2021 Short Course: InSAR Processing & Analysis (ISCE+)

2021 InSAR Processing and Time-Series Analysis for Geophysical Applications: ISCE, ARIA-Tools, and MintPy short course

Dates: August 23-27, 2021 and pre-course work
Times: This course will take place 4 hours per day, Monday through Friday. Live lectures will take place during Pacific Daylight Time (PDT) (UTC-7) business hours; exact start/end times to be announced. Office hours will be scheduled at the beginning and end of day, PDT business hours.
Venue: This course will be offered online only

This 5-day course will cover basic & advanced InSAR theories, InSAR processing with JPL/Caltech InSAR Scientific Computing Environment (ISCE), and time-series InSAR processing with interferometric products generated by different processing centers. We will use Zoom for this training course. For computing and training modules, we’ll use the Alaska Satellite Facility’s OpenSARLab. We expect to have pre-workshop training modules, and Zoom-based Q&A sessions. Additional, asynchronous means of communication will be provided via Slack.

Participants will apply to participate as we expect demand to exceed capacity. Decisions will be made on responses to prompts in the application. Priority will be given to applicants from UNAVCO member institutions and who need the training to conduct research in the next year. (Check to see if your institution is a member of the UNAVCO consortium.) Review of applications begins May 2; applicants will be notified of their status May 13.

General participation in this course does not require a fee. If you are interested in receiving graduate credit for the course, there is a nominal fee, information is below.

Brief Agenda

August 13 Short Course Kickoff Meeting (view recording)

August 16-20	Course pre-assessment Review of pre course material – self-directed math, unix, python, plotting, numpy basics, downloading data, cloud environment, GIS using GDAL, software installation, SAR theory (view recording) Set up and use an account in OpenSARLab – instructions will be offered via webinar (view recording) Get EarthData login and permissions through ASF (10-15 hour time commitment) August 17 – Office Hours (view recording) August 19 – Office Hours (view recording) August 20 – Office Hours (view recording)
August 23	10:00a – 2:00p Pacific Time (1700 to 2100 UTC) Overview of whole process from modeling to processing. (4 hours) – view recording Exercises*(1-3 hours) Evening Office Hours 5:00-6:00p Pacific Time (0000 – 0100 UTC) – view recording
August 24	Morning Office Hours 7:00 – 8:00a (1400 – 1500 UTC) – view recording 10:00a – 2:00p Pacific Time (1700 to 2100 UTC) Interpreting interferograms, TOPS Processing (4 hours) – view recording (Exercises* (1-3 hours) Evening Office Hours 5:00-6:00p Pacific Time (0000 – 0100 UTC) – view recording
August 25	Morning Office Hours 7:00 – 8:00a (1400 – 1500 UTC) – view recording 10:00a – 2:15p Pacific Time (1700 to 2115 UTC) Map projections, preparing data for modeling, tropospheric/ionospheric errors (4 hours) Exercises* (1-3 hours) – view recording Evening Office Hours 5:00-6:00p Pacific Time (0000 – 0100 UTC) – view recording
August 26	Morning Office Hours 7:00 – 8:00a (1400 – 1500 UTC) – view recording 10:00a – 2:00pm Pacific Time (1700 to 2100 UTC) Time-series theory, stack processing (4 hours) – view recording Exercises* (1-3 hours) Evening Office Hours 5:00-6:00p Pacific Time (0000 – 0100 UTC) – view recording
August 27	Morning Office Hours 7:00 – 8:00a (1400 – 1500 UTC) – view recording 10:00a – 2:00pm Pacific Time (1700 to 2100 UTC) Using Tools MintPy and ARIA (4 hours) – view recording Exercises* (1-3 hours)
After course	Course post assessment Webinar on installing ISCE on your own system

Expectations

Our data show that people who participate in all the activities and allot time to working on the exercises independently learn a lot and gain confidence. Those who do not fully participate often become frustrated and fall behind. We expect participants to:

• Review the pre-course materials
• Complete the pre-assessment (assessments are used to gauge the effectiveness of the course)
• Use OpenSARLab for all course exercises (information for establishing an OpenSARLab account will be provided in the pre-course materials)
• Apply for a NASA Earthdata account (this will enable access to ALOS PALSAR, Sentinel-1, and NISAR-relevant datasets via ASF)
• Attend the live lectures and/or complete same-day review of the lecture recordings
• Complete the exercises associated with the lectures
• Complete the post-assessment
• Attend the optional office hours if additional assistance is needed

Prerequisite, Computers and Data

• Students should have some facility with mathematical concepts such as complex numbers, trigonometry, integration and differentiation.
• Students will be expected to know basic Unix/Linux command line usage and basic Python programming, and have done basic InSAR processing in the past.
• Students should review materials from the 2020 InSAR Processing and Time-Series Analysis for Geophysical Applications: InSAR Scientific Computing Environment (ISCE), ARIA Tools, and MintPy course.
• Students should review online documentation and tutorial materials available for ISCE.
• Students must apply for WInSAR data access through their university representative if they don’t already have a WInSAR account.
• Participants will use their own computers to access the OpenSARLab environment via a web browser.

Graduate Course Credit

If you would like to receive graduate course credit for successful completion of the course (1 credit hour, pass/fail), please indicate your interest on the application form. Note that taking the course for graduate credit has a nominal fee of $155. Regular participation without credit is free of charge. If you are selected for participation in the course, we will communicate with you under separate cover about how to enroll for credit. We partner with the University of Montana for course credit.

Instructors

• Paul Rosen (NASA Jet Propulsion Laboratory (JPL))
• David Bekaert (JPL)
• Heresh Fattahi (JPL)
• Gareth Funning (University of California, Riverside)
• Franz Meyer (University of Alaska, Fairbanks)
• Brent Minchew (Massachusetts Institute of Technology)
• Zhang Yunjun (California Institute of Technology)
• Hilarie Davis (Technology for Learning Consortium)

Questions

Please contact Melissa Weber, UNAVCO: weber[at]unavco.org

Image credit: NASA