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GIS-based landslide susceptibility evaluation using fuzzy-AHP multi-criteria decision-making techniques in the Abha Watershed, Saudi Arabia

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Abstract

Landslides are natural geological disasters causing massive destructions and loss of lives, as well as severe damage to natural resources, so it is essential to delineate the area that probably will be affected by landslides. Landslide susceptibility mapping (LSM) is making increasing implications for GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. It is considered to be an effective tool to understand natural disasters related to mass movements and carry out an appropriate risk assessment. This study is based on an integrated approach of GIS and statistical modelling including fuzzy analytical hierarchy process (FAHP), weighted linear combination and MCE models. In the modelling process, eleven causative factors include slope aspect, slope, rainfall, geology, geomorphology, distance from lineament, distance from drainage networks, distance from the road, land use/land cover, soil erodibility and vegetation proportion were identified for landslide susceptibility mapping. These factors were identified based on the (1) literature review, (2) the expert knowledge, (3) field observation, (4) geophysical investigation, and (5) multivariate techniques. Initially, analytical hierarchy process linked with the fuzzy set theory is used in pairwise comparisons of LSM criteria for ranking purposes. Thereafter, fuzzy membership functions were carried out to determine the criteria weights used in the development of a landslide susceptibility map. These selected thematic maps were integrated using a weighted linear combination method to create the final landslide susceptibility map. Finally, a validation of the results was carried out using a sensitivity analysis based on receiver operator curves and an overlay method using the landslide inventory map. The study results show that the weighted overlay analysis method using the FAHP and eigenvector method is a reliable technique to map landslide susceptibility areas. The landslide susceptibility areas were classified into five categories, viz. very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility, and very high susceptibility. The very high and high susceptibility zones account for 15.11% area coverage. The results are useful to get an impression of the sustainability of the watershed in terms of landsliding and therefore may help decision makers in future planning and mitigation of landslide impacts.

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Acknowledgements

The authors wish to acknowledge the financial support by Deanship of Scientific Research, King Khalid University, Saudi Arabia: Project Code: 411/2017-2018. NASA-USGS personnel at the land DAAC who provided the latest LANDSAT-8 satellite image which is also much appreciated. We are also thankful to the General Authority of Meteorology and Environmental, Saudi Arabia and Saudi Geological Survey for providing the Rainfall and geological data for the present study.

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  1. Department of Civil Engineering, College of Engineering, King Khalid University, Abha, Saudi Arabia

    Javed Mallick, Ram Karan Singh, Saiful Islam & Roohul Abad Khan

  2. Department of Industrial Engineering, College of Engineering, King Khalid University, Abha, Saudi Arabia

    Mohammed A. AlAwadh & Mohamed Noor Qureshi

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  1. Javed Mallick
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Correspondence to Javed Mallick.

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Mallick, J., Singh, R.K., AlAwadh, M.A. et al. GIS-based landslide susceptibility evaluation using fuzzy-AHP multi-criteria decision-making techniques in the Abha Watershed, Saudi Arabia. Environ Earth Sci 77, 276 (2018). https://doi.org/10.1007/s12665-018-7451-1

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