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Professor Bob Haining, MA MSc PhD FAcSS FRGS

Professor Bob Haining, MA MSc PhD FAcSS FRGS

Emeritus Professor of Human Geography and Fellow of Fitzwilliam College

Methodologies for spatial data analysis with applications in health services research, the geography of crime and economic geography.



  • 1974-1976: Lecturer, Queen's University Belfast
  • 1977-2000: University of Sheffield (Personal Chair awarded 1993; Head of Department 1994-97)
  • 2000-2016: Department of Geography, University of Cambridge.
    • 2002-2007 Head of Department
  • 2016- Emeritus Professor of Human Geography, Department of Geography, University of Cambridge


  • MA University of Cambridge
  • MSc Northwestern University, USA
  • PhD Northwestern University, USA


Bayesian modelling of small area spatial and spatial temporal data:

  • Modelling spatial and spatial-temporal data using Bayesian methods.
  • Achieving statistical precision when working with small area data (Spatial precision and statistical precision: having the best of both worlds)

Geography and health:

  • An interactive spatial decision support system for monitoring public health using geoinformatics.
  • Crime and its effects on health

Geographical criminology:

  • Evaluating crime reduction programmes: weighing-up the balance sheet
  • Modelling offence geographies


Selected recent publications:

Spatial analysis with GIScience (2003 onwards)

  • R.Haining. "Thinking spatially, thinking statistically." In E.Silva, P.Healey, N.Harris, P.Vander Boeck (eds), The Routledge Handbook of Planning Research Methods, 2014, Routledge, London, Chapter 4.2, p.255-267.
  • R.Haining. "Spatial data and statistical methods: a chronological overview." In M.Fischer and P.Nijkamp (eds). Handbook of Regional Science, 2013, Springer Heidelbrg, Dordrecht, p.1277-1294.
  • J.Wang, R.P.Haining, T.Liu, L.Li and C.Jiang. "Sandwich Estimation for Multi-Unit Reporting on a Stratified Heterogeneous Surface." Environment and Planning, A. 2013, 45(10), 2515-2534.
  • D.A.Griffith, Y.Chun, M.O'Kelly, B.J.L. Berry, R.P.Haining and M-P Kwan. "Geographical Analysis: Its first forty years." Geographical Analysis, 2013, 45, 1-27.
  • R.Haining and J.Law 'Geographical Information Systems models and spatial data analysis.' In A.Batabyal and P.Nijkamp (eds) Research Tools in Natural Resource and Environmental Economics, 2011. World Scientific Publishing, Singapore, p.377-402.
  • D.Griffith and R.Haining 'Analyzing small geographic area datasets containing values having high levels of uncertainty.' In N. Tate and P. Fisher (eds.), Accuracy 2010, Proceedings of the 9th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences (University of Leicester, 20-23 July), Leicester, UK: MPG Books Group, pp. 289-292
  • J.Wang, R.Haining and Z.Cao 'Sample surveying to estimate the mean of a heterogeneous surface: reducing the error variance through zoning.' International Journal of Geographical Information Science, 2010, 24(4), 523-43.
  • R.Haining 'The nature of georeferenced data.' In M.Fischer and A.Getis (Eds). Handbook of Applied Spatial Analysis, 2010, Springer, Heidelberg, p.197-217.
  • R.Haining, R.Kerry and M.Oliver 'Geography, spatial data analysis and geostatistics: an overview'. Geographical Analysis, 2010, 42, 7-31. Click here for extended literature review (see footnotes 2 and 3)
  • R.Haining 'The special nature of spatial data.' In A.Fotheringham and P.Rogerson (eds) The SAGE Handbook of Spatial Analysis, 2009, Sage, Los Angeles, p.5-23.
  • R.Haining 'Spatial autocorrelation and the Quantitative Revolution.' Geographical Analysis, 2009, 41, 364-74.
  • R.Haining, J.Law and D.Griffith 'Modelling small area counts in the presence of overdispersion and spatial autocorrelation.' Computational Statistics and Data Analysis, 2009, 53, 2923-37.
  • D.Griffith and R.Haining 'Beyond mule kicks: the Poisson distribution in geographical analysis' Geographical Analysis, 2006, 38, 123-139.
  • R.Maheswaran and R.Haining 'Basic issues in geographical analysis.' In R.Maheswaran and M.Craglia (eds) GIS in Public Health Practice, Taylor and Francis, London, 2004, 13-29.
  • J.Law and R.Haining 'A Bayesian approach to modelling binary data: the case of high intensity crime areas.' Geographical Analysis, 2004, 36 (3), 197-216.
  • M.Goodchild and R.Haining 'GIS and spatial data analysis: converging perspectives'. Papers in Regional Science 2004, 83, 363-385.
  • R.Haining 'Spatial Data Analysis: Theory and Practice.' Cambridge University Press. April, 2003, pp 432.

