Discovering and measuring giant trees through the integration of multi‐platform lidar data

IF 6.3 2区 环境科学与生态学 Q1 ECOLOGY
Yu Ren, Hongcan Guan, Haitao Yang, Yanjun Su, Shengli Tao, Kai Cheng, Wenkai Li, Zekun Yang, Guoran Huang, Cheng Li, Guangcai Xu, Zhi Lu, Qinghua Guo
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引用次数: 0

Abstract

Giant trees are pivotal in forest ecosystems, yet our current understanding of their significance is constrained primarily by the limited knowledge of their precise locations and structural characteristics. Amidst escalating human‐induced disturbances globally, there is an urgent need to devise a practical approach to discover and measure giant trees accurately and efficiently. Here, we propose a novel light detection and ranging (lidar)‐based framework designed for the discovery and measurement of giant trees. Our framework integrates cutting‐edge lidar platforms, including spaceborne, Unmanned Aerial Vehicle (UAV), and backpack lidar, to create an end‐to‐end workflow. The algorithm involved in the proposed framework was compiled into a code package and made available as open source. The method successfully identified the tallest trees in China, including the tallest tree in Asia, a Cupressus austrotibetica with a height of 102.3 m, discovered in Yarlung Zangbo Grand Canyon in May 2023. This finding has not only established a new record but also demonstrated the efficacy of our proposed framework. Utilising lidar data, we performed meticulous measurements at both individual and stand levels, revealing the unique characteristics of this giant tree. The new framework for the discovery and measurement of giant trees, encompassing detailed procedures and codes, is expected to facilitate the discovery and measurement of giant trees with high efficiency, thus fostering advancements in giant tree ecology.
通过整合多平台激光雷达数据发现和测量巨树
巨树在森林生态系统中举足轻重,但我们目前对其重要性的认识主要受限于对其精确位置和结构特征的有限了解。在全球人为干扰不断升级的情况下,我们迫切需要设计一种实用的方法来准确有效地发现和测量巨树。在此,我们提出了一种基于光探测和测距(激光雷达)的新型框架,用于发现和测量巨树。我们的框架整合了最先进的激光雷达平台,包括机载激光雷达、无人机激光雷达和背负式激光雷达,创建了一个端到端的工作流程。拟议框架中涉及的算法已编译成一个代码包,并以开放源代码的形式提供。该方法成功识别了中国最高的树木,包括2023年5月在雅鲁藏布大峡谷发现的亚洲最高树--高达102.3米的濯缨树。这一发现不仅创造了新的记录,也证明了我们提出的框架的有效性。利用激光雷达数据,我们对个体和树丛进行了细致的测量,揭示了这棵巨树的独特特征。新的巨树发现和测量框架包含详细的程序和代码,有望促进巨树的高效发现和测量,从而推动巨树生态学的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
11.60
自引率
3.00%
发文量
236
审稿时长
4-8 weeks
期刊介绍: A British Ecological Society journal, Methods in Ecology and Evolution (MEE) promotes the development of new methods in ecology and evolution, and facilitates their dissemination and uptake by the research community. MEE brings together papers from previously disparate sub-disciplines to provide a single forum for tracking methodological developments in all areas. MEE publishes methodological papers in any area of ecology and evolution, including: -Phylogenetic analysis -Statistical methods -Conservation & management -Theoretical methods -Practical methods, including lab and field -This list is not exhaustive, and we welcome enquiries about possible submissions. Methods are defined in the widest terms and may be analytical, practical or conceptual. A primary aim of the journal is to maximise the uptake of techniques by the community. We recognise that a major stumbling block in the uptake and application of new methods is the accessibility of methods. For example, users may need computer code, example applications or demonstrations of methods.
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