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To consume less time and less memory, this paper presents a flow to generate DEM from Lidar data. Firstly the flow labels non-ground points based on multi-echo information. Secondly by the relativity among neighbor points, the flow labels many other non-ground points. After these two up-to-down steps, many non-ground points have been eliminated, which has reduced the amount of the Lidar points successful...
The aim of this research is to extract objects i.e. buildings, trees and roads important for noise mapping but also for applications such as 3D city modelling, land cover classification, change detection and many others. Earlier research has focused on the extraction of these objects independently either from aerial imagery or LIDAR (Light Detection and Ranging) data. This paper however, focuses on...
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