National Gravity Compilation 2019: Half-Vertical Derivative Grid of Australia

Geoscience Australia's National Gravity Compilation 2019 - CSCBA 0.5VD image is a processed gravity anomaly grid derived from approximately 1.8 million ground and airborne observations. The grid has a cell size of 0.00417 degrees (approximately 435m) and shows a half vertical derivative of complete Bouguer anomalies over Australia and its continental margins. Data sources include the Australian National Gravity Database as of September 2019 and global offshore gravity data from Scripps Institution of Oceanography, NOAA, and NGA.

Use Cases

• Model subsurface geological structures based on gravity anomaly patterns.
• Train computer vision models for mineral exploration based on processed gravity grid imagery.
• Integrate gravity data with other geospatial layers for comprehensive resource assessment.
• Analyze continental-scale geophysical trends based on the 0.5VD transformation.

Strengths

• Derived from approximately 1.8 million gravity observations, including nearly 1.4 million ground stations.
• Incorporates 345,000 line km of Airborne Gravity and 106,000 line km of Airborne Gravity Gradiometry surveys.
• Data collection spans from the 1940s to the present day, providing historical depth.
• Grid cell size is precisely 0.00417 degrees (approximately 435m).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific ML tasks.
• Data may reflect geographic and source bias inherent to the aggregation of government, industry, and research data over decades.

Provenance

Source

Geoscience Australia Data

Collection Method

Ground and airborne gravity observations processed via standard methods and FFT to create a half vertical derivative grid.

Time Range

Observations from the 1940s to September 2019.

Freshness

Last updated 2026-03-25 17:07:34.787671; freshness should be verified.

Geography

Australia and its continental margins.