Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale

CATENA ◽  
2021 ◽  
Vol 201 ◽  
pp. 105213
Author(s):  
Vicente Medina ◽  
Marcel Hürlimann ◽  
Zizheng Guo ◽  
Antonio Lloret ◽  
Jean Vaunat
Keyword(s):  
Landslide Susceptibility ◽  
Regional Scale ◽  
Susceptibility Assessment ◽  
Physically Based Model ◽  
Landslide Susceptibility Assessment ◽  
Physically Based

Regional scale rainfall- and earthquake-triggered landslide susceptibility assessment in Wudu County, China

2013 ◽  
Vol 10 (5) ◽  
pp. 743-753 ◽  
Author(s):  
Shi-biao Bai ◽  
Chen Cheng ◽  
Jian Wang ◽  
Benni Thiebes ◽  
Zhi-gang Zhang
Keyword(s):  
Landslide Susceptibility ◽  
Regional Scale ◽  
Susceptibility Assessment ◽  
Landslide Susceptibility Assessment

GIS techniques for regional-scale landslide susceptibility assessment: the Sicily (Italy) case study

2013 ◽  
Vol 27 (7) ◽  
pp. 1433-1452 ◽  
Author(s):  
G. Manzo ◽  
V. Tofani ◽  
S. Segoni ◽  
A. Battistini ◽  
F. Catani
Keyword(s):  
Landslide Susceptibility ◽  
Regional Scale ◽  
Susceptibility Assessment ◽  
Landslide Susceptibility Assessment ◽  
Gis Techniques

scholarly journals Exploring the Impact of Analysis Scale on Landslide Susceptibility Modeling: Empirical Assessment in Northern Peloponnese, Greece

Geosciences ◽  
2018 ◽  
Vol 8 (7) ◽  
pp. 261 ◽  
Author(s):  
Christos Polykretis ◽  
Antigoni Faka ◽  
Christos Chalkias
Keyword(s):  
Landslide Susceptibility ◽  
Regional Scale ◽  
Quantitative Model ◽  
Scale Analysis ◽  
Susceptibility Assessment ◽  
Operating Characteristics ◽  
Prediction Ability ◽  
Landslide Susceptibility Assessment ◽  
Analysis Scale ◽  
The Impact

The main purpose of this study is to explore the impact of analysis scale on the performance of a quantitative model for landslide susceptibility assessment through empirical analyses in the northern Peloponnese, Greece. A multivariate statistical model like logistic regression (LR) was applied at two different scales (a regional and a more detailed scale). Due to this scale difference, the implementation of the model was based on two landslide inventories representing in a different way the landslide occurrence (as point and polygon features), and two datasets of similar geo-environmental factors characterized by a different size of grid cells (90 m and 20 m). Model performance was tested by a standard validation method like receiver operating characteristics (ROC) analysis. The validation results in terms of accuracy (about 76%) and prediction ability (Area under the Curve (AUC) = 0.84) of the model revealed that the more detailed scale analysis is more appropriate for landslide susceptibility assessment and mapping in the catchment under investigation than the regional scale analysis.

scholarly journals Integrating Expert Knowledge with Statistical Analysis for Landslide Susceptibility Assessment at Regional Scale

Geosciences ◽  
2016 ◽  
Vol 6 (1) ◽  
pp. 14 ◽  
Author(s):  
Christos Chalkias ◽  
Christos Polykretis ◽  
Maria Ferentinou ◽  
Efthimios Karymbalis
Keyword(s):  
Statistical Analysis ◽  
Landslide Susceptibility ◽  
Expert Knowledge ◽  
Regional Scale ◽  
Susceptibility Assessment ◽  
Landslide Susceptibility Assessment

Application of GIS Techniques for Landslide Susceptibility Assessment at Regional Scale

2013 ◽  
pp. 459-465 ◽  
Author(s):  
Goffredo Manzo ◽  
Veronica Tofani ◽  
Samuele Segoni ◽  
Alessandro Battistini ◽  
Filippo Catani
Keyword(s):  
Landslide Susceptibility ◽  
Regional Scale ◽  
Susceptibility Assessment ◽  
Landslide Susceptibility Assessment ◽  
Gis Techniques ◽  
Application Of Gis

Regional-scale landslide susceptibility assessment for the hilly state of Uttarakhand, NW Himalaya, India

2021 ◽  
Vol 131 (1) ◽  
Author(s):  
Vikram Gupta ◽  
Sandeep Kumar ◽  
Ramandeep Kaur ◽  
Ruchika S Tandon
Keyword(s):  
Landslide Susceptibility ◽  
Regional Scale ◽  
Susceptibility Assessment ◽  
Nw Himalaya ◽  
Landslide Susceptibility Assessment
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