Map and map database of susceptibility to slope failure by sliding and earthflow in the Oakland area, California

Metadata Updated: February 22, 2019

Map data that predict the varying likelihood of landsliding can help public agencies make informed decisions on land use and zoning. This map, prepared in a geographic information system from a statistical model, estimates the relative likelihood of local slopes to fail by two processes common to an area of diverse geology, terrain, and land use centered on metropolitan Oakland. The model combines the following spatial data: (1) 120 bedrock and surficial geologic-map units, (2) ground slope calculated from a 30-m digital elevation model, (3) an inventory of 6,714 old landslide deposits (not distinguished by age or type of movement and excluding debris flows), and (4) the locations of 1,192 post-1970 landslides that damaged the built environment. The resulting index of likelihood, or susceptibility, plotted as a 1:50,000-scale map, is computed as a continuous variable over a large area (872 km2) at a comparatively fine (30 m) resolution. This new model complements landslide inventories by estimating susceptibility between existing landslide deposits, and improves upon prior susceptibility maps by quantifying the degree of susceptibility within those deposits. Susceptibility is defined for each geologic-map unit as the spatial frequency (areal percentage) of terrain occupied by old landslide deposits, adjusted locally by steepness of the topography. Susceptibility of terrain between the old landslide deposits is read directly from a slope histogram for each geologic-map unit, as the percentage (0.00 to 0.90) of 30-m cells in each one-degree slope interval that coincides with the deposits. Susceptibility within landslide deposits (0.00 to 1.33) is this same percentage raised by a multiplier (1.33) derived from the comparative frequency of recent failures within and outside the old deposits. Positive results from two evaluations of the model encourage its extension to the 10-county San Francisco Bay region and elsewhere. A similar map could be prepared for any area where the three basic constituents, a geologic map, a landslide inventory, and a slope map, are available in digital form. Added predictive power of the new susceptibility model may reside in attributes that remain to be explored-among them seismic shaking, distance to nearest road, and terrain elevation, aspect, relief, and curvature.

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License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Dates

Metadata Date June 10, 2016
Metadata Created Date December 1, 2018
Metadata Updated Date February 22, 2019
Reference Date(s) January 1, 2001 (publication)
Frequency Of Update asNeeded
Frequency Of Update asNeeded

Metadata Source

Harvested from DOI CKAN Harvest Source

Graphic Preview

Image of entire map on white background

Additional Metadata

Resource Type Dataset
Metadata Date June 10, 2016
Metadata Created Date December 1, 2018
Metadata Updated Date February 22, 2019
Reference Date(s) January 1, 2001 (publication)
Responsible Party U.S. Geological Survey, GEO-WRG-NGM (Point of Contact)
Contact Email
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Bbox East Long -122.0000000
Bbox North Lat 38.00000000
Bbox South Lat 37.62500000
Bbox West Long -122.3750000
Coupled Resource
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Frequency Of Update asNeeded
Graphic Preview Description Image of entire map on white background
Graphic Preview File http://pubs.usgs.gov/mf/2002/2385/images/mf2385.gif
Graphic Preview Type GIF
Guid
Harvest Object Id dab6fcc2-a11b-4498-8bab-cd3d6a257594
Harvest Source Id 34ce571b-cb98-4e0b-979f-30f9ecc452c5
Harvest Source Title DOI CKAN Harvest Source
Licence Information in this data set is approved for release to the public by the Director, U.S. Geological Survey. This information has been reviewed but may still contain errors or inconsistencies, of which we would like to be made aware. Generally USGS data is not intended for use in navigation. Trade names are given for reference and do not constitute institutional endorsement.
Metadata Language
Metadata Type geospatial
Progress completed
Spatial Data Service Type
Spatial Reference System
Spatial Harvester true

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