|Dear authors, I have read and carefully aevaluated your manuscript "Assessing the importance of feature selection in Landslide Susceptibility for Belluno province (Veneto Region, NE Italy)". I found that the idea of the work is original and the outcomes are interesting, thus I recommend publication after a round of minor revisions. Please consider my comments hereafter.|
- English is understandable but a further revision from the most experienced coauthors would be useful to improve it.
- The idea behind this work is interesting and original. The analysis performed is incomplete. The comparison between different models and different parameters’ configurations is performed only in terms of performance metrics and visual inspections. In my opinion this is not enough to characterize the differences between the maps, a more thorough comparison is needed. I strongly recommend following the approach of Xiao et al. 2020, which is quite simple and could be done in a few minutes, adding a nice part in the discussion: the authors could make a comparison between the “full” and “reduced” version of each model by making the arithmetical difference of the susceptibility values calculated by the 14-factors-version of the model and the 9-factors-version of the same model. The same comparison could be repeated for the three models. The calculated difference would be useful to check if the differences are randomly distributed or if they consist in systematic errors driven by the spatial distribution of some variable (maybe one of the discarded ones? That would be even more interesting). That would add a nice value to the discussion and interpretation of the differences encountered.
- It is not clear how you actually implement the models. Do you use Matlab, R, or other software?
L21= which threshold? This is not clear
L22-24= I suggest being more precise and accurate. I would name clearly which are the variables discarded and the most important ones.
L26-30= I suggest deleting. The first sentence is a repetition. The second one is not fundamental.
L34= A reference is needed here about impacts of landslides, e.g. Froude et al., 2018
L47-48= what do you mean with “the significance of landslide studies”? I suggest rephrasing.
L51= reference needed (e.g. Reichenbach et al., 2018)
L62= data driven is a broader “family” of approaches, it does not apply to FR alone.
Section 2.1= I would move the figure of the study area here.
L165 (and elsewhere)= please use a more specific term instead of “precipitation”: which variable are you using? Mean annual precipitation? Mean monthly rainfall?
Table 1: I have some concerns about some factors. Elevation: I think at this latitude it is important because it largely influences climate, including the amount, intensity and distribution of rainfall. Slope: I would use the range 0°-86°. Aspect: motivation is quite confused. TWI: please change “measures” with “estimates”. TRI: please, rephrase the last part of the description (fluctuation, moves): it seems that the topographic surface moves. 7 and 8: please add the values of the ranges. 10: which feature of the rainfall regime are you considering? Mean monthly rainfall? 11: I don’t know the study cited here and I couldn’t find it in the reference list; I suggest to cite a paper specifically focused on the importance of lithology in LSM (e.g. Segoni et al., 2020). 11 and 13: I would include all the classes in the third column and not “etc.”.
L306 and 310: here I understand that you use natural breaks (l306) […] which is better than natural breaks (l310). Please, revise.
Fig 6 and 10: it would be nice to mark somehow the discarded factors. E.g. by coloring them in a different way or by adding a horizontal red line at 0.3 to show the cut-off value.
L408: after this discussion, it would be interesting to show the comparison I suggested in my general comment. You can show the three maps FREBF14 - FREBF9, WGB14-XG9 and RF14-RF9. And briefly describe the spatial patterns of the differences shown: if you remove 5 factors, are the differences random or do they follow a systematic pattern?
L460: instead of making reference to two figures that are not here, you could provide another figure, or a table, listing the factors ranked by importance. It would be meaningful to observe if the ranks are similar and if the discarded variables are similar.
Froude, M. J., & Petley, D. N. (2018). Global fatal landslide occurrence from 2004 to 2016. Natural Hazards and Earth System Sciences, 18(8), 2161-2181.
Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., & Guzzetti, F. (2018). A review of statistically-based landslide susceptibility models. Earth-science reviews, 180, 60-91.
Segoni, S., Pappafico, G., Luti, T., & Catani, F. (2020). Landslide susceptibility assessment in complex geological settings: Sensitivity to geological information and insights on its parameterization. Landslides, 17(10), 2443-2453.
Xiao, T., Segoni, S., Chen, L., Yin, K., & Casagli, N. (2020). A step beyond landslide susceptibility maps: a simple method to investigate and explain the different outcomes obtained by different approaches. Landslides, 17(3), 627-640.