Regional-scale landslide susceptibility mapping using the weights of evidence method: an example applied to linear infrastructure

Abstract

Large landslides are common in the gently sloping clay plains of the Saint Lawrence Lowlands of eastern Canada. These tend to occur along rivers carved into the marine soils deposited in the former Champlain Sea, which occupied the area roughly 10 000 years ago. This paper presents a landslide susceptibility model, developed at the regional scale using a bivariate statistical method: the weights of evidence method. The analysis considers the association of existing large landslides in a portion of the study area with key terrain features, such as ground elevation, flow accumulation in adjacent streams, soil type, soil thickness, and land use. The resulting model identifies three different levels of susceptibility: low, low to moderate, and moderate to high. These descriptors are related statistically to the probability of encountering existing large landslides within 500 m, 1 or 2 km, respectively. The model is tested along primary railway corridors and isolates 8% of the total length for further consideration of landslide hazard. Reconnaissance level air photo survey results further reduce the length of corridor with elevated susceptibility to 2% of the total length, thus focusing the application of additional resources to a very small proportion of the total inventory.

Estimation of the susceptibility of a road network to shallow landslides with the integration of the sediment connectivity

“…Mean accuracy of ical, hydrological and geological parameters taken into account for these analyses in different contexts by other authors (Budetta, 2004;Jaiswal et al, 2010aJaiswal et al, , b, 2011Quinn et al, 2010;Michoud et al, 2012;Bil et al, 2014Bil et al, , 2017Penna et al, 2014;Ramesh and Anbazhagan, 2015;Pellicani et al, 2017). The reliability of the model is quite fair, as testified by its AUC value (0.73) and by its high value of FP and TN indexes (22.3 and 45.8 %,respectively).…”

“…Different authors (Budetta, 2004;Jaiswal et al, 2010aJaiswal et al, , b, 2011Quinn et al, 2010;Michoud et al, 2012;Bil et al, 2014Bil et al, , 2017Ramesh and Anbazhagan, 2015;Pellicani et al, 2017;Postance et al, 2017) had already used some of the previously described predictors in different data-driven model aiming to assess roads susceptible to being hit by shallow landslides. Until now, sediment connectivity has not been considered yet.…”

“…In contrast, the triggering mechanism and landslide runout of the second landslide type can be related to the geological, geomorphological and hydrological predisposing factors of the natural or engineered slopes upstream to the roads. Furthermore, these events are the most widespread in terms of affected routes, in many cases including the involvement of extended sectors of hilly and mountainous road networks (Quinn et al, 2010;Bil et al, 2014).…”

“…In recent years, several data-driven methodologies were built to identify the susceptible sectors of a road network to landslides (Budetta, 2004;Hearn et al, 2008;Jaiswal et al, 2010aJaiswal et al, , b, 2011Quinn et al, 2010;Michoud et al, 2012;Tarolli et al, 2013;Bil et al, 2014Bil et al, , 2017Penna et al, 2014;Ramesh and Anbazhagan, 2015;Tarolli and Sofia, 2016;Winter et al, 2016;Donnini et al, 2017;Pellicani et al, 2017;Postance et al, 2017;Martinovic et al, 2018). These methods are based on quantitative statistical relationships between predisposing factors and a response variable.…”

Application of a complex assessment of landslide hazards in mountain regions

“…Static model was constructed using information theory assumption and the use of the method of weighting coeffi cient assessment (Quinn, Hutchinson, Diederichs & Rowe, 2010). The method implies determination of the degree of signifi cance (impact, weight) of each of the factors considered in formation of landslides (Carrara, 1 -sea pebble stones and Holocene sandstone; 2 -blocky limestone; landslide deposits, upper pleistocene; biased masses of 3 -sandstones and argillites of Middle Jurassic and Tauric suite; 4 -of limestone of Upper Jurassic; 5 -dealluvial middle and upper pleistocene loamy and rubble formations; 6 -banked -talus formations; 7 -limestones of Upper Jurassic; 8 -sandstones, argillites, siltstones of Upper Jurassic; 9 -argillites and sandstones of Tauric suite; 10 -recess of subsidence.…”