Lidar-Derived Rockfall Inventory—An Analysis of the Geomorphic Evolution of Rock Slopes and Modifying the Rockfall Activity Index (RAI)
Rockfall presents a significant risk to the safety and economy of communities and infrastructure in mountainous regions. The recently-developed Rockfall Activity Index (RAI) utilizes high-resolution terrestrial lidar-derived digital elevation models (DEMs) of rock slopes to categorize a slope face i...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/15/17/4223 |
| _version_ | 1797581890147844096 |
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| author | Shane J. Markus Joseph Wartman Michael Olsen Margaret M. Darrow |
| author_facet | Shane J. Markus Joseph Wartman Michael Olsen Margaret M. Darrow |
| author_sort | Shane J. Markus |
| collection | DOAJ |
| description | Rockfall presents a significant risk to the safety and economy of communities and infrastructure in mountainous regions. The recently-developed Rockfall Activity Index (RAI) utilizes high-resolution terrestrial lidar-derived digital elevation models (DEMs) of rock slopes to categorize a slope face into seven distinct morphological units, or “RAI classes”. This paper focuses on a comprehensive study conducted at four sites in Alaska, USA, where a robust lidar-based five-year inventory of 4381 rockfall events was analyzed. The primary objective was to investigate variations in failure characteristics, such as cumulative magnitude–frequency distributions, non-cumulative power–law parameters, average annual failure rates, and average failure depths, among the different RAI classes. The findings demonstrate that the seven RAI classes effectively differentiate the rock slope based on unique mass-wasting characteristics. Furthermore, the research explores spatial and temporal variations in these failure characteristics. Based on the study’s outcomes, recommendations are provided for modifying the RAI parameters for each RAI class, specifically the annual failure rate and average failure depth. These modifications aim to enhance the accuracy and effectiveness of rockfall hazard assessments. |
| first_indexed | 2024-03-10T23:14:03Z |
| format | Article |
| id | doaj.art-138009cbcbc241acbe73c0055d866a4c |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T23:14:03Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-138009cbcbc241acbe73c0055d866a4c2023-11-19T08:46:12ZengMDPI AGRemote Sensing2072-42922023-08-011517422310.3390/rs15174223Lidar-Derived Rockfall Inventory—An Analysis of the Geomorphic Evolution of Rock Slopes and Modifying the Rockfall Activity Index (RAI)Shane J. Markus0Joseph Wartman1Michael Olsen2Margaret M. Darrow3Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USADepartment of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USASchool of Civil and Construction Engineering, Oregon State University, Corvallis, OR 97331, USADepartment of Civil, Geological and Environmental Engineering, University of Alaska Fairbanks, Fairbanks, AK 99775, USARockfall presents a significant risk to the safety and economy of communities and infrastructure in mountainous regions. The recently-developed Rockfall Activity Index (RAI) utilizes high-resolution terrestrial lidar-derived digital elevation models (DEMs) of rock slopes to categorize a slope face into seven distinct morphological units, or “RAI classes”. This paper focuses on a comprehensive study conducted at four sites in Alaska, USA, where a robust lidar-based five-year inventory of 4381 rockfall events was analyzed. The primary objective was to investigate variations in failure characteristics, such as cumulative magnitude–frequency distributions, non-cumulative power–law parameters, average annual failure rates, and average failure depths, among the different RAI classes. The findings demonstrate that the seven RAI classes effectively differentiate the rock slope based on unique mass-wasting characteristics. Furthermore, the research explores spatial and temporal variations in these failure characteristics. Based on the study’s outcomes, recommendations are provided for modifying the RAI parameters for each RAI class, specifically the annual failure rate and average failure depth. These modifications aim to enhance the accuracy and effectiveness of rockfall hazard assessments.https://www.mdpi.com/2072-4292/15/17/4223terrestrial laser scanningRockfall Activity Indexmagnitude–frequency distributionrockfall inventoryhazard assessmentchange detection |
| spellingShingle | Shane J. Markus Joseph Wartman Michael Olsen Margaret M. Darrow Lidar-Derived Rockfall Inventory—An Analysis of the Geomorphic Evolution of Rock Slopes and Modifying the Rockfall Activity Index (RAI) Remote Sensing terrestrial laser scanning Rockfall Activity Index magnitude–frequency distribution rockfall inventory hazard assessment change detection |
| title | Lidar-Derived Rockfall Inventory—An Analysis of the Geomorphic Evolution of Rock Slopes and Modifying the Rockfall Activity Index (RAI) |
| title_full | Lidar-Derived Rockfall Inventory—An Analysis of the Geomorphic Evolution of Rock Slopes and Modifying the Rockfall Activity Index (RAI) |
| title_fullStr | Lidar-Derived Rockfall Inventory—An Analysis of the Geomorphic Evolution of Rock Slopes and Modifying the Rockfall Activity Index (RAI) |
| title_full_unstemmed | Lidar-Derived Rockfall Inventory—An Analysis of the Geomorphic Evolution of Rock Slopes and Modifying the Rockfall Activity Index (RAI) |
| title_short | Lidar-Derived Rockfall Inventory—An Analysis of the Geomorphic Evolution of Rock Slopes and Modifying the Rockfall Activity Index (RAI) |
| title_sort | lidar derived rockfall inventory an analysis of the geomorphic evolution of rock slopes and modifying the rockfall activity index rai |
| topic | terrestrial laser scanning Rockfall Activity Index magnitude–frequency distribution rockfall inventory hazard assessment change detection |
| url | https://www.mdpi.com/2072-4292/15/17/4223 |
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