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

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.