Articles | Volume 9, issue 4
https://doi.org/10.5194/esurf-9-1013-2021
https://doi.org/10.5194/esurf-9-1013-2021
Research article
 | 
26 Aug 2021
Research article |  | 26 Aug 2021

Beyond 2D landslide inventories and their rollover: synoptic 3D inventories and volume from repeat lidar data

Thomas G. Bernard, Dimitri Lague, and Philippe Steer

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Thomas Bernard on behalf of the Authors (24 Feb 2021)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (17 Mar 2021) by Giulia Sofia
RR by Alexander Densmore (24 Mar 2021)
RR by Dave Milledge (31 Mar 2021)
ED: Reconsider after major revisions (01 Apr 2021) by Giulia Sofia
AR by Thomas Bernard on behalf of the Authors (29 Jun 2021)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to technical corrections (05 Jul 2021) by Giulia Sofia
ED: Publish subject to technical corrections (12 Jul 2021) by Niels Hovius (Editor)
AR by Thomas Bernard on behalf of the Authors (20 Jul 2021)  Manuscript 
Download
Short summary
Both landslide mapping and volume estimation accuracies are crucial to quantify landscape evolution and manage such a natural hazard. We developed a method to robustly detect landslides and measure their volume from repeat 3D point cloud lidar data. This method detects more landslides than classical 2D inventories and resolves known issues of indirect volume measurement. Our results also suggest that the number of small landslides classically detected from 2D imagery is underestimated.