文献类型：期刊文献

英文题名：Dominant Trees Analysis Using UAV LiDAR and Photogrammetry

作者：Liu, Qingwang[1] Li, Shiming[1] Tian, Xin[1] Fu, Liyong[1]

第一作者：刘清旺

机构：[1] Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, China

年份：2020

起止页码：4649-4652

外文期刊名：International Geoscience and Remote Sensing Symposium (IGARSS)

收录：EI(收录号：20211010035940)

基金：This work was supported in part by the National Key R&D Program of China under Grant 2017YFD0600904

语种：英文

外文关键词：Statistics - Ecosystems - Photogrammetry - Remote sensing - Forestry - Unmanned aerial vehicles (UAV)

摘要：Dominant trees compose the upper story of forest canopies, and are one of the key factors that affect the light redistribution for forest ecosystem. UAV lidar and photogrammetry can be used to measure spatial variation of upper crowns of dominant trees with details. How about the differences of tree crowns using lidar and photogrammetry with very different observation geometry? This paper aims to extract parameters of dominant trees and analyze the differences using lidar and photogrammetry. The lidar and photogrammetry-based CHMs were smoothed by Gaussian algorithm for three times. The result indicated that the positions of potential tops of dominant trees from lidar-based CHM were near to that from photogrammetry. The mean and standard deviation of position differences were 0.5m and 0.3m respectively. The heights of potential tops from lidar-based CHM were highly correlated with that from photogrammetry-based CHM. The height differences had the mean of -0.4m and standard deviation of 0.4m. The smoothing of crowns will weaken the effects of height variation within crowns on detection of dominant trees. ? 2020 IEEE.