Geodesy Technical Short Course: Strain Accumulation and Release from GNSS
Rhode Island Bar Assn., Hartford, CT, United States
Led by members of CRESCENT's Coupling, Seismicity, and Slow Slip (C3S) working group, this technical short course provides requisite tools for recognizing how earthquake cycle signatures in the Cascadia Subduction Zone are expressed in geodetic observations. It will introduce basic processing of geodetic time series to interpret longer-term strain accumulation processes and slow slip events. It will cover extracting velocities and displacements from geodetic time-series observations and introduce basic inverse methods to use geodetic data to constrain fault slip patterns. Analysis of geodetic data offers opportunities for students to gain geoscience-specific skills, but also data science skills, and will contribute to improving our understanding of the spectrum of slip processes on the subduction interface.
The course will include lectures and introduction to Python computing tools, as well as free time for participants to gain hands‑on experience with the tools using Jupyter notebooks.
Learning Objectives
Understanding basic GNSS time series signals
Load and visualize GNSS time series data
Use algorithms to estimate interseismic, coseismic, and slow slip signatures
Use geodetic displacement fields to estimate fault slip patterns
Use geodetic velocity fields to estimate interseismic coupling patterns
Understand how viscoelastic processes influence observed deformation
How to Apply
The application closes April 15, 2026 at 11:59 pm Pacific Daylight Time.
Apply Here
See the Course Page for more information.
Prerequisites
This course is for upper‑level undergraduate students, graduate students, postdocs, and professionals in the field of geodesy and tectonics who have specific research or application needs for using geodetic data to image fault slip processes.
An individual computer that has an internet browser and a minimum stable internet connection speed of 5 Mb/s.
Ability to explain how this course aligns with your current research or technical goals.
Recommended Background To get the most out of this course, participants are encouraged to have:
Intermediate Python computing skills including: Use of numpy and pandas
Familiarity with working in a development environment (conda, pixi, etc.)
Proficient knowledge in Jupyter notebooks
General understanding of linear algebra and inverse theory
Basic understanding of the earthquake cycle and tectonic settings
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The course will include lectures and introduction to Python computing tools, as well as free time for participants to gain hands‑on experience with the tools using Jupyter notebooks.
Learning Objectives
Understanding basic GNSS time series signals
Load and visualize GNSS time series data
Use algorithms to estimate interseismic, coseismic, and slow slip signatures
Use geodetic displacement fields to estimate fault slip patterns
Use geodetic velocity fields to estimate interseismic coupling patterns
Understand how viscoelastic processes influence observed deformation
How to Apply
The application closes April 15, 2026 at 11:59 pm Pacific Daylight Time.
Apply Here
See the Course Page for more information.
Prerequisites
This course is for upper‑level undergraduate students, graduate students, postdocs, and professionals in the field of geodesy and tectonics who have specific research or application needs for using geodetic data to image fault slip processes.
An individual computer that has an internet browser and a minimum stable internet connection speed of 5 Mb/s.
Ability to explain how this course aligns with your current research or technical goals.
Recommended Background To get the most out of this course, participants are encouraged to have:
Intermediate Python computing skills including: Use of numpy and pandas
Familiarity with working in a development environment (conda, pixi, etc.)
Proficient knowledge in Jupyter notebooks
General understanding of linear algebra and inverse theory
Basic understanding of the earthquake cycle and tectonic settings
#J-18808-Ljbffr