Wrap-up and Discussion

Last updated on 2025-09-07 | Edit this page

Estimated time: 12 minutes

Overview

Questions

  • 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?

Objectives

  • Summarize the core processing steps learned: visualization, AGC, background removal, time-zero correction, bandpass filtering, and deconvolution.
  • Reflect on how each step alters the data and what geophysical problem it addresses.
  • Encourage critical evaluation of parameters and their impact on results.
  • Prepare learners to design their own GPR processing workflows for new datasets.
Key Points
  • GPR traces are raw recordings that must be processed for reliable interpretation.
  • Each processing step—AGC, background removal, time-zero correction, filtering, deconvolution—has a clear physical motivation.
  • Parameters (e.g., filter cutoffs, stabilization constants) control the trade-off between resolution and noise.
  • No single workflow is universal; effective GPR interpretation requires testing, visual inspection, and critical judgment.
  • Python offers a transparent environment for experimenting with and combining different methods.