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Erschienen in:
2021 | OriginalPaper | Buchkapitel
Feature-Based Model for Landslide Prediction Using Remote Sensing and Digital Elevation Data
verfasst von : Litesh Bopche, Priti P. Rege
Erschienen in: Advances in Signal and Data Processing
Verlag: Springer Singapore
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Abstract
This study aims to generate landslide susceptible maps and landslide hazard zonation maps using the digital elevation model for the prediction of future landslides. The landslide zone is based on the qualitative and quantitative factors combined using the weighted sum of the different features and hydrological parameters. The main aim of the research is to discover the damaged areas with the help of detailed field observation of prior and post landslide events. Landslide hazard zonation is a map classified into six different zones ranging from very low hazard zone to scars hazard zone and to represents the prediction of future landslide occurrence under the area of the study. The result of this study shows that a very high and scars susceptible region depicts a higher chance of landslides.