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UCL Home  /  Geography  /  People  /  Research Staff  /  Guy Lansley

Guy Lansley

Senior Research Fellow in Consumer Data

The Chorley Institute
Department of Geography
University College London
Pearson Building
Gower Street

Tel: 020 3108 1099

Office hours: Email to book an appointment
Thu: 14:00 - 15:00
Fri: 14:00 - 16:00

Twitter: @GuyLansley



Guy Lansley, Tom Randall-Page, Benedetta Rogers and Cake Industries

The density of Tweets about education in Central London (Lansley and Longley, 2016)Guy Lansley is a research associate at the Consumer Data Research Centre (CDRC), based at the Department of Geography, UCL. His main academic interests are geodemographics and demographic data, and geographical information systems. He has a BA  in Geography from the University of Sheffield and an MSc in Geographic Information Systems (GIS) from the University of Leeds. He also has a PhD in Big Data and Geodemographics from the Department of Geography at UCL.

Guy joined the Department of Geography as a Teaching Fellow in Population Geography in 2012. During this post he also contributed towards an EPSRC funded project titled "Uncertainty of Identity: Linking Spatio-Temporal Information between the real and virtual worlds". His research explored the geography of UK naming conventions and geotagged social media activity in London.

In 2014 he took up a new position as a Research Associate for the Consumer Data Research Centre, an ESRC funded initiative between UCL, the University of Leeds, the University of Liverpool and the University of Oxford. Guy is currently researching information which can be generated from the wealth of ‘big' consumer data sets created from various different sectors. He also still lectures in undergraduate and postgraduate taught courses at UCL as a specialist in quantitative methods.

Estimating migration
Journal Articles
Book Chapters
  • Lansley, G., Wu, Q., Singleton, A., Unwin, D., and Kemp. K. (2015) Geographic Information Science and Systems: Instructor’s Manual (4th Edition). Wiley, Chichester.
  • Lansley, G., Wei, Y. and Rains, T. (2015) Identifying the Major Traits of Ethnic Clustering in England and Wales from the 2011 Census. The Consumer Data Research Centre Working Paper Series, 1.

Estimations of population churn (Guy Lansley, 2017)

Guy’s research focuses on exploring and harnessing information gained from various types of data sources pertaining to the population across space and time.

Consumer Data

As a part of the Consumer Data Research Data, Guy’s primary interest is in data on British consumers produced through a range of mediums such as credit card databases, store records, and mobile phone generated data. Notable examples of research have included modelling the characteristics of forenames using market data and exploring population movements through GPS traces from various apps. The CDRC Masters Research Dissertation Programme has presented an invaluble opportunity to link commercial datasets with academics. Short summaries of projects can be found here:

Administrative Data

Government produced administrative data often have an advantage of pertaining to considerable shares of the population thus it is of particular value for geodemographics research. Previous research has included examining variations in car ownership traits using records provided by the DVLA and estimating population change and mobility from linking electoral registers collected over consecutive years.

Social Media Data

Guy also conducts research into social media activity. Primarily an analyst of geo-tagged Tweets, Guy has analysed variances in Twitter use across time and space within the UK to evaluate the utility of the dataset to urban planners. His most recent research has entailed topic modelling Tweets from London to produce a Twitter classification to understand how behaviour on the social network vary by space, time and also by the users’ characteristics.

Open Data

Guy is also an advocate of open data. He has conducted several research projects at UCL which sought to establish new information about the UK population derived exclusively from open datasets.


3D GISThe CDRC Masters Research Dissertation Programme

The CDRC MRDP gives Masters level students from all UK institutions the opportunity to conduct their dissertation with the co-supervision of a large Business.

A brief overview of the programme:

  • Students usually apply to projects proposed by retail companies (see below)
  • Successful applicants undertake their dissertations over the spring and summer, with regular supervisory meetings with their retail sponsors
  • Students are also offered regular support from a supervisor from their own university
  • Retail sponsors usually provide £500 in sponsorship, plus travel expenses, to be paid upon successful project completion
  • PDF copies of (completed) dissertations are submitted in September to their retail sponsor and also to the CDRC
  • Each dissertation is considered for a cash prize (£500, £250 and £250) to be awarded at an academic conference in October
  • Students may also be invited to produce A1 posters of their work and present it at the conference
  • Students are also invited to produce a 600 word extended abstract for their projects to be published on the CDRC website

The programme offers students:

  • A stimulating project to work on over the coming months
  • Co-supervision from a major UK business
  • Industry advice on how data are used in real-world problem solving, and experience of addressing problems that matter
  • A chance of winning one of three prizes (£500, £250 and £250), awarded to the best three dissertations (funded by the CDRC)
  • An expenses-paid opportunity to showcase your research findings to an audience of leading retailers, at an annual academic conference in October which is attended by representatives from several UK businesses
  • An opportunity to have your work published and made freely available on the CDRC website
Information for Students (including how to apply): Here
Information for retailers: Here

    CDRC Masters Dissertations Guy Lansley.png

    Undergraduate courses

    GEOG3054: Independent Study

    GEOG3040: Undergraduate Dissertation

    Postgraduate courses

    GEOGG099: MSc Dissertation

    Free online courses

    Lansley, G and Cheshire, J (2018). Creating a Geodemographic Classification Using K-means Clustering in R. CDRC Learning Resources

    Lansley, G and Cheshire, J (2016). An Introduction to Spatial Data Analysis and Visualisation in R. CDRC Learning Resources.

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