Robin J. L. Hartley, Sadeepa Jayathunga, Justin Morgenroth, Grant D. Pearse
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引用次数: 0
Abstract
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.
Current Forestry ReportsAgricultural and Biological Sciences-Ecology, Evolution, Behavior and Systematics
CiteScore
15.90
自引率
2.10%
发文量
22
期刊介绍:
Current Forestry Reports features in-depth review articles written by global experts on significant advancements in forestry. Its goal is to provide clear, insightful, and balanced contributions that highlight and summarize important topics for forestry researchers and managers.
To achieve this, the journal appoints international authorities as Section Editors in various key subject areas like physiological processes, tree genetics, forest management, remote sensing, and wood structure and function. These Section Editors select topics for which leading experts contribute comprehensive review articles that focus on new developments and recently published papers of great importance. Moreover, an international Editorial Board evaluates the yearly table of contents, suggests articles of special interest to their specific country or region, and ensures that the topics are up-to-date and include emerging research.