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

机译:审阅模型自动改善地图中色彩对比的模型:应用于风险地图

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摘要

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 Geographique 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.
机译:地图可能是查找和分析灾害(洪水,滑坡)和受到这些灾害威胁的元素(建筑物,道路)的有用工具。然而,在这样的地图上,信息的阅读和理解可能是困难的,特别是因为大量且重叠的图形符号可能会形成强烈的对比。颜色比其他参数更重要,对于提高地图的可读性很重要。在法国国家地理研究所(IGN)COGIT实验室的博士学位框架下(Chesneau 2006a),设计了一种自动改善地图中颜色对比的模型。定义了一种特定的数据和规则方案,以允许自动改善色彩对比度。解决方案是迭代的:通过连续的循环,可以解决初始图上最差的对比度。已经开发出用于应急工作的地图原型“ ARiCo”,并且使用此模型进行的实验测试表明地图的清晰度得到了实际改善。

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