Titlebook: Geomorphic Risk Reduction Using Geospatial Methods and Tools; Raju Sarkar,Sunil Saha,Rajib Shaw Book 2024 The Editor(s) (if applicable) an

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Measuring Landslide Susceptibility in Jakholi Region of Garhwal Himalaya Using Landsat Images and Ens. To begin, landslides were established and a landslide inventory map was prepared. The total locations considered for this study were divided into 70% for the training datasets and 30% for the validation datasets. Following that, a total of 15 landslide conditioning factors were chosen. Furthermor

Promotion

Landslide Susceptibility Mapping Using Satellite Images and GIS-Based Statistical Approaches in Partture, thereby requiring researchers to delve into more in-depth landslide-related studies with a focus on finding effective methods to better delineate landslide-prone areas as well as better understand the various underlying causative factors. The district of Kullu, situated in the Indian state of

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Plane Electromagnetic Wave Propagation,ation of policy and practices. Soil erosion through gully development is a natural geomorphic process that controlled by human activities and?highly effected environmental quality, ecosystem, natural resources, and agricultural activities; and it promotes hazards. So, gully erosion management is a k

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Time-Varying Boundary-Value Problems,are highly susceptible to landslide. In the present study ensemble of ANN, general linear model (GLM), and ensemble ANN-GLM machine learning methods were applied for producing the landslide susceptibility maps (LSMs) of the Mirik region. A total of 373 landslide locations and twelve landslide condit

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Metallic Waveguides and Resonant Cavities,ble NBT-RTF, Naive Bayes tree (NBT), and rotation forest (RTF). For landslide susceptibility modelling, 189 landslide sites and 12 landslide conditioning factors (LCFs) were gathered. Multi-collinearity analysis was done among the LCFs to determine the best LCFs to use. The metrics utilized to asses