Landslide identification and classification by object-based image analysis and fuzzy logic: An example from the Azdavay region (Kastamonu, Turkey)

Publication year: 2011
Source: Computers & Geosciences, In Press, Accepted Manuscript, Available online 13 June 2011

Beliz, Aksoy , Murat, Ercanoglu

This study presents a data-driven and semiautomatic classification system carried out by object-based image analysis and fuzzy logic in a selected landslide-prone area in the Western Black Sea region of Turkey. In the first stage, a multiresolution segmentation process was performed using Landsat ETM+ satellite images of the study area. The model was established on 5235 image objects obtained by the segmentation process. A total of 70 landslide locations and 10 input parameters including normalized difference vegetation index, slope angle, curvature, brightness, mean band blue, asymmetry, shape index, length/width ratio, gray level co-occurrence matrix, and mean difference to infrared band…

 Highlights: Landslide identification and classification were carried out by OBIA and fuzzy logic. “Fuzzy and” operator showed better performance than the other fuzzy operators. This approach provides rapid assessment in landslide identification studies.