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Books > Earth & environment > The environment > Environmental impact of natural disasters & phenomena
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Statistical Approaches for Landslide Susceptibility Assessment and Prediction (Hardcover, 1st ed. 2019)
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Statistical Approaches for Landslide Susceptibility Assessment and Prediction (Hardcover, 1st ed. 2019)
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This book focuses on the spatial distribution of landslide hazards
of the Darjeeling Himalayas. Knowledge driven methods and
statistical techniques such as frequency ratio model (FRM),
information value model (IVM), logistic regression model (LRM),
index overlay model (IOM), certainty factor model (CFM), analytical
hierarchy process (AHP), artificial neural network model (ANN), and
fuzzy logic have been adopted to identify landslide susceptibility.
In addition, a comparison between various statistical models were
made using success rate cure (SRC) and it was found that artificial
neural network model (ANN), certainty factor model (CFM) and
frequency ratio based fuzzy logic approach are the most reliable
statistical techniques in the assessment and prediction of
landslide susceptibility in the Darjeeling Himalayas. The study
identified very high, high, moderate, low and very low landslide
susceptibility locations to take site-specific management options
as well as to ensure developmental activities in theDarjeeling
Himalayas. Particular attention is given to the assessment of
various geomorphic, geotectonic and geohydrologic attributes that
help to understand the role of different factors and corresponding
classes in landslides, to apply different models, and to monitor
and predict landslides. The use of various statistical and physical
models to estimate landslide susceptibility is also discussed. The
causes, mechanisms and types of landslides and their destructive
character are elaborated in the book. Researchers interested in
applying statistical tools for hazard zonation purposes will find
the book appealing.
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