Reconstructing the Spatial and Temporal Patterns of Daily Life in the 19th Century City: A Historical GIS Approach

In recent years, historians and historical geographers have become interested in the use of GIS to study historical patterns, populations, and phenomena. The result has been the emergence of a new discipline, historical GIS. Despite the growing use of GIS across geography and history, the use of GIS in historical research has been limited largely to visualization of historical records, database management, and simple pattern analysis. This is, in part, due to a lack of accessible research on methodologies and spatial frameworks that outline the integration of both quantitative and qualitative historical sources for use in a GIS environment. The first objective of this dissertation is to develop a comprehensive geospatial research framework for the study of past populations and their environments. The second objective of this dissertation is to apply this framework to the study of daily life in the nineteenth-century city, an important area of scholarship for historical geographers and social historians. Other daily life studies have focused on various experiences of daily life, from domestic duties and child rearing to social norms and the experience of work in early factories. An area that has received little attention in recent years is the daily mobility of individuals as they moved about the ‘walking city’. This dissertation advances our understanding of the diurnal patterns of daily life by recreating the journey to work for thousands of individuals in the city of London, Ontario, and its suburbs in the late nineteenth century. Methodologies are created to capture past populations, their workplaces, and their relationship to the environments they called home. Empirical results outline the relationship between social class, gender, and the journey to work, as well as how social mobility was reflected through the quality of individuals’ residential and neighbourhood environments. The results provide a new perspective on daily mobility, social mobility, and environment in the late nineteenth-century city. Results suggest that individuals who were able to be upwardly socially mobile did so at the expense of substantial increases in their journey to work

Towards real-time geodemographic information systems: design, analysis and evaluation

Geodemographic classifications provide discrete indicators of the social, economic and demographic characteristics of people living in small neighbourhood areas. They have been regarded as products, which are the final 'best' outcome that can be achieved using available data and algorithms. However, reduction in the cost of geocomputation, increased network bandwidths and increasingly accessible spatial data infrastructures have together created the potential for the creation of classifications in near real-time within distributed environments. Current geodemographic classifications are said to be 'closed' in nature due to the data and algorithms used. This thesis is a step towards an open geodemographic information system that allows users to specify the importance of their selected variables and then perform a range of statistical analysis functions which are necessary to create classifications tailored to user requirements. This thesis discusses the socio-economic data sources currently used in the creation of geodemographic classifications, and explains the work towards the creation of a non-conventional data sources arising out of the UCL's surname database. Such data sources are seen as key to the creation of tailor made classifications. The thesis explains and compares different cluster analysis techniques for the segmentation of geodemographic classifications. The development of an online information system employs an optimisation of k-means clustering algorithm. This optimisation uses CUDA (Computer Unified Development Architecture) for parallel processing of computationally expensive k-means on NVIDIA's graphics cards. The concluding chapters of the thesis set out the architecture of a real-time geodemographic information system. The thesis also presents the results of the creation of bespoke local area classifications. The developmental work culminates in a pilot real-time geodemographic information system for the specification, estimation and testing of classifications on the fly

From buildings to cities: techniques for the multi-scale analysis of urban form and function

The built environment is a significant factor in many urban processes, yet direct measures of built form are seldom used in geographical studies. Representation and analysis of urban form and function could provide new insights and improve the evidence base for research. So far progress has been slow due to limited data availability, computational demands, and a lack of methods to integrate built environment data with aggregate geographical analysis. Spatial data and computational improvements are overcoming some of these problems, but there remains a need for techniques to process and aggregate urban form data. Here we develop a Built Environment Model of urban function and dwelling type classifications for Greater London, based on detailed topographic and address-based data (sourced from Ordnance Survey MasterMap). The multi-scale approach allows the Built Environment Model to be viewed at fine-scales for local planning contexts, and at city-wide scales for aggregate geographical analysis, allowing an improved understanding of urban processes. This flexibility is illustrated in the two examples, that of urban function and residential type analysis, where both local-scale urban clustering and city-wide trends in density and agglomeration are shown. While we demonstrate the multi-scale Built Environment Model to be a viable approach, a number of accuracy issues are identified, including the limitations of 2D data, inaccuracies in commercial function data and problems with temporal attribution. These limitations currently restrict the more advanced applications of the Built Environment Model

