LiDAR, UAV or compass-clinometer? Accuracy, coverage and the effects on structural models

A J Cawood, Clare E. Bond, John A. Howell, Robert W.H. Butler, Yukitsugu Totake

Research output: Contribution to journalArticle

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62 Downloads (Pure)

Abstract

Abstract Light Detection and Ranging (LiDAR) and Structure from Motion (SfM) provide large amounts of digital data from which virtual outcrops can be created. The accuracy of these surface reconstructions is critical for quantitative structural analysis. Assessment of LiDAR and SfM methodologies suggest that SfM results are comparable to high data-density LiDAR on individual surfaces. The effect of chosen acquisition technique on the full outcrop and the efficacy on its virtual form for quantitative structural analysis and prediction beyond single bedding surfaces, however, is less certain. Here, we compare the accuracy of digital virtual outcrop analysis with traditional field data, for structural measurements and along-strike prediction of fold geometry from Stackpole syncline. In this case, the SfM virtual outcrop, derived from UAV imagery, yields better along-strike predictions and a more reliable geological model, in spite of lower accuracy surface reconstructions than LiDAR. This outcome is attributed to greater coverage by UAV and reliable reconstruction of a greater number of bedding planes than terrestrial LiDAR, which suffers from the effects of occlusion. Irrespective of the chosen acquisition technique, we find that workflows must incorporate careful survey planning, data processing and quality checking of derived data if virtual outcrops are to be used for robust structural analysis and along-strike prediction.
Original languageEnglish
Pages (from-to)67-82
Number of pages16
JournalJournal of Structural Geology
Volume98
Early online date20 Apr 2017
DOIs
Publication statusPublished - May 2017

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outcrop
structural analysis
prediction
bedding plane
syncline
data quality
imagery
effect
detection
fold
geometry
methodology

Keywords

  • LiDAR
  • Structure from motion
  • UAV
  • Virtual outcrop
  • Structural model

Cite this

LiDAR, UAV or compass-clinometer? Accuracy, coverage and the effects on structural models. / Cawood, A J; Bond, Clare E.; Howell, John A.; Butler, Robert W.H.; Totake, Yukitsugu.

In: Journal of Structural Geology, Vol. 98, 05.2017, p. 67-82.

Research output: Contribution to journalArticle

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note = "This study was carried out as part of a University of Aberdeen provided PhD supported by The NERC Centre for Doctoral Training in Oil & Gas, (grant reference: NE/M00578X/1). Thanks to Magda Chmielewska for her training and help with LiDAR processing, without which this study could not have been undertaken. Midland Valley Exploration is thanked for academic use of Move 2016 software. We gratefully acknowledge the detailed and constructive reviews by Mike James and an anonymous reviewer, and thanks to Bill Dunne for careful and thorough editorial comments, all of which greatly improved the manuscript.",
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N1 - This study was carried out as part of a University of Aberdeen provided PhD supported by The NERC Centre for Doctoral Training in Oil & Gas, (grant reference: NE/M00578X/1). Thanks to Magda Chmielewska for her training and help with LiDAR processing, without which this study could not have been undertaken. Midland Valley Exploration is thanked for academic use of Move 2016 software. We gratefully acknowledge the detailed and constructive reviews by Mike James and an anonymous reviewer, and thanks to Bill Dunne for careful and thorough editorial comments, all of which greatly improved the manuscript.

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N2 - Abstract Light Detection and Ranging (LiDAR) and Structure from Motion (SfM) provide large amounts of digital data from which virtual outcrops can be created. The accuracy of these surface reconstructions is critical for quantitative structural analysis. Assessment of LiDAR and SfM methodologies suggest that SfM results are comparable to high data-density LiDAR on individual surfaces. The effect of chosen acquisition technique on the full outcrop and the efficacy on its virtual form for quantitative structural analysis and prediction beyond single bedding surfaces, however, is less certain. Here, we compare the accuracy of digital virtual outcrop analysis with traditional field data, for structural measurements and along-strike prediction of fold geometry from Stackpole syncline. In this case, the SfM virtual outcrop, derived from UAV imagery, yields better along-strike predictions and a more reliable geological model, in spite of lower accuracy surface reconstructions than LiDAR. This outcome is attributed to greater coverage by UAV and reliable reconstruction of a greater number of bedding planes than terrestrial LiDAR, which suffers from the effects of occlusion. Irrespective of the chosen acquisition technique, we find that workflows must incorporate careful survey planning, data processing and quality checking of derived data if virtual outcrops are to be used for robust structural analysis and along-strike prediction.

AB - Abstract Light Detection and Ranging (LiDAR) and Structure from Motion (SfM) provide large amounts of digital data from which virtual outcrops can be created. The accuracy of these surface reconstructions is critical for quantitative structural analysis. Assessment of LiDAR and SfM methodologies suggest that SfM results are comparable to high data-density LiDAR on individual surfaces. The effect of chosen acquisition technique on the full outcrop and the efficacy on its virtual form for quantitative structural analysis and prediction beyond single bedding surfaces, however, is less certain. Here, we compare the accuracy of digital virtual outcrop analysis with traditional field data, for structural measurements and along-strike prediction of fold geometry from Stackpole syncline. In this case, the SfM virtual outcrop, derived from UAV imagery, yields better along-strike predictions and a more reliable geological model, in spite of lower accuracy surface reconstructions than LiDAR. This outcome is attributed to greater coverage by UAV and reliable reconstruction of a greater number of bedding planes than terrestrial LiDAR, which suffers from the effects of occlusion. Irrespective of the chosen acquisition technique, we find that workflows must incorporate careful survey planning, data processing and quality checking of derived data if virtual outcrops are to be used for robust structural analysis and along-strike prediction.

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