A Review of Software Solutions to Process Ground-based Point Clouds in Forest Applications

IF 9 1区 农林科学 Q1 FORESTRY
Arnadi Murtiyoso, Carlos Cabo, Arunima Singh, Dimas Pereira Obaya, Wout Cherlet, Jaz Stoddart, Cyprien Raymi Fol, Mirela Beloiu Schwenke, Nataliia Rehush, Krzysztof Stereńczak, Kim Calders, Verena Christiane Griess, Martin Mokroš
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引用次数: 0

Abstract

Purpose of Review

In recent years, the use of 3D point clouds in silviculture and forest ecology has seen a large increase in interest. With the development of novel 3D capture technologies, such as laser scanning, an increasing number of algorithms have been developed in parallel to process 3D point cloud data into more tangible results for forestry applications. From this variety of available algorithms, it can be challenging for users to decide which to apply to fulfil their goals best. Here, we present an extensive overview of point cloud acquisition and processing tools as well as their outputs for precision forestry. We then provide a comprehensive database of 24 algorithms for processing forest point clouds obtained using close-range techniques, specifically ground-based platforms.

Recent Findings

Of the 24 solutions identified, 20 are open-source, two are free software, and the remaining two are commercial products. The compiled database of solutions, along with the corresponding technical guides on installation and general use, is accessible on a web-based platform as part of the COST Action 3DForEcoTech. The database may serve the community as a single source of information to select a specific software/algorithm that works for their requirements.

Summary

We conclude that the development of various algorithms for processing point clouds offers powerful tools that can considerably impact forest inventories in the future, although we note the necessity of creating a standardisation paradigm.

Abstract Image

森林应用中处理地基点云的软件解决方案综述
综述目的 近年来,人们对三维点云在造林和森林生态学中的应用兴趣大增。随着激光扫描等新型三维捕捉技术的发展,人们同时开发了越来越多的算法,用于将三维点云数据处理成更具体的林业应用结果。对于用户来说,要从这些种类繁多的可用算法中选择最能实现其目标的算法是一项挑战。在此,我们将广泛介绍点云采集和处理工具及其在精准林业中的应用。然后,我们提供了一个包含 24 种算法的综合数据库,用于处理利用近距离技术(特别是地面平台)获取的森林点云。作为 COST 行动 3DForEcoTech 的一部分,汇编的解决方案数据库以及相应的安装和一般使用技术指南可在网络平台上访问。该数据库可作为社区的单一信息来源,用于选择符合其要求的特定软件/算法。小结我们的结论是,各种点云处理算法的开发提供了强大的工具,可对未来的森林资源清查工作产生重大影响,尽管我们注意到有必要创建一个标准化范例。
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来源期刊
Current Forestry Reports
Current Forestry Reports Agricultural 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.
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