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Erschienen in:
Landslides: An Overview Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

6. Probabilistic Approaches and Landslide Susceptibility

verfasst von : Sujit Mandal, Subrata Mondal

Erschienen in: Geoinformatics and Modelling of Landslide Susceptibility and Risk

Verlag: Springer International Publishing

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Abstract

The present study is associated with the implication of weight of evidence model and certainty factor model to prepare landslide susceptibility maps of the Balason river basin of Darjeeling Himalaya using data layers of elevation, slope, aspect, curvature, geology, geomorphology, soil, distance to lineament, lineament density, drainage density, distance to drainage, stream power index (SPI), topographic wetness index (TWI), land use and land cover (LULC) and NDVU in ARC GIS 10.1. The developed landslide susceptibility map was classified in five i.e. very low, low, moderate, high and very high landslide susceptibility. The prepared landslide susceptibility maps were also validated using ROC curve which stated that certainty factor mode is best suited for developing landslide susceptibility zonation map of the Balason river basin of Darjeeling Himalaya.

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Vorheriges Kapitel Prediction of Landslide Susceptibility Using Bivariate Models
Nächstes Kapitel Machine Learning Models and Spatial Distribution of Landslide Susceptibility
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Metadaten
Titel
Probabilistic Approaches and Landslide Susceptibility
verfasst von
Sujit Mandal
Subrata Mondal
Copyright-Jahr
2019
Buch
Geoinformatics and Modelling of Landslide Susceptibility and Risk

Print ISBN: 978-3-030-10494-8

Electronic ISBN: 978-3-030-10495-5

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-10495-5_6