Analysis of UAV lidar information loss and its influence on the estimation accuracy of structural and functional traits in a meadow steppe

• DOI: 10.1016/j.ecolind.2021.108515
• Publication Date: 2021-12-29T11:18:06Z
• Authors: Xiaoxia Zhao; Yanjun Su; Tianyu Hu; Mengqi Cao; Xiaoqiang Liu; Qiuli Yang; Hongcan Guan; Lingli Liu; Qinghua Guo
• Keywords: Information loss; Functional trait; Structural trait; Ecology; TLS; UAV lidar; 0401 agriculture, forestry, and fisheries; 04 agricultural and veterinary sciences; 15. Life on land; QH540-549.5

Accurate quantification of grassland structural and functional traits is the foundation for management restoration. Light detection ranging (lidar), especially unmanned aerial vehicle (UAV) lidar, has been recognized as an accurate effective technique local to regional-scale vegetation estimation. However, in ecosystems, it more likely be influenced by UAV lidar information loss caused dense canopies. In this study, we investigated how may occur influence estimation accuracy comparing with terrestrial laser scanning (TLS) field measurements a meadow steppe northern China. Five (i.e., mean height, maximum standard deviation canopy cover, volume) one trait aboveground biomass) were estimated from data TLS evaluation. The results showed that TLS-derived had much higher than lidar-derived traits. By data, found prevailing at tops bottoms. average height reached over 0.30 m, relative 49%, value 0.03 m 6% Maximum deviation, distance system ground three most influential factors on tops, indicating commonly seen sharp grasslands prone missed system. stronger With decrease can used extract comparable TLS. Among five traits, biomass was least loss. This study very first evaluation ecosystems its estimation, which provide guidance collection processing future applications.