LANDSLIDE SUSCEPTIBILITY EVALUATION OF SUMMIT COUNTY, NORTHEAST OHIO, USING GIS TECHNIQUES

Landslide susceptibility of Summit County, northeastern Ohio was assessed using numerical susceptibility models in Geographic Information Systems (GIS). The study was based on statistical relationships between landslides and the factors that influence their occurrence. Aerial photographs, field checks, and exiting literature were used to identify landslide locations in Summit County and a landslide inventory map was prepared at a scale of 1:24,000. The occurrence of landslides in a given area depends upon the complex interaction of different factors like slope angle, slope aspect, soil type, erodible soil, engineering properties of soil, depth to groundwater, landcover pattern, proximity to a stream, flood-prone area, etc. These factors were imported as raster data layers in ArcGIS and a digital database was prepared for the landslide susceptibility analysis. The above-listed factors were classified and coded in a numerical scale depending upon landslide frequency distribution. In order to investigate the role of each factor in controlling the spatial distribution of landslides, susceptibility priority number, landslide susceptibility index, and logistic regression models were generated using the acquired digital dataset. Each model was evaluated for its suitability in reference to the landslide inventory map. The logistic regression model was found to be the best model for predicting the landslide susceptibility of the area. The results indicated that factors such as slope angle, proximity to stream, erodible soil, and flood-prone area were statistically significant in controlling the slope movement, whereas the other factors were not so important and thus excluded from the model computation. The logistic regression model was transferred in ArcGIS to produce a landslide susceptibility map of the county that categorized the susceptibility into four classes: low, moderate, high, and very high.