Process and visualize GPR data with Python workflows for loading, filtering, and depth conversion.
npx skills add https://github.com/SteadfastAsArt/geoscience-skills --skill gprpy
Please help me install this Agent Skill. Skill: gprpy Source: https://github.com/SteadfastAsArt/geoscience-skills/tree/main/gprpy Command: npx skills add https://github.com/SteadfastAsArt/geoscience-skills --skill gprpy
Process and visualize ground-penetrating radar (GPR) data by providing a Python-based workflow that converts raw surveys into actionable, interpreted outputs, including velocity analysis and depth conversion.
Load a GPR file with gprpyProfile, apply dewow, set velocity, and export a processed figure.
High-intent search queries and answers about installing and using this skill.
To process and visualize ground-penetrating radar data in Python, you can load raw GPR files, apply dewow and background removal, apply gain and filters, and export the results as figures. This workflow converts raw surveys into interpreted outputs.
Yes, you can load common GPR file formats such as .DZT, .DT1, .GPR, .rd3, and .sgy. A provided script allows you to batch process multiple files for automated workflows across your survey data.
To perform velocity analysis and depth conversion for GPR surveys, use the Python-based workflow to analyze CMP or WARR data. This allows you to convert time sections to depth for accurate subsurface interpretation.
Standard signal processing steps for ground-penetrating radar data include dewow, background removal, time-power gain, and filtering. These steps prep signals before performing velocity analysis or topographic correction.
You need the gprpy library and matplotlib installed in your Python environment to run GPR processing scripts. These dependencies support data loading, visualization, and the execution of automated batch workflows.
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