Thomas Bernard

Thomas Bernard
Université de Rennes 1 | UR1 · UMR CNRS 6118 - Géosciences Rennes

PhD student at Géosciences Rennes France

About

5
Publications
922
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
14
Citations
Citations since 2016
5 Research Items
14 Citations
20162017201820192020202120220246810
20162017201820192020202120220246810
20162017201820192020202120220246810
20162017201820192020202120220246810
Introduction
I currently working on landslide detection based on point cloud LiDAR data as well as landscape analysis from DEM LiDAR data and 2D hydraulic simulation.
Additional affiliations
May 2017 - June 2017
Université de Rennes 1
Position
  • internship
Education
September 2016 - June 2017
Université de Rennes 1
Field of study
  • Earth sciences

Publications

Publications (5)
Thesis
Full-text available
L’objectif fondamental de la géomorphologie est l’identification et la caractérisation des processus façonnant les paysages. En fournissant une représentation 3D haute précision et haute densité des paysages, le LiDAR aéroporté a révolutionné notre capacité à extraire des informations sur la topographie fournissant ainsi de nouvelles opportunités p...
Article
Full-text available
Topographic metrics are designed to quantify scale‐relevant relationships between geometric properties of landscapes to reveal the processes shaping them. They have long been derived from topographic flow routing algorithms, initially developed for coarse Digital Elevation Models (DEMs), whose resolution (≥30 m) and poor precision did not resolve c...
Article
Full-text available
Efficient and robust landslide mapping and volume estimation is essential to rapidly infer landslide spatial distribution, to quantify the role of triggering events on landscape changes, and to assess direct and secondary landslide-related geomorphic hazards. Many efforts have been made to develop landslide mapping methods, based on 2D satellite or...
Preprint
Full-text available
Efficient and robust landslide mapping and volume estimation is essential to rapidly infer landslide spatial distribution, to quantify the role of triggering events on landscape changes and to assess direct and secondary landslide-related geomorphic hazards. Many efforts have been made during the last decades to develop landslide areal mapping meth...

Network

Cited By