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2008 Joint Meeting of The Geological Society of America, Soil Science Society of America, American Society of Agronomy, Crop Science Society of America, Gulf Coast Association of Geological Societies with the Gulf Coast Section of SEPM

Paper No. 4
Presentation Time: 8:00 AM-4:45 PM

Statewide Landslide Information Database of Oregon (SLIDO)-Release 1


BURNS, William J., Oregon Department of Geology and Mineral Industries, 800 NE Oregon Street #28, Suite 965, Portland, OR 97232, MADIN, Ian P., Dept of Geology and Mineral Industries, 800 NE Oregon St. #28 Suite 965, Portland, OR 97232 and MA, Lina, Oregon Department of Geology and Mineral Industries, 800 NE Oregon St. #28, Suite 965, Portland, OR 97232, bill.burns@dogami.state.or.us

One of the most common and devastating geologic hazards in Oregon is landslides. Landslides that have failed in the past often remain in a weakened state and can fail repeatedly. Thus, creating a landslide inventory is critical. Recent research at DOGAMI was performed to choose the best remote sensing dataset to use as a primary tool to begin systematic mapping of landslides in Oregon. One of the conclusions of this recent research was to systematically compile all previously mapped landslides from geologic and hazard maps statewide. This new GIS database, Statewide Landslide Information Database of Oregon (SLIDO), can serve as a starting place for future landslide studies and as a place to house LIDAR-based landslide inventories (Burns, 2007).

To create SLIDO-1, we extracted existing landslide, debris/alluvial fan, and colluvium/talus (landslide-related features) polygons from 257 previous studies to populate the initial GIS database. Two sets of spatial data were compiled: the polygon (outline) of the mapped landslide or landslide related feature and the polygon (outline) of the extent of the original study. This data was compiled through digitization of paper maps and conversion of existing digital data. The resulting database includes more than 15,000 landslide and landslide-related features.

The original studies vary widely in scale, scope, and focus which are reflected in a wide range in the accuracy, detail and completeness with which landslides are mapped across the state. Therefore, we recommend that SLIDO-1 be improved and updated in the future following the LIDAR-based landslide inventory mapping protocol being developed by Burns and Madin. This study was partially funded by the U.S. Geologic Survey (USGS) Landslide Hazards Program.

Burns, W.J., 2007. Comparison of Remote Sensing Datasets for the establishment of a landslide mapping protocol in Oregon. AEG Special Publication 23. Conference Presentations, 1st North American Landslide Conference, Vail, CO

Session No. 155--Booth# 278

T112. Landslide Inventories, Landslide Hazards, Databases, and Mapping: Status of Information and Progress toward a Shared Standard (Posters)
Sunday, 5 October 2008: 8:00 AM-4:45 PM
Geological Society of America Abstracts with Programs. Vol. 40, No. 6, p.173
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