The term 'exposome' emerged in an attempt to address the under appreciation of exposure sciences in the elucidation of the role of environmental stressors in many common chronic diseases such as cancer, diabetes and vascular and neurodegenerative diseases. To respond to this concept, there is a need for a new way to analyze the environment-human health relationships. The use of GIS as a platform for data storage, statistical analysis, and spatial interpolation remains an important cornerstone to link data from different sources and supports databases to describe the global source-effect chain. GIS is a promising tool to analyze health data and putative covariates, such as environmental, exposure, socio-economic, behavioral or demographic factors. The objective of this work is to develop a GIS-based (Geographic Information System) platform combining environment and health information to map environmental disparities and detect vulnerable populations. This platform should permit the ongoing systematic collection, integration, and analysis of data regarding emission sources, environmental contamination, exposure to environmental hazards, population and health. To achieve this objective, combining exposure assessment and spatial data is a fundamental prerequisite that imply to first overcome different scientific limitations such as the linkage of the several databases to describe the global source-effect chain, the feasibility to integrate these data to the platform at a fine scale and the construction of interest variables and indicators by the development of spatial analysis and geostatistic tools combined to a multimedia exposure model. This later allows to assess the transfer of contaminants from the environment (air, soil, water, food chain) to population. Spatial data from the platform are used to implement environmental and population characteristics into the model. The purpose of this work is to present the scientific development of the platform, focusing on the limitations described above and based on the example of lead. Secondly, illustrations of the several possibilities in the exposome characterization context will be given among which : mapping environmental disparities throughout France ; identifying vulnerable population and determinants of exposure to manage and plan remedial actions ; highlighting hot-spot areas with significantly elevated exposure indicator values to define environmental monitoring campaigns ; assessing spatial relationships between health, environmental and socio-economic data in order to identify factors influencing variability in disease patterns.