Knowledge-Driven Statistical Approach for Landslide Susceptibility Assessment Using GIS and Fuzzy Logic (FL) Approach

2018 ◽  
pp. 163-180
Author(s):  
Sujit Mandal ◽  
Subrata Mondal
Keyword(s):  
Fuzzy Logic ◽  
Landslide Susceptibility ◽  
Statistical Approach ◽  
Susceptibility Assessment ◽  
Landslide Susceptibility Assessment

A New Statistical Approach for Landslide Susceptibility Assessment in the Urban Area of Napoli (Italy)

2017 ◽  
pp. 881-889 ◽  
Author(s):  
Francesco Carotenuto ◽  
Anna Claudia Angrisani ◽  
Akram Bakthiari ◽  
Maria Teresa Carratù ◽  
Diego Di Martire ◽  
...  
Keyword(s):  
Urban Area ◽  
Landslide Susceptibility ◽  
Statistical Approach ◽  
Susceptibility Assessment ◽  
Landslide Susceptibility Assessment

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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