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STATISTICAL APPROACHES FOR LANDSLIDE SUSCEPTIBILITY ASSESSME IBD

SPRINGER
09 / 2018
9783319938967
Inglés

Sinopsis

Thisábookáfocuses on the spatial distribution of landslide hazards ofátheáDarjeeling 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,áa 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 inátheáDarjeeling 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 inátheDarjeeling Himalayas.Particular attention is given to the assessment of various geomorphic, geotectonic and geohydrologic attributes that help to understand the roleáofádifferent factors and corresponding classes in landslides, toáapplyádifferent models,áandáto monitor and predict landslides. The use of various statistical and physical models to estimate landslide susceptibility is also discussed. The causes, mechanismsáand 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.

PVP
146,93