Abstract
Important infrastructure such as highways or railways traverse unstable terrain in many mountainous and scenic parts of the world. Rockfalls and landslides result in frequent maintenance needs, system unreliability due to frequent closures and restrictions, and safety hazards. Seismic activity significantly amplifies these negative economic and community impacts by generating large rockfalls and landslides as well as weakening the terrain. This paper interrogates a rich database of repeat terrestrial lidar scans collected during the Canterbury New Zealand Earthquake Sequence to document geomorphic processes as well as quantify rockfall activity rates through time. Changes in the activity rate (spatial distribution) and failure depths (size) were observed based on the Rockfall Activity Index (RAI) morphological classification. Forecasting models can be developed from these relationships that can be utilized by transportation agencies to estimate increased maintenance needs for debris removal to minimize road closures from rockfalls after seismic events.
Funding source: Pactrans
Funding source: Oregon Department of Transportation
Award Identifier / Grant number: SPR809
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: Funding for this research was provided by Oregon DOT and the Federal Highway Administration through project SPR-809 as well as through ongoing support from Pactrans. This material was adapted from the final report submitted to Oregon DOT. Support for the data acquisition was provided by GeoNet and the New Zealand Strategic Science Investment Fund. Leica Geosystems and Maptek I-Site provided software utilized in this study. The authors thank the developers of the open-source CloudCompare software, which was also utilized in this analysis.
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Conflict of interest statement: Dr. Olsen has financial interests in EZDataMD LLC, a company which commercializes the technology related to point cloud data processing for rockslope analysis used for this analysis. The conduct, outcomes, or reporting of this research could benefit EZDataMD LLC and could potentially benefit the author.
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Articles in the same Issue
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- Guest Editorial
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- On the quality checking of persistent scatterer interferometry data by spatial-temporal modelling
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- Supervoxel-based targetless registration and identification of stable areas for deformed point clouds
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Articles in the same Issue
- Frontmatter
- Guest Editorial
- Special Issue: Deformation Monitoring
- Research Articles
- High-precision intermode beating electro-optic distance measurement for mitigation of atmospheric delays
- EDM-GNSS distance comparison at the EURO5000 calibration baseline: preliminary results
- A mobile robot for monitoring floor flatness in real-time
- On the quality checking of persistent scatterer interferometry data by spatial-temporal modelling
- Image segmentation of breakwater blocks by edge-base Hough transformation
- Real movement or systematic errors? – TLS-based deformation analysis of a concrete wall
- Investigation of space-continuous deformation from point clouds of structured surfaces
- Supervoxel-based targetless registration and identification of stable areas for deformed point clouds
- Forecasting post-earthquake rockfall activity