Detection of rock bridges by infrared thermal imaging and modeling.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
11 Sep 2019
Historique:
received: 12 11 2018
accepted: 23 08 2019
entrez: 13 9 2019
pubmed: 13 9 2019
medline: 13 9 2019
Statut: epublish

Résumé

Characterization of rock discontinuities and rock bridges is required to define stability conditions of fractured rock masses in both natural and engineered environments. Although remote sensing methods for mapping discontinuities have improved in recent years, remote detection of intact rock bridges on cliff faces remains challenging, with their existence typically confirmed only after failure. In steep exfoliating cliffs, such as El Capitan in Yosemite Valley (California, USA), rockfalls mainly occur along cliff-parallel exfoliation joints, with rock bridges playing a key role in the stability of partially detached exfoliation sheets. We employed infrared thermal imaging (i.e., thermography) as a new means of detecting intact rock bridges prior to failure. An infrared thermal panorama of El Capitan revealed cold thermal signatures for the surfaces of two granitic exfoliation sheets, consistent with the expectation that air circulation cools the back of the partially detached sheets. However, we also noted small areas of warm thermal anomalies on these same sheets, even during periods of nocturnal rock cooling. Rock attachment via rock bridges is the likely cause for the warm anomalies in the thermal data. 2-D model simulations of the thermal behavior of one of  the monitored sheets reproduce the observed anomalies and explain the temperature differences detected in the rock bridge area. Based on combined thermal and ground-based lidar imaging, and using geometric and rock fracture mechanics analysis, we are able to quantify the stability of both sheets. Our analysis demonstrates that thermography can remotely detect intact rock bridges and thereby greatly improve rockfall hazard assessment.

Identifiants

pubmed: 31511533
doi: 10.1038/s41598-019-49336-1
pii: 10.1038/s41598-019-49336-1
pmc: PMC6739350
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

13138

Subventions

Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation)
ID : 200020_146426
Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation)
ID : 200020_159221
Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation)
ID : 200020_146426
Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation)
ID : 200020_159221
Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation)
ID : 200020_146426
Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation)
ID : 200020_159221
Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation)
ID : 200020_146426

Références

Sensors (Basel). 2014 Jul 10;14(7):12305-48
pubmed: 25014096
Sensors (Basel). 2017 May 18;17(5):
pubmed: 28524110
Nat Commun. 2018 Feb 22;9(1):762
pubmed: 29472534

Auteurs

Antoine Guerin (A)

Institute of Earth Sciences, University of Lausanne, Lausanne, 1015, Switzerland. guerina74200@gmail.com.

Michel Jaboyedoff (M)

Institute of Earth Sciences, University of Lausanne, Lausanne, 1015, Switzerland.

Brian D Collins (BD)

U.S. Geological Survey, Landslide Hazards Program, Menlo Park, California, 94025, USA.

Marc-Henri Derron (MH)

Institute of Earth Sciences, University of Lausanne, Lausanne, 1015, Switzerland.

Greg M Stock (GM)

U.S. National Park Service, Yosemite National Park, El Portal, California, 95318, USA.

Battista Matasci (B)

Institute of Earth Sciences, University of Lausanne, Lausanne, 1015, Switzerland.

Martin Boesiger (M)

Institute of Earth Sciences, University of Lausanne, Lausanne, 1015, Switzerland.

Caroline Lefeuvre (C)

Institute of Earth Sciences, University of Lausanne, Lausanne, 1015, Switzerland.

Yury Y Podladchikov (YY)

Institute of Earth Sciences, University of Lausanne, Lausanne, 1015, Switzerland.

Classifications MeSH