Landslide susceptibility assessment in complex geological settings: sensitivity to geological information and insights on its parameterization

Samuele Segoni,Tania Luti,Filippo Catani,Giulio Pappafico

doi:10.1007/s10346-019-01340-2

Samuele Segoni, Tania Luti + Show 2 more

Open Access

https://doi.org/10.1007/s10346-019-01340-2

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Journal: Landslides	Publication Date: Jan 4, 2020
Citations: 86	License type: open-access

Affiliation: University of Florence, University of Urbino

Abstract

The literature about landslide susceptibility mapping is rich of works focusing on improving or comparing the algorithms used for the modeling, but to our knowledge, a sensitivity analysis on the use of geological information has never been performed, and a standard method to input geological maps into susceptibility assessments has never been established. This point is crucial, especially when working on wide and complex areas, in which a detailed geological map needs to be reclassified according to more general criteria. In a study area in Italy, we tested different configurations of a random forest–based landslide susceptibility model, accounting for geological information with the use of lithologic, chronologic, structural, paleogeographic, and genetic units. Different susceptibility maps were obtained, and a validation procedure based on AUC (area under receiver-operator characteristic curve) and OOBE (out of bag error) allowed us to get to some conclusions that could be of help for in future landslide susceptibility assessments. Different parameters can be derived from a detailed geological map by aggregating the mapped elements into broader units, and the results of the susceptibility assessment are very sensitive to these geology-derived parameters; thus, it is of paramount importance to understand properly the nature and the meaning of the information provided by geology-related maps before using them in susceptibility assessment. Regarding the model configurations making use of only one parameter, the best results were obtained using the genetic approach, while lithology, which is commonly used in the current literature, was ranked only second. However, in our case study, the best prediction was obtained when all the geological parameters were used together. Geological maps provide a very complex and multifaceted information; in wide and complex area, this information cannot be represented by a single parameter: more geology-based parameters can perform better than one, because each of them can account for specific features connected to landslide predisposition.

Highlights

Landslide susceptibility mapping (LSM ) is a very important activity in landslide hazard assessment, consisting in representing over appropriate spatial units the relative spatial probability of landslide occurrence (Brabb 1984)
It seems that these undoubtedly useful and interesting aspects overshadowed the importance of geology in LSM: to the best of our knowledge, a sensitivity analysis on the use of geological information has never been performed, nor a standard method to input geological maps into susceptibility assessments has ever been established
The examination of the AUC values obtained in our tests (Table 1) reveals that geology is very important in landslide susceptibility assessment: the model configuration that does not encompass any geological information is by far the one providing the worst prediction

Summary

Introduction

Landslide susceptibility mapping (LSM ) is a very important activity in landslide hazard assessment, consisting in representing over appropriate spatial units the relative spatial probability of landslide occurrence (Brabb 1984). Some works performed a sensitivity analysis to different model settings (resolution, scale, parameters, or methods to use parameters) that can be a reference for future works to design a correct and robust model configuration (Catani et al 2013; Greco and Sorriso-Valvo 2013). It seems that these undoubtedly useful and interesting aspects overshadowed the importance of geology in LSM: to the best of our knowledge, a sensitivity analysis on the use of geological information has never been performed, nor a standard method to input geological maps into susceptibility assessments has ever been established. Geological maps are not directly conceived to assist landslide modeling, and sometimes, they can be subdivided into a very large number of mapped elements, some of which are not directly related to slope stability (e.g., different units may be defined based on the appearance/disappearance of a fossil species, even if they have the same lithology and geomechanical characteristics)

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