LANDSLIDE SUSCEPTIBILITY MAPPING USING REMOTE SENSING AND GIS APPLICATION: A CASE STUDY IN QALA DIZA AND SURROUNDING AREA, KURDISTAN REGION, NE IRAQ

F. Al-Maamar, Ahmed; A. Al-Manmi, Diary; U. Al-Jaff, Azad; A. Othman, Arsalan

	LANDSLIDE SUSCEPTIBILITY MAPPING USING REMOTE SENSING AND GIS APPLICATION: A CASE STUDY IN QALA DIZA AND SURROUNDING AREA, KURDISTAN REGION, NE IRAQ
Iraqi Bulletin of Geology and Mining
Article 1, Volume 14, Issue 1, 2018, Pages 65-90
Authors
Ahmed F. Al-Maamar; Diary A. Al-Manmi; Azad U. Al-Jaff; Arsalan A. Othman
Abstract
During the last decades, expansion of settlements into areas prone to landslides in Iraq has increased the importance of accurate landslide inventory and susceptibility studies. The Landslide inventory map is the spatial distribution of the gravity-induced mass movements. Susceptibility mapping provides information about hazardous locations and thus helps to potentially prevent infrastructure damages due to mass wasting. This study aims to assess the localization and size distribution of potential landslides, in addition to implement selected parameters to predict landslide susceptibility using remote sensing techniques in mountainous environments. The study covers the Qala Diza area, Kurdistan Region (NE Iraq), within the Zagros Fold – Thrust Belt, which includes the High Folded Zone (HFZ), the Imbricate Zone (IZ), the Zagros Suture Zone (ZSZ) and the Shalair (Sanandaj – Sirjan) Terrain. The available reference inventory includes 353 landslides (representing a cumulated surface of 35.38 Km2) mapped from twelve Quick Bird scenes using manual delineation. The landslide types involve rock falls, translational slides, slumps and toppling which have occurred in different lithological units. At the beginning, cumulative landslide number-size distributions are analyzed using the inventory map. Then, twelve factors, mainly derived from a Digital Elevation Model (DEM) of Shuttle Radar Topography Mission (SRTM), as well as geological and environmental predicting factors were appraised. Logistic regression approaches are used to determine the landslide susceptibility (LS). The areas under the curve (AUC) of the prediction rate curve (PRC) for the landslide susceptibility shows that the accuracy of the map is about 85%. The results indicate that the Hypsometric Integral (HI), lithology and structure are the more significant factors in the detection of potential occurrence of landslides in the studied area.
Keywords
Landslide; susceptibility; inventory; DEM; Zagros Fold; geomorphic indices

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