SY002-0004
A Modular SAR/InSAR Imaging Geodesy Training Course for Capacity Building

Monday, 7 December 2020
Poster
Paul Alan Rosen, NASA Jet Propulsion Laboratory, Pasadena, CA, United States, Franz Josef Meyer, University of Alaska Fairbanks, Fairbanks, AK, United States, Scott Hensley, JPL-Radar Science & Engrg, Pasadena, CA, United States, Andrea Donnellan, NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, Hilarie B Davis, Technology for Learning, Stuart, FL, United States, David P Bekaert, JPL/NASA/Caltech, Pasadena, CA, United States, Heresh Fattahi, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States and Gareth Funning, University of California, Riverside, Department of Earth and Planetary Sciences, Riverside, CA, United States
Abstract:
With the expanded use of repeat-pass interferometric synthetic aperture radar (InSAR) time-series methods for solving problems of interest to the geodetic and geophysical communities in the United States and around the world, the National Aeronautics and Space Administration (NASA) Earth Surface and Interior (ESI) program is investing in the development of training materials to prepare the next generation of scientists for the effective use of SAR data in their research. These tools are open source, cloud accessible, and modular, and lend themselves to either in-class instruction or self-directed learning. This effort has the goal of developing lecture notes and computer lab exercises suitable for a semester-long university course or a short course, in the area of geodetic imaging using InSAR and its application to geophysical modeling of earthquakes, volcanoes, and other surface deformation phenomena. The techniques are applicable to other Earth remote sensing problems involving time series and interferometric methods. The course expands on a successful data processing short course already deployed at the University NAVSAR Consortium (UNAVCO) that is given annually. The course is being structured modularly using Jupyter notebooks, with the intent that instructors can tailor curriculum to their needs and the students’ interests. An important element of the effort is the development of design criteria for the curriculum and assessment of the effectiveness of the course through deployment and evaluation. The course material is deployable on cloud instances with sufficient capacity (at least 4 cores and 16 GB of memory) with Jupyter hub or Jupyter lab installed. Currently, we are working with the Alaska Satellite Facility’s OpenSARLab cloud computing environment, developed specifically for remote training and capacity building, with the intent of creating an integrated capacity building environment. In addition to presenting the concepts of the project and the developed materials, we will share our experience from using these materials along with cloud-based tools in a large virtual InSAR training held in August 2020 in collaboration with UNAVCO.
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