Frequently researchers in the health and other fields are faced with multiple digital data sets containing different spatial data for the same area, but they do not line-up. For instance, the road network on one may not match the spatial position of the road network on another. Conflation is a process through which multiple spatial geometries representing the same area on earth are reconciled. It enables researchers to use non compatible spatial data [link to figure]. Our research team at the Institute for Health Research and Education (IHRE) has worked on this problem at length with special emphasis on Canada Census data. An abstract for a manuscript to be published March 2006 is below:

Enabling spatial analysis across Canadian time and space:
a conflation protocol for census geometry

Nadine Schuurman (corresponding author), Darrin Grund, Michael Hayes, and Suzana Dragicevic

Abstract

The Canada Census is one of the chief sources of demographic, socio-economic, and immigration data for researchers in this country. Census variables are linked to geography files that allow researchers using geographic information systems (GIS) to view and analyse spatial data. Some of the most useful analysis, however, is based on changes in attribute values over time and space. Analysis of spatio-temporal events such as land-use change or shifting migration patterns permits a more dimensioned perspective than the viewing of static spatial phenomena. The analysis of spatio-temporal phenomena is limited by major changes in the spatial framework (e.g. location of road networks and other spatial entities) between national censuses. This paper addresses this limitation by (i) illustrating the extent of spatial mis-match between the 1996 and 2001 census; (ii) examining attempts to rectify this problem in other jurisdictions; and (iii) presenting a “made-in-Canada” solution for conflation of census geometries. We conclude by presenting an example of an analysis in the Canadian context that was facilitated by conflation of census geographies. We believe that this solution will enhance the ability of Canadian researchers to describe and analyse socio-economic, health, and demographic shifts across time and space. The research is supported by a ftp site for downloading the census geography rectification software presented in this paper.