Automated reconstruction of tree and canopy structure for modeling the internal canopy radiation regime

Leeuwen, Martin van; Coops, Nicholas C.; Hilker, Thomas; Wulder, Michael A.; Newnham, Glenn; Culvenor, Darius

doi:10.1016/j.rse.2013.04.019

Cited by 37 publications

(38 citation statements)

References 45 publications

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“…An important future objective is to improve the data acquisition with instruments producing less noise, e.g., by the use of pulsed (cf. [12]) or full waveform scanners [33,34], to develop applications for improved monitoring of the growing season and litter production, and to produce large-area (e.g., plot-level) statistics on branching structures (cf. [25]).…”

Section: Discussionmentioning

confidence: 99%

Change Detection of Tree Biomass with Terrestrial Laser Scanning and Quantitative Structure Modelling

et al. 2014

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Abstract:We present a new application of terrestrial laser scanning and mathematical modelling for the quantitative change detection of tree biomass, volume, and structure. We investigate the feasibility of the approach with two case studies on trees, assess the accuracy with laboratory reference measurements, and identify the main sources of error, and the ways to mitigate their effect on the results. We show that the changes in the tree branching structure can be reproduced with about ±10% accuracy. As the current biomass detection is based on destructive sampling, and the change detection is based on empirical models, our approach provides a non-destructive tool for monitoring important forest characteristics without laborious biomass sampling. The efficiency of the approach enables the repeating of these measurements over time for a large number of samples, providing a fast and effective means for monitoring forest growth, mortality, and biomass in 3D.

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Section: Discussionmentioning

confidence: 99%

Change Detection of Tree Biomass with Terrestrial Laser Scanning and Quantitative Structure Modelling

et al. 2014

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“…A 3D virtual forest scene was reconstructed from the ground-based laser scanning data using a modeling approach described by [33]. Briefly, single scans are projected onto a panoramic plane where individual pixels show range (m) to target.…”

Section: Scene Reconstructionmentioning

confidence: 99%

“…To limit data dimensionality, a clump of leaves may be represented by its convex hull [24] or as a planar polygon or plate-like shoot model that exhibits scattering properties similar to the assembly of individual leaves or needles [25,26]. Recent studies have demonstrated the combined use of tree-growing algorithms and time-of-flight laser scanning technology [27,28] for the reconstruction of virtual forest canopies [29][30][31][32][33].…”

Section: Introductionmentioning

confidence: 99%

Using Stochastic Ray Tracing to Simulate a Dense Time Series of Gross Primary Productivity

2015

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Eddy-covariance carbon dioxide flux measurement is an established method to estimate primary productivity at the forest stand level (typically 10 ha). To validate eddy-covariance estimates, researchers rely on extensive time-series analysis and an assessment of flux contributions made by various ecosystem components at spatial scales much finer than the eddy-covariance footprint. Scaling these contributions to the stand level requires a consideration of the heterogeneity in the canopy radiation field. This paper presents a stochastic ray tracing approach to predict the probabilities of light absorption from over a thousand hemispherical directions by thousands of individual scene elements. Once a look-up table of absorption probabilities is computed, dynamic illumination conditions can be simulated in a computationally realistic time, from which stand-level gross primary productivity can be obtained by integrating photosynthetic assimilation over the scene. We demonstrate the method by inverting a leaf-level photosynthesis model with eddy-covariance and meteorological data. Optimized leaf photosynthesis parameters and canopy structure were able to explain 75% of variation in eddy-covariance gross primary productivity estimates, and commonly used parameters, including photosynthetic capacity and quantum yield, fell within reported ranges. Remaining challenges are discussed including the need to address the distribution of radiation within shoots and needles.

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“…From the ceiling of the scene-bounding box, rays were projected into the scene and intersections with scene elements were computed using SRT (Van Leeuwen et al 2013). The bounding box was used as a periodic boundary, so that rays would cyclically re-enter the scene until they either intersected a tree element or hit the scene floor.…”

Section: Data Simulationmentioning

confidence: 99%

A Box-Counting Method to Characterize Degrees of Foliage Clumping Using Airborne and Simulated Lidar Data

Leeuwen

Aardt

Kampe

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Monitoring forest productivity and health is key to sustainable ecosystem management and informed decision making. A key parameter used in monitoring forest resources is the leaf area index (LAI), which is defined as the one-sided leaf area per unit ground area and is used to describe the canopy radiation regime, among other forest biophysical dynamics. Traditional optics-based methods to estimate LAI rely on the measurement of canopy transmission and foliage clumping. Extending optical methods to LiDAR data has been challenging and studies have reported effective LAI assessments, with no further quantification of foliage clumping. This study investigates the use of the box-counting method to assess the fractal dimension of point cloud data for contrasting forest types and along a gradient of foliage dispersal. We demonstrate the box-counting method on simulated 'range-to-hit', as well as acquired airborne discrete LiDAR data. Coherent results obtained from the different test cases hint at the potential of the box-counting fractal dimension to characterize foliage clumping and bode well for the use of clumping assessments in support of airborne, wall-to-wall estimates of LAI.

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Automated reconstruction of tree and canopy structure for modeling the internal canopy radiation regime

Cited by 37 publications

References 45 publications

Change Detection of Tree Biomass with Terrestrial Laser Scanning and Quantitative Structure Modelling

Change Detection of Tree Biomass with Terrestrial Laser Scanning and Quantitative Structure Modelling

Using Stochastic Ray Tracing to Simulate a Dense Time Series of Gross Primary Productivity

A Box-Counting Method to Characterize Degrees of Foliage Clumping Using Airborne and Simulated Lidar Data

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