Normalized Landslide Index Method for susceptibility map development in El Salvador

Ari Posner () and Konstantine Georgakakos

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2015, vol. 79, issue 3, 1825-1845

Abstract: El Salvador and Central America in general are highly prone to landsliding. In November 1998, Hurricane Mitch killed 240 people, displaced about 85,000 people, caused more than $600 million in economic losses, and damaged about 60 % of the nation’s roads (Rose et al. in Natural hazards in El Salvador. Geologic Society of America of special paper 375, Boulder, 2004 ). An understanding of susceptibility of locations to landsliding is critical for development and mitigation planning. This work presents the development of the Normalized Landslide Index Method which is a derivative of the bivariate statistical methods commonly used in landslide susceptibility assessment. The resultant map was amended through a tangential analysis, also commonly used in landslide susceptibility mapping, the Analytical Hierarchy Process (AHP), which reduces multi-criteria analysis to pair-wise comparisons. The assimilation of results from the AHP analysis into the statistically derived susceptibility map skewed the original results by emphasizing the extremes already found. It was determined that addition of AHP results did not increase the value of the derived susceptibility map. Finally, a physically based a priori approach to landslide susceptibility mapping, developed by El Salvador National Service of Territorial Studies, was compared to the statistically derived map developed herein. It was found that the a priori approach was not sufficiently discriminant to be useful for planners and regulators, as very large areas were designated high susceptibility that included areas with low slope angles. The development of the normalized landslide index is a significant improvement to the class of bivariate statistical strategies to assess regional landslide susceptibility. Copyright Springer Science+Business Media Dordrecht 2015

Keywords: Landslide susceptibility; Analytical Hierarchy Process; Landslide index method; Bivariate statistics; El Salvador (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s11069-015-1930-4

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