Enhancing Landslide Inventorying, Lidar Hazard Assessment and Asset Management

Leshchinsky, Ben A.; Olsen, Michael J.; Bunn, Michael D.; Oregon State University. School of Civil and Construction Engineering

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Enhancing Landslide Inventorying, Lidar Hazard Assessment and Asset Management

2018-06-01
By Leshchinsky, Ben A. ; Olsen, Michael J. ; Bunn, Michael D.

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English

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Details:

Creators:

Leshchinsky, Ben A. ; Olsen, Michael J. ; Bunn, Michael D.

Leshchinsky, Ben A. ; Olsen, Michael J. ; Bunn, Michael D. Less -
Corporate Creators:

Oregon State University. School of Civil and Construction Engineering
Corporate Contributors:

Oregon. Dept. of Transportation. Research Section ; United States. Federal Highway Administration

Oregon. Dept. of Transportation. Research Section ; United States. Federal Highway Administration Less -
Subject/TRT Terms:

[+]

Accuracy Asset Management Automation Detectors Geographic Information Systems Hazard Evaluation Highway Operations Highways Landslides Laser Radar Lidar Mapping Methodology Risk Assessment Risk Mapping
Publication/ Report Number:

FHWA-OR-RD-18-18
Resource Type:

Tech Report
Geographical Coverage:

Oregon ; United States

Oregon ; United States Less -
TRIS Online Accession Number:

01675103
Edition:

Final Report
Corporate Publisher:

Oregon. Dept. of Transportation. Research Section
NTL Classification:

NTL-SAFETY AND SECURITY-Highway Safety;NTL-ENERGY AND ENVIRONMENT-Environment Impacts;
Abstract:

Landslides are frequent hazards that result in major economic, environmental and social impacts for operation, maintenance and construction of highways. Current landslide databases are limited and often fragmented since they are based on a variety of inventories/geologic maps from various sources, which have been mapped sporadically over time as funding permits. Recent geospatial technologies such as lidar provide detailed geomorphologic information of the topography that significantly improves the accuracy of landslide mapping, particularly in forested terrain where these features can be masked by vegetation. This research significantly modified and improved the Contour Connection Method (CCM), a semi-automated approach to mapping existing landslides from digital elevation models to efficiently produce inventories. Supporting GIS-based tools were developed for straightforward implementation of the research. A special paper documenting workflows to utilize the tool for different applications was produced and will be published by the Department of Geology and Mineral Industries. The report also provides a detailed accuracy assessment of the accuracy and limitations of the CCM approach. The methodology was applied to large sections of several highway corridors that routinely experience landslides including US Routes 36 and 126, 42, and 101. The inventories were then integrated with traffic modeling analyses in a risk-based framework to evaluate economic consequences resulting from damages and closure time from the occurrence of landsliding.
Format:

PDF
Funding:

SPR 786
Collection(s):

US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:80c5e5abd538560bae61d7db070c4ee088a73b8b16b7020c77703475539e5e39
Download URL:

https://rosap.ntl.bts.gov/view/dot/36676/dot_36676_DS1.pdf
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Enhancing Landslide Inventorying, Lidar Hazard Assessment and Asset Management

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