工学院能源与资源工程系学术报告10.18（报告人：Professor Yang Hong）
发布时间: 2010-10-13 08:22:00
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北京大学工学院 能源与资源工程系学术报告报告 |
题目：Satellite Remote Sensing for Global Water and Hydrologic Cycle Study
报告人 Professor Yang Hong
School of Civil Engineering and Environmental Sciences,
University of Oklahoma，Center for Natural Hazard and Disaster Research
National Weather Center, Norman, OK
时 间：10月18日（周一）下午3:30
地 点：方正大厦301会议室
报告内容摘要
Better understanding of the spatial and temporal distribution of precipitation, soil moisture, and evapotranspiration critical to climatic, hydrologic, and ecological applications. Recent development of satellite remote sensing techniques provides a unique opportunity for better observation of these hydrological variables for regions where ground measurement is limited. We will first review the progress of satellite-based retrieval algorithms and products available for user community. Then we will discuss applications of the remotely sensed products at global (http://trmm.gsfc.nasa.gov ) and regional (SERVIR-Africa: http://www.servir.net ) for disasters (flood/landslide) prediction and decision-making support through a new “state-of-the art” global hydrological model.
报告人简介
Dr. Yang Hong received the B.S. and M.S. degrees in environmental sciences from Beijing (Peking) University, China in 1996 and 1999, respectively, and the Ph.D. degree in Hydrology and Water Resources with emphasis in remote sensing and spatial analysis from the University of Arizona in 2003. Following a postdoctoral appointment at the Center for Hydrometeorology and Remote Sensing in University of California, Irvine, CA, he joined NASA Goddard Space Flight Center in 2005. Dr. Hong is currently an associate professor in School of Civil Engineering and Environmental Sciences at University of Oklahoma and Director of Remote Sensing Hydrology Lab at the National Weather Center. His primary research interests are remote sensing precipitation retrieval and validation, hydrologic remote sensing, natural hazard prediction and reduction, land surface modeling and data assimilation systems for water resource planning under changing climate.
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