Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 25, issue 1
Articles | Volume 25, issue 1
https://doi.org/10.5194/nhess-25-183-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-25-183-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 1
Research article
 | 
07 Jan 2025
Research article |  | 07 Jan 2025

Comparison of conditioning factor classification criteria in large-scale statistically based landslide susceptibility models

Marko Sinčić, Sanja Bernat Gazibara, Mauro Rossi, and Snježana Mihalić Arbanas

Viewed

Total article views: 1,697 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,324 307 66 1,697 233 73 106
  • HTML: 1,324
  • PDF: 307
  • XML: 66
  • Total: 1,697
  • Supplement: 233
  • BibTeX: 73
  • EndNote: 106
Views and downloads (calculated since 26 Feb 2024)
Cumulative views and downloads (calculated since 26 Feb 2024)

Viewed (geographical distribution)

Total article views: 1,697 (including HTML, PDF, and XML) Thereof 1,618 with geography defined and 79 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 26 Oct 2025
Download
Short summary
The paper focuses on classifying continuous landslide conditioning factors for susceptibility modelling, which resulted in 54 landslide susceptibility models that tested 11 classification criteria in combination with 5 statistical methods. The novelty of the research is that using stretched landslide conditioning factor values results in models with higher accuracy and that certain statistical methods are more sensitive to the landslide conditioning factor classification criteria than others.
Read more
Share
Altmetrics
Final-revised paper
Preprint