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.
