International Benchmarking of the Individual Tree Detection Methods for Modeling 3-D Canopy Structure for Silviculture and Forest Ecology Using Airborne Laser Scanning

作者：Yunsheng Wang, Juha Hyyppä, Xinlian Liang, Harri Kaartinen, Xiaowei Yu, Eva Lindberg, Johan Holmgren, Yuchu Qin, Clément Mallet, António Ferraz, Hossein Torabzadeh, Felix Morsdorf, Lingli Zhu, Jingbin Liu, Petteri Alho · 发表于：IEEE Transactions on Geoscience and Remote Sensing · 年份：2016 · DOI：10.1109/tgrs.2016.2543225 · 被引用次数：199 · 研究领域：Remote Sensing and LiDAR Applications、Forest ecology and management、Forest Ecology and Biodiversity Studies

Canopy structure plays an essential role in biophysical activities in forest environments. However, quantitative descriptions of a 3-D canopy structure are extremely difficult because of the complexity and heterogeneity of forest systems. Airborne laser scanning (ALS) provides an opportunity to automatically measure a 3-D canopy structure in large areas. Compared with other point cloud technologies such as the image-based Structure from Motion, the power of ALS lies in its ability to penetrate canopies and depict subordinate trees. However, such capabilities have been poorly explored so far. In this paper, the potential of ALS-based approaches in depicting a 3-D canopy structure is explored in detail through an international benchmarking of five recently developed ALS-based individual tree detection (ITD) methods. For the first time, the results of the ITD methods are evaluated for each of four crown classes, i.e., dominant, codominant, intermediate, and suppressed trees, which provides insight toward understanding the current status of depicting a 3-D canopy structure using ITD methods, particularly with respect to their performances, potential, and challenges. This benchmarking study revealed that the canopy structure plays a considerable role in the detection accuracy of ITD methods, and its influence is even greater than that of the tree species as well as the species composition in a stand. The study also reveals the importance of utilizing the point cloud data for the d...