T150 Landslide Hazards: Inventories, Hazard Maps, Risk Analysis, and Warning Systems (Posters)

Monday, 26 September 2016
9:00 AM - 6:30 PM
Exhibit Hall E/F

EVALUATING THE EFFICACY OF LIDAR-BASED LANDSLIDE HAZARD IDENTIFICATION IN ADDISON COUNTY, VERMONT

Paper number: T150-10
Program: Technical Sessions
Time: 9:00 AM – 6:30 PM

Authors

Abstract

Following landfall of Tropical Storm Irene, numerous communities throughout Vermont and northeast were affected by mass wasting events. These events included extensive fluvial-derived bank erosion, gully headcut migration, debris flows and debris avalanches, rotational slides and landslides. The IPCC’s climate projections for the northeast suggest that annual mean precipitation and weather-related events are very likely to increase so there is considerable interest in developing techniques that help identify at-risk communities. Clift and Springston (2012) developed a GIS-based protocol - specific to Vermont - for identifying areas sensitive to mass wasting events. We translated this protocol into an ArcGIS toolbox that used a combination of 1.6 - 0.7 meter LIDAR to produce slope, roughness and topographic wetness index layers. The model combines these derivative products with distance to streams and various soil properties to produce continuous raster layers depicting the sensitivity to mass wasting.

We used this model to create preliminary hazard maps, to digitize the location and extent of existing mass wasting features and prioritize windshield and walking surveys to both evaluate the efficacy of this approach and contribute to an emerging statewide landslide database. We also used frequency ratio analysis to evaluate the number of pixels classified as mass wasting pixels at each digitized polygon to the total number of pixels within each site polygon for each variable of interest. This allowed us to identify those regions most susceptible to slope instability and produce updated mass wasting hazard maps for the entire county.

Geological Society of America Abstracts with Programs. Vol. 48, No. 7

doi: 10.1130/abs/2016AM-285836

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