Andrea Albright and Sean Zhu Defend Ph.D. Dissertations in April
Two doctoral candidates from the Geosensing Systems Engineering & Sciences (GSES) graduate program recently defended their Ph.D. dissertations. Andrea Albright defended on, "Nearshore Bathymetry from Fusion of ICESat-2 and Multispectral Satellite Imagery." There is a global need for accurate and updated nearshore bathymetry data, but high costs limit their collection. Andrea's dissertation fused ICESat-2/ATLAS satellite green laser data with satellite-derived bathymetry from high-resolution multispectral imagery. The results overcome the issues of other collection methods by allowing estimates of spaceborne bathymetry at a high frequency. The experiment provided proof-of-concept that spaceborne bathymetry estimates are possible in clear water where the bottom is homogeneous.
Xinxiang (Sean) Zhu defended on, "Estimated Distributed Near-Field Surface Displacements Using Nascent Mobile Laser Scanning." Modeling fault dynamics requires dense observations of surface displacement over time but remains challenging to observe, because fault displacements are small, non-linear deformations. Sean's dissertation introduced a mobile laser scanning-based change detection framework capable of detecting distributed fault displacement in the near field at high resolution and accuracy. Several corresponding point clouds from a section of the Hayward Fault were extracted using a deep neural network and random sample consensus estimator. The results gave a time series of distributed fault creep displacement that matched in situ observations. The new method showed to be accurate and practical for fault displacement detection in the near field, and provides geodetic observations of non-linear displacement patterns at an unprecedented scale.
Andrea will be doing a post doc with the USDA Watershed Research Laboratory in Tifton, GA. Sean will be working for Torc Robotics as a software engineer. Dr. Craig Glennie was advisor to both students.
Congratulations, Andrea and Sean!