A new Landslide Investigation and Simulation Archive through downscaled landslide experiments.

Area of Science:

• Geosciences
• Earthquake Engineering
• Natural Hazards

Background:

• Small-scale landslide experiments effectively analyze complex triggering factors.
• Quantifying phenomena at reduced scales offers higher accuracy than real-scale studies.
• Analyzing individual triggering factors is facilitated by controlled laboratory settings.

Purpose of the Study:

• To present the Landslide Investigation and Simulation Archive (LISA) dataset.
• To provide a structured database of over 50 landslide simulation experiments.
• To facilitate the testing and validation of landslide models and rainfall thresholds.

Main Methods:

• Utilized a landslide simulator at the Gap²Lab, Lecco Campus of Politecnico di Milano.
• Conducted over 50 experiments spanning 7 years.
• Structured experimental data into a comprehensive database (Microsoft Access) and CSV files.

Main Results:

• The LISA dataset comprises extensive data from controlled landslide experiments.
• The database allows for detailed querying and interaction with experimental results.
• Data are readily available for model validation and the establishment of critical rainfall thresholds.

Conclusions:

• The LISA dataset is a valuable resource for landslide research.
• The structured database format enhances data accessibility and usability.
• Open access availability on Harvard Dataverse promotes wider scientific collaboration and data sharing.