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

Abstract

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.

Keywords

• 3D point cloud data
• Asia's tallest tree
• forest structural attribute
• giant tree
• multi‐platform lidar