Zhigang Pan defended his Ph.D. dissertation, "Shallow Water Bathymetry Using Full Waveform Bathymetric LiDAR and Hyperspectral Imagery." High-resolution airborne hyperspectral imagery and high-resolution, low-pulse energy, full waveform lidar were investigated to determine their capabilities for predicting water column characteristics and bathymetry. Using multiple evaluations, significant improvements in point density, multiple return detection, water turbidity, and accuracy were determined for full waveform bathymetric lidar. Additionally, improvements were made to the determination of shallow water bathymetry, water turbidity, and water column constituent concentration using hyperspectral imagery.

Zhigang becomes the fifth Geosensing Systems Engineering & Sciences (GSES) doctoral student to defend in 2016. His advisor was Dr. Craig Glennie. Zhigang will be working closely with Dr. Glennie and Leica Geosystems as a postdoctoral researcher, where he will be concentrating on single photon lidar calibration and filtering.

Congratulations, Zhigang!

Doctoral student Hongzhou Wang, from the Geosensing Systems Engineering & Sciences (GSES) graduate studies program, recently defended his dissertation on, “Fusion of Full Waveform LiDAR and Passive Remote Sensing for Improved Land-Cover Classification.” Land cover classification is a crucial step in interpreting remote sensing data, and the accuracy of the classification determines the reliability of the product for further downstream applications. Hyperspectral sensors have been widely utilized for classification because of the discrimination afforded by their rich spectral information and high resolution in both the spatial and spectral domains. Additionally, lidar data has gained increased interest for use in classification, because it provides precise 3D data with information regarding target backscattering properties. With the introduction of full waveform lidar (FWL), the possibility of using lidar for target discrimination has been enhanced due to the additional structural information acquired. The geometrical information and backscattering properties measured by FWL is complementary to the reflectance characteristics recorded within hyperspectral imagery (HI). The fusion of FWL and HI is, consequently, desirable. Hongzhou’s research aimed to build a framework for fusing FWL and HI while demonstrating the application of combined datasets for land cover classification. Feature extraction methods and classifier designs were proposed after considering characteristics of both datasets, and performance of the proposed methods were evaluated. Experimental results showed that the suggested methods were successful in extracting features from reconstructed FWL data.

Hongzhou has accepted a position at CGG as a Seismic Imager. Dr. Craig Glennie was Hongzhou’s graduate advisor. Congratulations and good luck!

A Ph.D. student from the Geosensing Systems Engineering & Sciences (GSES) graduate research program successfully defended his dissertation. Ning Cao defended on, “Advanced SAR Interferometry Methods for Ground Displacement Estimation from Spaceborne and Airborne Platforms.” Ground deformation measurements are important for monitoring and improving understanding of many natural geological phenomena or human-induced events, such as earthquakes, volcanoes, landslides, and land subsidence. Therefore, ground deformation studies can provide critical information for disaster prevention and protection of people and property. Interferometric synthetic aperture radar (InSAR) is a powerful technique for monitoring ground deformation phenomena.

In Ning's dissertation, several problems with the current advanced InSAR techniques were expressed, and corresponding approaches were proposed to solve them. He mainly focused on studying subsidence and landslide phenomena, producing results that can be used to monitor land subsidence in high spatial and temporal resolutions and to assess the impacts on civil infrastructure. The research also improves understanding of landslides to provide critical predictions and warnings.

Ning will be working as a postdoctoral researcher with NCALM/GSES at the University of Houston. Ning’s advisor was Dr. Hyongki Lee.

Congratulations, Ning!

Dr. Jennifer Telling recently joined the NCALM/GSES team as a postdoctoral researcher. She graduated in 2013, from the Georgia Institute of Technology, with a Ph.D. in Earth & Atmospheric Sciences. At Georgia Tech, her concentration was in geophysics and volcanology, with a minor in atmospheric science. Jennifer’s areas of interest in research include geophysics, volcanology, hazard modeling, planetary science, and image analysis. She is interested in “any work that allows me to combine techniques from different fields” of study. Previously, she completed a two-year postdoc in volcano remote sensing at Michigan Technological University.

We would like to welcome Jennifer to our team of researchers and students!