Creating a digital outcrop model by using hyper-spectrometry and terrestrial LiDAR

Junhyeok Park, Melissa Bates, Y. S. Jeong, Kwangmin Kim, John M Kemeny

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Conventional methods for rock mass classification such as cell mapping and scanline survey have limitation because of human bias and hazard to access rock wall. Development of data collection methods utilizing hyperspectral imagery and terrestrial laser scanning enables engineers to obtain more sophisticated and accurate information about rock mass conditions, without human bias. This paper shows that rock mass parameters can be investigated from those two imagery systems. Hyperspectral imagery identifies weathering and alteration zone, and terrestrial laser scanning indicates orientation, roughness, and joint spacing of a given rock slope. The supervised learning procedure with a small training image is used to understand sitespecific or area-specific discontinuity and weathering trends. The final result shows quantified values for rock mass parameters with a 3D digital geology model fused with a hyperspectral thematic image. The site-specific rock mass representation by the proposed method can be advisable to reduce the time required for the survey in a hazardous environment, and provide consistent classification results regardless of the surveyor.

Original languageEnglish (US)
Title of host publication50th US Rock Mechanics / Geomechanics Symposium 2016
PublisherAmerican Rock Mechanics Association (ARMA)
Pages783-788
Number of pages6
Volume1
ISBN (Electronic)9781510828025
StatePublished - 2016
Event50th US Rock Mechanics / Geomechanics Symposium 2016 - Houston, United States
Duration: Jun 26 2016Jun 29 2016

Other

Other50th US Rock Mechanics / Geomechanics Symposium 2016
CountryUnited States
CityHouston
Period6/26/166/29/16

Fingerprint

outcrops
Spectrometry
spectrometry
outcrop
Rocks
rocks
imagery
rock
spectroscopy
Weathering
weathering
laser
rock mass classification
Wall rock
Scanning
wall rock
Lasers
Supervised learning
roughness
Geology

ASJC Scopus subject areas

  • Geochemistry and Petrology
  • Geophysics

Cite this

Park, J., Bates, M., Jeong, Y. S., Kim, K., & Kemeny, J. M. (2016). Creating a digital outcrop model by using hyper-spectrometry and terrestrial LiDAR. In 50th US Rock Mechanics / Geomechanics Symposium 2016 (Vol. 1, pp. 783-788). American Rock Mechanics Association (ARMA).

Creating a digital outcrop model by using hyper-spectrometry and terrestrial LiDAR. / Park, Junhyeok; Bates, Melissa; Jeong, Y. S.; Kim, Kwangmin; Kemeny, John M.

50th US Rock Mechanics / Geomechanics Symposium 2016. Vol. 1 American Rock Mechanics Association (ARMA), 2016. p. 783-788.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Park, J, Bates, M, Jeong, YS, Kim, K & Kemeny, JM 2016, Creating a digital outcrop model by using hyper-spectrometry and terrestrial LiDAR. in 50th US Rock Mechanics / Geomechanics Symposium 2016. vol. 1, American Rock Mechanics Association (ARMA), pp. 783-788, 50th US Rock Mechanics / Geomechanics Symposium 2016, Houston, United States, 6/26/16.
Park J, Bates M, Jeong YS, Kim K, Kemeny JM. Creating a digital outcrop model by using hyper-spectrometry and terrestrial LiDAR. In 50th US Rock Mechanics / Geomechanics Symposium 2016. Vol. 1. American Rock Mechanics Association (ARMA). 2016. p. 783-788
Park, Junhyeok ; Bates, Melissa ; Jeong, Y. S. ; Kim, Kwangmin ; Kemeny, John M. / Creating a digital outcrop model by using hyper-spectrometry and terrestrial LiDAR. 50th US Rock Mechanics / Geomechanics Symposium 2016. Vol. 1 American Rock Mechanics Association (ARMA), 2016. pp. 783-788
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