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GIScience,environmental justice, & estimating populations at risk: The case of landfills in Wales
Authors:Gary Higgs  Mitch Langford
Institution:1. Institute for Sustainable Futures, University of Technology Sydney, Australia;2. Department of Geography, King''s College London, United Kingdom;3. School of Mathematical and Physical Sciences, University of Technology Sydney, Australia;1. University of Technology Sydney, Faculty of Health, Ultimo, NSW, Australia;2. University of Technology Sydney, Institute for Sustainable Futures, Ultimo, NSW, Australia;3. University of Dundee, Dundee, Discipline of Geography, School of Social Science, Dundee, Scotland, United Kingdom of Great Britain and Northern Ireland;4. University of Dundee, Dundee, Centre for Environmental Change and Human Resilience, School of Social Science, Dundee, Scotland, United Kingdom of Great Britain and Northern Ireland
Abstract:There has been a notable increase in the use of geographic information systems (GIS) in studies of environmental (in)justice in the last two decades. Whilst the potential of such techniques is increasingly being recognised, there remain some key research challenges facing researchers interested in wider notions of environmental justice (EJ). One avenue of research concerns the estimation of population denominator and the influence of the estimation model on the conclusions emanating from such studies. Whilst the potential of so-called dasymetric mapping techniques have been explored in other substantive areas such as crime and health geography, their use in EJ applications remains under-explored. This paper represents a preliminary attempt to redress this gap in the literature through a comparison of the deprivation profiles of residents living in the vicinity of landfill sites in Wales using both ‘traditional’ and innovative methods of population estimation that provide a more realistic representation of actual population distribution. The results as we demonstrate suggest that more emphasis needs to be placed on the methods by which population is estimated if the results of GIS-based environmental justice studies are to be more widely applied.
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