Health services, spatial epidemiology and related research (2003 onwards)

  • S-Y Tan and R.P.Haining. 'Crime victimization and the implications for individual health and wellbeing: a Sheffield case study.' Social Science and Medicine, 2016 (in press).
  • A.Lawson, S.Banerjee, R.P.Haining and M.D.Ugarte. Handbook of Spatial Epidemiology. 2016, CRC Press, Boca Raton. 684pp.
  • R.P.Haining and R.Maheswaran. 'Geographic information systems in spatial epidemiology and public health.' In A.Lawson, S.Banerjee, R.Haining and M.D.Ugarte (eds) Handbook of Spatial Epidemiology, 2016, CRC Press, Boca raton, p.69-97.
  • G.Sun, R.Haining, H.Lin, N.Oreskovic and J.Hie. 'Comparing the perception with the reality of walking in a hilly environment: an accessibility method applied to a university campus in Hong Kong.' Geospatial Health, 2015, 10(1). DOI 10.4081/gh.2015.340
  • Y.Wang, T.Jia, J.Zhang, Y.Zhang, W.Li and R.P.Haining. 'Community health services in urban China: a geographical case study of access to care.' In P.Watson (ed) Health Care Reform and Globalisation, 2013, Routledge, London, p.164-181.
  • E.J. Ge, R.Haining, C.P.Li, Z.G.Yu, M.M.Y Waye, K.H.Chu and Y.Leung. 'Using knowledge fusion to analyze avian influenza H5N1 in East and South East Asia.' PLoS ONE 2012, 7(5):e29617.
  • R.Haining, G.Li, R.Maheswaran, M.Blangiardo, J.Law, N.Best and S.Richardson. 'Inference from ecological models:estimating the relative risk of stroke from air pollution exposure using small area data.' Spatial and Spatio-Temporal Epidemiology, 2010, 1, 123-131.
  • R.Haining, J.Law, R.Maheswaran, T.Pearson and N.Best. 'Bayesian modelling of environmental risk: example using a small area ecological study of coronary heart disease mortality in relation to modelled outdoor nitrogen oxide levels.' Stochastic Environmental Research and Risk Assessment, 2007, 21(5), 501-509.
  • R.Maheswaran, R.Haining, P.Brindley, J.Law, T.Pearson, N.Best. 'Outdoor NOx and stroke mortality - adjusting for small area level smoking prevalence using a Bayesian approach.' Statistical Methods in Medical Research, 2006, 15, 499-516.
  • R Maheswaran, R.Haining, T.Pearson, M.Campbell, P.Brindley, S.Wise, J.Law'Outdoor air pollution and stroke in Sheffield, United Kingdom - a small area level geographical study.' Stroke, 2005, 36, 239-243.
  • P.Brindley, S.Wise, R.Maheswaran and R.Haining. The effect of alternative representations of population location in the area interpolation of air pollution exposure.' Computers, Environmental and Urban Systems, 2005, 29, 455-469.
  • J.Law, R.Haining, R.Maheswaran, and T.Pearson. 'Analysing the relationship between smoking and coronary heart disease at the small area level.' Geographical Analysis 2006, 38, 140-159.
  • R.Haining and A.Cliff. 'Using a scan statistic to map the incidence of an infectious disease: measles in the USA 1962-1995. In L.Toubiana, C.Viboud, A.Flahault, and A-J.Valleron (eds) Geography & Health. 2003, Chapter 16, 177-194. Proceedings of GEOMED 2001, Paris. Inserm, Paris.
  • P.Brindley, R.Maheswaran, T.Pearson, R.Haining. 'Using modelled outdoor air pollution data for health surveillance.' In R.Maheswaran and M.Craglia (eds) GIS in Public Health Practice,2004, Taylor and Francis, London, 2004, 125-149.
  • R.Maheswaran and R.Haining. 'Basic issues in geographical analysis.' In R.Maheswaran and M.Craglia (eds) GIS in Public Health Practice. 2004, Taylor and Francis, London. 13-29.
  • P.Brindley,R.Maheswaran,T.Pearson, S.Wise and R.Haining. 'Using modelled outdoor air pollution data for health surveillance.' In R.Maheswaran and M.Craglia (eds) GIS in Public Health Practice, 2004, Taylor and Francis, London. 125-149.
  • M.Craglia, R.Haining and P.Signoretta. 'Identifying areas of multiple social need: a case study in the preparation of children services plans.' Environment and Planning C, 2003, 21, 259-276.

