Comparative GIS-based automated landform classifications: Application of Jenness and Shary methods to the Jebel Chaambi area (west-central Tunisia)

Abstract

Two landform classifications (Jenness and Shary methods) using spatial statistics and image processing algorithms were performed for the first time in Tunisia. They were applied to the J. Chaambi area (West-central Tunisia). Attempting to highlight geo-morphometric properties of 30 m resolution Digital Elevation Models (DEM), the Jenness classification leads to define ten classes using the ‘Topographical Position Index’ as performed by the module in Arcgis 10.2. The Shary classification is based on a combination of five slope curvature signs producing twelve main landform categories. Plains characterize the main landform type in the first classification; however, convex and concave saddles correspond to the second. The window of perception, in both classification cases, has a major influence on the representation of results. Indeed, the scale effect on classification should be tested by applying both methods to the same area but at different scales.