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School of Geography

Nick Malleson Dr Nick Malleson

Contact details

Room Manton 10.114
School of Geography
University of Leeds
University Road
Leeds LS2 9JT   UK

Email:
n.s.malleson

Telephone:
+44 (0) 113 34 35248

Student hours:

Work in progress

surf - Simulating Urban Flows

The aim of the surf project is to create a simulation that is capable of modelling the individual movements of people in an urban environment as they undertake their daily routine activities (commuting, shopping, schooling, etc.). It will use a combination of 'big data' analysis and cutting-edge computer simulation to create a highly realistic siulation that we can use to better undestand the daily ebb and flow of urban life. Ultimately, the results will be used to quantify the impacts of levels of crime and pollution on citizens

Consumer Data Research Centre (CDRC)

The aim of the CDRC is to create, supply, maintain and deliver consumer-related data to a range of end users, alongside a programme of research and outreach activities. I am leading a research strand that will apply advanced spatial analysis and modelling techniques to reveal new insights into the causes and distributions of crime through the inclusion of novel ‘Big’ data sources.

N8 Policing Research Partnership: Innovation and the Application of Knowledge for More Effective Policing

This 5 year project will develop and test mechanisms of research co-production between the Police and Universities. I am involved in the Policing Data Analytics strand, that will look at new ways to safely access and analyse police and crime data.

GeoCrimeData: Exploring Geospatial Data for Crime Analysis

The work of crime analysts and modellers could benefit substantially from the use of new spatial data sets that are becoming more readily available. Examples include road networks (e.g. Open Street Map), building boundary datasets (e.g Ordnance Survey MasterMap) as well as under-utilised social network data (e.g. Twitter) or other volunteered sources. The GeoCrimeData Project is exploring many novel data sources and manipulating them using geographical routines in order to generate new forms of spatial intelligence that can help to add value to the interpretation of recorded crime data

Agent-Based Modelling of Crime

Crime is an extremely complex phenomenon which is driven by a wide array of both environmental and human-behavioural characteristics. Traditional techniques which utilise statistical methods to investigate crime and predict future crime rates struggle to incorporate the highly detailed, low-level factors which will determine whether or not a crime is likely to occur.

This research utilises agent-based modelling which is a methodology that can account for these low-level characteristics. By incorporating detailed behavioural information into a simulation consisting of many "intelligent" agents it might be possible to produce hypotheses regarding how offenders behave in the real world and the factors which determine their movements.

The product of the work will be an application which could be used by local authorities to predict the effects of new environmental developments or policies. Specifically, the model will be used to experiment with the effects that a major development project will have on rates of residential burglary in Leeds.