Titlebook: Geoinformatics and Modelling of Landslide Susceptibility and Risk; An RS & GIS-based Mo Sujit Mandal,Subrata Mondal Book 2019 Springer Natu

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內(nèi)行

Deceit

Die elektrolytischen Metallniederschl?geto find out the role of drainage parameters and relief parameters in slope failure using drainage diversity (DD) and relief diversity (RD) models respectively. For that total 14 morphometric data layers were considered. The relationship of each data layers with landslide susceptibility was judge usi

Morose

JADED

Alveolar-Bone

Ausbreitung freier und geführter Wellen tools machine learning model i.e. support vector machine (SVM) and artificial neural network model (ANNM). Fifteen landslide causative factors i.e. slope, aspect, curvature, elevation, geology, geomorphology, soil, distance to drainage, drainage density, distance to lineaments, lineament density, l

不吉祥的女人

https://doi.org/10.1007/978-3-322-98866-9tering of various factors i.e. geomorphological factors, lithological factors group, hydrological factors, triggering factor, protective factor and anthropogenic factor. The geomorphological factors, lithological factors group, hydrological factors, triggering factor, protective factor and anthropog

Congeal

https://doi.org/10.1007/978-3-663-13546-3 region and suffered several types of large and small landslides. At the time of pre-independence landslides took place mostly in the areas where the setup of the physical environment was weak, less strong and more disturbed geological formations, rugged and high slope areas, low vegetation cover ar

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