Geospatial Science and Technology

Geospatial research is the study of geographic information, how we collect, store, manage, analyse, and visualise it. This is in isolation from the specifics of the driving geographic questions, that is, that we study the representations of the real world rather than the real world itself.

Within the School of Earth & Environment at Canterbury University, we tackle a range of geospatial research questions. These research topics include advances in spatial analysis methods, such as new methods for simulating real world populations through spatial microsimulation modelling, new data models or representations of geographic phenomena such as process based data models, representing the semantics of geographic information, and creating methods for determining whether we can trust crowd sourced data.

Spatial Microsimulation is a quantitative geographical technique used to create simulated data by combining, or merging various datasets to populate and therefore create a new synthetic population that is as close as possible to the 'real’ population with an inbuilt geography.


SIMALBA: A spatial microsimulation model for Scotland (Funded by the ESRC and The Scottish Government)
(Ministry of Health PhD Scholarship: SimAotearoa - a spatial microsimulation model for policy analysis in NZ


To undertake Microsimulation of health and socio-economic variables at small area geographies
To create a powerful policy-relevant framework for NZ that will assist in assessing both current and future policy scenarios
To refine and develop existing modeling methods to become more policy relevant and that can be applied to NZ


  • Campbell M. and Ballas D. (2016) SimAlba: A spatial microsimulation approach to the analysis of health inequalities. Frontiers in Public Health 4(OCT)
  • Campbell, M.H. and Ballas, D. (2013) A spatial microsimulation approach to economic policy analysis in Scotland. Regional Science Policy & Practice 5(3): 263–288. (Journal Articles)
  • Ballas, D., Campbell, M., Clarke, G., Hanaoka, K., Nakaya, T. and Waley, P. (2012) A spatial microsimulation approach to small area income estimation in Britain and Japan. Studies in Regional Science 42(1): 163-187. (Journal Article)
  • Campbell, M.H. and Ballas, D. (2012) Social and spatial inequalities in Scotland: A spatial microsimulation approach. Edinburgh, UK: RGS-IBG Annual International Conference, 3-5 Jul 2012.(Conference Contribution - Oral presentation)
  • Campbell, M. and Ballas, D. (2011) A spatial microsimulation approach to the analysis of health and wealth inequalities in Scotland. Harokopio University of Athens, Greece: The 17th European Colloquium on Quantitative and Theoretical Geography (ECQTG2011), 4 Sep 2011. (Conference Contribution - Oral presentation)
  • Campbell, M.H. (2011) Exploring the social and spatial inequalities of ill-health in Scotland: A spatial microsimulation approach. PhD, Univeristy of Sheffield, UK. (Thesis - Doctor of Philosophy)

Staff involved

The GeoHealth Laboratory undertakes applied research in the areas of health geography, spatial epidemiology and Geographical Information Systems. In particular, work in the GeoHealth Laboratory focuses upon how the local and national contexts shape health outcomes and health inequalities.

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Urban and Regional Analytics

Accommodation-sharing platforms, such as Airbnb, can be seen as a disruptive force in comparison to more conventional accommodation providers and rental markets in many cities and regions worldwide.

This project focuses on understanding the spatial distribution of the accommodation provided by Airbnb in NZ. This research theme on Regional Science is funded by NSC11: Building Better Homes, Towns and Cities. Using urban and regional analytics we are conducting research on Airbnb and Regional Development questions.



Campbell M., McNair H., Mackay M. and Perkins HC. (2019) Disrupting the regional housing market: Airbnb in New Zealand. Regional Studies, Regional Science 6(1): 139-142.


Staff Involved

Malcolm Campbell

Hamish McNair

Michael Mackay

Harvey C Perkins

Our research team

Ioannis Delikostidis

Senior Lecturer
Geographic Information Science
Beatrice Tinsley Rm 314
Internal Phone: 94387

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