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

Mitigation is superior to post-disaster response in reducing the billions of
dollars in losses resulting from U.S. natural disasters, and information that
predicts the varying likelihood of geologic hazards can help public agencies
improves the necessary decision making on land use and zoning. Accordingly,
this map was created to increase the resistance of one urban area, metropolitan
Oakland, California, to land sliding. Prepared in a geographic information
system from a statistical model, the map estimates the relative likelihood of
local slopes to fail by two processes common to this area of diverse geology,
terrain, and land use.

Map data that predict the varying likelihood of land sliding 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.