Geography of crime (2004 onwards)

  • R.Haining. "Targeting disruption: how can geographic modelling improve our understanding of drivers in serious and organized crime." In C.Ellis (ed) Disrupting Organized Crime. Proceedings of the Conference: Disrupting Organized Crime: developing the evidence base to understand effective action. Royal United Services Institute, Whitehall, London, July 2014, p.40-48.
  • G.Li, R.P.Haining, S.Richardson and N.Best. "Space-time variability in burglary risk: a Bayesian spatio-temporal modelling approach." Spatial Statistics, 2014, 9, 180-191.
  • G.Li, R.P.Haining, S.Richardson and N.Best. "Evaluating the No Cold Calling zones in Peterborough, England: application of a novel statistical method for evaluating neighbourhood policing policies." Environment and Planning, A.,2013, 45(8), 2012-2026.
  • R.Haining. 'The ecological analysis of offence and offender data'. In V.Ceccato (Ed) The Urban Fabric of Crime and Fear, 2012. Springer, Dordrecht, p.141-163.
  • R.Kerry, P.Goovaerts, R.Haining and V.Ceccato. 'Applying geostatistical analysis to crime data: car related thefts in the Baltic States.' Geographical Analysis, 2010, 42, 53-77.
  • R.Haining. 'Spatial methodologies to support local policing in the UK: glimpsing the future.' 21st Century Society, 2009, 4, 161-74.
  • V.Ceccato and R.Haining. 'Short and medium term dynamics and their influence on acquisitive crime rates in the transition states of Estonia, Latvia and Lithuania'. Applied Spatial Analysis and Policy, 2008, 1, 215-244.
  • P.Brindley, M.Craglia, R.Haining and Young Hoon-Kim. 'Crime map analyst: a GIS to support local area crime reduction' In S.Wise and M.Craglia (eds) GIS and Evidence-Based Policy Making, 2008, Taylor and Francis, Boca Raton, p.113-131.
  • R.Haining and J.Law. 'Combining police perceptions with police records of serious crime areas: a modelling approach.' Journal of the Royal Statistical Society Series A (Statistics in Society), 2007, 170(4), 1019-1034.
  • V.Ceccato, R.Haining and T.Kahn. 'The Geography of homicide in Sao Paolo, Brazil.' Environment and Planning, A, 2007, 39(7), 1632-53.
  • V.Ceccato and R.Haining. 'Assessing the geography of vandalism: evidence from a Swedish city.' Urban Studies, 2005, 42, 1637-1656.
  • M.Craglia, R.Haining and P.Signoretta. 'Modelling high intensity crime areas: comparing police perceptions with offence/offender data in Sheffield.' Environment & Planning A. 2005, 37(3), 503-524.
  • V.Ceccato and R.Haining. 'Crime in border regions: the Scandinavian case of Oresund 1998-2001.' Annals, Association of American Geographers, 2004, 94, 807-826.

Economic Geography (2003 onwards)

  • P.Plummer, E.Sheppard and R.P.Haining. "Rationality, stability and endogeneous price formation in spatially interdependent markets." Environment and Planning A, 2012, 44, 538-559.
  • X.Ning and R.Haining. 'Spatial pricing in interdependent markets: a case study of petrol retailing in Sheffield.' Environment and Planning A, 2003, 35, 2131-2159. [Download data]


Short Courses (recent)

  • 'Spatial and Spatial-Temporal Data Analysis using Bayesian Hierarchical Models.' ESRC-funded 3-day short course in association with the Social Science Research Methods Centre (with G.Li and G.Amable). Cambridge, 2015-2016.
  • 'Spatial data analysis.' University of Central Karnataka, India. November 2015.
  • 'Spatial data analysis.' Wuhan University, China. October 2015 and October 2017.
  • 'Spatial data analysis with spatial econometrics'. IPSA-USP Summer School, Sao Paulo, Brazil. Feb 2015.
  • 'Spatial data analysis' KTH, Stockholm, Sweden. April 2017.

Journal activities (current)

  • Associate Editor: Spatial and Spatio-Temporal Epidemiology
  • Editorial Board: Jo. of Geographical Systems; Int. Jo. of Geographical Information Science.