Limits...
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 clustering and filtering result of the experiment in polar form.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4541849&req=5

sensors-15-15661-f006: The clustering and filtering result of the experiment in polar form.

Mentions: In the equation, Lmin is the minimum measured range of the cluster and j is the sequence of points in the cluster. For both the individual points and the whole cluster, the values must be greater than or equal to zero, which means the laser clusters all have a convex surface. Moreover, the measurement clusters also satisfy following criteria:(5)l(j)≥0;curv≥0;curvmin<curv<curvmaxwhere curvmin is the minimum curvature of the whole cluster and curvmax is the corresponding maximum limit, which prescribes the acceptable value scope of the trunk radius. Finally the laser data clustered by the acceptable width and depth in Equation (2) can filter out the ground or other uninteresting things with the above Formula (5). Considering that the distance between two trunks is large in the experiment, ∆Rmax is chosen as 0.8 m and the width of cluster is limited in the range of 3 to 50 based on the divergence of the laser scanner. Eventually, eight clusters can be confirmed as tree trunks from the raw point cloud after clustering and filtering as shown in Figure 6.


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 clustering and filtering result of the experiment in polar form.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-15661-f006: The clustering and filtering result of the experiment in polar form.
Mentions: In the equation, Lmin is the minimum measured range of the cluster and j is the sequence of points in the cluster. For both the individual points and the whole cluster, the values must be greater than or equal to zero, which means the laser clusters all have a convex surface. Moreover, the measurement clusters also satisfy following criteria:(5)l(j)≥0;curv≥0;curvmin<curv<curvmaxwhere curvmin is the minimum curvature of the whole cluster and curvmax is the corresponding maximum limit, which prescribes the acceptable value scope of the trunk radius. Finally the laser data clustered by the acceptable width and depth in Equation (2) can filter out the ground or other uninteresting things with the above Formula (5). Considering that the distance between two trunks is large in the experiment, ∆Rmax is chosen as 0.8 m and the width of cluster is limited in the range of 3 to 50 based on the divergence of the laser scanner. Eventually, eight clusters can be confirmed as tree trunks from the raw point cloud after clustering and filtering as shown in Figure 6.

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.