This thesis addresses how built environment characteristics shape walking behavior by examining the relationship between GIS-based built environment measures and GPS-tracked transport walking, along with self-reported socio-demographic and psychological characteristics of individuals, in two medium-sized Swedish cities, Umeå and Linköping, across multiple datasets collected in 2019 and 2021.

A methodological foundation for the empirical work is established by evaluating two emerging data sources for pedestrian study: a Wi-Fi-based flow measurement system (Bumbee Labs) and a GPS-enabled travel survey application (TravelVu), finding that the two methods are complementary, with the former capturing large-scale pedestrian flow patterns and the latter providing individual-level route, distance, and attitudinal data suited to behavioral analysis. Built environment exposure, in this thesis, is operationalized at two spatial scales: 1) potential exposure, measured within a 750 m radius of each participant's home location, and 2) realized exposure, measured within a 15 m buffer along GPS-traced actual routes and their shortest-path alternatives. This dual-scale design enables a direct empirical comparison of which environmental features predict how much people walk versus which features shape the paths they take when they do. Socio-demographic variables and psychological variables, derived from a Theory of Planned Behavior questionnaire integrated into the tracking application, are examined both for their direct associations with GPS-measured walking outcomes and as potential mediators and moderators of built environment effects. Analytical methods include bivariate correlation analysis, structural equation modelling, linear mixed models, and discrete choice analysis.

At the neighborhood level, building density, bus stop access, commercial land use, tree cover, paved surface area, and pedestrian network length show modest but statistically significant positive associations with walking distance and walking ratio. Structural equation modelling confirms that the built environment retains a significant direct effect on walking when attitudes are simultaneously controlled, though attitudes are the stronger predictor. Contrary to the mediation hypothesis, the built environment does not significantly influence walking through attitudes in the overall sample; however, moderated mediation analysis reveals conditional pathways by age, with a significant indirect effect via attitudes among middle-aged adults and a stronger direct environmental effect among young adults.

At the route level, about 96% of observed trips follow the shortest available path, confirming distance minimization as the dominant pedestrian strategy. For trips that deviate, commercial land use is the strongest positive predictor of route selection in the discrete choice analysis, while dedicated non-vehicular pedestrian infrastructure and low-speed streets are consistently negatively associated with route deviation across both linear mixed models and discrete choice models. Moderation analyses further show that income, age, and scenic motivation condition how specific built environment features influence route behavior, while no socio-demographic or attitudinal variable produces a significant unconditional main effect on route choice.

The comparison across scales reveals that the environmental variables associated with walking volume are indicated to be different from those shaping route selection, a finding that challenges walkability frameworks and suggests that planning interventions targeting modal shift and those targeting route quality require different built environment priorities. These results support further understanding of scale-dependent built environment effects on pedestrian behavior and provide an empirical basis for more targeted assessment of walking behavior in Nordic urban contexts. The results also indicate a continued need for more data on the topic, as well as methodological development to collect quantitative data on pedestrian travel.

Objective data on pedestrian travel has long been lacking, especially pertaining to quantitative information about flows and route choices. Recent ICT development has opened opportunities to collect position-determined data automatically/passively but has rarely been used to study walking behavior. This study analyses the use of two such data sources for pedestrian study. Data was collected in the autumn of 2019 in Umeå, Sweden, where residents (N = 88) in the study area were asked to use the travel survey app (TravelVu) for 5 days. A total of 3,856 trips were recorded of which 51% were walking. A measurement of travel patterns was also carried out with Wi-Fi (Bumbee) for 8 days at 14 points, which recorded 279,791 entries. The results show that what Bumbee loses in precision it makes up for in the number of registrations, while TravelVu provides a detailed picture of an individual’s travels. This pilot study addresses how well the combination of these data types describes pedestrian traffic in an area in terms of flow, route choice, and distribution in time and space. Furthermore, the study provides knowledge on how new data sources can be used to provide municipalities with a picture of their pedestrian traffic. 

Theory of planned behavior (TPB) is a social cognition model that proposes that a persons' surroundings influences their behavior. Pedestrian studies based on TPB are few, and often, not only measure walking subjectively, but also have very generic measures of TPB constructs that do not account for built environment. Urban planners have, on the other hand, emphasized for decades the importance of built environment on walking and use of public spaces. This paper aims to develop a detailed understanding of the factors that affect an individual's walking that would assist planners in developing strategies to increase the modal share of walking. Thus, unlike most studies, it measures attitude towards and perceived control over the behavior (i.e., walking) and the built environment, in addition to measuring walking objectively (at both individual and trip levels).Data was collected in the autumn of 2019 in Umea, Sweden, using a smartphone app in the form of GPS-based travel data (i.e., distance, time, location, activity) and survey questions (i.e., demographics and psychological constructs of TPB). The results reinforced previous findings that attitude and perceived control correlate to walking and identified the key variables under each behavioral construct. The purpose, the reasons people like to walk and their attitude towards the built environment showed significant correlation to individuals' walking behavior. Perceived control over the behavior and built environment, was also found to have a significant correlation to walking. Thus, this paper makes important methodological contribution towards using TPB to analyze walking.

Addressing the complex interrelationships between city making and the resources needed for its production, Predatory Urbanism explores the link between urbanization and resources in the global South. It particularly focuses on urban megaprojects, highlighting these planned developments and re-developments carried out by the state or state-linked agencies. 

This paper reports on a detailed analysis of the metabolism of the Island City of Mumbai should the Indian Government’s proposal for ‘smart’ cities be implemented. It focuses on the environmental impact of increased population density achieved by demolishing existing medium-rise (3-5 storey) housing and replacing it with the proposed high-rise (40-60 storey) towers. The resulting increase in density places a burden on the demand on such things as electricity and water and simultaneously increases the output flows of drainage, solid waste and greenhouse gas production.An extended urban metabolism analysis is carried out on a proposed development in Mumbai (Bhendi Bazaar) that has been put forward as an exemplar case study by the Government. The flows of energy, water and wastes are calculated based on precedents and from first principles. The results of the case study are then extrapolated across the City in order to identify the magnitude of increased demands and wastes should the ‘smart’ city proposals be fully realised.Mumbai is the densest city in the world. It already suffers from repeated blackouts, water rationing and inadequate waste and sewage treatment. The results of the study indicate, on a per capita basis, increasing density will have a significant further detrimental effect on the environment.