Classification of vegetation in aerial LiDAR data
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This contribution summarises a doctoral dissertation which proposes an algorithm for the classification of vegetation points in aerial LiDAR data. The algorithm characterizes vegetated areas based on statistically large dispersion in elevations of points, and the context in which the points are located. The algorithm is able to classify vegetation in both rural and urban areas with an average F1 score of 97.9 \ % and 91.0 \ %, respectively. The point-clouds can contain different types of vegetation and various degrees of canopy densities.
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