Terrestrial laser scanning in forest ecology: Expanding the horizon

Calders, Kim; Adams, Jennifer; Armston, John; Bartholomeus, Harm; Bauwens, Sébastien; Bentley, Lisa Patrick; Chave, Jérôme; Danson, F. Mark; Demol, Miro; Disney, Mathias; Gaulton, Rachel; Moorthy, Sruthi M. Krishna; Levick, Shaun R.; Saarinen, Ninni; Schaaf, Crystal B.; Stovall, Atticus; Terryn, Louise; Wilkes, Phil; Verbeeck, Hans

doi:10.1016/j.rse.2020.112102

Cited by 234 publications

(148 citation statements)

References 220 publications

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“…Laser Scanning (LS) systems integrated on various airborne and terrestrial platforms achieved a great success. A road map of LSbased forest investigation is currently being formulated, which uses the terrestrial laser scanning (TLS) and/or Mobile Laser Scanning (MLS) to collect plot-level field data (Liang et al 2016;Wallace et al 2017;Saarinen et al 2017;Hyyppä et al 2020b;Calders et al 2020), and to further calibrate airborne laser scanning (ALS) data as well as other aerial and satellite data for regional and national level assimilation (Coomes et al 2017;Urbazaev et al 2018;Dalponte et al 2019). However, barriers still exist for the automated systems to be independent from the conventional field measurements as a supplier of in situ reference information.…”

Section: Introductionmentioning

confidence: 99%

Seamless integration of above- and under-canopy unmanned aerial vehicle laser scanning for forest investigation

et al. 2021

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Background Current automated forest investigation is facing a dilemma over how to achieve high tree- and plot-level completeness while maintaining a high cost and labor efficiency. This study tackles the challenge by exploring a new concept that enables an efficient fusion of aerial and terrestrial perspectives for digitizing and characterizing individual trees in forests through an Unmanned Aerial Vehicle (UAV) that flies above and under canopies in a single operation. The advantage of such concept is that the aerial perspective from the above-canopy UAV and the terrestrial perspective from the under-canopy UAV can be seamlessly integrated in one flight, thus grants the access to simultaneous high completeness, high efficiency, and low cost. Results In the experiment, an approximately 0.5 ha forest was covered in ca. 10 min from takeoff to landing. The GNSS-IMU based positioning supports a geometric accuracy of the produced point cloud that is equivalent to that of the mobile mapping systems, which leads to a 2–4 cm RMSE of the diameter at the breast height estimates, and a 4–7 cm RMSE of the stem curve estimates. Conclusions Results of the experiment suggested that the integrated flight is capable of combining the high completeness of upper canopies from the above-canopy perspective and the high completeness of stems from the terrestrial perspective. Thus, it is a solution to combine the advantages of the terrestrial static, the mobile, and the above-canopy UAV observations, which is a promising step forward to achieve a fully autonomous in situ forest inventory. Future studies should be aimed to further improve the platform positioning, and to automatize the UAV operation.

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Section: Introductionmentioning

confidence: 99%

Seamless integration of above- and under-canopy unmanned aerial vehicle laser scanning for forest investigation

et al. 2021

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“…Targeted field surveys will be always needed to validate these predictions and community annotation efforts will allow for assessment of this component of uncertainty. In particular, combining terrestrial LiDAR sampling with airborne sensors is a promising route to both validate the number of stems and establish subcanopy diversity ( Calders et al, 2020 ). In addition, when co-registered hyperspectral data are available, it may help to separate neighboring trees in diverse forests, provided it does not cause lumping of neighboring trees of the same species.…”

Section: Discussionmentioning

confidence: 99%

A remote sensing derived data set of 100 million individual tree crowns for the National Ecological Observatory Network

Weinstein

Marconi

Bohlman

et al. 2021

eLife

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Forests provide biodiversity, ecosystem, and economic services. Information on individual trees is important for understanding forest ecosystems but obtaining individual-level data at broad scales is challenging due to the costs and logistics of data collection. While advances in remote sensing techniques allow surveys of individual trees at unprecedented extents, there remain technical challenges in turning sensor data into tangible information. Using deep learning methods, we produced an open-source data set of individual-level crown estimates for 100 million trees at 37 sites across the United States surveyed by the National Ecological Observatory Network’s Airborne Observation Platform. Each canopy tree crown is represented by a rectangular bounding box and includes information on the height, crown area, and spatial location of the tree. These data have the potential to drive significant expansion of individual-level research on trees by facilitating both regional analyses and cross-region comparisons encompassing forest types from most of the United States.

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“…TLS provides clear benefits over traditional manual field surveys and is increasingly utilised in the research community. However, capital cost has been a major barrier to the wider adoption of this technology, constricting the application of research outcomes by the wider community [34,35]. We show that rapid developments in commercial scanners now enable us to cost-effectively acquire point clouds of sufficient quality for detailed vegetation surveys.…”

Section: Negating the Cost Barriermentioning

confidence: 97%

“…A major limiting factor to the adoption of TLS for vegetation surveys is the budgetary implications of purchasing high-quality scanners (>USD 100,000) generally used for geomorphological and ecological surveys [34]. Such scanners generally have small beam divergence, high signal-to-noise ratio and in-built GPS systems.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Variability of Tropical Savanna Tree Structural Allometry with Terrestrial Laser Scanning

et al. 2020

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Individual tree carbon stock estimates typically rely on allometric scaling relationships established between field-measured stem diameter (DBH) and destructively harvested biomass. The use of DBH-based allometric equations to estimate the carbon stored over larger areas therefore, assumes that tree architecture, including branching and crown structures, are consistent for a given DBH, and that minor variations cancel out at the plot scale. We aimed to explore the degree of structural variation present at the individual tree level across a range of size-classes. We used terrestrial laser scanning (TLS) to measure the 3D structure of each tree in a 1 ha savanna plot, with coincident field-inventory. We found that stem reconstructions from TLS captured both the spatial distribution pattern and the DBH of individual trees with high confidence when compared with manual measurements (R2 = 0.98, RMSE = 0.0102 m). Our exploration of the relationship between DBH, crown size and tree height revealed significant variability in savanna tree crown structure (measured as crown area). These findings question the reliability of DBH-based allometric equations for adequately representing diversity in tree architecture, and therefore carbon storage, in tropical savannas. However, adoption of TLS outside environmental research has been slow due to considerable capital cost and monitoring programs often continue to rely on sub-plot monitoring and traditional allometric equations. A central aspect of our study explores the utility of a lower-cost TLS system not generally used for vegetation surveys. We discuss the potential benefits of alternative TLS-based approaches, such as explicit modelling of tree structure or voxel-based analyses, to capture the diverse 3D structures of savanna trees. Our research highlights structural heterogeneity as a source of uncertainty in savanna tree carbon estimates and demonstrates the potential for greater inclusion of cost-effective TLS technology in national monitoring programs.

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Terrestrial laser scanning in forest ecology: Expanding the horizon

Cited by 234 publications

References 220 publications

Seamless integration of above- and under-canopy unmanned aerial vehicle laser scanning for forest investigation

Seamless integration of above- and under-canopy unmanned aerial vehicle laser scanning for forest investigation

A remote sensing derived data set of 100 million individual tree crowns for the National Ecological Observatory Network

Exploring the Variability of Tropical Savanna Tree Structural Allometry with Terrestrial Laser Scanning

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