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D point clouds of natural environments relevant to geomorphology problems (rivers, cliffs…) often require to classify the data into elementary relevant classes. A typical example is the separation of riparian vegetation from soil in fluvial environments, the distinction between fresh surfaces and rockfall in cliff environments, or more generally the classification of surfaces according to their morphology (ripples, grain size…). Natural surfaces are very heterogeneous and their distinctive properties are seldom defined at a unique scale. We have thus defined a multi-scale measure of the point cloud dimensionality around each point. The dimensionality characterizes the local 3D organization of the point cloud and varies from being 1D (points set along a line) to really taking all 3D volume, at each scale. Read More
