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Geoinformatics and modelling of land...
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Mandal, Sujit.
Geoinformatics and modelling of landslide susceptibility and riskan RS & GIS-based model building approach in the Eastern Himalaya /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Geoinformatics and modelling of landslide susceptibility and riskby Sujit Mandal, Subrata Mondal.
Reminder of title:
an RS & GIS-based model building approach in the Eastern Himalaya /
Author:
Mandal, Sujit.
other author:
Mondal, Subrata.
Published:
Cham :Springer International Publishing :2019.
Description:
xiii, 223 p. :ill., color maps, digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Landslide hazard analysis.
Online resource:
https://doi.org/10.1007/978-3-030-10495-5
ISBN:
9783030104955$q(electronic bk.)
Geoinformatics and modelling of landslide susceptibility and riskan RS & GIS-based model building approach in the Eastern Himalaya /
Mandal, Sujit.
Geoinformatics and modelling of landslide susceptibility and risk
an RS & GIS-based model building approach in the Eastern Himalaya /[electronic resource] :by Sujit Mandal, Subrata Mondal. - Cham :Springer International Publishing :2019. - xiii, 223 p. :ill., color maps, digital ;24 cm. - Environmental science,1431-6250. - Environmental science..
Landslides: An Overview -- Geomorphic, Geo-tectonic and Hydrologic Attributes and Landslide Susceptibility -- Slope instability analysis: A Sub-Watershed Scale Study -- Geomorphic Diversity and Landslide Susceptibility: A Multi-Criteria Evaluation Approach -- Landslide Susceptibility Prediction and Assessment using Bivariate Models -- Multivariate Models and Prediction and Assessment of Landslide Susceptibility -- Application of Probabilistic Approach in Landslide Susceptibility Analysis -- Machine Learning Models in Landslides Susceptibility Assessment -- Factor and Factors' Cluster Analysis and Landslide Susceptibility Assessment -- Micro level Landslide Susceptibility and Risk Assessment -- Comparison between Susceptibility Models: A critical Review and Evaluation.
This book discusses various statistical models and their implications for developing landslide susceptibility and risk zonation maps. It also presents a range of statistical techniques, i.e. bivariate and multivariate statistical models and machine learning models, as well as multi-criteria evaluation, pseudo-quantitative and probabilistic approaches. As such, it provides methods and techniques for RS & GIS-based models in spatial distribution for all those engaged in the preparation and development of projects, research, training courses and postgraduate studies. Further, the book offers a valuable resource for students using RS & GIS techniques in their studies.
ISBN: 9783030104955$q(electronic bk.)
Standard No.: 10.1007/978-3-030-10495-5doiSubjects--Topical Terms:
274003
Landslide hazard analysis.
LC Class. No.: QE599.2 / .M363 2019
Dewey Class. No.: 551.307
Geoinformatics and modelling of landslide susceptibility and riskan RS & GIS-based model building approach in the Eastern Himalaya /
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an RS & GIS-based model building approach in the Eastern Himalaya /
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Landslides: An Overview -- Geomorphic, Geo-tectonic and Hydrologic Attributes and Landslide Susceptibility -- Slope instability analysis: A Sub-Watershed Scale Study -- Geomorphic Diversity and Landslide Susceptibility: A Multi-Criteria Evaluation Approach -- Landslide Susceptibility Prediction and Assessment using Bivariate Models -- Multivariate Models and Prediction and Assessment of Landslide Susceptibility -- Application of Probabilistic Approach in Landslide Susceptibility Analysis -- Machine Learning Models in Landslides Susceptibility Assessment -- Factor and Factors' Cluster Analysis and Landslide Susceptibility Assessment -- Micro level Landslide Susceptibility and Risk Assessment -- Comparison between Susceptibility Models: A critical Review and Evaluation.
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This book discusses various statistical models and their implications for developing landslide susceptibility and risk zonation maps. It also presents a range of statistical techniques, i.e. bivariate and multivariate statistical models and machine learning models, as well as multi-criteria evaluation, pseudo-quantitative and probabilistic approaches. As such, it provides methods and techniques for RS & GIS-based models in spatial distribution for all those engaged in the preparation and development of projects, research, training courses and postgraduate studies. Further, the book offers a valuable resource for students using RS & GIS techniques in their studies.
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Earth and Environmental Science (Springer-11646)
based on 0 review(s)
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EB QE599.2 .M271 2019 2019
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https://doi.org/10.1007/978-3-030-10495-5
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