Abstract
A method for the automatic main road extraction in urban area from airborne LiDAR (Light Detection And Ranging) data is proposed. Elevation and intensity information are used to classify road points from the raw airborne LiDAR point clouds. Firstly, the adaptive TIN (Triangulated Irregular Network) model filtering algorithm is utilized to classify the LiDAR point clouds into ground and non-ground point clouds. Secondly, the ground point clouds are classified into candidate road and non-road point clouds by intensity information. Lastly, the constrained Delaunay TIN of candidate road point clouds is constructed to improve the accuracy of classification and then the road contour is extracted from the road points image. Experimental results show that the method can extract the main road of urban area effectively.
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