Post-Event Ground Motion Estimation Data for New Zealand

Claudio Schill's dataset supports the journal paper "Post-Event Ground Motion Estimation Using Graph Neural Networks." It likely contains ground motion intensity measures and spatial data for forensic analysis of structural damage after earthquakes. The dataset is 2.7 GB in size and was last updated on May 7, 2026.

Use Cases

• Estimating ground motion intensity measures based on nearby seismic observations.
• Training graph neural networks to capture spatial dependencies in earthquake data.
• Forensic analysis of structural damage based on estimated ground motions.
• Comparing GNN performance with established multivariate normal conditional IM methods.
• Extending ground motion estimation models to support additional observation types like macroseismic intensity.

Strengths

• Dataset size is 2.7 GB, indicating a substantial volume of data.
• Data is associated with a published journal paper, suggesting research-grade quality.
• License is CC-BY-4.0, providing clear and open usage permissions.
• Last update date is 2026-05-07, indicating recent maintenance.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Claudio Schill

Collection Method

Likely gathered for a case study in New Zealand, as referenced in the paper abstract.

Freshness

Last updated 2026-05-07 04:20:07; freshness should be verified.

Geography

New Zealand