What Are We Missing? Occlusion in Laser Scanning Point Clouds and Its Impact on the Detection of Single-Tree Morphologies and Stand Structural Variables

2023-01-12 | journal article. A publication with affiliation to the University of Göttingen.

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​What Are We Missing? Occlusion in Laser Scanning Point Clouds and Its Impact on the Detection of Single-Tree Morphologies and Stand Structural Variables​
Mathes, T.; Seidel, D.; Häberle, K.-H.; Pretzsch, H. & Annighöfer, P.​ (2023) 
Remote Sensing15(2).​ DOI: https://doi.org/10.3390/rs15020450 

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Authors
Mathes, Thomas; Seidel, Dominik; Häberle, Karl-Heinz; Pretzsch, Hans; Annighöfer, Peter
Abstract
Laser scanning has revolutionized the ability to quantify single-tree morphologies and stand structural variables. In this study, we address the issue of occlusion when scanning a spruce (Picea abies (L.) H.Karst.) and beech (Fagus sylvatica L.) forest with a mobile laser scanner by making use of a unique study site setup. We scanned forest stands (1) from the ground only and (2) from the ground and from above by using a crane. We also examined the occlusion effect by scanning in the summer (leaf-on) and in the winter (leaf-off). Especially at the canopy level of the forest stands, occlusion was very pronounced, and we were able to quantify its impact in more detail. Occlusion was not as noticeable as expected for crown-related variables but, on average, resulted in smaller values for tree height in particular. Between the species, the total tree height underestimation for spruce was more pronounced than that for beech. At the stand level, significant information was lost in the canopy area when scanning from the ground alone. This information shortage is reflected in the relative point counts, the Clark–Evans index and the box dimension. Increasing the voxel size can compensate for this loss of information but comes with the trade-off of losing details in the point clouds. From our analysis, we conclude that the voxelization of point clouds prior to the extraction of stand or tree measurements with a voxel size of at least 20 cm is appropriate to reduce occlusion effects while still providing a high level of detail.
Issue Date
12-January-2023
Journal
Remote Sensing 
Organization
Fakultät für Forstwissenschaften und Waldökologie ; Burckhardt-Institut ; Abteilung Räumliche Strukturen und Digitalisierung von Wäldern 
eISSN
2072-4292
Language
English
Sponsor
Bavarian State Ministry of Nutrition, Agriculture and Forestry

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