Abstract. Landslides are the most recurrent natural hazards in the Metropolitan District of Quito (DMQ), affecting sometimes lives but extremely frequently and severely the traffic and associated infrastructure. The present research proposes the calculation of the landslide susceptibility cartographic model in the city of Quito and its main highway, the Simón Bolívar avenue, using the Fuzzy logic and multicriteria evaluation techniques in geographic information systems (GIS). Based on the Today and the past son key to the future principle, landslides have been located using aerial photographs and field work. Based on the characteristics of historical landslides, photointerpreted and previous studies, the causal factors have been variable such as topography, structural geology, lithology, precipitation, water network, vegetation cover, among others. Each factor has been processed, analyzed and standardized according to its relationship to the occurrence of landslides, by means of a sinusoidal linked function that assigns to each element a degree of correlation [0, 1] to the diffuse set. The landslide vulnerability map has been obtained from the combination of causal factors by map algebra, such as weighting techniques that include the hierarchical analysis process (HAP) and the weighted linear line (WLL), whose validation considered the locations of inventoried landslides. According to the susceptibility map, 5 % of the direct study area has critical, 19 % high, 58 % average and 18 % low sensitivity. The quality of the results has been validated according to their standard error and adjustment value, being 0.216 and 78.4 %, respectively.
Received: 27 Mar 2018 – Discussion started: 16 Jul 2018
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This research demonstrates impressively, what has been possible by counting with a variety of variables and data sets in order to model landslides in a mega-vulnerable city, in this case Quito in Ecuador. Furthermore, we also compared the previously existing map of landslides in the city based on the current municipality with our new map, which allows an improved, high-resolution view of the potential and most vulnerable sites and zones.
This research demonstrates impressively, what has been possible by counting with a variety of...
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