Capturing seasonal radial growth of boreal trees with terrestrial laser scanning

Yrttimaa, Tuomas; Junttila, Samuli; Luoma, Ville; Calders, Kim; Kankare, Ville; Saarinen, Ninni; Kukko, Antero; Holopainen, Markus; Hyyppä, Juha; Vastaranta, Mikko

doi:10.1016/j.foreco.2022.120733

Cited by 9 publications

(4 citation statements)

References 47 publications

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“…Although tree stems increment changed significantly in infested trees, it is challenging to measure such small alterations in diameter (less than 1 mm) using basic dendrometry methods on the scale of a large forest area on the individual trees. Terrestrial laser scanning could provide a solution but is currently capable of monitoring seasonal increments greater than 1 mm in diameter (Yrttimaa et al, 2023).…”

Section: Discussionmentioning

confidence: 99%

Physiological and biochemical indicators in Norway spruces freshly infested by Ips typographus: potential for early detection methods

Stříbrská

Hradecký

Čepl

et al. 2023

Front. For. Glob. Change

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IntoductionThe bark beetle Ips typographus currently represents the primary pest of Norway spruce (Picea abies) in Central Europe. Early detection and timely salvage cutting of bark beetle-infested trees are functional management strategies for controlling bark beetle outbreaks. However, alternative detection methods are currently being developed, and possible indicators of bark beetle infestation can be assessed through changes in the physiological, biochemical, and beetle-acceptance characteristics of trees.MethodThis study monitored infested and non-infested Norway spruce trees before and 3 weeks after Ips typographus natural attack. Permanently installed sensors recorded physiological features, such as sap flow, tree stem increment, bark surface temperature, and soil water potential, to monitor water availability. Defensive metabolism characteristics, beetle host acceptance, and attractiveness to trees were monitored discretely several times per season. The forest stand that was later attacked by bark beetles had lower water availability during the 2018–2020 seasons compared to the non-attacked stands.ResultsAfter the attack, sap flow and tree stem increment were significantly lower in infested trees than in intact ones, and bark surface temperature moderately increased, even when measured in the inner forest stand from the shadowed side. Infested trees respond to attacks with a surge in monoterpene emissions. In addition, freshly infested trees were more accepted by males in the no-choice bioassays, and a significantly higher number of beetles were caught in passive traps in the first week of infestation.ConclusionThe most promising characteristics for early detection methods of bark beetle-infested trees include tree bark temperature measured only in certain meteorological conditions, elevated monoterpene emissions, and significantly high catches in passive traps.

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Section: Discussionmentioning

confidence: 99%

Physiological and biochemical indicators in Norway spruces freshly infested by Ips typographus: potential for early detection methods

Stříbrská

Hradecký

Čepl

et al. 2023

Front. For. Glob. Change

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“…The extraction accuracy for both tree height and DBH reached the highest R 2 value of 0.89, with the corresponding values for RMSE, MAD, and MAPE being the lowest (Figure 6). TLS has a significant advantage in depicting understory vegetation information [46]. However, due to the occlusion of branches and undergrowth, the point cloud density at the top of trees scanned using TLS is low in some cases [47].…”

Section: Individual Tree Parameter Extractionmentioning

confidence: 99%

Multifiltering Algorithm for Enhancing the Accuracy of Individual Tree Parameter Extraction at Eucalyptus Plantations Using LiDAR Data

Huang,

He,

Yao

2023

Forests

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Accurately quantifying individual tree parameters is a critical step for assessing carbon sequestration in forest ecosystems. However, it is challenging to gather comprehensive tree point cloud data when using either unmanned aerial vehicle light detection and ranging (UAV-LiDAR) or terrestrial laser scanning (TLS) alone. Moreover, there is still limited research on the effect of point cloud filtering algorithms on the extraction of individual tree parameters from multiplatform LiDAR data. Here, we employed a multifiltering algorithm to increase the accuracy of individual tree parameter (tree height and diameter at breast height (DBH)) extraction with the fusion of TLS and UAV-LiDAR (TLS-UAV-LiDAR) data. The results showed that compared to a single filtering algorithm (improved progressive triangulated irregular network densification, IPTD, or a cloth simulation filter, CSF), the multifiltering algorithm (IPTD + CSF) improves the accuracy of tree height extraction with TLS, UAV-LiDAR, and TLS-UAV-LiDAR data (with R2 improvements from 1% to 7%). IPTD + CSF also enhances the accuracy of DBH extraction with TLS and TLS-UAV-LiDAR. In comparison to single-platform LiDAR (TLS or UAV-LiDAR), TLS-UAV-LiDAR can compensate for the missing crown and stem information, enabling a more detailed depiction of the tree structure. The highest accuracy of individual tree parameter extraction was achieved using the multifiltering algorithm combined with TLS-UAV-LiDAR data. The multifiltering algorithm can facilitate the application of multiplatform LiDAR data and offers an accurate way to quantify individual tree parameters.

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“…Some research describes methods for analyzing tree growth from TLS point clouds, focusing on specific parameters, such as stem diameters [ 22 , 23 ], where the full-potential geometric coherence and accuracy inherent to TLS point clouds are used. However, mainly due to the aforementioned lower accuracy and higher presence of noise, as far as we are aware, there is a research gap in the methods that use MLS point clouds for analyzing tree growth.…”

Section: Introductionmentioning

confidence: 99%

A Handheld Laser-Scanning-Based Methodology for Monitoring Tree Growth in Chestnut Orchards

Pereira-Obaya,

Cabo,

Ordóñez

et al. 2024

Sensors

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Chestnut and chestnut byproducts are of worldwide interest, so there is a constant need to develop faster and more accurate monitoring techniques. Recent advances in simultaneous localization and mapping (SLAM) algorithms and user accessibility have led to increased use of handheld mobile laser scanning (HHLS) in precision agriculture. We propose a tree growth monitoring methodology, based on HHLS point cloud processing, that calculates the length of branches through spatial discretization of the point cloud for each tree. The methodology was tested by comparing two point clouds collected almost simultaneously for each of a set of sweet chestnut trees. The results obtained indicated that our HHLS method was reliable and accurate in efficiently monitoring sweet chestnut tree growth. The same methodology was used to calculate the growth of the same set of trees over 37 weeks (from spring to winter). Differences in week 0 and week 37 scans showed an approximate mean growth of 0.22 m, with a standard deviation of around 0.16 m reflecting heterogeneous tree growth.

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Capturing seasonal radial growth of boreal trees with terrestrial laser scanning

Cited by 9 publications

References 47 publications

Physiological and biochemical indicators in Norway spruces freshly infested by Ips typographus: potential for early detection methods

Physiological and biochemical indicators in Norway spruces freshly infested by Ips typographus: potential for early detection methods

Multifiltering Algorithm for Enhancing the Accuracy of Individual Tree Parameter Extraction at Eucalyptus Plantations Using LiDAR Data

A Handheld Laser-Scanning-Based Methodology for Monitoring Tree Growth in Chestnut Orchards

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