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Automated quantification of distributed landslide movement using circular tree trunks extracted from terrestrial laser scan data Public Deposited

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https://ir.library.oregonstate.edu/concern/articles/6395w8846

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  • This manuscript presents a novel algorithm to automatically detect landslide movement in a forested area using displacements of tree trunks distributed across the landslide surveyed repeatedly using terrestrial laser scanning (TLS). Common landslide monitoring techniques include: inclinometers, global position system (GPS), and interferometric synthetic aperture radar (InSAR). While these techniques provide valuable data for monitoring landslides, they can be difficult to apply with adequate spatial or temporal resolution needed to understand complex landslides, specifically in forested environments. Comparison of the center coordinates (determined via least-squares fit of the TLS data) of a cross section of the tree trunk between consecutive surveys enable quantification of landslide movement rates, which can be used to analyze patterns of landslide displacement. The capabilities of this new methodology were tested through a case-study analyzing the Johnson Creek Landslide, a complex, quick moving coastal landslide, which has proven difficult to monitor using other techniques. A parametric analysis of fitting thresholds was also conducted to determine the reliability of tree trunk displacements calculated and the number of features that were extracted. The optimal parameters in selecting trees for movement analysis were found to be less than 1.5 cm for the RMS residuals of the circle fit and less than 1.0 cm for the difference in the calculated tree radii between epochs.
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  • Conner, J. C., & Olsen, M. J. (2014). Automated quantification of distributed landslide movement using circular tree trunks extracted from terrestrial laser scan data. Computers & Geosciences, 67, 31-39. doi:10.1016/j.cageo.2014.02.007
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  • The United States Army, Eric HI and Janice Hoffman and Oregon Department of Transportation (SPR 740) provided funding for this study.
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  • description.provenance : Approved for entry into archive by Erin Clark(erin.clark@oregonstate.edu) on 2014-06-27T21:53:57Z (GMT) No. of bitstreams: 1 OlsenMichaelCivilConstructionEngAutomatedQuantificationDistributed.pdf: 2273055 bytes, checksum: 5b3597c3ef1c0023c6c17523006e373f (MD5)
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