Influence of measurement set-up of ground-based LiDAR for derivation of tree structure

Zande, Dimitry Van der; Hoet, W.; Jonckheere, Inge; Aardt, Jan van; Coppin, Pol

doi:10.1016/j.agrformet.2006.09.007

Cited by 152 publications

(105 citation statements)

References 26 publications

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“…The fact that all indirect methods, except for the TLS, tend to underestimate the LAI (or PAI) due to foliage clustering is well known (Nackaerts et al 1999). Another contributing factor is that optical approaches are more or less blind of what is behind the first object in each and every viewing direction (Aber 1979;Watt et al 2003;Watt and Donoghue 2005;Van der Zande et al 2006), which could also result in an underestimation of the present biomass (Bréda 2003). Therefore, each method has its advantages and disadvantages.…”

Section: Comparison Of Techniques and Discussionmentioning

confidence: 99%

“…The scanner is moved to different positions in and around the investigated scene, in which artificial targets are fixed to allow the combination of the scans in the computer in one common coordinate frame Pfeifer et al 2004;Dold and Brenner 2006;Henning and Radtke 2006;Van der Zande et al 2006;Fleck et al 2007). The scanning procedure is usually fast and can be done in a few minutes for a full hemisphere with a state-of-the-art scanner, e.g.…”

Section: Lidar and Optical Point Quadrat Methodsmentioning

confidence: 99%

“…Automatical measurements of length and diameter of tree trunks and individual branches, including the changes in their radii , are as well possible as tree lean, sweep and taper (Watt et al 2003;, gap fraction, PAI and LAI (Lovell et al 2003;Chasmer et al 2004;Henning and Radtke 2006;Danson et al 2007;Takeda et al 2008). Most of these applications are still under development, and validation remains a problem ; Van der Zande et al 2006). …”

Section: Lidar and Optical Point Quadrat Methodsmentioning

confidence: 99%

“…1) to separate data gained from direct LAI measurements from those of indirect measurements. Indirect approaches do not allow separating between photosynthetically active and inactive biomass, and therefore, the actually measured parameter is the whole plant area (PAI, woody and non-woody plant material) instead of the photosynthetically active area only (Parker et al 2004;Henning and Radtke 2006;Van der Zande et al 2006). PAI can be considered as one half of the total area of all plant surfaces per unit of ground area (Henning and Radtke 2006).…”

Section: Suitable Parameters and Their Definitionsmentioning

confidence: 99%

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Review of ground-based methods to measure the distribution of biomass in forest canopies

Seidel

Fleck

Leuschner

et al. 2011

Annals of Forest Science

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& Context Ecological research and an effective forest management need accurate information on the structure of the forest canopy to understand the biochemical, physiological and biogeochemical processes within a forest. & Research question This paper reviews the currently available instruments for measuring the distribution of biomass within forest canopies. We compare the most well-established approaches and present the different measurable parameters. A special focus lies on the resolution of the obtained data. & Results It was found that only 3D laser scanners offer data with the resolution required by ecologists, private landholders, the forest industry and the public to detect trends in tree growth patterns and canopy interactions in all three spatial dimensions. But data validation, data analysis and parameter extraction are still under development, and the price of the instrument is quite high. & Conclusion Research should focus on the parameter extraction from terrestrial laser scanner data as this could allow the calculation of functional attributes for different sections of a canopy on a high spatial resolution. It could also help ecologists characterize the structure of forest stands in a quick and precise way.

