Associate Professor

Jane Law.Degrees

Ph.D. Geodesy and Geomatics Engineering, University of New Brunswick, Canada, 2000

University Teaching Diploma - University of New Brunswick, Canada, 1999

M.Sc. Land Information Systems, Hong Kong Polytechnic University, Hong Kong, 1994

B.Sc. Survey and Mapping Sciences, North East London Polytechnic, UK, 1985

Contact information
519-888-4567 ext. 47369
Location: EV3 3251

Research interests

  • Geographic information systems and spatial analysis methodologies and their applications in public health and crime research
  • Spatial demography
  • Spatial statistics
  • Bayesian spatial analysis/Hierarchical spatial modeling
  • Spatial epidemiology
  • Environmental criminology
  • Healthy communities and the built environment
  • Neighbourhood/community effect
  • Geomatics, land information systems
  • Public health planning
  • Law enforcement planning
Contact Jane Law for more information on research opportunities.

Research grants/projects

  • Advancing spatial analysis methodologies using a Bayesian approach (Principal investigator), 2009-2022.

Graduate student supervision

  Number of students currently supervising/co-supervising Total number of student supervisions/co-supervisions
Masters 2 43
PhD 1 5

Recent/key publications

[* = student co-authors]

  • Rutter EC, Tyas SL, Maxwell CJ, Law, J., O’Connell, M., Konnert, C., & Oremus, M. (2020) Association between functional social support and cognitive function in middle-aged and older adults: a protocol for a systematic review, BMJ Open 2020;10:e037301. DOI: 10.1136/bmjopen-2020-037301

  • Law, J., Quick M. *, & Jadavji, A*. (2020) A Bayesian spatial shared component model for identifying crime-general and crime-specific hotspots, Annals of GIS, DOI: 10.1080/19475683.2020.1720290

