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A model for the automatic improvement of colour contrasts in maps: application to risk maps

A map may be a useful tool for locating and analysing hazards (flood, landslide) and elements threatened by these hazards (buildings, roads). However, on such a map, the reading and understanding of information can be difficult, in particular because the graphic signs, numerous and in superimposition, can be badly contrasted. More than other parameters, colour seems important for the improvement of map legibility. In the framework of a PhD at COGIT laboratory of Institut Géographique National (IGN) France (Chesneau 2006a), a model for the automatic improvement of colour contrasts in maps was designed. A specific schema of data and rules to allow an automatic improvement in colour contrasts are defined. The solution is iterative: through successive cycles, the worst contrasts on the initial map are solved. A prototype for maps used in emergency response efforts, ‘ARiCo’, has been developed and experimental tests carried out with this model show an actual improvement of maps' legibility.