Work

Brief communication: Visualizing uncertainties in landslide susceptibility modelling using bivariate mapping

Year: 2025

Type: article

Abstract: . Effectively communicating uncertainties inherent to statistical models is a challenging yet crucial aspect of the modeling process. This is particularly important in applied research, where output is used and interpreted by scientists and decision makers alike. In disaster risk reduction, susceptibility maps for natural hazards are vital for spatial planning and risk assessment. We present a novel type of landslide susceptibility map that jointly visualizes the estimated susceptibility and the corresponding prediction uncertainty, using an example from a mountainous region in Carinthia, Austria. We also provide implementation guidelines to create such maps using popular free and open-source software packages.

Source: Natural hazards and earth system sciences

DOI: 10.5194/nhess-25-1425-2025

Authors: Matthias Schlögl, Anita Graser, Raphael Spiekermann, Jasmin Lampert, Stefan Steger

Institutions: AIT Austrian Institute of Technology GmbH, GeoSphere Austria

Language: English

Topic: Landslides and related hazards

Subfield: Management, Monitoring, Policy and Law

Field: Environmental Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,553

Funder: Österreichische Forschungsförderungsgesellschaft