Articles | Volume 9, issue 4
https://doi.org/10.5194/esurf-9-1013-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-9-1013-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Aug 2021
Research article |
| 26 Aug 2021
| 26 Aug 2021
Beyond 2D landslide inventories and their rollover: synoptic 3D inventories and volume from repeat lidar data
Thomas G. Bernard
CORRESPONDING AUTHOR
Univ. Rennes, CNRS, Géosciences Rennes – UMR 6118, 35000 Rennes, France
Dimitri Lague
Univ. Rennes, CNRS, Géosciences Rennes – UMR 6118, 35000 Rennes, France
Philippe Steer
Univ. Rennes, CNRS, Géosciences Rennes – UMR 6118, 35000 Rennes, France
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Latest update: 17 May 2025
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.
Both landslide mapping and volume estimation accuracies are crucial to quantify landscape...
