APPLICATIONS OPEN AROUND JUNE 8, 2026

Course Description:

This 5-day course covers basic and advanced InSAR theory and hands-on processing of Sentinel-1 and NISAR data using the JPL/Caltech InSAR Scientific Computing Environment (ISCE/ISCE3). Topics include noise mitigation, accessing ARIA and OPERA standard InSAR products and preparing them for time-series analysis, InSAR time-series analysis with MintPy, pixel offset tracking, and basic interpretation and modeling.

Primary Audience:  Graduate students, postdocs, and early career scientists interested in using InSAR in their research.

Secondary Audience:  Instructors who plan to teach InSAR processing and analysis.

Learning Objectives:

• Process interferograms using the ISCE software environments and adjacent open source software tools.
• Distinguish between different sources of noise in InSAR data and apply appropriate corrections.
• Interpret interferograms and prepare them for modeling.
• Utilize pixel offset tracking to measure large surface motions (e.g., glaciers and large earthquakes).
• Produce and utilize InSAR time series for applications of interest.

Participant Commitment:

Around 40 hours total: 5 main sessions over 5 days, with additional morning and evening office hours and homework assignments.

Prerequisites, Computer and Data:

Coursework/content background: Graduate student status or equivalent past experience in the geosciences (or a related field). Applicants should be able to describe their research need (or other need) for taking the course in writing.
Scientific computing background: Basic skills in Python and use of a command-line environment.
Hardware/Software/Internet: Computer with a functioning web browser and a stable internet connection capable of sustaining live streaming.

Brief Agenda:

Tentative agenda is listed below, and subject to change.

• Day 1 (4 hours): Plenary Lectures: Introduction and InSAR theory; PM Office Hour (1 hour)
• Day 2 (4 hours): Plenary Lectures: Sentinel-1 processing and interpretation; AM/PM Office Hours (1 hour each)
• Day 3 (4 hours): Plenary Lectures: NISAR processing and interpretation; AM/PM Office Hours (1 hour each)
• Day 4 (4 hours): Plenary Lectures: InSAR time series theory; AM/PM Office Hours (1 hour each)
• Day 5 (4 hours – midday): Plenary Lectures: InSAR time series analysis; AM Office Hour (1 hour)

Content highlights:

• Day 1: Examples of InSAR applications, background theory, data interpretation, and a modeling exercise.
• Day 2: Sentinel-1 interferogram processing using the topsApp.py workflow and preparation for modeling.
• Day 3: NISAR InSAR processing with ISCE3; addressing tropospheric and ionospheric error sources.
• Day 4: InSAR time series theory and complementary techniques (e.g., pixel offset tracking).
• Day 5: Time series analysis using MintPy and Dolphin, including tools for error analysis and correction.

Assessment:

Participants will demonstrate the learning goals by successfully completing at least 80% of the course assignments.

Instructors:

Gareth Funning, University of California, Riverside

Franz J. Meyer, University of Alaska, Fairbanks

Kang Wang, EarthSope

Heresh Fattahi, Jet Propulsion Laboratory

Zhang Yunjun, Chinese Academy of Sciences

Eric Fielding, Jet Propulsion Laboratory

Ann Chen, University of Texas, Austin

Zachary Hoppinen, Cold Regions Research and Engineering Laboratory

Alex Lewandowski, University of Alaska, Fairbanks / Alaska Satellite Facility

Simran Sangha, Jet Propulsion Laboratory

Rowena Lohman, Cornell University

Becca Bussard, Pennsylvania State University

Sara Mirazee, Jet Propulsion Laboratory

Others TBD.