  • Oremus, M., Konnert, C., Law, J., Maxwell, C.J., O’Connell, M., & Tyas, S. (2019). Social support and cognitive function in middle- and older-aged adults: descriptive analysis of CLSA tracking data, European Journal of Public Health, , ckz047,
  • Quick, M.*, Li, G., & Law, J. (2019). Spatiotemporal modelling of correlated small-area outcomes: Analyzing the shared and type-specific patterns of crime and disorder. Geographical Analysis, 51, 221–248, doi:10.1111/gean.12173
  • Leung, A*, Law, J, Cook, M. & Leatherdale, S. (2019). Exploring and visualizing the small-area level socio-economic factors, alcohol availability and built environment influences of alcohol expenditure for the city of Toronto: A spatial analysis approach. Health Promotion and Chronic Disease Prevention in Canada, Vol. 39, No. 1,
  • Law, J., & Perlman, C. (2018). Exploring geographic variation of mental health risk and service utilization of doctors and hospitals in Toronto: A shared component spatial modeling approach. International Journal of Environmental Research and Public Health, 15(4), 593. doi:10.3390/ijerph15040593
  • Perlman, C. M., Law, J., Luan, H.*, Rios, S., Seitz, D., & Stolee, P. (2018). Geographic clustering of admissions to inpatient psychiatry among adults with cognitive disorders in Ontario, Canada: Does distance to hospital matter? The Canadian Journal of Psychiatry, 63(6), 404-409. doi:10.1177/0706743717745870
  • Luan, H.*, Law, J., & Lysy, M. (2018). Diving into the consumer nutrition environment: A Bayesian spatial factor analysis of neighborhood restaurant environment. Spatial and Spatio-temporal Epidemiology, 24, 39-51. doi:10.1016/j.sste.2017.12.001
  • Quick, M.*, Law, J., & Li, G. (2017). Time-varying relationships between land use and crime: A spatio-temporal analysis of small-area seasonal property crime trends. Environment and Planning B: Urban Analytics and City Science, 0(0), 1-18. doi:10.1177/2399808317744779
  • Luan, H.*, Quick, M.*, & Law, J. (2016). Analyzing local spatio-temporal patterns of police calls-for-service using Bayesian Integrated Nested Laplace Approximation. ISPRS International Journal of Geo-Information, 5(9), 162. doi:10.3390/ijgi5090162
  • Du, Y.*, & Law, J. (2016). How do vegetation density and transportation network density affect crime across an urban central-peripheral gradient: A case study in Kitchener - Waterloo, Ontario. ISPRS International Journal of Geo-Information, 5(7), 118. doi:10.3390/ijgi5070118
  • Quick, M.*, Law, J., Christidis, T.*, & Paller, C.* (2016). Exploring the socioeconomic composition of wind farm communities in Ontario: Implications for wind farm planning and policy. Canadian Journal of Urban Research, 25(2), 62-72. Available at:  Last accessed on 20 June 2018
  • Paller, C.*, Christidis, T.*, Majowicz, S., Aramini, J., Law, J., & Bigelow, P. (2016). Use of Admail and a geographic information system to send surveys to target populations. Canadian Journal of Rural Medicine, 21(3), 67-72. PMID:2738691
  • Law, J. (2016). “Exploring the Specifications of Spatial Adjacencies and Weights in Bayesian Spatial Modeling with Intrinsic Conditional Autoregressive Priors in a Small-area Study of Fall Injuries” AIMS Public Health, Special issue: Spatial Aspects of Health Methods and Applications, 3(1): 65-82. doi: 10.3934/publichealth.2016.1.65.
  • Quick, M*, Law, J. and Luan, H.* (2016). “The influence of on-premise and off-premise alcohol outlets on reported violent crime in the Region of Waterloo, Ontario: Applying Bayesian spatial modeling to inform land use planning and policy”, Applied Spatial Analysis and Policy (in press).
  • Law, J., M. Quick*, and P.W. Chan (2015). “Open area and road density as land use indicators of young offender residential locations at the small-area level: A case study in Ontario, Canada” Urban Studies, DOI: 10.1177/0042098015576316
  • Luan H.*, Law, J., and Quick, M.* (2015) “Identifying food deserts and swamps based on relative healthy food access: a spatio-temporal Bayesian approach” International Journal of Health Geographies, DOI: 10.1186/s12942-015- 0030-8
  • Law, J., M.* Quick, and P.W. Chan. (2015). “Analyzing Hotspots of Crime Using a Bayesian Spatiotemporal Modeling Approach: A Case Study of Violent Crime in the Greater Toronto Area” Geographical Analysis, 1-19, DOI: 10.1111/gean.12047, 47: 1-19
  • Luan, H.*, and Law, J. (2014). “Web GIS-Based Public Health Surveillance Systems: A Systematic Review” ISPRS International Journal of Geo-Information, Vol. 3, 481-506, DOI 10.3390/ijgi3020481
  • Law, J., M.* Quick, and P.W. Chan. (2014). “Analyzing local patterns of crime over time at the small-area level: A Bayesian spatio-temporal modeling approach” Journal of Quantitative Criminology, DOI 10.1007/s10940-013- 9194-1, Vol. 30: 57-78
  • Christidis, T.* and J. Law. (2013), “Mapping Ontario’s wind turbines: challenges and limitations” ISPRS International Journal of Geo-Information, 2(4), 1092-1105, DOI 10.3390/ijgi2041092.
  • Law, J., and M. Quick* (2013), “Exploring links between juvenile offenders and social disorganisation at a large map scale: a Bayesian spatial modeling approach” Journal of Geographical Systems” Vol. 15:1, 89-113, DOI: 10.1007/s10109-012- 0164-1s, Vol. 15: 89-113
  • Quick, M.* and J. Law (2013) “Exploring hotspots of drug offences in Toronto, Ontario: a comparison of four local spatial cluster detection methods”, Canadian Journal of Criminology and Criminal Justice, Vol. 55:2, 215-238.
