International Journal of Applied Earth Observation and Geoinformation
Research PaperAccuracy of tree diameter estimation from terrestrial laser scanning by circle-fitting methods
Graphical abstract
Introduction
High-density point clouds from terrestrial laser scanning (TLS) open up new possibilities for accurate measurement of tree parameters and detailed three-dimensional modelling of forest stands. New TLS devices are small and lightweight; therefore, they can be easily used in a forest environment.
Trunks of all diameters can be detected and measured in high-density TLS point clouds. Studies have been carried out with a focus on deriving diameter at breast height (DBH), tree height (Király and Brolly, 2007; Liang and Hyyppä, 2013), and plot basal area (Seidel and Ammer, 2014). Point clouds completely cover the trees and canopy. This fact allows researchers to derive the shape and size of the tree crown (Moorthy et al., 2011), crown volume (Fernández-Sarría et al., 2013), and tree biomass (Kankare et al., 2013, Saarinen et al., 2017) from TLS data. Analysis of the amount and spatial distribution of reflected laser beams can be used in gap analysis (Ramirez et al., 2013) and estimation of leaf area index (Culvenor et al., 2014).
The prospective applications of TLS in forestry include 3D modelling of trees (Hackenberg et al., 2014), 3D modelling of tree root systems (Smith et al., 2014), and derivation of forest canopy fuel properties (García et al., 2011). Multi-temporal TLS of a forest stand was used to evaluate the influence of skidding operations on soil disturbance (Koreň et al., 2015).
DBH is one of the most important parameters required for forest inventory. Callipers or girth tapes are used to measure DBH in forest practices. TLS data offers new opportunities to derive tree diameter not only at breast height but potentially at any height above ground.
Trunk circumference is usually represented by a circle. The position and diameter of the circle are estimated by circle-fitting algorithms from a spatial cluster of points. Other geometric approaches approximate tree sections with cylinders (Brolly and Király, 2009), free-form curves (Pfeifer and Winterhalder, 2004), polygons (Wezyk et al., 2007) or skeletonization (Pál, 2008). Procedures based on three-dimensional rasters (Moskal and Zheng, 2012), Hough transformation (Aschoff and Spiecker, 2004) and morphological analysis (Maas et al., 2008) are under development.
Circle-fitting methods for deriving DBH from point clouds are based on horizontal cross-sectional slices. Horizontal cross-sectional slices of a point cloud are created at a given height above the ground. The thickness of the horizontal cross section is chosen according to the density of a point cloud to include the sufficient number of points needed for a reliable identification of trunks and measurement of their DBH. Cross-sections of individual trunks are identified by spatial clustering. Spatial clusters are also used for noise filtering. Spatial clusters with a low number of points are excluded from the subsequent data processing.
The accuracy of DBH estimated from a TLS point cloud is influenced by the technical parameters and settings of the scanner, scanning mode, positioning of the scanner, and data processing techniques. Most previous works studied the accuracy of one preferred DBH estimation algorithm. The results of these studies are difficult to compare because experiments were carried out in different forest stands and point clouds were processed by different methods. In our study, the accuracy of DBH estimation using different circle-fitting algorithms has been analysed in the same point cloud.
The aim of this work was to compare the results of DBH estimation using five circle-fitting methods from cross-sections of a TLS point cloud of European beech (Fagus sylvatica L.). The circle-fitting methods were evaluated by bias, precision, and accuracy of DBH estimation in a multi-scan and a single-scan mode. The results of DBH estimation by five algorithms have been statistically tested. Our findings provide deeper insight into the performance of the studied circle-fitting algorithms.
Section snippets
Research plot and field measurements
The research plot was established on the property of the University Forest Enterprise of the Technical University in Zvolen, central Slovakia. The research plot (Fig. 1) was located in a monoculture of European beech (Fagus sylvatica L.). The size of the research plot was 50 × 50 m. The forest stand was 80 years old with 160 beech trees, four European hornbeams (Carpinus betulus L.) and one European silver (Abies alba Mill.). To eliminate the influence of tree species on the results, only DBH
DBH estimation
The number of points recorded by a terrestrial laser scanner on a trunk is influenced by several factors: scanning density, the distance from the scanner, the number of scans of the tree, the scanning angle, shadowing by trees, low vegetation and terrain. The merged point cloud consisted of 592 million points. The point cloud was reduced to 499 million points by the 58 m × 58 m box filter. A cross-section of the heights 1.28–1.32 m above the ground in the filtered point cloud contained 570,594
Discussion
The accuracy of DBH estimation has also been addressed by other authors (Antonarakis, 2011; Brolly and Király, 2009; Pueschel et al., 2013; Tansey et al., 2009). In most cases, methods of tree DBH estimation from TLS data were compared by bias and root mean square error of DBH estimation. An overview of studies focused on DBH estimation from TLS point clouds was given by Pueschel et al. (2013). DBH bias reported by authors varied from underestimation of −1.5 cm to overestimation greater than 4
Conclusions
This study provides insight into the performance and properties of circle-fitting methods. Circle-fitting methods proved to be effective algorithms for tree diameter estimation from TLS data. The Monte Carlo and the optimal circle methods are especially attractive due to easy implementation and high accuracy of DBH estimation in the multi-scan and the single-scan modes.
The initial estimations of DBH with the minimum bounding box and maximum distance methods were significantly more accurate than
Acknowledgement
This work was supported by the Scientific Grant Agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic and the Slovak Academy of Sciences under the grant VEGA 1/0881/17.
References (28)
- et al.
Different methodologies for calculating crown volumes of Platanus hispanica trees using terrestrial laser scanner and a comparison with classical dendrometric measurements
Comput. Electron. Agric.
(2013) - et al.
Terrestrial laser scanning to estimate plot-level forest canopy fuel properties
Int. J. Appl. Earth Obs. Geoinf.
(2011) - et al.
Individual tree biomass estimation using terrestrial laser scanning
ISPRS J. Photogramm. Remote Sens.
(2013) - et al.
Field characterization of olive (Olea europaea L.) tree crown architecture using terrestrial laser scanning data
Agric. Forest Meteorol.
(2011) - et al.
The influence of scan mode and circle fitting on tree stem detection, stem diameter and volume extraction from terrestrial laser scans
ISPRS J. Photogramm. Remote Sens.
(2013) - et al.
Feasibility of Terrestrial laser scanning for collecting stem volume information from single trees
ISPRS J. Photogramm. Remote Sens.
(2017) Evaluating forest biometrics obtained from ground lidar in complex riparian forests
Remote Sens. Lett.
(2011)- et al.
Algorithms for the automatic detection of trees in laser scanner data
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.
(2004) - et al.
Extraction of objects from terrestrial laser scans by integrating geometry image and intensity data with demonstration on trees
Remote Sens.
(2012) - et al.
Algorithms for stem mapping by means of terrestrial laser scanning
Acta Silv. Lign. Hung.
(2009)
Least squares fitting of circles
J. Math. Imaging Vision
Automated in-situ laser scanner for monitoring forest leaf area index
Sensors
Adjusting for nondetection in forest inventories derived from terrestrial laser scanning
Canad. J. Remote Sens.
Highly accurate tree models derived from terrestrial laser scan data: a method description
Forests
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