A spatial microsimulation model with student agents

Wu, Belinda; Birkin, Mark; Rees, Phil

doi:10.1016/j.compenvurbsys.2008.09.013

Cited by 48 publications

(37 citation statements)

References 24 publications

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“…However, the obvious problem with this approach is that the future is by definition uncertain, meaning that any attempts to project current trends into the future risk being misleading (Smil, 1993), regardless of whether the future scenarios are created by a top-down 'aggregate projection' (Ballas et al, 2005a), in which constraints are imposed for each zone, or via some kind of agent-based model (e.g. Wu et al, 2008). There is much work to be done in this area and we hope that the static model used in this paper could provide ideas (theoretical as well as methodological) for dynamic simulations of the societal responses to changes in the availability of fossil fuels, whether this is imposed by an oil price shock (as assumed in this paper) or planned, for example as a strategy to mitigate climate change.…”

Section: Discussionmentioning

confidence: 99%

The ‘oil vulnerability’ of commuter patterns: A case study from Yorkshire and the Humber, UK

Lovelace

Philips

2014

Geoforum

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Motorised transport infrastructure and increasingly specialised labour markets have resulted in energy intensive commuter patterns in many parts of the world. This is cause for concern due to the possibility of oil price shocks and the need to restrict the combustion of fossil fuels to minimise the chances of runaway climate change. The paper investigates methods to identify the spatial distribution and socio-demographic profiles of those who are vulnerable to high oil prices. It does this by use of four metrics of oil vulnerability which were developed using a spatial microsimulation model and applied to the case study region of Yorkshire and the Humber, UK. The metrics capture different aspects of vulnerability and highlight the importance of translating conceptual definitions into practical metrics. The geographically aggregated results coincide with the literature: rural areas are associated with the highest levels of vulnerability. The individual level results indicate that vulnerability can be prevalent even in seemingly resilient areas. Ultimately, we conclude that the social and spatial distribution of oil vulnerability depends on how an energy-constrained future is envisioned. Creating localised metrics about the future is a challenging task fraught with danger but could, provided that these metrics are interpreted with sufficient humility, aid the development of equitable policies to encourage resilience, as part of a worldwide transition away from fossil fuels.

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Section: Discussionmentioning

confidence: 99%

The ‘oil vulnerability’ of commuter patterns: A case study from Yorkshire and the Humber, UK

Lovelace

Philips

2014

Geoforum

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“…Such intelligence will then guide agents to make decisions and take actions during their interactions with other agents and the environment that they live in, according to their individual attributes and rules. The ease of introducing unique rules for different agents without affecting the remaining agents/components in the ABM helps us to improve the MSM when there is a knowledge gap or unavailability of data (Wu et al, 2008). ABM approach also enables the modelling of heterogeneous agents to represent individuals with distinctive characteristics and behaviors within the system (Axtell, 2000).…”

Section: Methodsmentioning

confidence: 99%

“…As a result of students joining the general migration process, the MSM results in a considerable number of students reside in suburban areas and many students continue to stay in Leeds after their study and grow old in the central area. This projection is not an accurate reflection of the reality (Wu et al, 2008). Therefore a hybrid approach combining MSM and ABM techniques is adopted to strengthen the modelling of the subtlety of the local migration patterns in our model and the behavior modelling of the student migrants, as this is less well studied and lacks an appropriate theoretical basis in MSM.…”

Section: Residential Land Use Application: Student Accommodationsmentioning

confidence: 99%

Moses: Planning for the Next Generation

Birkin

2013

IRSPSD International

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Abstract:The study of population changes has always been at the centre of public policy and planning. People's movements, interactions and behaviors will inevitably have an important impact on the society and environment that they are living in. At the same time, such changes will also lead to an evolution of the population itself over time. Advances in technologies and new tools often bring new visions to such studies. To facilitate strategic decision making and to plan developments for a more sustainable future, it is vital to study and understand the changes in our population. This paper introduces Moses, an individual based model that simulates the UK population through discrete demographic processes at a fine spatial scale for 30 years from 2001 to 2031. The modeling method is grounded in a dynamic spatial MicroSimulation Model (MSM), but also introduced Agent Based Model (ABM) insights to strengthen the modeling of movements, interactions and behaviors of distinctively different subpopulations. The MSM can not only produce projections of baseline population with rich information on individuals to facilitate various studies, it can be also useful in providing an assessment of multiple scenarios for different planning applications. In this paper, we will demonstrate three spatial planning applications in the areas of residential land use planning, public health planning and public transport planning. Whilst the demonstrations are deliberately made simple, the contribution of intelligent agents in the modeling of interaction, behavior and the impact of personal histories on demographic changes is clearly shown. Within this framework, it enables researchers to effectively model the heterogeneous decision making units on a large scale, as well as provide the flexibility to introduce different modeling techniques to strengthen various aspects of the model.

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“…Geographers and other social scientists have also become interested in microsimulation as a means for representing spatial or social disaggregation, and example applications are widespread in healthcare planning, transport research and demographic analysis. Typically, microsimulation is seen as a means for applying well-defined rules to a wide variety of individual circumstances in order to achieve insights with real predictive or applied value, in contrast to agent-based modelling approaches, which focus on a more theoretically rich understanding of the interaction between individuals and their environment [10].…”

Section: Existing Neiss Simulation Tools (A) Background: Microsimulationmentioning

confidence: 99%

Towards victim-oriented crime modelling in a social science e-infrastructure

Malleson

Birkin

2011

Phil. Trans. R. Soc. A.

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The National e-Infrastructure for Social Simulation (NeISS) is a multi-disciplinary collaboration between computation and social science within the UK Digital Social Research programme. The project aims to develop new tools and services for social scientists and planners to assist in performing 'what-if' scenario predictions in a variety of policy contexts. A key part of the NeISS remit is to explore real-world scenarios and evaluate real policy applications. Research into the processes and drivers behind crime is an important application area that has major implications for both improving crime-related policy and developing effective crime prevention strategies. This paper will discuss how the current e-infrastructure and available microsimulation tools can be used to improve an existing agent-based burglary simulation (BurgdSIM) by including a more realistic representation of the victims of crime. Results show that the model produces different spatial patterns when individual-level victim data are used and a risk profile of the synthetic victims suggests which types of people have the largest burglary risk.

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A spatial microsimulation model with student agents

Cited by 48 publications

References 24 publications

The ‘oil vulnerability’ of commuter patterns: A case study from Yorkshire and the Humber, UK

The ‘oil vulnerability’ of commuter patterns: A case study from Yorkshire and the Humber, UK

Moses: Planning for the Next Generation

Towards victim-oriented crime modelling in a social science e-infrastructure

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