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08.05.2018 | Original Paper | Ausgabe 4/2019

Bulletin of Engineering Geology and the Environment 4/2019

Spatial prediction of landslide-susceptible zones in El-Qaá area, Egypt, using an integrated approach based on GIS statistical analysis

Zeitschrift:
Bulletin of Engineering Geology and the Environment > Ausgabe 4/2019
Autoren:
Sara M. Abuzied, Hamed A. Alrefaee

Abstract

The spatial prediction of landslide susceptibility locations is a crucial task to support risk management and development plans in mountainous areas, such as El-Qaá area. The study aims to delineate landslide-susceptible zones that can cause enormous damage to property, infrastructure, and loss of life. An innovative integrated approach using remote sensing, geographic information systems, and geophysical techniques was used in the current work to evaluate landslide susceptibility locations. Magnetic data were supported by information derived from geologic, geomorphologic, topographic, and seismic data to reveal the landslides-prone zones. Several factors contributing to landslide susceptibility in El-Qaá area were determined, such as distance to faults, lithology, stream power index, slope, density of earthquake events, distance to epicenters, tilt derivative of magnetic data, distance to drainages, aspect, and topographic wetness index. A unique landslide susceptibility model (LSM) was developed in this study by integration all the spatial data that represent the contributing factors. The bivariate statistical index method was constructed to assign logic ranks and weights for the causative factors and their classes representing their realistic relations with landslide susceptibility in El-Qaá area. The landslide susceptibility map classifies El-Qaá area into five relative susceptibility zones: very high, high, moderate, low, and very low. The very high- and high-susceptibility zones are distributed in the eastern side of El-Qaá area where structurally controlled channels, steep topography to downhill lands, and Precambrian basement rocks are located. The resulting susceptibility map was tested and validated using the landslide locations that were delineated from field survey and satellite images at high resolution. The integrated methodology shows a more realistic landslide susceptibility map and adds a powerful tool to design a fruitful management plan in mountainous areas.

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