At the invitation of Professor Gou Xiaohua and Associate Professor Nian Yanyun of the College of Earth and Environmental Sciences of Lanzhou University and the Key Laboratory of Western China's Ministry of Environment and Education, Researcher Su Yanjun from the Institute of Botany, Chinese Academy of Sciences, conducted academic exchange and online academic report on November 3, 2022.
Speaker: Researcher Su Yanjun, Institute of Botany, Chinese Academy of Sciences
Topic: LIDAR-based multi-scale vegetation canopy structure analysis
Host: Professor Gou Xiaohua, College of Earth and Environmental Sciences, Lanzhou University
Time: November 3, 2022 (Thursday), 15:00-17:00
Tencent Conference Number: 288-340-551
Expert Introduction:
Su Yanjun is a researcher and Ph.D. supervisor at the Institute of Botany, Chinese Academy of Sciences, and a selected candidate for the Talent Program of the Chinese Academy of Sciences. His main research interests are to quantify the forest canopy structure and spatial pattern using LIDAR-based remote sensing technology and to analyze the impact of human activities and global changes on terrestrial ecosystems. He has published more than 70 papers in international journals such as Remote Sensing Environment, ISPRS Journal of Photogrammetry, and Remote Sensing. He has served as an associate editor or editorial board member of the Geoscience Data Journal, Journal of Remote Sensing, Journal of Plant Ecology, etc. He has been awarded the William A. Fischer Memorial Scholarship by the American Society for Photogrammetry. He has been awarded the "William A. Fischer Memorial Scholarship" by the American Society for Photogrammetry, the "Li Xiaowen Award for Young Scientists in Remote Sensing", and the "Youth Science and Technology Award" by the Natural Resources Association of China.
Report Introduction:
The vegetation canopy structure affects the allocation of light and water resources within the canopy. Achieving accurate cross-scale estimation of vegetation canopy structure is a prerequisite and basis for understanding plant resource use strategies and their response mechanisms to environmental changes. The development of LiDAR technology provides a more effective technical tool for vegetation canopy structure information acquisition, but there are still a series of technical difficulties and challenges in extracting vegetation canopy structure parameters from the massive and disordered LiDAR point cloud data and realizing the up-scaling of vegetation canopy structure parameters. This report will focus on the research and development progress of near-ground mobile LiDAR systems and their corresponding data processing algorithms and introduce the method of inversion of large-scale vegetation canopy structure parameters based on the fusion of near-ground LiDAR data and multi-source satellite remote sensing data. Finally, this presentation will explore the role of vegetation canopy structure in ecosystem processes by means of case studies.
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