Measuring spatial separation processes through the minimum commute : the case of Flanders

The average distance covered by individual commuting trips increases year after year, regardless of the travel mode. The causes of this phenomenon are diverse. Although increasing prosperity is often invoked as the main reason, the discipline of spatial planning also points to the relevance of land-use policies that enable processes of suburbanization and sprawl. By calculating time series of spatially disaggregated theoretical minimum commuting distances, this paper offers a method to identify and quantify the process of spatial separation between the housing market and the job market. We identify the detected spatial separation as one of the possible indicators for the contribution of spatial processes to the growth of traffic. In the case study area of Flanders and Brussels (Belgium), it is found that over time the minimum commuting distance increased in many municipalities, especially where population is growing faster than job supply, or where traditionally high concentrations of employment still increase. Decreases are noticed in suburban areas that are getting a more urban character by acquiring a considerable functional mix. For the study area in its entirety, we do indeed register an increasing spatial separation between home and work locations. However, this separation evolves less rapidly than the increase in commuting distances itself. Regarding the methodology, we find that the use of municipalities as a spatial entity is suitable for grasping regional transformations of the economy and intermunicipal forms of suburbanization and peri-urbanization. However, a similar methodology, applied at a more detailed geographical scale, could be used to detect processes of sprawl in the morphological sense

Linking complexity economics and systems thinking, with illustrative discussions of urban sustainability

The expanding research of complexity economics has been signalling its preference for a formal quantitative investigation of diverse interactions between heterogeneous agents at the lower, micro-level resulting in emergent, realistic socioeconomic dynamics at the higher, macro-level. However, there is scarcity in research that explicitly links complexity perspectives in economics with the systems thinking literature, despite these being highly compatible, with strong connections and common historical traces. We aim to address this gap by exploring commonalities and differences between the two bodies of knowledge, seen particularly through an economics lens. We argue for a hybrid approach, in that agent-based complexity perspectives in economics could more closely connect to two main systems thinking attributes: a macroscopic approach to analytically capturing the complex dynamics of systems, and an inter-subjective interpretivist dimension, when investigating complex social-economic order. Illustrative discussions of city sustainability are provided, with an emphasis on decarbonisation and residential energy demand aspects

Proceedings of the Salford Postgraduate Annual Research Conference (SPARC) 2011

These proceedings bring together a selection of papers from the 2011 Salford Postgraduate Annual Research Conference(SPARC). It includes papers from PhD students in the arts and social sciences, business, computing, science and engineering, education, environment, built environment and health sciences. Contributions from Salford researchers are published here alongside papers from students at the Universities of Anglia Ruskin, Birmingham City, Chester,De Montfort, Exeter, Leeds, Liverpool, Liverpool John Moores and Manchester

Methodology for an integrated modelling of macro and microscopic processes in urban transport demand

The paper presents the theoretical formulation and the underlying assumptions for an activity-based approach of transport demand modelling. Starting with the definition of a time hierarchy of decision-making in the urban environment, rules are formulated that dictate the general hierarchic structure of individuals’ choices in the urban system. The temporal scale defines decisions for activities and their daily sequence, the geographical scale decisions associated to destination choice processes. We build activity plans (number and daily sequence of activities) from an empirical data set and calculate trip paths (time-spatial trajectories including transport modes and travel destinations) assuming consumers to maximize their utility in the decision-making process. First results of the translation of the theoretical model into a real-world application are shown for the city of Santiago, Chile

Challenges in Complex Systems Science

FuturICT foundations are social science, complex systems science, and ICT. The main concerns and challenges in the science of complex systems in the context of FuturICT are laid out in this paper with special emphasis on the Complex Systems route to Social Sciences. This include complex systems having: many heterogeneous interacting parts; multiple scales; complicated transition laws; unexpected or unpredicted emergence; sensitive dependence on initial conditions; path-dependent dynamics; networked hierarchical connectivities; interaction of autonomous agents; self-organisation; non-equilibrium dynamics; combinatorial explosion; adaptivity to changing environments; co-evolving subsystems; ill-defined boundaries; and multilevel dynamics. In this context, science is seen as the process of abstracting the dynamics of systems from data. This presents many challenges including: data gathering by large-scale experiment, participatory sensing and social computation, managing huge distributed dynamic and heterogeneous databases; moving from data to dynamical models, going beyond correlations to cause-effect relationships, understanding the relationship between simple and comprehensive models with appropriate choices of variables, ensemble modeling and data assimilation, modeling systems of systems of systems with many levels between micro and macro; and formulating new approaches to prediction, forecasting, and risk, especially in systems that can reflect on and change their behaviour in response to predictions, and systems whose apparently predictable behaviour is disrupted by apparently unpredictable rare or extreme events. These challenges are part of the FuturICT agenda

