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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.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.

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

Flowchart of methods used in this study.
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sensors-15-12133-f004: Flowchart of methods used in this study.

Mentions: This shows that the terrain-induced canopy height difference is, in essence, the elevation difference between the laser hit and tree root elevation. That is, canopy height differences exist without exception because of the uneven ground. The differences will, in turn, influence the extraction of canopy vertices, trunk location, crown, volume and biomass. Extracted forest parameters will be distorted. It is thus imperative to remove the influence of terrain to conduct a more accurate extraction of canopy height. Because the normalized point cloud or CHM is obtained by subtracting the DEM data from DSM data or the raw point cloud, the influence of topography on canopy height varies with individual trees. Therefore, the point cloud of individual trees should be segmented first and foremost. Figure 4 shows a flowchart of the method used. The details are described below.


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)

Flowchart of methods used in this study.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-12133-f004: Flowchart of methods used in this study.
Mentions: This shows that the terrain-induced canopy height difference is, in essence, the elevation difference between the laser hit and tree root elevation. That is, canopy height differences exist without exception because of the uneven ground. The differences will, in turn, influence the extraction of canopy vertices, trunk location, crown, volume and biomass. Extracted forest parameters will be distorted. It is thus imperative to remove the influence of terrain to conduct a more accurate extraction of canopy height. Because the normalized point cloud or CHM is obtained by subtracting the DEM data from DSM data or the raw point cloud, the influence of topography on canopy height varies with individual trees. Therefore, the point cloud of individual trees should be segmented first and foremost. Figure 4 shows a flowchart of the method used. The details are described below.

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.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.

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