首页
首页 / 通知公告 / 正文

【活动预告】信息地学论坛第1期——Subsurface Imaging Using Ground Penetrating Radar:Air-based v.s. Ground Based Systems

作者:信息地学研究中心 来源:unknown 阅读次数:日期:2017-02-22

时间:1118(周五)下午14:30

地点:研究院大楼505A会议室

主讲人:Professor Lanbo Liu (刘澜波)

主讲人简介:Dr. Lanbo Liu is a Professor of Geophysics and Civil & Environmental Engineering at the University of Connecticut, Storrs, CT. He received BS and MS degrees in Geophysics from Peking University, MS in Civil and Environmental Engineering, and PhD in Geophysics from Stanford University. He was the Carnegie Fellow at Carnegie Institution of Washington before joining the faculty of Geology and Geophysics at the University of Connecticut. He was the Summer Faculty Fellow at Schlumberger-Doll Research, and at NASA’s Goddard Space Flight Center. He was a Fulbright Scholar to Norway in 2009-2010, and is the Blaustein Visiting Professor to Stanford University in 2017. He is a member of the Connecticut Academy of Science and Engineering (CASE). He published extensively on pure and applied geophysics in peer-referred journals, conference proceedings, and technical reports. He is a member of the editing board for Journal of Applied Geophysics, Geodesy and Geodynamics, and Journal of Earth Science. He also previously served as an Associate Editor for the journal of Geophysics and Journal of Environmental and Engineering Geophysics.

主讲内容:In this talk, I will start with reviewing the fundamental principles of radar technology, and emphasize the differences of ground penetrating radar (GPR) and most space-borne or airborne remote sensing (RS) systems.Next, I will describe the use of GPR technique in air-based and land-based format, as well as their pros and cons, through the introduction and comparison of a number of field survey cases in different physiographic provinces.Finally, I will link remote sensing and subsurface sensing together by emphasizing the importance of ‘ground truth’ calibration for RS measurements, and highlight the benefit of the integration of RS and GPR for providing more informative and comprehensive data sets in resources and environmental research and engineering.