Our direct environment affects our lives directly. Christopher Alexander saw that we are able to feel or see if an object or structure is natural through the characteristics of them. He also saw that we generally feel better near these living, natural structures as it more closely resembles ourselves. Our bodies and our surroundings are made up of far more smaller than large things. When structures follow this pattern they are considered to be more natural, and when they move away from this pattern they are considered to be less natural and thus often boring or ugly. This scaling law is used to analyse the complex networks within cities. By analysing underlying structures instead of direct geometry it becomes possible to identify how living they are.This study applies these theories to analyse urban morphology within different cities. By identifying living structure within cities comparisons can be made between different types of cities. Specifically artificial and historical cities are analysed as they are counterparts in livingness. Following the identification of the living structure within these different types of cities an assessment can be made on what kind of an effect this has on our wellbeing based on Alexander’s theory. To see how living structure evolves over time a second analysis is performed which compares a city with its own evolution through time.Firstly natural cities and natural streets are identified in a bottom up approach based on the underlying structures of OpenStreetMap road data. Thereafter historical cities are compared with artificial cities because historical cities generally have living structure while artificial cities lack this. Then the developments of a historic city are identified and compared temporally. This research finds that current usage of concrete, steel and glass combined with very fast development speeds is detrimental to living structure within cities currently. Newer city developments should be performed in symbiosis with older city structures and the structure of the development should inhibit scaling as well as the buildings themselves. It is not sufficient to look only at geometry when managing cities, the importance of the fractal geometry, which is initially invisible must not be underestimated.

Walkability is the measure of walking comfortably in the urban environment, based on numerous parameters, including traversability, compactness, attractiveness, and safety. Recently, walkability has become a significant key to well-being quality in the urban environment through enhancement of the walking environment, including filling spaces with life, promoting sustainability, and attracting people for exercise. The walkable environment’s design and planning have been focused of attention because of its numerous benefits in various aspects, such as improvement of social life, sustainability, public health, and economy. Therefore, there is a crucial need to do more research to increase the understanding of walkability in the urban environment. There are different factors that affect the level of walkability in the built environment. Subsequently, using a geographic information system (GIS) together with multi-criteria decision-making and analysis (MCDA) is an efficient method for walkability analysis. Space syntax and its application can also serve as a critical factor in walkability assessment by evaluating the number of connections for each route. The validity of this analysis model was tested in two study cases. These cases covered two municipalities in Sweden that differ in many aspects, including size, number of roads, and public density; these are Gävle and Uppsala. Furthermore, the MCDA model was integrated with the analytic hierarchy process (AHP), and eight factors were selected based on their relative importance to the walkability assessment. The generated factor maps were set based on the widely implemented criteria of walkability, otherwise known as the 5Cs, which is developed by Transport for London (TFL). The 5Cs consists of connectivity, comfort, convenience, conviviality, and conspicuousness. The density of connections for each route was derived using natural streets based on the space syntax approach. The natural street map was used as the main map that incorporated all factors, after their derivation and normalization of their values. The final produced AHP-based maps were classified into three walkability classes representing routes with low to high levels of walkability. The One Factor At-time sensitivity analysis technique (OAT) was also applied to the GIS-MCDA model to analyse the uncertainty that can occur based on different reasons such as human error and weighting uncertainty.

The natural streets model is a research prototype that has been shown to perform better than the conventional GIS-based streets segments for explaining traffic flow and human movement. However, given its experimental status, a gap in the literature was identified. Therefore, the aim of this thesis was to contribute to the literature by investigating the wider applications of natural streets and observe whether a city’s spatial configuration (or structure) is related to outcomes of human behaviour and activity. In this case, the two previously unstudied outcomes were chosen: crime and traffic accidents. Taking an exploratory approach, Stockholm was chosen as the case study. Using the space syntax methodology, the street segments and natural streets connectivity was used to analyse whether accessibility or ‘potential through movement’ is associated with crime and traffic accidents. Two study areas were generated: a primary study area consisting of six nested zones and a secondary study area with hot spots and cold spots for events of crime and traffic accidents. To observe the statistical association between connectivity and events of crime and traffic accidents for natural streets and street segments, a classical regression model was used. The regression analysis showed that natural streets perform significantly better than street segments as they are better able to explain events of crime and traffic accidents. However, more so for traffic accidents. Most importantly, the topological structure or scaling characteristics of natural streets served as a better indicator for measuring human phenomena. The implication of this is that it could potentially be used to further the understanding of human activities in the context of the urban environment.