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To Fill or Not to Fill: Sensitivity Analysis of the Influence of Resolution and Hole Filling on Point Cloud Surface Modeling and Individual Rockfall Event Detection Public Deposited

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  • Monitoring unstable slopes with terrestrial laser scanning (TLS) has been proven effective. However, end users still struggle immensely with the efficient processing, analysis, and interpretation of the massive and complex TLS datasets. Two recent advances described in this paper now improve the ability to work with TLS data acquired on steep slopes. The first is the improved processing of TLS data to model complex topography and fill holes. This processing step results in a continuous topographic surface model that seamlessly characterizes the rock and soil surface. The second is an advance in the automated interpretation of the surface model in such a way that a magnitude and frequency relationship of rockfall events can be quantified, which can be used to assess maintenance strategies and forecast costs. The approach is applied to unstable highway slopes in the state of Alaska, U.S.A. to evaluate its effectiveness. Further, the influence of the selected model resolution and degree of hole filling on the derived slope metrics were analyzed. In general, model resolution plays a pivotal role in the ability to detect smaller rockfall events when developing magnitude-frequency relationships. The total volume estimates are also influenced by model resolution, but were comparatively less sensitive. In contrast, hole filling had a noticeable effect on magnitude-frequency relationships but to a lesser extent than modeling resolution. However, hole filling yielded a modest increase in overall volumetric quantity estimates. Optimal analysis results occur when appropriately balancing high modeling resolution with an appropriate level of hole filling.
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  • Olsen, M. J., Wartman, J., McAlister, M., Mahmoudabadi, H., O’Banion, M. S., Dunham, L., & Cunningham, K. (2015). To Fill or Not to Fill: Sensitivity Analysis of the Influence of Resolution and Hole Filling on Point Cloud Surface Modeling and Individual Rockfall Event Detection. Remote Sensing, 7(9), 12103-12134. doi:10.3390/rs70912103
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  • 7
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  • 9
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  • Partial financial support for this project was provided by PacTrans and the Alaska Department of Transportation and Public Facilities.
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  • description.provenance : Made available in DSpace on 2015-12-07T18:00:01Z (GMT). No. of bitstreams: 2 license_rdf: 1370 bytes, checksum: cd1af5ab51bcc7a5280cf305303530e9 (MD5) OlsenMichaelCivilConstructionEnginFillNotFill.pdf: 2822825 bytes, checksum: 796267c9aaa4c65bbdbf04acb8736eb2 (MD5) Previous issue date: 2015-09
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2015-12-07T18:00:01Z (GMT) No. of bitstreams: 2 license_rdf: 1370 bytes, checksum: cd1af5ab51bcc7a5280cf305303530e9 (MD5) OlsenMichaelCivilConstructionEnginFillNotFill.pdf: 2822825 bytes, checksum: 796267c9aaa4c65bbdbf04acb8736eb2 (MD5)
  • description.provenance : Submitted by Patricia Black (patricia.black@oregonstate.edu) on 2015-12-07T17:59:25Z No. of bitstreams: 2 license_rdf: 1370 bytes, checksum: cd1af5ab51bcc7a5280cf305303530e9 (MD5) OlsenMichaelCivilConstructionEnginFillNotFill.pdf: 2822825 bytes, checksum: 796267c9aaa4c65bbdbf04acb8736eb2 (MD5)

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