Ground-based Laser Imaging for Assessing Three-dimensional Forest Canopy Structure

2006 ◽  
Vol 72 (12) ◽  
pp. 1349-1358 ◽  
Author(s):  
Jason G. Henning ◽  
Philip J. Radtke
Author(s):  
S. C. Huang ◽  
J. Y. Yeh ◽  
C. T. Chen ◽  
J. C. Chen

Forest canopy structure is composed by the various species. Sun light is a main factor to affect the crown structures after tree competition. However, thinning operation is an appropriate way to control canopy density, which can adjust the competition conditions in the different crown structures. Recently, Airborne Light Detection and Ranging (LiDAR), has been established as a standard technology for high precision three dimensional forest data acquisition; it could get stand characteristics with three-dimensional information that had develop potential for the structure characteristics of forest canopy. The 65 years old, different planting density of <i>Cryptomeria japonica</i> experiment area was selected for this study in Nanytou, Taiwan. Use the LiDAR image to estimate LiDAR characteristic values by constructed CHM, voxel-based LiDAR, mu0ltiple echoes, and assess the accuracy of stand characteristics with intensity values and field data. The competition index was calculated with field data, and estimate competition index of LiDAR via multiple linear regression. The results showed that the highest accuracy with stand characteristics was stand high which estimate by LiDAR, its average accuracy of 91.03%. LiDAR raster grid size was 20 m × 20 m for the correlation was the best, however, the higher canopy density will reduce the accuracy of the LiDAR characteristic values to estimate the stand characteristics. The significantly affect canopy thickness and the degree of competition in different planting distances.


2019 ◽  
Vol 11 (16) ◽  
pp. 1919 ◽  
Author(s):  
Annette Dietmaier ◽  
Gregory J. McDermid ◽  
Mir Mustafizur Rahman ◽  
Julia Linke ◽  
Ralf Ludwig

Forest canopy openings are a key element of forest structure, influencing a host of ecological dynamics. Light detection and ranging (LiDAR) is the de-facto standard for measuring three-dimensional forest structure, but digital aerial photogrammetry (DAP) has emerged as a viable and economical alternative. We compared the performance of LiDAR and DAP data for characterizing canopy openings and no-openings across a 1-km2 expanse of boreal forest in northern Alberta, Canada. Structural openings in canopy cover were delineated using three canopy height model (CHM) alternatives, from (i) LiDAR, (ii) DAP, and (iii) a LiDAR/DAP hybrid. From a point-based detectability perspective, the LiDAR CHM produced the best results (87% overall accuracy), followed by the hybrid and DAP models (47% and 46%, respectively). The hybrid and DAP CHMs experienced large errors of omission (9–53%), particularly with small openings up to 20m2, which are an important element of boreal forest structure. By missing these, DAP and hybrid datasets substantially under-reported the total area of openings across our site (152,470 m2 and 159,848 m2, respectively) compared to LiDAR (245,920 m2). Our results illustrate DAP’s sensitivity to occlusions, mismatched tie points, and other optical challenges inherent to using structure-from-motion workflows in complex forest scenes. These under-documented constraints currently limit the technology’s capacity to fully characterize canopy structure. For now, we recommend that operational use of DAP in forests be limited to mapping large canopy openings, and area-based attributes that are well-documented in the literature.


Author(s):  
S. C. Huang ◽  
J. Y. Yeh ◽  
C. T. Chen ◽  
J. C. Chen

Forest canopy structure is composed by the various species. Sun light is a main factor to affect the crown structures after tree competition. However, thinning operation is an appropriate way to control canopy density, which can adjust the competition conditions in the different crown structures. Recently, Airborne Light Detection and Ranging (LiDAR), has been established as a standard technology for high precision three dimensional forest data acquisition; it could get stand characteristics with three-dimensional information that had develop potential for the structure characteristics of forest canopy. The 65 years old, different planting density of &lt;i&gt;Cryptomeria japonica&lt;/i&gt; experiment area was selected for this study in Nanytou, Taiwan. Use the LiDAR image to estimate LiDAR characteristic values by constructed CHM, voxel-based LiDAR, mu0ltiple echoes, and assess the accuracy of stand characteristics with intensity values and field data. The competition index was calculated with field data, and estimate competition index of LiDAR via multiple linear regression. The results showed that the highest accuracy with stand characteristics was stand high which estimate by LiDAR, its average accuracy of 91.03%. LiDAR raster grid size was 20 m × 20 m for the correlation was the best, however, the higher canopy density will reduce the accuracy of the LiDAR characteristic values to estimate the stand characteristics. The significantly affect canopy thickness and the degree of competition in different planting distances.


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Fan Xu ◽  
Yuan-Qing Wang ◽  
Xiao-Fei Zhang ◽  
Cai-Yun Wang

A Correction to this paper has been published: https://doi.org/10.1038/s42005-021-00520-8.


2022 ◽  
Vol 505 ◽  
pp. 119945
Author(s):  
Jian Zhang ◽  
Zhaochen Zhang ◽  
James A. Lutz ◽  
Chengjin Chu ◽  
Jianbo Hu ◽  
...  

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