Towards 3D mapping of forests: A comparative study with first/last pulse and full waveform LiDAR data

This paper highlights several approaches to segment and reconstructtrees from LIDAR data and compares the results acquired both from first/last pulse and full waveform data. In a first step, weset up a conventional watershed based segmentation procedure, whichrobustly interpolates the CHM from the LIDAR data and finds possiblestem positions of the tallest trees in the segments calculated from the local maxima of the CHM. Secondly, we combine this segmentationapproach with a special stem detection method. Stem positions in the segments of the watershed segmentation are detectedby hierarchically clustering points below the crown base height and reconstructing the stems with a robust RANSAC-based adjustmentof the stem points. Finally, we implement a new 3D segmentation of single trees using the normalized cut method. Thistackles the problem of how to segment small trees below the CHM. Experiments were conducted in the Bavarian Forest National Parkwith conventional first/last pulse data and full waveform LIDAR data. The first/last pulse data were collected in a flight withthe Falcon II system from TopoSys in a leaf-on situation at a point density of 10 points/m². Full waveform data were captured withthe Riegl LMS Q-560 system at a point density of 25 points/m² (leaf-off and leaf-on) and at a point density of 10 points/m²(leaf-on). The study results prove that the new 3D segmentation approach is capable of detecting small trees in the lowerforest layer. So far, this has been practically impossible when tree segmentation techniques based on the CHM were applied to LIDARdata. Compared to the standard watershed segmentation procedure, the combination of the stem detection method and the normalizedcut segmentation leads to the best segmentation results and is superior in the best case by 12%. Moreover, the experimentsshow clearly that the usage of full waveform data is superior tofirst/last pulse data.     «

This paper highlights several approaches to segment and reconstructtrees from LIDAR data and compares the results acquired both from first/last pulse and full waveform data. In a first step, weset up a conventional watershed based segmentation procedure, whichrobustly interpolates the CHM from the LIDAR data and finds possiblestem positions of the tallest trees in the segments calculated from the local maxima of the CHM. Secondly, we combine this segmentationapproach with a special stem detectio...     »