Field Data and Teaching Datasets

Course datasets are separated by provenance so students can see what was measured, what was derived, and what was generated for teaching. Two paths are kept distinct: real observations from the Ashton Prairie Living Laboratory (APLL) data hub and the explicitly synthetic Field Missions and teaching CSVs below.

Ashton Prairie Living Laboratory (APLL)

The Ashton Prairie Living Laboratory (APLL) data hub maps retained survey lines from the University of Iowa's field site. Individual survey points, synthetic map overlays, and the non-straight June 25 pre-processing ERT track are omitted. It includes layer controls, popups, a downloadable file catalog, and a companion PyHydroGeophysX processing notebook.

All 60 source files were checked. The public catalog contains 29 retained source files, 13 organized EM files, and 2 curated map products; redundant EM mirrors/intermediates and six problematic ERT measurement files are not published. The EM package keeps the full 24,212-row averaged in-phase/quadrature table as its processing input, provides separately named location tables for Profile 01–09, and places the valid layered inversion under models/ as a derived result. The ERT teaching workflow uses only the positive-only April 11 Wenner and May 2 dipole–dipole PyGIMLi datasets. Thirteen zero-placeholder elevations on EM Profile 04 are replaced in the organized profile geometry and Web GIS by flagged IDW estimates; the external source archive remains unchanged.

Map layers remain explicit

Survey lines show retained acquisition geometry, while processed EM resistivity and the survey footprint are labeled as derived products. Synthetic cases remain in the separate Field Missions activity rather than overlapping the real-data map. See the data license and machine-readable quality report.

Synthetic Field Data: Field Missions

The Field Missions provide four guided, physically plausible investigations. Every mission is explicitly synthetic and is designed for method selection, signal prediction, interpretation, and discussion of limitations.

Supporting Synthetic Teaching Data

The files below are clean synthetic examples that match the activities and notebooks, so every exercise works out of the box. They are not observations from Ashton Prairie.

By Module

Module	Dataset	Download	Used In
Gravity	Base-station drift readings	drift_readings.csv	Activity 1 · Drift Correction
Gravity	Sphere anomaly profile	anomaly_profile.csv	Activity 3 · Depth Detective
Gravity	Revised, forward-constructed cavity-survey loop	cavity_survey.csv	Classroom Labs · Gravity
Magnetics	Base-station time series	base_station.csv	Classroom Labs · Magnetics
Magnetics	Raw concealed-dyke profile	raw_dyke_profile.csv	Classroom Labs · Magnetics
Magnetics	Buried-vessel two-sensor difference profile (nT)	gradiometer_profile.csv	Classroom Labs · Magnetics
Seismic	First-break travel times	first_breaks.csv	Seismic Refraction Lab
Seismic	Three-layer first arrivals	three_layer_first_arrivals.csv	Classroom Labs · Seismic
Electrical	VES Schlumberger sounding	ves_sounding.csv	3-Layer VES Forward Modeling

Using a Synthetic Dataset

=== "Download directly"

Click the link in the table, then save the file. Open it in a spreadsheet or load it into the matching interactive tool.

=== "Load in Colab"

```python
import pandas as pd
url = "https://raw.githubusercontent.com/geohang/environmental-geophysics/main/docs/data/gravity/drift_readings.csv"
df = pd.read_csv(url)
df.head()
```

See the Notebooks page for ready-made Colab exercises that use these files.