Geomorphic Risk Reduction Using Geospatial Methods and Tools -

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Résumé :
Landslide Susceptibility Assessment Based on Machine Learning Techniques.- Measuring landslide susceptibility in Jakholi region of Garhwal Himalaya applying novel ensembles of statistical and machine learning algorithms.- Landslide Susceptibility Mapping using GIS-based Frequency Ratio, Shannon Entropy, Information Value and Weight-of-Evidence approaches in part of Kullu district, Himachal Pradesh, India.- An advanced hybrid machine learning technique for assessing the susceptibility to landslides in the Meenachil river basin of Kerala, India.- Novel ensemble of M5P and Deep learning neural network for predicting landslide susceptibility: A cross-validation approach.- Artificial neural network ensemble with General linear model for modeling the Landslide Susceptibility in Mirik region of West Bengal, India.- Modeling gully erosion susceptibility using advanced machine learning method in Pathro River Basin, India.- Quantitative Assessment of Interferometric Synthetic Aperture 2 Radar(INSAR) for Landslide Monitoring and Mitigation.- Assessment of Landslide Vulnerability using Statistical and Machine Learning Methods in Bageshwar District of Uttarakhand, India.- Assessing the shifting of the River Ganga along Malda District of West Bengal, India.- An ensemble of J48 Decision Tree with AdaBoost, and Bagging for flood susceptibility mapping in the Sundarban of West Bengal, India.- Assessment of mouza level flood resilience in lower part of Mayurakshi River basin, Eastern India.- Spatial flashflood modeling in Beas River Basin of Himachal Pradesh, India using GIS-based machine learning algorithms.- Geospatial study of river shifting and erosion deposition phenomenon along a selected stretch of River Damodar, West Bengal, India.- An Evaluation of Hydrological Modeling Using CN Method in Ungauged Barsa River Basin of Pasakha, Bhutan.- The Adoption of Random Forest (RF) and Support Vector Machine (SVM) with Cat Swarm Optimization (CSO) to Predict the Soil Liquefaction....

Sommaire:
This book explores the use of advanced geospatial techniques in geomorphic hazards modelling and risk reduction. It also compares the accuracy of traditional statistical methods and advanced machine learning methods and addresses the different ways to reduce the impact of geomorphic hazards.