Landform classification: a high-performing mapping unit partitioning tool for landslide susceptibility assessment—a test in the Imera River basin (northern Sicily, Italy)

Landslides ◽  
2022 ◽  
Author(s):  
Chiara Martinello ◽  
Chiara Cappadonia ◽  
Christian Conoscenti ◽  
Edoardo Rotigliano
Keyword(s):  
River Basin ◽  
Landslide Susceptibility ◽  
Susceptibility Assessment ◽  
Mapping Unit ◽  
High Performing ◽  
Landslide Susceptibility Assessment ◽  
Landform Classification

scholarly journals Forward logistic regression for earth-flow landslide susceptibility assessment in the Platani river basin (southern Sicily, Italy)

Landslides ◽  
2013 ◽  
Vol 11 (4) ◽  
pp. 639-653 ◽  
Author(s):  
Dario Costanzo ◽  
José Chacón ◽  
Christian Conoscenti ◽  
Clemente Irigaray ◽  
Edoardo Rotigliano
Keyword(s):  
Logistic Regression ◽  
River Basin ◽  
Landslide Susceptibility ◽  
Susceptibility Assessment ◽  
Landslide Susceptibility Assessment ◽  
Earth Flow ◽  
Forward Logistic Regression

scholarly journals Comparing Forward Conditional Analysis and Forward Logistic Regression Methods in a Landslide Susceptibility Assessment: A Case Study in Sicily

Hydrology ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 37
Author(s):  
Dario Costanzo ◽  
Clemente Irigaray
Keyword(s):  
Logistic Regression ◽  
Landslide Susceptibility ◽  
Stochastic Approach ◽  
Conditional Analysis ◽  
Susceptibility Assessment ◽  
Landslide Susceptibility Assessment ◽  
Landform Classification ◽  
Kinematic Evolution ◽  
Forward Logistic Regression ◽  
Existing Data

Forward logistic regression and conditional analysis have been compared to assess landslide susceptibility across the whole territory of the Sicilian region (about 25,000 km2) using previously existing data and a nested tiered approach. These approaches were aimed at singling out a statistical correlation between the spatial distribution of landslides that have affected the Sicilian region in the past, and a set of controlling factors: outcropping lithology, rainfall, landform classification, soil use, and steepness. The landslide inventory used the proposal of building the models like the official one obtained in the PAI (hydro geologic asset plan) project, amounting to more than 33,000 events. The 11 types featured in PAI were grouped into 4 macro-typologies, depending on the inherent conditions believed to generate various kinds of failures and their kinematic evolution. The study has confirmed that it is possible to carry out a regional landslide susceptibility assessment based solely on existing data (i.e., factor maps and the landslide archive), saving a considerable amount of time and money. For scarp landslides, where the selected factors (steepness, landform classification, and lithology) are more discriminate, models show excellent performance: areas under receiver operating characteristic (ROC) (AUCs) average > 0.9, while hillslope landslide results are highly satisfactory (average AUCs of about 0.8). The stochastic approach makes it possible to classify the Sicilian territory depending on its propensity to landslides in order to identify those municipalities which are most susceptible at this level of study, and are potentially worthy of more specific studies, as required by European-level protocols.

Discriminant analysis as an efficient method for landslide susceptibility assessment in cities with the scarcity of predisposition data

2021 ◽  
Author(s):  
Cahio Guimarães Seabra Eiras ◽  
Juliana Ribeiro Gonçalves de Souza ◽  
Renata Delicio Andrade de Freitas ◽  
César Falcão Barella ◽  
Tiago Martins Pereira
Keyword(s):  
Discriminant Analysis ◽  
Efficient Method ◽  
Landslide Susceptibility ◽  
Susceptibility Assessment ◽  
Landslide Susceptibility Assessment

scholarly journals Landslide Susceptibility Assessment of Mauritius Island (Indian Ocean)

Geosciences ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 493 ◽  
Author(s):  
Vincenzo Marsala ◽  
Alberto Galli ◽  
Giorgio Paglia ◽  
Enrico Miccadei
Keyword(s):  
Indian Ocean ◽  
Landslide Susceptibility ◽  
Integrated Approach ◽  
Geographical Information ◽  
Susceptibility Assessment ◽  
Gis Technology ◽  
Mountain Areas ◽  
Landslide Susceptibility Assessment ◽  
Hydrological Hazards ◽  
Mauritius Island

This work is focused on the landslide susceptibility assessment, applied to Mauritius Island. The study area is a volcanic island located in the western part of the Indian Ocean and it is characterized by a plateau-like morphology interrupted by three rugged mountain areas. The island is severely affected by geo-hydrological hazards, generally triggered by tropical storms and cyclones. The landslide susceptibility analysis was performed through an integrated approach based on morphometric analysis and preliminary Geographical Information System (GIS)-based techniques, supported by photogeological analysis and geomorphological field mapping. The analysis was completed following a mixed heuristic and statistical approach, integrated using GIS technology. This approach led to the identification of eight landslide controlling factors. Hence, each factor was evaluated by assigning appropriate expert-based weights and analyzed for the construction of thematic maps. Finally, all the collected data were mapped through a cartographic overlay process in order to realize a new zonation of landslide susceptibility. The resulting map was grouped into four landslide susceptibility classes: low, medium, high, and very high. This work provides a scientific basis that could be effectively applied in other tropical areas showing similar climatic and geomorphological features, in order to develop sustainable territorial planning, emergency management, and loss-reduction measures.

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