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New Hybrid Algorithms for Estimating Tree Stem Diameters at Breast Height Using a Two Dimensional Terrestrial Laser Scanner.

Kong J, Ding X, Liu J, Yan L, Wang J - Sensors (Basel) (2015)

Bottom Line: In this paper, a new algorithm to improve the accuracy of estimating diameter at breast height (DBH) for tree trunks in forest areas is proposed.Compared with previous works, this proposed method improves the accuracy of diameter estimation of trees significantly and effectively reduces the calculation time.Moreover, the experimental results indicate that this method is stable and suitable for the most challenging conditions, which has practical significance in improving the operating efficiency of forest harvester and reducing the risk of causing accidents.

View Article: PubMed Central - PubMed

Affiliation: School of Technology, Beijing Forestry University, Beijing 100083, China. kongjianlei_slgc@163.com.

ABSTRACT
In this paper, a new algorithm to improve the accuracy of estimating diameter at breast height (DBH) for tree trunks in forest areas is proposed. First, the information is collected by a two-dimensional terrestrial laser scanner (2DTLS), which emits laser pulses to generate a point cloud. After extraction and filtration, the laser point clusters of the trunks are obtained, which are optimized by an arithmetic means method. Then, an algebraic circle fitting algorithm in polar form is non-linearly optimized by the Levenberg-Marquardt method to form a new hybrid algorithm, which is used to acquire the diameters and positions of the trees. Compared with previous works, this proposed method improves the accuracy of diameter estimation of trees significantly and effectively reduces the calculation time. Moreover, the experimental results indicate that this method is stable and suitable for the most challenging conditions, which has practical significance in improving the operating efficiency of forest harvester and reducing the risk of causing accidents.

No MeSH data available.


The estimation error decreased with increasing number of point hitting the tree, which was associated with the size of the circles.
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sensors-15-15661-f012: The estimation error decreased with increasing number of point hitting the tree, which was associated with the size of the circles.

Mentions: In view of that the error curves was seriously noisy, a potential cause was that the average error in one distance was achieved by using tree trunks with different diameters. Thereby, a depth analysis was carried out to reveal the effects of diameter on the estimation error. To avoid the influence of distance on the error, only partial laser data at three distances (2 m, 2.6 m and 3.2 m) were chosen as independent observations. Meanwhile, the number of laser points hitting the tree corresponded to the actual diameter of the trees and distances. Thus, the parameter was designed as a single predictor to reveal the influence of the trunk diameters on the estimated errors. Finally, 29 sets of data were randomly selected to compute the estimation errors in different algorithms as shown in Figure 12. For observation trees with diameters between 9 and 35 cm, there was a reasonable relationship in that the error decreased with increasing tree trunk diameter in different positions and distances. As presented in Figure 12, the result demonstrates that the estimation error was influenced by tree trunk diameter in a negative correlation. The error curve in the proposed algorithm was much smoother than the curves in other methods except for the TDE algorithm, which obtained an even smoother (almost linear) curve. This indicated that the new method lowered the error noise regardless of the number of points, and in a sense, this method was much more stable in the process of estimating diameter errors corresponding to most of the other methods. Moreover, the new method obtained the lowest error value comparing with most of the algorithms in the range between 3 and 21, except for the CFAA algorithm, which was affected significantly by the noise. When the number of points reached 21, the proposed method maintained the minimum value. Thus, with the efficiency of the diameters varying between distances, our algorithm could have highest accuracy in estimating the diameters of the tree trunks and suffered lower error estimation noise.


New Hybrid Algorithms for Estimating Tree Stem Diameters at Breast Height Using a Two Dimensional Terrestrial Laser Scanner.

Kong J, Ding X, Liu J, Yan L, Wang J - Sensors (Basel) (2015)

The estimation error decreased with increasing number of point hitting the tree, which was associated with the size of the circles.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541849&req=5

sensors-15-15661-f012: The estimation error decreased with increasing number of point hitting the tree, which was associated with the size of the circles.
Mentions: In view of that the error curves was seriously noisy, a potential cause was that the average error in one distance was achieved by using tree trunks with different diameters. Thereby, a depth analysis was carried out to reveal the effects of diameter on the estimation error. To avoid the influence of distance on the error, only partial laser data at three distances (2 m, 2.6 m and 3.2 m) were chosen as independent observations. Meanwhile, the number of laser points hitting the tree corresponded to the actual diameter of the trees and distances. Thus, the parameter was designed as a single predictor to reveal the influence of the trunk diameters on the estimated errors. Finally, 29 sets of data were randomly selected to compute the estimation errors in different algorithms as shown in Figure 12. For observation trees with diameters between 9 and 35 cm, there was a reasonable relationship in that the error decreased with increasing tree trunk diameter in different positions and distances. As presented in Figure 12, the result demonstrates that the estimation error was influenced by tree trunk diameter in a negative correlation. The error curve in the proposed algorithm was much smoother than the curves in other methods except for the TDE algorithm, which obtained an even smoother (almost linear) curve. This indicated that the new method lowered the error noise regardless of the number of points, and in a sense, this method was much more stable in the process of estimating diameter errors corresponding to most of the other methods. Moreover, the new method obtained the lowest error value comparing with most of the algorithms in the range between 3 and 21, except for the CFAA algorithm, which was affected significantly by the noise. When the number of points reached 21, the proposed method maintained the minimum value. Thus, with the efficiency of the diameters varying between distances, our algorithm could have highest accuracy in estimating the diameters of the tree trunks and suffered lower error estimation noise.

Bottom Line: In this paper, a new algorithm to improve the accuracy of estimating diameter at breast height (DBH) for tree trunks in forest areas is proposed.Compared with previous works, this proposed method improves the accuracy of diameter estimation of trees significantly and effectively reduces the calculation time.Moreover, the experimental results indicate that this method is stable and suitable for the most challenging conditions, which has practical significance in improving the operating efficiency of forest harvester and reducing the risk of causing accidents.

View Article: PubMed Central - PubMed

Affiliation: School of Technology, Beijing Forestry University, Beijing 100083, China. kongjianlei_slgc@163.com.

ABSTRACT
In this paper, a new algorithm to improve the accuracy of estimating diameter at breast height (DBH) for tree trunks in forest areas is proposed. First, the information is collected by a two-dimensional terrestrial laser scanner (2DTLS), which emits laser pulses to generate a point cloud. After extraction and filtration, the laser point clusters of the trunks are obtained, which are optimized by an arithmetic means method. Then, an algebraic circle fitting algorithm in polar form is non-linearly optimized by the Levenberg-Marquardt method to form a new hybrid algorithm, which is used to acquire the diameters and positions of the trees. Compared with previous works, this proposed method improves the accuracy of diameter estimation of trees significantly and effectively reduces the calculation time. Moreover, the experimental results indicate that this method is stable and suitable for the most challenging conditions, which has practical significance in improving the operating efficiency of forest harvester and reducing the risk of causing accidents.

No MeSH data available.