Inequalities in Mental Health Across Urban Canada

Introduction There is a plethora of research describing the inverse relationship between socioeconomic status, a social determinant of health, and an individual’s health status. Inequalities, such as the discrepancy in health status by income, are harmful to a society’s well being, socially, physically and economically. Mental health disorders are widely prevalent across Canada but are not well documented in terms of the social determinants of health or in terms of health inequalities. This thesis aims to increase knowledge pertaining to the presence of mental health inequalities in urban Canadian cities, as well as how the social determinants of health impact mental health outcomes. Methods This thesis was conducted in two parts: The first part utilized fifteen years (2001-2015) of the Canadian Community Health Survey and three iterations of the Canadian Census of Population. Relative, absolute and overall mental health inequalities were calculated at the city, provincial and national level using self-reported mental health outcomes (Mood Disorder, Anxiety Disorder, Life Stress, and Poor Mental Health). Comparisons were made of prevalence rates and measures of inequality between cities and provinces, and over time. The second study used the 2012 mental health component of the Canadian Community Health Survey. Fifteen variables describing various social determinants of health were individually fitted into simple logistic regression models, then together in multiple logistic regression models predicting the odds of having a Mood Disorder, Anxiety Disorder, Substance Use Disorder and Any Mental or Substance Disorder. Results At the national level, the prevalence of Poor Mental Health, Mood Disorders and Anxiety Disorders had significantly increased over time. Inequalities were present in all levels of geographies and were maintained or worsened over time. Prevalence rates and inequalities for Poor Mental Health, Mood Disorders and Anxiety Disorders were city dependent. They were more consistent when comparing cities of similar population than geographical proximity and no city could report a lack of inequality or constantly reported the highest level of inequalities. Demographics, socioeconomic status, culture, mental health status, home life, and other categories were significant when added to the simple logistic regression models. The adjusted odds ratios differed in magnitude and direction by mental health outcome when added to the multiple logistic regression models. Together these results point towards a need for increased city and social determinant specific data surrounding mental health in urban Canada

Commuting to School in Leeds : How useful is the PLASC?

Children's daily travel behaviour is dominated by the journey to school. In some cases, this movement takes only a few minutes and involves no means of transport other than foot; in other instances, the journey can be over substantial distances, be extensive in duration and involve some form of public or private transport. The combination of journeys taking place is likely to have a substantial impact on traffic congestion, particularly since the morning peak coincides with that associated with the journey to work. What datasets exist that allow us to measure and understand this behaviour

Consumer Data Research

Big Data collected by customer-facing organisations – such as smartphone logs, store loyalty card transactions, smart travel tickets, social media posts, or smart energy meter readings – account for most of the data collected about citizens today. As a result, they are transforming the practice of social science. Consumer Big Data are distinct from conventional social science data not only in their volume, variety and velocity, but also in terms of their provenance and fitness for ever more research purposes. The contributors to this book, all from the Consumer Data Research Centre, provide a first consolidated statement of the enormous potential of consumer data research in the academic, commercial and government sectors – and a timely appraisal of the ways in which consumer data challenge scientific orthodoxies

Accessing Healthy Food: A sentinel mapping study of healthy food retailing in Scotland

This study on the availability of an affordable healthy food shopping basket was commissioned by the Food Standards Agency Scotland and undertaken between 2005 and 2007 by the Centre for the Study of Retailing in Scotland

Consumer Data Research

Big Data collected by customer-facing organisations – such as smartphone logs, store loyalty card transactions, smart travel tickets, social media posts, or smart energy meter readings – account for most of the data collected about citizens today. As a result, they are transforming the practice of social science. Consumer Big Data are distinct from conventional social science data not only in their volume, variety and velocity, but also in terms of their provenance and fitness for ever more research purposes. The contributors to this book, all from the Consumer Data Research Centre, provide a first consolidated statement of the enormous potential of consumer data research in the academic, commercial and government sectors – and a timely appraisal of the ways in which consumer data challenge scientific orthodoxies

The Chorography of the Modern City

Until the nineteenth century, space was represented and produced through mathematically constructed drawings: plans and sections captured buildings and the scientific map recorded the territory. The development of technologies of transport brought crisis into this static and balanced world as speed and displacement radically reconfigured the subject’s orientation. This thesis examines the maps, plans, guides and signs produced in Britain in the nineteenth and twentieth century to accompany railway travelling, motoring, underground commuting and walking in the city, arguing that they indeed became chorographies of the modern metropolis. These modern chorographies not only exploited the possibilities of the graphein in order to deal with the complexities of space, time and movement, but they also prescribed a very specific knowledge, one that dictated a new way of being in space. In fact, they created a new set of spaces altogether