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About us

The vision of the Geoanalytics and Modelling Group (GAM) is that spatial thinking and computing contribute to a great variety of research areas, spanning from the natural sciences to the social sciences and the humanities. GAM promotes the adoption of geographic information as a powerful integrator for multidisciplinary approaches to address fundamental challenges in human and natural systems. We use quantitative and computational methods to investigate social and natural phenomena, including urban dynamics, crime, and coastal erosion.

Recent funded projects

  • Deer as vectors of bovine TB (2015-2018): This Wellcome Trust ISSF study by Dr Shino Shiode confirmed that the spatial distribution of estimated deer population shared some degree of similar geographical pattern with that of bTB herd breakdown ratios. This association becomes more evident when their distributions are reaggregated to areal units confined by the physical barriers (e.g. motorways, railway tracks, rivers) that affect deer’s movements, as opposed to using the original aggregate unit of church parishes.
  • Human-wildlife encounters (2017-19): Globally, where populations of wild animals survive outside protected areas, traumatic encounters with humans occur, resulting in both physical and psychological traumas and damage to livelihoods and the harming of wild animals. Working in India and southern Africa, Dr Simon Pooley’s Wellcome Trust-funded ISSF grant investigated how people understand, represent and communicate about traumatic encounters with wild animals, and the after-effects, in particular places and cultural contexts.
  • Crime Geosurveillance (2013-2015): Dr Shino Shiode’s British Academy funded project developed a new crime geo-surveillance method that can rapidly detect and alarm at the individual street-address level, where and when a problem is emerging. Through empirical analyses, the project confirmed that crime tends to concentrate at very small places, although the size of their concentration may vary greatly.

Staff