Dynamic path-dependent landslide susceptibility modelling

Samia, Jalal; Temme, Arnaud; Bregt, Arnold; Wallinga, Jakob; Guzzetti, Fausto; Ardizzone, Francesca

doi:https://doi.org/10.5194/nhess-20-271-2020

Articles | Volume 20, issue 1

https://doi.org/10.5194/nhess-20-271-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-20-271-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 1

Research article

|

22 Jan 2020

Research article |

| 22 Jan 2020

Dynamic path-dependent landslide susceptibility modelling

Jalal Samia, Arnaud Temme, Arnold Bregt, Jakob Wallinga, Fausto Guzzetti, and Francesca Ardizzone

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Final revised paper (published on 22 Jan 2020)
Preprint (discussion started on 08 Jul 2019)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review of "Dynamic path dependent landslide susceptibility modelling" by Jalal Samia and others', Ben Mirus, 31 Jul 2019
- AC1: 'Author's responses to the referee1', Jalal Samia, 05 Nov 2019
RC2: 'Review of the manuscript “Dynamic path dependent landslide susceptibility modelling” by Samia et al.', Anonymous Referee #2, 06 Sep 2019
- AC2: 'Author's responses to the referee2', Jalal Samia, 05 Nov 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to minor revisions (review by editor) (05 Nov 2019) by Thomas Glade

AR by Jalal Samia on behalf of the Authors (08 Nov 2019) Author's response Manuscript

ED: Publish as is (16 Dec 2019) by Thomas Glade

AR by Jalal Samia on behalf of the Authors (17 Dec 2019)

Short summary

For the Collazzone study area in Italy, we quantified how much landslides follow others using Ripley's K function, finding that susceptibility is increased within 60 m and 17 years after a previous landslide. We then calculated the increased susceptibility for every pixel and for the 17-time-slice landslide inventory. We used these as additional explanatory variables in susceptibility modelling. Model performance increased substantially with this landslide history component included.