YAN Guangjian, Beijing Normal University (BNU) Jing Shi Special-appointed Professor and Doctoral Supervisor, serves as the Associate director of the State Key Laboratory of Remote Sensing and Digital Earth, overseeing the BNU branch. In addition, he is the associate deputy editor of the Science collaboration journal - Journal of Remote Sensing, and the executive deputy director of the Quantitative Remote Sensing Professional Committee of the China Association of Remote Sensing Application (CARSA).

He has received six provincial and ministerial-level science and technology awards and has published over 300 papers. His work has earned him a continuous ranking among the top 2% of scientists globally, as jointly released by Elsevier and Stanford University. Yan led the development of China’s first airborne multi-angle power line patrol system, proposed the vegetation remote sensing path length distribution method, and established a series of remote sensing radiative transfer models tailored for complex terrain and cloudy conditions. His achievements have been applied to China’s UAV remote sensing payload integrated verification system, playing a significant role in several large-scale integrated remote sensing experiments.

WANG Shaohua is a researcher at the Aerospace Information Research Institute, Chinese Academy of Sciences(CAS), and serves as the associate director of the State Key Laboratory of Remote Sensing and Digital Earth. He is supported by the Chinese Academy of Sciences High-Level Young Talent Recruitment Program, and his research focuses on remote sensing big data analysis, remote sensing intelligent computation, geospatial intelligence, and social geographic computation in remote sensing.

He has successively led and undertaken projects such as the Ministry of Science and Technology’s National Key R&D Program, the NSFC General Program, and the New Pioneers Initiative Selective Project, among others. He has published over 120 academic papers, co-authored two monographs, and been granted more than 10 invention patents. His accolades include the First Prize for Science and Technology of Beijing, the Second Prize for Science and Technology Progress of Gansu Province, and the Special Award for Geographic Information Science and Technology Progress of China, among others. Prior to returning to China, he served as a postdoctoral researcher at the Department of Geography, University of California, Santa Barbara; the SPARC Center at Arizona State University; and the CyberGIS Center at the University of Illinois at Urbana–Champaign. He also concurrently holds positions as the Vice Chairman of Social Remote Sensing Geographic Computing of the China Remote Sensing Applications Association, a Board of Directors member of the International Association of Chinese Geographical Information Science (CPGIS), and an Executive Committee member of the ACM SIGSPATIAL China Chapter, among others.

WANG Li, Aerospace Information Research Institute, Chinese Academy of Sciences full professor and doctoral supervisor, serves as the Associate director of the State Key Laboratory of Remote Sensing and Digital Earth. His research focuses on remote sensing of global change and the carbon cycle, remote sensing-based estimation of carbon sources and sinks, and ecological restoration and carbon sink assessment.

He has led multiple major national research projects, including National Key R&D programs of China and projects, sub-projects of the Chinese Academy of Sciences’ Strategic Priority Research Programs, National Natural Science Foundation of China, and has published over 160 academic papers in top journals such as Science, Science Advances, Nature Sustainability, Nature Communications, and PNAS. Additionally, he has published three monographs, and received six provincial and ministerial-level science and technology awards. He has established a comprehensive remote sensing technology framework for detecting vegetation carbon sink baselines across the “classification - structure - function” chain. He also proposed an ecosystem carbon flux estimation approach driven by “observation stations, remote sensing data, and AI models,” and contributed to the development of the world's first 32-band full-waveform hyperspectral LiDAR for Earth observation. These achievements have been applied in multiple critical carbon sequestration practices, such as remote sensing-based high-accuracy estimation of carbon sources and carbon sink performance evaluation in ecological restoration projects，and featured in prominent media outlets,  including CCTV's News Live and News Broadcast, as well as Guangming Daily and Science and Technology Daily.