THE EFFECT of WIND on TREE STEM PARAMETER ESTIMATION USING TERRESTRIAL LASER SCANNING
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume 3
AbstractThe 3D measurement technique of terrestrial laser scanning (TLS) in forest inventories has shown great potential for improving the accuracy and efficiency of both individual tree and plot level data collection. However, the effect of wind has been poorly estimated in the error analysis of TLS tree measurements although it causes varying deformations to the trees. In this paper, we evaluated the effect of wind on tree stem parameter estimation at different heights using TLS. The data consists of one measured Scots pine captured from three different scanning directions with two different scanning resolutions, 6.3 mm and 3.1 mm at 10 m. The measurements were conducted under two different wind speeds, approximately 3 m/s and 9 m/s, as recorded by a nearby weather station of the Finnish Meteorological Institute. Our results show that the wind may cause both the underestimation and overestimation of tree diameter when using TLS. The duration of the scanning is found to have an impact for the measured shape of the tree stem under 9 m/s wind conditions. The results also indicate that a 9 m/s wind does not have a significant effect on the stem parameters of the lower part of a tree (<28% of the tree height). However, as the results imply, the wind conditions should be taken into account more comprehensively in analysis of TLS tree measurements, especially if multiple scans from different positions are registered together. In addition, TLS could potentially be applied to indirectly measure wind speed by observing the tree stem movement.
Pine, Stem Diameter, Stem Location, Terrestrial Laser Scanning, Tree Reconstruction, Wind
Vaaja , M T , Virtanen , J P , Kurkela , M , Lehtola , V , Hyyppä , J & Hyyppä , H 2016 , ' THE EFFECT of WIND on TREE STEM PARAMETER ESTIMATION USING TERRESTRIAL LASER SCANNING ' , ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences , vol. 3 , pp. 117-122 . https://doi.org/10.5194/isprs-annals-III-8-117-2016