  • Law, J. and P. Chan (2012). “Bayesian spatial random effect modeling for analyzing burglary risks controlling for offender, socioeconomic, and unknown risk factors.” Applied Spatial Analysis and Policy, Vol. 5, 73-96, DOI: 10.1007/s12061-011- 9060-1.
  • Law, J. and P. Chan (2012). “Monitoring residual spatial pattern using Bayesian hierarchical spatial modelling for exploring unknown risk factors.” Transactions in GIS, Vol. 15 (4): 521-549.
  • Chan, W.*, J. Law, and P. Seliske (2011) “Bayesian Spatial Methods for Small-Area Injury Analysis: a Study of Geographic Variation of Falls in Older People in the Wellington-Dufferin-Guelph Health Region in Ontario, Canada” Injury Prevention, DOI:10.1136/injuryprev-2100-040068.
  • Law (2011)  “Bayesian Spatial Analysis of Recorded Injuries for Strategic Planning to Prevent Injuries: Variable versus Equal Weighting of Neighbours in Conditional Autoregressive Modelling”, GEOMED: 7th International, Interdisciplinary Conference on Spatial Statistics and Geomedical Systems, Victoria, British Columbia, 2011
  • Law (2011) “Understanding the Distribution of Crime: Does It Matter When and Where They Occur? A Bayesian Spatio-temporal Analysis approach”, Session onApplications of Spatial-temporal Analysis in GIScience, American Association of Geographers Annual Meeting, Seattle, USA, 2011
  • Chan, W.*, J. Law, and P. Seliske (2011) “Bayesian Spatial Methods for Small-area Injury Analysis: a Case Study of Seniors’ Falls in the Wellington-Dufferin-Guelph Health Region”, Association of Public Health Epidemiologists in Ontario 2011 Conference, Horseshoe Valley, Ontario.
  • Meng, G., J. Law, and M. Thompson (2010). “Small-scale health-related indicator acquisition using secondary data spatial interpolation.”  International Journal of Health Geographics 2010, 9:50 (13 October 2010).
  • Haining R., G. Li, R. Maheswaran, M. Blangiardo, J. Law, N. Best, and S. Richardson (2010). "Inference from ecological models: estimating the relative risk of stroke from air pollution exposure using small area data.”  Spatial and Spatio-temporal Epidemiology Vol. 1, 123-131.
  • Law, J., and P. W. Chan (2009).  “GIS in Public Health”in W. Dong (ed.) Public Health Sciences,Renmin University Press, Beijing, pp 199-218. 
  • Haining,R., J. Law, and D. Griffith (2009). “Modelling small area counts in the presence of overdispersion and spatial autocorrelation.” Computational Statistics and Data Analysis, 53: 2923-2937.
  • Haining, R.P and J. Law (2007). “Combining Police Perceptions with Police Records of Serious Crime Areas: a Modelling Approach.” Journal of the Royal Statistical Society, Series A, Vol. 170: 4, 1019-1034.
  • Haining, R.P, J. Law, Maheswaran, R., T. Pearson, and P. Brindley (2007).  “Bayesian Modelling of Environmental Risk: a Small Area Ecological Study of Coronary Heart Disease Mortality in relation to Modelled Outdoor Nitrogen Oxide Levels.”  Stochastic Environmental Research and Risk Assessment Vol. 21, No. 5, 501-509.
  • Law, J., R. P. Haining, R. Maheswaran, and T. Pearson (2006). "Analysing the Relationship between Smoking and Coronary Heart Disease at the Small Area Level: A Bayesian Approach to Spatial Modelling." Geographical Analysis 38:2 140-159.
  • Maheswaran, R., R. P. Haining, T. Pearson, J. Law, P. Brindley, and N. G. Best (2006). "Outdoor NOx and Stroke Mortality: Adjusting for Small Area Level Smoking Prevalence Using a Bayesian Approach." Statistical Methods in Medical Research 15, 499-516.
  • Maheswaran, R., R. P. Haining, P. Brindley, J. Law, T. Pearson, P. R. Fryers, S. Wise, and M. J. Campbell (2005). "Outdoor Air Pollution and Stroke in Sheffield, United Kingdom: A Small-Area Level Geographical Study." Stroke 36, 239-43.
  • Maheswaran, R., R. P. Haining, P. Brindley, J. Law, T. Pearson, P. R. Fryers, S. Wise, and M. J. Campbell (2005). "Outdoor Air Pollution, Mortality, and Hospital Admissions from Coronary Heart Disease in Sheffield, UK: A Small-Area Level Ecological Study." European Heart Journal 2543-2549.
  • Law, J., and R. P. Haining (2004). "A Bayesian Approach to Modelling Binary Data: The case of High-Intensity Crime Areas." Geographical Analysis 36:3 197-216.


  • Quick, M.* & Law, J. (2015). Analyzing the Influence of Ethnic Composition and Immigrant Residents on the Spatial Distribution of Violent Crime. In F. Harvey & Y. Leung (Eds.), Advances in Spatial Data Handling and Analysis, (pp. 227-243). Switzerland: Springer International Publishing.
  • Haining, R. and J. Law (2011) “Geographical Information Systems Models and Spatial Data Analysis” in Research Tools in Natural Resource and Environmental Economics, edited by Batabyal, A. and P. Nijkamp, World Scientific Publishing, pp 377-401.
  • Law, J. (2009). Book review: “Lawson, A.B. Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology. CRC 2008.” Biometrics Vol. 65, 661-662.
  • Law, J. & Chan, P. (2009). GIS in Public Health. In W. Dong (ed.), Public Health Sciences, (pp. 199- 218) Beijing: Renmin University Press.  
  • Law, J., and D. Willms (2002). “Provincial maps depicting neighbourhood types” in: D. Willms (ed.) Vulnerable Children: Findings from Canada’s National Longitudinal Survey of Children and Youth,The University of Alberta Press and Human Resources Development Canada 389-406.

Courses taught

University of Waterloo

Profiles by type

Research in Planning

35 new PhD positions available.