the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 11 Mar 2024
Brief Communication: Weak correlation between building damage and loss of life from landslides
Abstract. Mapping exposure to landslides is necessary to mitigate risk and reduce vulnerability. Exposure maps can be constructed from building databases, akin to seismic risk assessments, but there has been little investigation of the predictive relationship between building damage and risk to human life from landslides. Our study investigates this relationship globally and in Nepal (47,213 and 5,664 landslides, respectively). While a correlation exists for nationwide totals (R2=0.75), it is near zero for individual events (R2=0.025). It is important not to use building datasets in isolation for landslide exposure maps and disaster planning to avoid unintentionally prioritising building damage over human lives.
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RC1: 'Comment on nhess-2024-40', Daniel Costantini, 09 Apr 2024
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Interesting statistical analyses and results!
Below are a few comments that I have noticed:
- Lines 20-24: I would not say that seismic risk maps are constructed only on the basis of the type and condition of buildings. Rather, the seismic microzonation or the type and condition of the soil plays a central role (cf. various earthquakes such as the one in Emiglia Romagna or Abruzzo). I would suggest supplementing this.Â
- Lines 78-80: That's an interesting observation. However, I believe that this observation also has a lot to do with the type of process. For example, when a large slide is activated, you have often little human loss and a lot of damage to buildings. This is not the case with rockfalls, however, where there is often a high level of human loss and less damage to buildings, because these tend to be more localised. I would suggest that the type of landslide process must also be taken into account in any case.
- Further observation: It would be interesting to carry out such statistical analyses on databases that have a high level of detail in terms of geographical localisation and content/description of the event in order to compare whether the results are similar. One example is the IdroGEO platform in Italy - see, for example, the landslides of the Autonomous Province of Bolzano. We are at your complete disposal for a discussion of the analysis of our detailed datasets.
Citation: https://doi.org/10.5194/nhess-2024-40-RC1
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