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ISSN: 2157-7617

Journal of Earth Science & Climatic Change
黑料网

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Zhao Na

Zhao Na

Zhao Na, a professor at the State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, serves as a distinguished member of the Chinese Academy of Sciences and a faculty member at the University of Chinese Academy of Sciences

Biography

She is the Secretary-General of the Ecology and Environment Modeling Professional Committee of the China Environmental Science Society and a member of the Ecological Society of China, an expert in scenario and model methods assessment for the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) and an expert in ecological environment model methods assessment for the Ministry of Industry and Information Technology’s China Academy of Electronic Information Industry Development. Additionally, she serves as an editorial board member and guest editor for renowned international journals such as Transactions in GIS, Water, Applied Science, Remote Sensing, and Frontiers in Applied Science and Technology. Her research focuses on geographic spatiotemporal data analysis, multisource data fusion, extreme climate events, and risk assessment. She has led numerous projects funded by the National Natural Science Foundation of China, international cooperation projects, and projects from the Chinese Academy of Sciences. Her research findings have been published in over 100 academic papers in journals such as Science Advance, Nature Communications, Remote Sensing of Environment, Environmental International, Science of the Total Environment, and Transactions in GIS. She has also authored one English monograph and holds eight granted patents. Her achievements have been applied in IPBES assessments, regional ecological environment element fusion simulations, and regional carbon storage calculations.

Research Interest

Her research focuses on geographic spatiotemporal data analysis, multisource data fusion, extreme climate events, and risk assessment.

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