a examiné le statut socioéconomique du quartier comme modérateur de la relation entre l’environnement urbain et le transport actif en utilisant des mesures d’environnement urbain qui proviennent de toute la trajectoire spatiale estimé des individus. Les trois variables de l’environnement urbain, la connectivité, la densité des commerces et services et la diversité du territoire avaient une plus grande influence sur le transport actif de ceux avec un haut statut socioéconomique. Nos résultats suggèrent que même quand la configuration de l’environnement urbain est favorable pour le transport actif, il peut y avoir des barrières sociales ou physiques qui empêchent les gens qui habitent dans un quartier à bas statut socioéconomique de bénéficier d’un environnement urbain favorable au transport actif. / Researchers have called for policymakers to modify the built environment determinants of active travel in low SES areas in the hopes of reducing disparities in physical activity and health. However, different population sub-groups may be differently responsive to the built environment. Researchers have examined whether the influence of walkable built environments on active transportation differs for those of different socio-economic status and have obtained mixed results. These equivocal findings could be due to the way the built environment measures were determined. More specifically, most studies have examined walkability in residential settings ignoring non-residential destinations. This study examined socio-economic status as a moderator of the relationship between the built environment and active transportation using a trip level analyses with measures of built environment exposure derived from the estimated spatial trajectory of transport trips. All three of the environmental variables, connectivity, density of business and services, and land-use mix, were found to have a greater association with AT if the individual undergoing the trip was from a high socioeconomic status neighbourhood. Our findings suggest that even when the built environment is favourable for AT there may be social or physical barriers that prevent those from low socio-economic status neighbourhoods from benefitting from built environments that are conducive to active transportation.