Summary and Schedule
This is a new lesson built with The Carpentries Workbench.
Before attending this course makesure to have: -python installed
| Setup Instructions | Download files required for the lesson | |
| Duration: 00h 00m | 1. introduction | How do you write a lesson using Markdown and sandpaper? |
| Duration: 00h 12m | 2. Intro and Theory Refresher |
What are the core components of a GPR system? How does GPR work to detect subsurface changes? What does a GPR trace represent? How can we process and visualize SEG-Y GPR data using Python? What are the core hardware and data-logging components of a GPR system, and how do they interact during acquisition? Through which physical contrasts does GPR detect subsurface changes, and how do antenna frequency and bandwidth control resolution and depth? What does a single GPR trace represent in time and in depth, and how is a radargram constructed from adjacent traces? How can we read, inspect metadata, and visualize SEG-Y GPR data in Python using ObsPy without modifying the raw samples? |
| Duration: 00h 32m | 3. AGC |
Why do GPR signals decrease in amplitude with increasing two-way travel
time? What is the principle of Automatic Gain Control (AGC) in signal processing? How does the choice of window length influence the effect of AGC on a radargram? How can AGC be implemented in Python to enhance deeper reflections in SEG-Y data? What are the potential benefits and drawbacks of applying AGC to GPR data? |
| Duration: 00h 44m | 4. Background Removal |
What is background removal in GPR data processing? Why is background removal needed for clearer interpretation? How can background removal be implemented programmatically? |
| Duration: 00h 56m | 5. Time-Zero Correction |
What does time-zero represent in a GPR trace? Why do system delays and antenna geometry cause time-zero to be shifted? How can first breaks be detected automatically in traces? What happens to interpretation if time-zero is not corrected? How can we compare sections before and after time-zero correction? |
| Duration: 01h 08m | 6. Bandpass Filtering |
What is a bandpass filter in the context of GPR signal
processing? Why apply a bandpass filter to GPR traces before interpretation? How do sampling frequency and Nyquist frequency constrain the choice of cutoffs? How does zero-phase filtering affect waveform shape compared with causal filtering? How can frequency spectra guide the selection of passband limits? :::::: |
| Duration: 01h 20m | 7. Deconvolution |
What is deconvolution in the context of GPR processing? Why do recorded GPR signals differ from the true earth response? How does spectral deconvolution recover sharper reflections? What is the role of the stabilization parameter in deconvolution? How can we evaluate the effect of deconvolution on traces and sections? :::::: |
| Duration: 01h 32m | 8. Wrap-up and Discussion |
What are the main processing steps applied to GPR data in this
course? How do these steps improve interpretability of radargrams? Which processing choices require the most careful parameter selection? How can Python be used flexibly to test and evaluate different workflows? :::::: |
| Duration: 01h 44m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
FIXME: Setup instructions live in this document. Please specify the tools and the data sets the Learner needs to have installed.
Data Sets
Download the data zip file and unzip it to your Desktop
Software Setup
Details
Setup for different systems can be presented in dropdown menus via a
spoiler tag. They will join to this discussion block, so
you can give a general overview of the software used in this lesson here
and fill out the individual operating systems (and potentially add more,
e.g. online setup) in the solutions blocks.
Use PuTTY
Use Terminal.app
Use Terminal