Perceived pollution around an industrial site: using INSEE grid data for high-resolution mapping
The use of geographic information systems (GIS) in epidemiological studies of environmental health has become commonplace, both for data analysis and for presenting results. To address these various challenges, a GIS was developed as part of an epidemiological study conducted around a chemical industrial site in Salindres in the Gard department. In particular, one of the objectives of the GIS was to produce an atlas based on the finest possible geographic division of the territory to map the individual data generated by the study, without compromising the anonymity of the respondents. The new spatial division using grid cells recently proposed by the National Institute of Statistics and Economic Studies (INSEE) appeared to be the most suitable for this problem. This article presents the use of the INSEE grid for mapping the results of the epidemiological study for the purpose of reporting to local stakeholders and decision-makers. By aggregating 200-meter-square grids into rectangles of varying sizes to ensure a minimum of 11 tax households per unit, the INSEE grid allowed for sufficiently detailed mapping of the epidemiological study’s results while guaranteeing the anonymity of individuals. The article illustrates the cartographic use of indicators of exposure to odorous, noise, and visual nuisances attributed to the industrial site and perceived by the local population. The combined representation of these indicators of perceived exposure to nuisances and objective information—such as atmospheric particulate matter concentration, distance from the industrial site, or topography—thus made it possible to illustrate the population’s perception to local stakeholders and decision-makers. The use of this reference demographic breakdown offers very interesting prospects for the visualization of sensitive data, particularly in public health in situations involving local exposure.
Author(s): Stempfelet M, Plancque E, Kermarec F, Daniau C
Publishing year: 2016
Pages: 153-64
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