GB-InSAR monitoring of slope deformations in a mountainous area affected by debris flow events

Frodella, William; Salvatici, Teresa; Pazzi, Veronica; Morelli, Stefano; Fanti, Riccardo

doi:https://doi.org/10.5194/nhess-17-1779-2017

Articles | Volume 17, issue 10

https://doi.org/10.5194/nhess-17-1779-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Landslide early warning systems: monitoring systems, rainfall...

https://doi.org/10.5194/nhess-17-1779-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 10

Research article

|

19 Oct 2017

Research article |

| 19 Oct 2017

GB-InSAR monitoring of slope deformations in a mountainous area affected by debris flow events

William Frodella, Teresa Salvatici, Veronica Pazzi, Stefano Morelli, and Riccardo Fanti

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Final revised paper (published on 19 Oct 2017)
Preprint (discussion started on 20 Jun 2017)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Report 1', Anonymous Referee #1, 24 Jul 2017
- AC1: 'Answer to referee#1', Veronica Pazzi, 03 Aug 2017
RC2: 'Reviewer's evaluation', Anonymous Referee #2, 28 Jul 2017
- AC2: 'Answer to referee#2', Veronica Pazzi, 03 Aug 2017

Peer-review completion

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

ED: Publish subject to minor revisions (further review by Editor) (17 Aug 2017) by Luca Piciullo

AR by Veronica Pazzi on behalf of the Authors (23 Aug 2017) Author's response Manuscript

ED: Publish as is (01 Sep 2017) by Luca Piciullo

Short summary

A local scale GB-InSAR system was implemented for mapping and monitoring slope landslide residual deformations and for early warning purposes in case of landslide reactivations, with the aim of assuring the safety of the valley inhabitants and the personnel involved in the post-event recovery phase. The here presented methodology could represent a useful contribution to a better understanding of landslide phenomena and decision making process during the post-emergency management activities.