Multi-Resolution Landslide Susceptibility Analysis Using a DEM and Random Forest

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International Journal of Geosciences

ISSN Print: 2156-8359
ISSN Online: 2156-8367
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"Multi-Resolution Landslide Susceptibility Analysis Using a DEM and Random Forest"
written by Uttam Paudel, Takashi Oguchi, Yuichi Hayakawa,
published by International Journal of Geosciences, Vol.7 No.5, 2016

has been cited by the following article(s):

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[23]	Impact study for landslide contributing factors using a multi-criterion approach for landslide susceptibility Arabian Journal of Geosciences, 2021 DOI:10.1007/s12517-021-08264-z

[24]	Evaluation of different DEMs for gully erosion susceptibility mapping using in-situ field measurement and validation Ecological Informatics, 2021 DOI:10.1016/j.ecoinf.2021.101425

[25]	The (f)utility to account for pre-failure topography in data-driven landslide susceptibility modelling Geomorphology, 2020 DOI:10.1016/j.geomorph.2020.107041

[26]	Optimizing collapsed pipes mapping: Effects of DEM spatial resolution CATENA, 2020 DOI:10.1016/j.catena.2019.104344

[27]	The performance of landslide susceptibility models critically depends on the quality of digital elevation models Geomatics, Natural Hazards and Risk, 2020 DOI:10.1080/19475705.2020.1776403

[28]	Performance Evaluation of GIS-Based Artificial Intelligence Approaches for Landslide Susceptibility Modeling and Spatial Patterns Analysis ISPRS International Journal of Geo-Information, 2020 DOI:10.3390/ijgi9070443

[29]	Stability prediction of Himalayan residual soil slope using artificial neural network Natural Hazards, 2020 DOI:10.1007/s11069-020-04141-2

[30]	Investigating the Effect of Cross-Modeling in Landslide Susceptibility Mapping Applied Sciences, 2020 DOI:10.3390/app10186335

[31]	On the Importance of Train–Test Split Ratio of Datasets in Automatic Landslide Detection by Supervised Classification Remote Sensing, 2020 DOI:10.3390/rs12183054

[32]	Assessing landslide characteristics in a changing climate in northern Taiwan CATENA, 2019 DOI:10.1016/j.catena.2018.12.023

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[43]	Sensitivity analysis of automatic landslide mapping: numerical experiments towards the best solution Landslides, 2018 DOI:10.1007/s10346-018-0986-0

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[46]	Prioritization of landslide conditioning factors and its spatial modeling in Shangnan County, China using GIS-based data mining algorithms Bulletin of Engineering Geology and the Environment, 2017 DOI:10.1007/s10064-017-1004-9

[47]	Evaluating the susceptibility of landslide landforms in Japan using slope stability analysis: a case study of the 2016 Kumamoto earthquake Landslides, 2017 DOI:10.1007/s10346-017-0872-1

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	+86 18163351462(WhatsApp)
	1655362766

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