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Section: Comparison Of Techniques and Discussionmentioning

confidence: 99%

Section: Lidar and Optical Point Quadrat Methodsmentioning

confidence: 99%

Section: Lidar and Optical Point Quadrat Methodsmentioning

confidence: 99%

Section: Suitable Parameters and Their Definitionsmentioning

confidence: 99%

See 2 more Smart Citations

Review of ground-based methods to measure the distribution of biomass in forest canopies

Seidel

Fleck

Leuschner

et al. 2011

Annals of Forest Science

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“…It uses a SICK LMS151 LiDAR and records the first and last returns at 905 nm over a 360 • horizontal and 270 • vertical scan in less than 35 s. It has a 0.25 • angular resolution and a 0.86 • beam divergence and a maximum range of 40 m. The CBL was placed on a tripod and oriented with a level so that the resulting x, y point cloud was in the horizontal plane. Four CBL scans were taken from opposing sides of each plot to minimize occlusion [45,46]. For each scan, the CBL was placed 1.6 m from the side of the plot at a height of 1.6 m. This ensured that the CBL was always above the grass (heights 50 to 70 cm) and meant that the grass was between 1.84 m and 2.80 m away from the CBL.…”

Section: Remotely Sensed Data Measurementmentioning

confidence: 99%

Examination of the Potential of Terrestrial Laser Scanning and Structure-from-Motion Photogrammetry for Rapid Nondestructive Field Measurement of Grass Biomass

et al. 2017

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Above ground biomass (AGB) is a parameter commonly used for assessment of grassland systems. Destructive AGB measurements, although accurate, are time consuming and are not easily undertaken on a repeat basis or over large areas. Structure-from-Motion (SfM) photogrammetry and Terrestrial Laser Scanning (TLS) are two technologies that have the potential to yield precise 3D structural measurements of vegetation quite rapidly. Recent advances have led to the successful application of TLS and SfM in woody biomass estimation, but application in natural grassland systems remains largely untested. The potential of these techniques for AGB estimation is examined considering 11 grass plots with a range of biomass in South Dakota, USA. Volume metrics extracted from the TLS and SfM 3D point clouds, and also conventional disc pasture meter settling heights, were compared to destructively harvested AGB total (grass and litter) and AGB grass plot measurements. Although the disc pasture meter was the most rapid method, it was less effective in AGB estimation (AGB grass r 2 = 0.42, AGB total r 2 = 0.32) than the TLS (AGB grass r 2 = 0.46, AGB total r 2 = 0.57) or SfM (AGB grass r 2 = 0.54, AGB total r 2 = 0.72) which both demonstrated their utility for rapid AGB estimation of grass systems.

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Measuring bluff erosion part 1: terrestrial laser scanning methods for change detection

Day

Gran

Belmont

et al. 2012

Earth Surf Processes Landf

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Human activities influence watershed sediment dynamics in profound ways, often resulting in excessive loading of suspended sediment to rivers. One of the primary factors limiting our ability to effectively manage sediment at the watershed scale has been our inability to adequately measure relatively small erosion rates (on the order of millimeters to centimeters per year) over annual and sub‐annual time scales on spatially‐extensive landforms, such as river banks and bluffs. Terrestrial laser scanning (TLS) can be employed to address this need. TLS collects high‐resolution data allowing for more accurate monitoring of erosion rates and processes, and provides a new opportunity to make precise measurements of geomorphic change on vertical landforms like banks and bluffs, but challenges remain. This research highlights challenges and limitations of using TLS for change detection on river banks and bluffs including the presence of vegetation, natural surface crenulations, and difficulties with creating benchmarks, and provides solutions developed to overcome these limitations. Results indicate that data processing algorithms for change detection can have a significant impact on the calculated erosion rates, with different methods producing results that can vary by over 100%. The most accurate change detection technique compares a point cloud to a triangulated irregular network (TIN) along a set of vectors that accommodate bluff curvature. This paper outlines a variety of methods used to measure bluff change via TLS and explains the accompanying error analysis that supports these methods. Copyright © 2012 John Wiley & Sons, Ltd.

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Influence of measurement set-up of ground-based LiDAR for derivation of tree structure

Cited by 152 publications

References 26 publications

Review of ground-based methods to measure the distribution of biomass in forest canopies

Review of ground-based methods to measure the distribution of biomass in forest canopies

Examination of the Potential of Terrestrial Laser Scanning and Structure-from-Motion Photogrammetry for Rapid Nondestructive Field Measurement of Grass Biomass

Measuring bluff erosion part 1: terrestrial laser scanning methods for change detection

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