Dear Editor,

Please find below my review of the paper nhess-2024-29:

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

by

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

This paper is related to the comparison of landslide susceptibility models. It uses landslide conditioning factors using different classification scenarios using 5 models. Results are discussed.

General Comments

The paper is well written, and references are appropriated, it is a valuable contribution to susceptibility model assessment, but a few problems remain. The paper is an attempt to objectivise comparison of methods and the impact of classification of conditioning factors. If from page 14 things are clear, it is more difficult to follow the pages 5 to 13. A clear description of the scenario’s meaning is necessary as well. The first clear sentence about the relationship between several important elements appears in lines 271-273: “Furthermore, 54 LSMs were derived using the prepared landslide dataset and 11 LCF sets in the five selected methods, i.e., Information Value (IV), Logistic Regression (LR), Neural Network (NN), Random Forests (RF) and Support Vector Machine (SVM).”, which must appear really earlier, but even though I count only 7 LCF in table 3 (this discrepancy must at least be introduced in the table legend).

I am sure that all the information, but for the reader (at least for me) it is difficult to go in the paper. I would recommend introducing a figure of a graphical flow chart to explain the relationships between LCF, LSM and section 3.2, figure 2 being rather difficult to follow (maybe adding image may help). This will greatly improve the understanding of the paper.

I also recommend carefully rereading sections 4.2 to 4.6 regarding discussions, there are some redundancies that can be avoided by having some arguments in the discussion, since the paper is already rather long.

Few specific comments

• Don does not forget parentheses for dates of publications.
• Corominas et al. is 2014 not 2013 (online version)
• Figures 8 and 9, if I understand well the first is linked area and the second is related on pixels.

Dear Authors,

The work proposes an analysis of the impact of classifying the conditioning factors on landslide susceptibility mapping. The authors identified eleven scenarios for classifying the conditioning factors and used five different statistical models to generate a total of 54 susceptibility maps. The results are satisfying (confirming the key role that the investigation of the most appropriate conditioning factors plays in producing reliable susceptibility maps), and the article is well-written. It represents a valuable contribution to the improvement of the technique.

 I have a few minor comments:

• The article is quite long and could be shortened, particularly by summarizing Chapter 2.2 (Input Data), where there are some repetitions, and the results chapter, which contains many statements repeated also in the discussion chapter.
• In Chapter 3.2, it would be very helpful for the reader to have an image or summary table to describe the 11 scenarios developed for the classification of the conditioning factors.
• In Figure 1.d there seems to be a problem with the legend: “geological contacts” and “faults” seem to be inverted, or am I mistaken?

I did not find any other particular issues with the content of the paper. As far as I'm concerned, the manuscript is ready for publication after these minor revisions.

Best regards,

Anonymous Reviewer