Measuring Change Using Quantitative Differencing of Repeat Structure-From-Motion Photogrammetry: The Effect of Storms on Coastal Boulder Deposits
1
Department of Geosciences, Williams College, Williamstown, MA 01267, USA
2
Department of Earth and Planetary Science, The University of New Mexico, Albuquerque, NM 87131, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(1), 42; https://doi.org/10.3390/rs12010042
Received: 21 November 2019 / Revised: 11 December 2019 / Accepted: 15 December 2019 / Published: 20 December 2019
(This article belongs to the Special Issue Structure from Motion (SfM) Photogrammetry for Geomatics and Geoscience Applications)
Repeat photogrammetry is increasingly the go-too tool for long-term geomorphic monitoring, but quantifying the differences between structure-from-motion (SfM) models is a developing field. Volumetric differencing software (such as the open-source package CloudCompare) provides an efficient mechanism for quantifying change in landscapes. In this case study, we apply this methodology to coastal boulder deposits on Inishmore, Ireland. Storm waves are known to move these rocks, but boulder transportation and evolution of the deposits are not well documented. We used two disparate SfM data sets for this analysis. The first model was built from imagery captured in 2015 using a GoPro Hero 3+ camera (fisheye lens) and the second used 2017 imagery from a DJI FC300X camera (standard digital single-lens reflex (DSLR) camera); and we used CloudCompare to measure the differences between them. This study produced two noteworthy findings: First, volumetric differencing reveals that short-term changes in boulder deposits can be larger than expected, and that frequent monitoring can reveal not only the scale but the complexities of boulder transport in this setting. This is a valuable addition to our growing understanding of coastal boulder deposits. Second, SfM models generated by different imaging hardware can be successfully compared at sub-decimeter resolution, even when one of the camera systems has substantial lens distortion. This means that older image sets, which might not otherwise be considered of appropriate quality for co-analysis with more recent data, should not be ignored as data sources in long-term monitoring studies.
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Keywords:
structure-from-motion; UAVs; coastal boulder deposits; time series; storm waves; distortion
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MDPI and ACS Style
Nagle-McNaughton, T.; Cox, R. Measuring Change Using Quantitative Differencing of Repeat Structure-From-Motion Photogrammetry: The Effect of Storms on Coastal Boulder Deposits. Remote Sens. 2020, 12, 42. https://doi.org/10.3390/rs12010042
AMA Style
Nagle-McNaughton T, Cox R. Measuring Change Using Quantitative Differencing of Repeat Structure-From-Motion Photogrammetry: The Effect of Storms on Coastal Boulder Deposits. Remote Sensing. 2020; 12(1):42. https://doi.org/10.3390/rs12010042
Chicago/Turabian StyleNagle-McNaughton, Timothy; Cox, Rónadh. 2020. "Measuring Change Using Quantitative Differencing of Repeat Structure-From-Motion Photogrammetry: The Effect of Storms on Coastal Boulder Deposits" Remote Sens. 12, no. 1: 42. https://doi.org/10.3390/rs12010042
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