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PRJ-3963 | Skagway Landslide Hazard
PI
Project Type
Field research | Geosciences | Reconnaissance
Natural Hazard Type(s)
Landslide
Facilities
Awards
Focused CoPe: Building Community Sensor Networks for Coastal Hazards and Climate Change Impacts in Southeast Alaska | 2052972 | National Science Foundation
Rockfalls are a common hazard in steep mountain valleys, especially near Skagway, Alaska, where recent events have threatened public safety and infrastructure. This study identifies zones prone to rockfall by analyzing rock formations, past rockfall deposits, and computer models predicting how rocks travel downslope. This dataset was used to perform kinematic rockfall susceptibility and runout modeling. Our findings highlight high-risk areas and provide insights to improve hazard mitigation, helping protect communities and tourism in the region.
Mission | Skagway Landslide Hazard
Cite This Data:
Roering, J., K. Dedinsky, M. Grilliot, I. Wachino, R. Cash (2025). "Skagway Landslide Hazard", in Skagway Landslide Hazard. DesignSafe-CI. https://doi.org/10.17603/ds2-2e3p-yn12
Hide Data
Date(s)
2023-05-17 ― 2023-05-19
Author(s)
; ; ; ;
Facility
RAPID - Natural Hazard and Disasters Reconnaissance Facility - University of Washington
Rockfalls are a common hazard in steep mountain valleys, especially near Skagway, Alaska, where recent events have threatened public safety and infrastructure. This study identifies zones prone to rockfall by analyzing rock formations, past rockfall deposits, and computer models predicting how rocks travel downslope. This dataset was used to perform kinematic rockfall susceptibility and runout modeling. Our findings highlight high-risk areas and provide insights to improve hazard mitigation, helping protect communities and tourism in the region.
Engineering/Geosciences Collection | Raw Data
Observation Type(s)
Geotechnical
Date(s) of Collection
2023-05-17 ― 2023-05-19
Data Collectors
; ; ;
Equipment
Large Fixed Wing Drone | Quantum Systems Trinity F90+ with iBase
Raw data downloaded from the data collection instruments. The Qube240 LiDAR and SonyRX1Rii RGB imagery data was collected with the Trinity F90+ fixed-wing drone, which was geolocated using the iBase and Leica GS18 GNSS survey observations. Corresponding flight logs from the Trinity F90+ are provided.
Processed aerial LiDAR and RGB imagery data from the Trinity F90+ fixed-wing drone, geolocated in reference to base station data from the iBase and GS18. Data is provided as 3D point cloud models; one has all features, and one is ground-filtered. LiDAR processing details are provided in the processing report, and flight KMLs and geotagging details are located within the light summaries folder.
