Limits...
Assessing and correcting topographic effects on forest canopy height retrieval using airborne LiDAR data.

Duan Z, Zhao D, Zeng Y, Zhao Y, Wu B, Zhu J - Sensors (Basel) (2015)

Bottom Line: Finally, a height weighted correction method is applied to correct the topological effects.The method is applied to LiDAR data acquired in South China, and its effectiveness is tested using 41 field survey plots.A strong correlation was detected between the slope gradient and the proportions of returns with height differences more than 0.3, 0.5 and 0.8 m in the total returns, with coefficient of determination R2 of 0.83, 0.76, and 0.60 (n = 41), respectively.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Science, Haidian District, Beijing 100094, China. zjj@mail.csu.edu.cn.

ABSTRACT
Topography affects forest canopy height retrieval based on airborne Light Detection and Ranging (LiDAR) data a lot. This paper proposes a method for correcting deviations caused by topography based on individual tree crown segmentation. The point cloud of an individual tree was extracted according to crown boundaries of isolated individual trees from digital orthophoto maps (DOMs). Normalized canopy height was calculated by subtracting the elevation of centres of gravity from the elevation of point cloud. First, individual tree crown boundaries are obtained by carrying out segmentation on the DOM. Second, point clouds of the individual trees are extracted based on the boundaries. Third, precise DEM is derived from the point cloud which is classified by a multi-scale curvature classification algorithm. Finally, a height weighted correction method is applied to correct the topological effects. The method is applied to LiDAR data acquired in South China, and its effectiveness is tested using 41 field survey plots. The results show that the terrain impacts the canopy height of individual trees in that the downslope side of the tree trunk is elevated and the upslope side is depressed. This further affects the extraction of the location and crown of individual trees. A strong correlation was detected between the slope gradient and the proportions of returns with height differences more than 0.3, 0.5 and 0.8 m in the total returns, with coefficient of determination R2 of 0.83, 0.76, and 0.60 (n = 41), respectively.

No MeSH data available.


Related in: MedlinePlus

Proportions of points with differences greater than given thresholds versus slope.
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sensors-15-12133-f011: Proportions of points with differences greater than given thresholds versus slope.

Mentions: Figure 11 shows the proportions of points higher than given thresholds for the total number of points. Average values of p0.3, p0.5, p0.8, p1.0, p1.2, and p1.5 of all plots were 20.0%, 11.0%, 4.2%, 2.2%, 1.1%, and 0.35%, respectively, and maximum values of p0.3, p0.5, p0.8, p1.0, p1.2, and p1.5 of all plots were 32.6%, 23.2%, 12.9%, 8.5%, 5.3%, and 2.6%, respectively. When the slope increases from zero to 38.2°, the proportions of points with differences larger than 0.3, 0.5, 0.8, 1.0, 1.2 and 1.5 m increase from 0% to 32.6%, 23.2%, 12.9%, 8.5%, 5.3% and 2.6%, respectively (Figure 11). Overall, the proportion increases as the slope increases, but it decreases as the threshold grows.


Assessing and correcting topographic effects on forest canopy height retrieval using airborne LiDAR data.

Duan Z, Zhao D, Zeng Y, Zhao Y, Wu B, Zhu J - Sensors (Basel) (2015)

Proportions of points with differences greater than given thresholds versus slope.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4507651&req=5

sensors-15-12133-f011: Proportions of points with differences greater than given thresholds versus slope.
Mentions: Figure 11 shows the proportions of points higher than given thresholds for the total number of points. Average values of p0.3, p0.5, p0.8, p1.0, p1.2, and p1.5 of all plots were 20.0%, 11.0%, 4.2%, 2.2%, 1.1%, and 0.35%, respectively, and maximum values of p0.3, p0.5, p0.8, p1.0, p1.2, and p1.5 of all plots were 32.6%, 23.2%, 12.9%, 8.5%, 5.3%, and 2.6%, respectively. When the slope increases from zero to 38.2°, the proportions of points with differences larger than 0.3, 0.5, 0.8, 1.0, 1.2 and 1.5 m increase from 0% to 32.6%, 23.2%, 12.9%, 8.5%, 5.3% and 2.6%, respectively (Figure 11). Overall, the proportion increases as the slope increases, but it decreases as the threshold grows.

Bottom Line: Finally, a height weighted correction method is applied to correct the topological effects.The method is applied to LiDAR data acquired in South China, and its effectiveness is tested using 41 field survey plots.A strong correlation was detected between the slope gradient and the proportions of returns with height differences more than 0.3, 0.5 and 0.8 m in the total returns, with coefficient of determination R2 of 0.83, 0.76, and 0.60 (n = 41), respectively.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Science, Haidian District, Beijing 100094, China. zjj@mail.csu.edu.cn.

ABSTRACT
Topography affects forest canopy height retrieval based on airborne Light Detection and Ranging (LiDAR) data a lot. This paper proposes a method for correcting deviations caused by topography based on individual tree crown segmentation. The point cloud of an individual tree was extracted according to crown boundaries of isolated individual trees from digital orthophoto maps (DOMs). Normalized canopy height was calculated by subtracting the elevation of centres of gravity from the elevation of point cloud. First, individual tree crown boundaries are obtained by carrying out segmentation on the DOM. Second, point clouds of the individual trees are extracted based on the boundaries. Third, precise DEM is derived from the point cloud which is classified by a multi-scale curvature classification algorithm. Finally, a height weighted correction method is applied to correct the topological effects. The method is applied to LiDAR data acquired in South China, and its effectiveness is tested using 41 field survey plots. The results show that the terrain impacts the canopy height of individual trees in that the downslope side of the tree trunk is elevated and the upslope side is depressed. This further affects the extraction of the location and crown of individual trees. A strong correlation was detected between the slope gradient and the proportions of returns with height differences more than 0.3, 0.5 and 0.8 m in the total returns, with coefficient of determination R2 of 0.83, 0.76, and 0.60 (n = 41), respectively.

No MeSH data available.


Related in: MedlinePlus