GAIA
Geospatial Automation and Inference Analysis
Magnetic Data Processing Platform
GAAS
Geophysical Automation as a Service. GAAS brings project setup, traverse planning, magnetic processing, prediction review, visualisation, and export delivery into one guided workspace so teams can move from uploaded survey data to usable outputs without jumping between tools.
Platform
Core capabilities
Aurora AI
Get clear, plain-language guidance about your survey setup, processing choices, outputs, and deliverables.
Corrections
Apply diurnal, IGRF, filtering, lag, and heading corrections to clean your data before modelling.
Spatial modelling
Fill gaps across your survey area using three modelling approaches - choose the one that fits your data.
Interactive visualisation
View your results as heatmaps, contour overlays, or 3D surface plots on an interactive map.
Multi-format export
Download your processed results as PDF, GeoJSON, KML, Shapefile, CSV, or a ready-to-present report.
End-to-end workflow
From raw survey CSV to final deliverable - everything happens in one place, no specialist software needed.
Ready to process your survey?
Open your projects hub, create a project, upload your CSV, and run the full pipeline.
Projects
View the full list of projects and jump into the one you want.
Project
Project context
Tasks
Projects
Create a project, configure tasks, and upload survey/reference data
Project
Reference files (optional)
Upload relevant project documents - previous reports, field notes, PDFs, spatial reference data, or any supporting materials for this survey.
Upload reference file
PDF, DOCX, TXT, KMZ, KML, Shapefile (.zip), GeoJSON · max 100 MB
Survey configuration
Ground
Airborne
Raw data
Corrected
Analysis Configuration
Three independent panels - configure what applies, skip what doesn't
A - Corrections
✓
Diurnal correction
Remove daily geomagnetic variation using base station reference data
When valid base station readings are present, station readings are corrected using linear interpolation between consecutive base station readings. This preserves local drift direction and magnitude.
If valid base station readings are unavailable, a fallback low-frequency trend correction is used.
✓
IGRF removal
Subtract International Geomagnetic Reference Field at survey date and location
Filtering
Spectral filtering - remove regional field or high-frequency noise
Lag correction
Sensor/GPS timing offset compensation - critical for vehicle-mounted sensors
Heading correction
Remove directional bias between opposing survey line traverses
B - Prediction modelling
Kriging
Geostatistical interpolation with spherical variogram — produces prediction variance map
Machine learning
Random-forest surface using coordinates and local density features. Explicit: train/predict split. Sparse: full dataset + generated targets
Hybrid
Random-forest trend plus kriged residuals, with weighted fallback only when the residual path cannot run
C — Processing add-ons
Reduction to Pole (RTP)
Uses supplied inclination and declination when available; QA will flag stabilized or fallback behaviour
✓
Analytic signal
Source body edge detection — maxima delineate geological contacts independent of inclination
Regional residual
Separate the processed surface into regional and residual components using Gaussian smoothing
First Vertical Derivative
Sharpen shallow anomalies and suppress broad regional trends for near-surface structure mapping
Horizontal Derivative
Highlight lateral gradients and edges along contacts, dykes, and fault traces
Aurora AIAI
Survey analysis
Pipeline execution
Data cleaning & validation
Dataset validated · schema confirmed · no null values detected
✓
Corrections applied
Corrections applied successfully
✓
Train / predict split
Dataset split complete
✓
ML modelling
Model training in progress
Analytic signal
FFT-based horizontal and vertical derivatives · edge delineation
Output generation
Grid assembly · GeoJSON · statistics · AI analysis
Persist results
Store outputs · update metadata · write audit log
Processing in progress...
Select formats
PDF report
Full survey report with maps, statistics, and delivery-ready summary
AI Presentation
Presentation deck with processing outputs, maps, and summary slides
Aurora AI
Word report
Editable .docx report with structured survey notes
GeoJSON bundle
Zipped GeoJSON package with measured points, traverses, predicted points, and compatible layers
GIS ready
KML / KMZ bundle
Zipped Google Earth package with KML layers and a quick-look KMZ
Google Earth
CSV bundle
Zipped CSV package with measured points, predicted points, grids, and metadata
Geosoft / Petrel
File GDB bundle
Zipped ArcGIS-style package with points, traverses, grids, and metadata
ArcGIS
Map image bundle
Zipped PNG and JPG package with every generated map image
300 DPI
Report options
2 formats selected