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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

Regression relationships between slope and proportions of points with differences greater than selected thresholds: (a) threshold = 0.3 m; (b) threshold = 0.5 m; (c) threshold = 0.8 m.
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sensors-15-12133-f012: Regression relationships between slope and proportions of points with differences greater than selected thresholds: (a) threshold = 0.3 m; (b) threshold = 0.5 m; (c) threshold = 0.8 m.

Mentions: Meanwhile, regression analysis shows a strong correlation between the slope gradient and the proportions of points with differences greater than 0.3, 0.5 and 0.8 m (Figure 12); the coefficient of determination R2 is 0.83, 0.76, and 0.60 (n = 41), respectively. But when the threshold is increased to ≥1.0 m, the correlation weakens. This is also attributable to smaller crowns, which means terrain creates less impact. Larger crowns apparently lead to more slope-caused canopy height differences.


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)

Regression relationships between slope and proportions of points with differences greater than selected thresholds: (a) threshold = 0.3 m; (b) threshold = 0.5 m; (c) threshold = 0.8 m.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-12133-f012: Regression relationships between slope and proportions of points with differences greater than selected thresholds: (a) threshold = 0.3 m; (b) threshold = 0.5 m; (c) threshold = 0.8 m.
Mentions: Meanwhile, regression analysis shows a strong correlation between the slope gradient and the proportions of points with differences greater than 0.3, 0.5 and 0.8 m (Figure 12); the coefficient of determination R2 is 0.83, 0.76, and 0.60 (n = 41), respectively. But when the threshold is increased to ≥1.0 m, the correlation weakens. This is also attributable to smaller crowns, which means terrain creates less impact. Larger crowns apparently lead to more slope-caused canopy height differences.

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