Validation of a Shallow Landslide Susceptibility Analysis Through a Real Case Study: An Example of Application in Rome (Italy)

2020 ◽  
pp. 265-280
Author(s):  
Geraud Poueme Djueyep ◽  
Carlo Esposito ◽  
Luca Schilirò ◽  
Francesca Bozzano
Keyword(s):  
Landslide Susceptibility ◽  
Shallow Landslide ◽  
Real Case ◽  
Susceptibility Analysis

scholarly journals Evaluating performances of simplified physically based models for landslide susceptibility

2015 ◽  
Vol 12 (12) ◽  
pp. 13217-13256 ◽  
Author(s):  
G. Formetta ◽  
G. Capparelli ◽  
P. Versace
Keyword(s):  
Landslide Susceptibility ◽  
Goodness Of Fit ◽  
Shallow Landslides ◽  
Model Parameters ◽  
Test Case ◽  
Susceptibility Analysis ◽  
Physically Based ◽  
Private And Public ◽  
Physically Based Models

Abstract. Rainfall induced shallow landslides cause loss of life and significant damages involving private and public properties, transportation system, etc. Prediction of shallow landslides susceptible locations is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, and statistics. Usually to accomplish this task two main approaches are used: statistical or physically based model. Reliable models' applications involve: automatic parameters calibration, objective quantification of the quality of susceptibility maps, model sensitivity analysis. This paper presents a methodology to systemically and objectively calibrate, verify and compare different models and different models performances indicators in order to individuate and eventually select the models whose behaviors are more reliable for a certain case study. The procedure was implemented in package of models for landslide susceptibility analysis and integrated in the NewAge-JGrass hydrological model. The package includes three simplified physically based models for landslides susceptibility analysis (M1, M2, and M3) and a component for models verifications. It computes eight goodness of fit indices by comparing pixel-by-pixel model results and measurements data. Moreover, the package integration in NewAge-JGrass allows the use of other components such as geographic information system tools to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. The system was applied for a case study in Calabria (Italy) along the Salerno-Reggio Calabria highway, between Cosenza and Altilia municipality. The analysis provided that among all the optimized indices and all the three models, the optimization of the index distance to perfect classification in the receiver operating characteristic plane (D2PC) coupled with model M3 is the best modeling solution for our test case.

scholarly journals Combined rock slope stability and shallow landslide susceptibility assessment of the Jasmund cliff area (Rügen Island, Germany)

2009 ◽  
Vol 9 (3) ◽  
pp. 687-698 ◽  
Author(s):  
A. Günther ◽  
C. Thiel
Keyword(s):  
Slope Stability ◽  
Landslide Susceptibility ◽  
Slope Failure ◽  
Rock Slope ◽  
Shallow Landslide ◽  
Material Strength ◽  
Spatial Integration ◽  
Inventory Data ◽  
Susceptibility Analysis ◽  
Susceptibility Model

Abstract. In this contribution we evaluated both the structurally-controlled failure susceptibility of the fractured Cretaceous chalk rocks and the topographically-controlled shallow landslide susceptibility of the overlying glacial sediments for the Jasmund cliff area on Rügen Island, Germany. We employed a combined methodology involving spatially distributed kinematical rock slope failure testing with tectonic fabric data, and both physically- and inventory-based shallow landslide susceptibility analysis. The rock slope failure susceptibility model identifies areas of recent cliff collapses, confirming its value in predicting the locations of future failures. The model reveals that toppling is the most important failure type in the Cretaceous chalk rocks of the area. The shallow landslide susceptibility analysis involves a physically-based slope stability evaluation which utilizes material strength and hydraulic conductivity data, and a bivariate landslide susceptibility analysis exploiting landslide inventory data and thematic information on ground conditioning factors. Both models show reasonable success rates when evaluated with the available inventory data, and an attempt was made to combine the individual models to prepare a map displaying both terrain instability and landslide susceptibility. This combination highlights unstable cliff portions lacking discrete landslide areas as well as cliff sections highly affected by past landslide events. Through a spatial integration of the rock slope failure susceptibility model with the combined shallow landslide assessment we produced a comprehensive landslide susceptibility map for the Jasmund cliff area.

Accuracy assessment of InSAR derived input maps for landslide susceptibility analysis: a case study from the Swiss Alps

Landslides ◽  
2005 ◽  
Vol 2 (3) ◽  
pp. 221-228 ◽  
Author(s):  
Lalan P. Singh ◽  
C. J. van Westen ◽  
P. K. Champati Ray ◽  
P. Pasquali
Keyword(s):  
Landslide Susceptibility ◽  
Accuracy Assessment ◽  
Swiss Alps ◽  
Susceptibility Analysis

Assessing shallow landslide susceptibility by using the Generalized Additive Model: a case study

2018 ◽  
Vol 46 ◽  
pp. 115-121
Author(s):  
Carlotta Bartelletti ◽  
Yuri Galanti ◽  
Michele Barsanti ◽  
Roberto Giannecchini ◽  
Giacomo D'Amato Avanzi ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Generalized Additive Model ◽  
Additive Model ◽  
Shallow Landslide
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