Masters Theses

Date of Award


Degree Type


Degree Name

Master of Science



Major Professor

Carol P. Harden

Committee Members

John Rehder, Bob Muenchen


In this study, Geographic Information System (GIS) techniques are combined with statistical analyses to create two debris slide susceptibility maps of the Mount Leconte-Newfound Gap area in the Great Smoky Mountains National Park (GRSMNP). This area has experienced numerous debris slide events in the past half century. Although the area has been the subject of several mass movement studies, this is the first known application of debris slide susceptibility mapping in the GRSMNP.

The factors that influence the potential for slope failure are extremely variable, and the interrelationships between these factors are complex. Six topographic variables (slope angle, slope aspect, slope form (plan and profile), geology, distance to ridge crest, and precipitation) were examined to determine their influence on slope stability. Results indicate that slope angles in the 35-40 degree range are the most susceptible to failure. Among slope aspects, south facing slopes are most failure prone. Slopes that are concave in cross section are more susceptible than other slope forms. The rock type with the highest degree of susceptibility is the Anakeesta Formation. Locations that are slightly below ridge crest have the highest incidences of failure. Lastly, susceptibility tends to increase with the amount of precipitation received.

The two statistical techniques used to produce the debris slide susceptibility maps were failure rate analysis and logistic regression. I found that logistic regression is a superior method because scalar values are used rather than categorical values so that a greater amount of information is retained. This type of slope failure analysis over a broad area provides important information to planners and demonstrates the utility of GIS in debris slide susceptibility mapping.

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Geography Commons