Introduction to the Lecture

In today's ecological research, the integration of big data and artificial intelligence (AI) technology has become an important development trend. In the field of vegetation ecology, in particular, this technology integration provides us with a brand-new perspective and method to study and monitor vegetation more accurately and efficiently. This report focuses on the technical progress and application prospect of Chinese vegetation product mapping based on big data, especially the role and potential of AI in this process. The report explores the mapping technology of big data-based vegetation remote sensing products. More accurate and efficient vegetation products in China can be developed by integrating multi-source remote sensing data, including field investigation, multi-source collection, multi-source near-surface remote sensing scanning and satellite remote sensing, and using AI algorithm (such as deep learning and machine learning) for data processing and analysis. The report further expounds the unique advantages of AI in analyzing the dynamic changes of vegetation. Through AI technology, researchers can better understand the effects of climate change, land use change and other influencing factors on vegetation distribution and its health status. In addition, combined with AI algorithm, we can extract valuable information from the large-scale data of vegetation products in China, reveal the change and driving mechanism of the vegetation distribution pattern in China, and predict the trend and response of ecosystem change. Meanwhile, the report also points out some challenges in applying AI technology to vegetation ecology research, such as data quality control, transparency and interpretability of AI algorithm. Finally, the report envisions the future research direction, including improving the generalization ability of AI models to adapt to different ecological environments, and discussing the application potential and value of large-scale AI models in ecological research.

Profile of the Speaker

Dr. Guo Qinghua is Professor and Doctoral Supervisor at Peking University. He obtained his bachelor’s and master’s degrees from Peking University, and Ph.D. from University of California, Berkeley. Before returning to China, Dr. Guo was a founding professor and tenured full professor at the School of Environmental Engineering, University of California, Merced. In 2020, he was selected into the "Ten Thousand Talents Program-Young and Middle-aged Leading Talents in Scientific and Technological Innovation" of the Innovation Talents Promotion Program of the Ministry of Science and Technology, China. Dr. Guo is currently Director of Peking University Institute of Remote Sensing, Deputy Director of UAV Application and Control Research Center of the Chinese Academy of Sciences, Associate Editor-in-Chief of Biodiversity Science, and Guest Professor at the Nevada Institute of the University of California. Dr. Guo has been selected as World’s top 2% scientists by Stanford in 2023. He is mainly dedicated to the research of multi-source remote sensing technology based on lidar and promoting its cross-application in ecology, forestry, agriculture and other disciplines. He has published over 160 SCI-indexed papers in mainstream journals, such as NAT. Commun., Nature Clim. Chang, Ecology, IEEE GRSM and Remote Sens Environ, in addition to three monographs.