Rockfall Simulator: Synthetic Geological Hazard Data from Physical Modeling

A simulated rockfall measurement dataset generated using a physical model. The dataset is associated with a GitHub repository and an arXiv paper, and was last updated on May 17, 2026. It is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).

Use Cases

• Training machine learning models for rockfall trajectory prediction based on simulated physical parameters.
• Benchmarking landslide risk assessment algorithms against synthetic measurement data.
• Validating physical models of geological processes using a controlled, simulated dataset.

Strengths

• Dataset is derived from a documented physical model, providing a controlled basis for simulation.
• Has associated academic documentation including a GitHub repository and an arXiv paper (arXiv:2506.16265).
• Uses a permissive Creative Commons Attribution 4.0 International license for broad reuse.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and file size are unknown, which may limit suitability assessment.
• Data is synthetic, which may limit direct applicability to real-world scenarios without validation.

Provenance

Source

Author 'zhaoyiww' on Hugging Face, with data from a physical simulation model.

Collection Method

Simulated using a physical model.

Freshness

Last updated 2026-05-17 07:55:00; freshness should be verified.