Tree Shape Variability in a Mixed Oak Forest Using Terrestrial Laser Technology: Implications for Mating System Analysis

Tomșa, Vlăduț Remus; Curtu, Alexandru Lucian; Niţă, M. D.

doi:10.3390/f12020253

Cited by 5 publications

(2 citation statements)

References 41 publications

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“…While the aforementioned works focused on conifers, previous studies have also detected branch structures in deciduous trees using TLSs during the leafless season, reporting no significant drawbacks [54,55].…”

Section: Branchinessmentioning

confidence: 99%

Advancements in Wood Quality Assessment: Standing Tree Visual Evaluation—A Review

Nocetti,

Brunetti

2024

Forests

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(1) The early assessment of wood quality, even while trees are standing, provides significant benefits for forest management, sales efficiency, and market diversification. Its definition cannot be in absolute terms but must always be linked to the material’s intended use. (2) In this contribution, a review of the scientific literature is given to discuss the visually evaluable attributes that define wood quality in standing trees, the applicability of the techniques used for their assessment, and the effectiveness of these attributes and technologies in predicting quality, to finally highlight future research needs. (3) The visual characteristics generally used to evaluate wood quality are linked to stem form and dimension, branchiness, and stem damage, but their assessment is challenging due to time and resource constraints. To address these challenges, laser-based and image-based techniques have been applied in field surveys. (4) Laser scanners offer detailed and accurate measurements. Photogrammetry, utilizing images to reconstruct 3D models, provides a cost-effective and user-friendly alternative. Studies have demonstrated the effectiveness of these tools in surveying the visible properties of stems and branches, but further development is necessary for widespread application, particularly in software development, with faster and more effective algorithmic advancements for automatic recognition and subsequent measurement of pertinent characteristics being critical for enhancing tool usability. (5) However, predicting wood quality from these surveys remains challenging, with a limited correlation between the visible tree characteristics assessed and the sawn product quality. Empirical studies evaluating products downstream in the forest-wood supply chain could provide valuable insights. In this sense, the implementation of traceability systems could facilitate the linkage between data on standing trees and the quality of the sawn product. Also, further research is needed to develop models that can accurately predict internal tree characteristics and their impact on product quality.

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Section: Branchinessmentioning

confidence: 99%

Advancements in Wood Quality Assessment: Standing Tree Visual Evaluation—A Review

Nocetti,

Brunetti

2024

Forests

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“…Virtual tree measurements are achieved today by using software applications and allometric approaches [28][29][30][31][32][33]. However, the quality of results and maturity of these algorithms are still low [34,35].…”

Section: Introductionmentioning

confidence: 99%

Testing Forestry Digital Twinning Workflow Based on Mobile LiDAR Scanner and AI Platform

Niţă

2021

Forests

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Climate-smart forestry is a sustainable forest management approach for increasing positive climate impacts on society. As climate-smart forestry is focusing on more sustainable solutions that are resource-efficient and circular, digitalization plays an important role in its implementation. The article aimed to validate an automatic workflow of processing 3D pointclouds to produce digital twins for every tree on large 1-ha sample plots using a GeoSLAM mobile LiDAR scanner and VirtSilv AI platform. Specific objectives were to test the efficiency of segmentation technique developed in the platform for individual trees from an initial cloud of 3D points observed in the field and to quantify the efficiency of digital twinning by comparing the automatically generated results of (DBH, H, and Volume) with traditional measurements. A number of 1399 trees were scanned with LiDAR to create digital twins and, for validation, were measured with traditional tools such as forest tape and vertex. The segmentation algorithm developed in the platform to extract individual 3D trees recorded an accuracy varying between 95 and 98%. This result was higher in accuracy than reported by other solutions. When compared to traditional measurements the bias for diameter at breast height (DBH) and height was not significant. Digital twinning offers a blockchain solution for digitalization, and AI platforms are able to provide technological advantage in preserving and restoring biodiversity with sustainable forest management.

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Tree Branch Characterisation from Point Clouds: a Comprehensive Review

Hartley,

Jayathunga,

Morgenroth

et al. 2024

Curr. For. Rep.

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Purpose of Review Since the late 1990s, researchers have been increasingly utilising digital methodologies to assess the branch structure of trees. The emergence of commercial terrestrial laser scanners during this period catalysed an entirely new domain focused on point cloud-based research. Over the years, this field has transformed from a complex computational discipline into a practical tool that effectively supports research endeavours. Through the combined use of non-destructive remote sensing techniques and advanced analytical methods, branch characterisation can now be carried out at an unprecedented level. Recent Findings While terrestrial laser scanning has traditionally been the dominant methodology for this research domain, the increased use of mobile laser scanners and unmanned aerial vehicles indicates a transition towards more mobile platforms. Quantitative structural modelling (QSM) has been pivotal in advancing this field, enhancing branch characterisation capabilities across diverse fields. The past five years have seen increased uptake of 2D and 3D deep learning techniques as alternatives. Summary This article presents a comprehensive synthesis of approximately 25 years of research in the field of digital branch characterisation, reviewing the data capture technologies and analytical methods, along with the forest types and tree species to which these technologies have been applied. It explores the current trends in this dynamic field of research, research gaps and some of the key challenges that remain within this field. In this review, we placed particular emphasis on the potential resolution of the significant challenge associated with occlusion through the utilisation of mobile technologies, such as mobile laser scanners and unmanned aerial vehicles. We highlight the need for a more cohesive method for assessing point cloud quality and derived structural model accuracy, and benchmarking data sets that can be used to test new and existing algorithms.

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Tree Shape Variability in a Mixed Oak Forest Using Terrestrial Laser Technology: Implications for Mating System Analysis

Cited by 5 publications

References 41 publications

Advancements in Wood Quality Assessment: Standing Tree Visual Evaluation—A Review

Advancements in Wood Quality Assessment: Standing Tree Visual Evaluation—A Review

Testing Forestry Digital Twinning Workflow Based on Mobile LiDAR Scanner and AI Platform

Tree Branch Characterisation from Point Clouds: a Comprehensive Review

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