Visual ecology: sensing the social world

Social animals, and even solitary animals, must at different points in their life actively search for and locate conspecifics within their environment, using one or multiple senses. One sense in particular, vision, can provide some of the most spatially detailed and temporally rapid information about the environment. Yet, the surrounding environment can also severely challenge animals’ abilities to find fellow conspecifics. Furthermore, once an animal successfully locates conspecifics, it must then make key decisions about when and where to enter group formations, decisions which may strongly impact their access to socially-acquired resources. Even after an animal has positioned itself within a group, it may still rely on vision to successfully interact with conspecifics and acquire the benefits of sociality. My thesis addresses the question of how and why animal visual systems are shaped by both the physical and the social world, as animals attempt to find (chapter 1), enter (chapter 2), and interact (chapter 3) with social formations. In addition, I address how and why the morphology of the eye itself may be linked to specific features of the physical and social environment (chapter 4). Chapters 1-3 focus on field-based behavioral experiments of the highly social terrestrial hermit crab (Coenobita compressus). Chapter 4 compares multiple species within the clade of hermit crabs, which span a range of environments. In chapter 1, we tested how the environment can place sensory constraints on an animal’s ability to locate a social group. In chapter 2, we tested how different elements of a social group’s orientation and organization impact an outsider’s ability to detect and position itself within the group. In chapter 3, we tested how the experimentally-induced loss of vision can impact individuals’ social behavior. Finally, in chapter 4, we compared macroscopic and microscopic dimensions of eye morphology across three species of hermit crab, which inhabit different environments. Overall, my thesis disentangles the complex relationship between an animal’s sensory system and the physical and social environment, revealing the overriding importance of vision in locating conspecifics, entering groups, and making social decisions in complex environments

Methodological and empirical challenges in modelling residential location choices

The modelling of residential locations is a key element in land use and transport planning. There are significant empirical and methodological challenges inherent in such modelling, however, despite recent advances both in the availability of spatial datasets and in computational and choice modelling techniques. One of the most important of these challenges concerns spatial aggregation. The housing market is characterised by the fact that it offers spatially and functionally heterogeneous products; as a result, if residential alternatives are represented as aggregated spatial units (as in conventional residential location models), the variability of dwelling attributes is lost, which may limit the predictive ability and policy sensitivity of the model. This thesis presents a modelling framework for residential location choice that addresses three key challenges: (i) the development of models at the dwelling-unit level, (ii) the treatment of spatial structure effects in such dwelling-unit level models, and (iii) problems associated with estimation in such modelling frameworks in the absence of disaggregated dwelling unit supply data. The proposed framework is applied to the residential location choice context in London. Another important challenge in the modelling of residential locations is the choice set formation problem. Most models of residential location choices have been developed based on the assumption that households consider all available alternatives when they are making location choices. Due the high search costs associated with the housing market, however, and the limited capacity of households to process information, the validity of this assumption has been an on-going debate among researchers. There have been some attempts in the literature to incorporate the cognitive capacities of households within discrete choice models of residential location: for instance, by modelling households’ choice sets exogenously based on simplifying assumptions regarding their spatial search behaviour (e.g., an anchor-based search strategy) and their characteristics. By undertaking an empirical comparison of alternative models within the context of residential location choice in the Greater London area this thesis investigates the feasibility and practicality of applying deterministic choice set formation approaches to capture the underlying search process of households. The thesis also investigates the uncertainty of choice sets in residential location choice modelling and proposes a simplified probabilistic choice set formation approach to model choice sets and choices simultaneously. The dwelling-level modelling framework proposed in this research is practice-ready and can be used to estimate residential location choice models at the level of dwelling units without requiring independent and disaggregated dwelling supply data. The empirical comparison of alternative exogenous choice set formation approaches provides a guideline for modellers and land use planners to avoid inappropriate choice set formation approaches in practice. Finally, the proposed simplified choice set formation model can be applied to model the behaviour of households in online real estate environments.Open Acces

"Last-Mile" preparation for a potential disaster

Extreme natural events, like e.g. tsunamis or earthquakes, regularly lead to catastrophes with dramatic consequences. In recent years natural disasters caused hundreds of thousands of deaths, destruction of infrastructure, disruption of economic activity and loss of billions of dollars worth of property and thus revealed considerable deficits hindering their effective management: Needs for stakeholders, decision-makers as well as for persons concerned include systematic risk identification and evaluation, a way to assess countermeasures, awareness raising and decision support systems to be employed before, during and after crisis situations. The overall goal of this study focuses on interdisciplinary integration of various scientific disciplines to contribute to a tsunami early warning information system. In comparison to most studies our focus is on high-end geometric and thematic analysis to meet the requirements of small-scale, heterogeneous and complex coastal urban systems. Data, methods and results from engineering, remote sensing and social sciences are interlinked and provide comprehensive information for disaster risk assessment, management and reduction. In detail, we combine inundation modeling, urban morphology analysis, population assessment, socio-economic analysis of the population and evacuation modeling. The interdisciplinary results eventually lead to recommendations for mitigation strategies in the fields of spatial planning or coping capacity