A theory driven, spatially explicit agent-based simulation to model the economic and social implications of urban regeneration

We model the economic mechanics of housing regeneration employing the rent-gap theory proposed by Neil Smith in 1979. We discuss the conditions for successful regeneration in theory, using an abstract representation of a city, then try and evaluate the possible outcomes of an actual regeneration programme in Salford, England in terms of property prices and area social composition

Investigating the Behaviour of Twitter Users to Construct an Individual-Level Model of Metropolitan Dynamics.

In this paper, consideration is given to the use of new forms of social network data as a means to enrich our understanding of complex structures and activity patterns in urban areas. Specifically, a sample of Twitter messages (‘tweets’) in the city of Leeds is assembled from publicly available sources, and spatial and temporal patterns in these data are demonstrated, with special reference to the geodemographic profiles of service users. It is argued that classical space-time models of individual behaviour provide one possible framework for the interpretation of patterns, and the process of attempting to classify activities is begun with reference to the geographical distribution, timing and, importantly, the content of messages. Some initial analysis is undertaken to examine emerging networks of interconnection between users and individual users’ spatio-temporal behaviour. In the discussion, it is suggested that the integration of this form of social data analysis with existing microscale representations and multi-agent models of city structure and dynamics will provide fertile ground for future research

Simple, multiple and multiway correspondence analysis applied to spatial census-based population microsimulation studies using R

As a bivariate and multivariate multidimensional exploratory method, simple and multiple correspondence analyses have been used successfully in social science for survey or questionnaire results descriptions. Nonetheless, the complexity of social interactions including health status indicators, with also the need to take into account the spatial and temporal realm of the survey, may incline to look at variable associations in a multiway approach instead of a two-way matrix analysis. This means for example, that interaction of order three between the spatial configuration (say the Output Areas of an urban zone), the set of categorical variables (say selected from a census survey) and the evolution (say every 5 years over a 30 years period) would be considered in order to differentiate spatio-temporal associations across categorical variables. For census-based spatial simulation models such as microsimulations, exhibiting this kind of properties is useful as forecasts moves of population characteristics to be considered for healthcare policy scenario analysis. In this paper it is shown how to run this type of analysis within R using a package dedicated to multiway analysis (the R package PTAk), that is, working on multi-entry array data using an algorithm extending classical multidimensional analysis. A didactic approach from two-way analyses to multiway ones, of the same dataset generated from a population spatial simulation model allows a critical demonstration of the potential of the different t methods. Particular attention is also given to the different choices of spatial units and the scale variation effect within a nested administrative zoning system that can be analysed by a correspondence analysis with respect to a model (extending the approach using the independence model) and which can be done for a simple, multiple of multiway correspondence analysis

Exurban land cover and land market evolution: Analysis, review and computational experimentation of spatial and agent heterogeneity from the bottom up

This dissertation investigates selected empirical and theoretical aspects of land-use and land-cover change (LUCC) in exurban areas. Two challenges – observation and monitoring of LUCC, and spatially explicit modeling, are addressed using three main approaches – measuring, reviewing and agent-based modeling (ABM). All of these approaches focus on LUCC at the individual household level, investigating how micro-scale elements interact to influence macro-scale functional patterns—bottom-up analysis. First, the temporal change of the quantity and pattern of land-cover types within exurban residential parcels in three townships in the southeastern Michigan is examined using landscape metrics and local indicators of spatial association at the parcel and parcel-neighborhood level respectively. The results demonstrate that the number and area of exurban residential parcels increased steadily from 1960 to 2000, and different land-cover types have distinctive temporal changes over time. The results also indicate that there is a convergence process at the neighborhood level through which the quantity and pattern of land cover in parcels conform with the neighborhood appearance. Second, 51 urban residential choice models based on ABM are reviewed. The results divide these models into three categories (i.e. models based on classical theories, models focusing on different stages of urbanization process; and integrated ABM and microsimulation models). This review also compares the differences among these models in their representations of three essential features brought by the technique of ABM: agent heterogeneity, the land market and output measurement. Challenges in incorporating these features, such as the trade-off between the simplicity and abstraction of model and the complexity of urban residential system, interactions of multiple features and demands for data at individual level, are also discussed. Third, the effects of agent heterogeneity on spatial and socioeconomic outcomes under different levels of land-market representations are explored through three experiments using a stylized agent-based land-market model. The results reveal that budget heterogeneity has prominent effects on socioeconomic outcomes, while preference heterogeneity is highly pertinent to spatial outcomes. The relationship between agent heterogeneity and macro-measures becomes more complex as more land-market mechanisms are represented. The results also imply that land-market representation (e.g., competitive bidding) is indispensable to reproduce the results of classical urban land market models (e.g., monocentric city model) in a spatial ABM when agents are heterogeneous

Modelling individual and place variations in residential moves using commercial data and official statistics

Through its ability to transform local area population size, composition and character, residential mobility is a subject of particular relevance for policy makers, service providers, academics and, to some extent, the population at large. Whilst the phenomenon can be understood in very basic terms as the relocation of an individual and/or household from one geographic location to another, the place-based and subject-specific determinants that are said to inform population movement, and the associated propensities and trends, are inherently complex and multifaceted. There is a long tradition in the quantitative study of population movement in Great Britain, with a great many models calibrated using different data sources of varying detail, size and coverage and designed with the purpose of providing improved interpretation and understanding of either micro (individual/household) or macro (area) processes. In this thesis a new source of commercial data is employed which has the potential to allow for a novel break from the traditional dichotomy of the micro/macro approach. Indeed, through the combined use of detailed geo-referenced and geographically extensive microdata, appropriate statistical methods, and well-informed micro and macro theory, this work is able to simultaneously measure, analyse and interpret a variety of individual and place variations in residential mobility in Britain. The thesis integrates a previously unused source of commercial data with official statistics and provides unique insights into various multilevel patterns, propensities and characteristics of residential mobility that have, whilst long theorised, often been difficult to demonstrate empirically due to a longstanding dearth in access to suitably detailed data and methods. In particular, new insights are gained through the examination of a number of understudied subjective and behavioural characteristics of movers vis-à-vis stayers across different life-course stages, the detailed interrogation of duration-of-residence effects and associated residential exposure times on future movement propensities and the simultaneous analysis of micro and macrogeographical (origin and destination) variations in the postcode-to-postcode distance travelled by recent movers