Joint 52nd Northeastern Annual Section / 51st North-Central Annual Section Meeting - 2017

Paper No. 25-16
Presentation Time: 1:30 PM-5:30 PM

TOWARDS A NEW LANDSLIDE SUSCEPTIBILITY MAP OF ALLEGHENY COUNTY, PA


DELANO, Helen L and WHITFIELD, Thomas G, Pennsylvania Geological Survey, DCNR, 3240 Schoolhouse Road, Middletown, PA 17057, hdelano@pa.gov

Landslides have been the subject of geologic investigations in the Pittsburgh, Pa. area for at least 60 years. General conclusions have been published about factors contributing to their occurrence, but formal susceptibility information has been elusive. We are approaching the problem again with a new compilation of available information on occurrences and increased detail in bedrock lithologic distribution. Geographic Information Systems (GIS), digital databases, and lidar elevation data offer improved tools to reexamine the controls on landslides in this famously unstable part of Pennsylvania.

Previous studies identified stratigraphic/lithologic zones as particularly susceptible to landslides. Formation-level geologic mapping in the cyclothemic sequences of western Pennsylvania does not break out lithologic variation within the sequences. Sub-formational detail of the bedrock geology gathered from borehole, measured section other data has been entered into the GIS and will be used to construct 3D models of the suspect geologic horizons.

Case files at the Pennsylvania Geological Survey, published technical reports, and media files have been mined for locations and other landslide characteristics, all of which have been entered into the GIS. Most of these incidents have some associated data on timing and circumstances of the event. Some have extensive information collected during investigations. Historical aerial photography, on-line street maps, property records, and lidar data have been valuable in improving the locations of features known from terse media reports.

After data entry for the landslide incidents are complete, attention will shift to the GIS and spatial analysis techniques to systematically assign a number of attributes to each event. Factors might include geologic details, soils, the slope and aspect of the land surface, and other derivatives from the lidar-derived 3.2-foot pixel DEM. It is hoped that a multivariate analysis of the landslide attributes will define susceptibility categories that can be applied to most of Allegheny County.