Landslide susceptibility maps – Dominica, 2025

Science Case Name

 Multi-hazards in the Caribbean SIDS

Dataset Name/Title

Landslide susceptibility maps – Dominica, 2025 

Dataset Description

Landslide susceptibility maps

Key Methodologies

As the basis for the landslide susceptibility assessment a data layer was generated that represents homogeneous terrain units. Initially an attempt was made to generate these automatically, using the r.slopeunits application, which generates Terrain Units using a set of parameters from a Digital Elevation Model. To compute the susceptibility, we opted for a terrain unit partition and for the implementation of statistical models, in combination with expert-based mapping. These models learn from past events (and specifically from past landslide occurrences) to find patterns with respect to a set of predisposing factors. On the basis of these patterns a prediction is then made on the expected unstable locations in the future. To assess the susceptibility, we used a statistical model known as binomial Generalized Linear Model or Logistic Regression. 

Temporal Domain

The maps are generated for the current situation (2025).

Spatial Domain

The maps cover the country of Dominica.

Key indicators

Landslide susceptibility classes (Very low, Low, Moderate, High, Very high).  

Data format

GeoTIF

Source data

The maps were generated by the University of Twente 

Accessibility

Zenodo, https://doi.org/10.5281/zenodo.15182981

Stakeholder Relevance

Identifying area affected by landslide and expected unstable area for future planning of landuse and mitigation measures

Limitations/Assumptions

The maps does not provide information on the actual landslide runout, and focuses on the initiation zones, based on the Geomorphological units

Additional Output/Information

Contact Information

University of Twente, Cees van Westen & Luigi Lombardo