Analytic hierarchy process applied to landslide susceptibility mapping of the North Branch of Argentino Lake, Argentina

Abstract

In the present study, we achieved the susceptibility mapping to slope instability processes by the implementation of Analytic Hierarchy Process and Weighted Linear Combination methods, in the North Branch of Argentino Lake, Southern Patagonian Icefield. The strong retraction of the glaciers in the area has triggered paraglacial readjustments, producing instability processes that favor the generation of mass removal processes. The results obtained from optical satellite images show that the highest degrees of susceptibility (4 and 5) are located on the western slopes of the Upsala Channel, Bertacchi and Cono Tributary Glaciers, and the Moyano and Norte Valleys, respectively. These slopes coincide with the geographic location of previous events surveyed by the inventory of unstable areas of the zone. Low degrees of susceptibility are found on the downhill valleys, outcrops rock and glaciers. The Consistency Ratio was 0.069, indicating that being less than 0.1 the study is reliable. The study sheds light on the knowledge of slopes and valleys that are more susceptible to processes of instability in mountainous areas, which would make it possible to prevent possible hazards associated with these events.

Incorporating Landslide Spatial Information and Correlated Features among Conditioning Factors for Landslide Susceptibility Mapping

“…In order to evaluate the validity of the proposed model, six statistical measures were chosen, such as the area under the receiver operating characteristic curve (AUROC), Sensitivity, Specificity, Accuracy, Root mean squared error (RMSE), and Kappa index, as is shown in Equations ( 9)- (15). The AUROC value is a quantitative indicator of the ROC curve ranging from 0.5 to 1.…”

“…In recent years, the development of Geographic Information Systems (GIS), Global Position Systems (GPS), and Remote Sensing (RS) technologies have improved the convenience of landslide inventory production and storage. The integration of remote sensing and statistical techniques has introduced various quantitative models to deal with LSM, including Analytic Hierarchy Processes [14,15], Weights of Evidence [16], the Frequency Ratio [17], and the Statistical Index [18]. These models are interpretable and can be rapidly implemented for LSM but may not achieve satisfactory performances when dealing with a nonlinear problem [19].…”

Caracterización y reconstrucción del deslizamiento Agassiz mediante el uso de datos geoespaciales. Patagonia Austral, Argentina

“…Por otro lado, también el factor litológico condiciona e incide en la ocurrencia de deslizamientos en ambientes paraglaciales (Johnson et al, 2007;Barlow et al, 2009;Feuillet et al, 2014;Santos-González et al, 2018;Moragues et al, 2020). La litología preponderante en áreas con procesos erosivos y de inestabilidad de laderas son aquellas con facies litológicas predominantemente arenosas y con grava, calcáreas, arcillosas y pizarrosas (Santos-González et al, 2018).…”

“…7A -Tabla 1). Esto propició el descenso por gravedad del material acumulado sobre la ladera y condicionó la velocidad del deslizamiento (Moragues et al, 2020). El factor orientación de la ladera también pudo jugar un papel importante, ya que la ladera oeste tiene una orientación aproximada noreste con pendiente al este.…”

“…remociones en masa (Moragues et al, 2020). El impacto de los témpanos de hielo desprendido de los glaciares, tiene una importante influencia en la generación de los procesos de remoción en masa y un gran potencial para inducir la ocurrencia de tsunamis (e.g., Schneider et al, 2014;Lüthi y Vieli, 2016;Yavari-Ramshe y Ataie-Ashtiani, 2016).…”