economic assessment of larger landslide affected areas, as well as a synoptic appreciation of the context within which landslides occur, especially in terms of land cover dynamics (Martha et al., 2010).
Our study aimed at classifying the landslide locations by object-based image analysis (OBIA) and fuzzy logic using Landsat ETMþ satellite image and some digital elevation model (DEM)derived thematic layers. OBIA, and to some extent GEOBIA (geographic object-based image analysis) (Blaschke, 2010), is a knowledge-driven method, whereby spectral, morphometric, and contextual diagnostic features of an object can be integrated based on expert knowledge (Barlow et al., 2003). It allows the user to apply locally different strategies for analyses. Incorporating both spectral information (tone, color) and spatial arrangements (size, shape, texture, pattern, and association with neighboring objects) comes closer to the way humans interpret information visually from aerial photos (Laliberte et al., 2004). In contrast to the traditional pixel-based classifications, the OBIA process is conducted on objects, which also contain shape, size, neighboring, and textural features in addition to spectral information (Blaschke et al., 2008). Thus, taking into consideration these advantages provided by OBIA, it was intended to classify landslide locations by OBIA, based on a data-driven and semiautomatic classification system, using different types of parameters and fuzzy logic.