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Kawabata, Daisaku, Bandibas, Joel (2009) Landslide susceptibility mapping using geological data, a DEM from ASTER images and an Artificial Neural Network (ANN) Geomorphology, 113 (1) 97-109 doi:10.1016/j.geomorph.2009.06.006

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Reference TypeJournal (article/letter/editorial)
TitleLandslide susceptibility mapping using geological data, a DEM from ASTER images and an Artificial Neural Network (ANN)
JournalGeomorphology
AuthorsKawabata, DaisakuAuthor
Bandibas, JoelAuthor
Year2009 (December)Volume113
Issue1
PublisherElsevier BV
DOIdoi:10.1016/j.geomorph.2009.06.006Search in ResearchGate
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Mindat Ref. ID944167Long-form Identifiermindat:1:5:944167:9
GUID0
Full ReferenceKawabata, Daisaku, Bandibas, Joel (2009) Landslide susceptibility mapping using geological data, a DEM from ASTER images and an Artificial Neural Network (ANN) Geomorphology, 113 (1) 97-109 doi:10.1016/j.geomorph.2009.06.006
Plain TextKawabata, Daisaku, Bandibas, Joel (2009) Landslide susceptibility mapping using geological data, a DEM from ASTER images and an Artificial Neural Network (ANN) Geomorphology, 113 (1) 97-109 doi:10.1016/j.geomorph.2009.06.006
In(2009, December) Geomorphology Vol. 113 (1) Elsevier BV

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Pavel, Mihai, Fannin, R. Jonathan, Nelson, John D. (2008) Replication of a terrain stability mapping using an Artificial Neural Network. Geomorphology, 97 (3) 356-373 doi:10.1016/j.geomorph.2007.08.012
Choi, Jaewon, Oh, Hyun-Joo, Lee, Hong-Jin, Lee, Changwook, Lee, Saro (2012) Combining landslide susceptibility maps obtained from frequency ratio, logistic regression, and artificial neural network models using ASTER images and GIS. Engineering Geology, 124. 12-23 doi:10.1016/j.enggeo.2011.09.011
Ermini, Leonardo, Catani, Filippo, Casagli, Nicola (2005) Artificial Neural Networks applied to landslide susceptibility assessment. Geomorphology, 66 (1) 327-343 doi:10.1016/j.geomorph.2004.09.025
Aditian, Aril, Kubota, Tetsuya, Shinohara, Yoshinori (2018) Comparison of GIS-based landslide susceptibility models using frequency ratio, logistic regression, and artificial neural network in a tertiary region of Ambon, Indonesia. Geomorphology, 318. 101-111 doi:10.1016/j.geomorph.2018.06.006
Gokceoglu, C. (2012) Discussion on “Combining landslide susceptibility maps obtained from frequency ratio, logistic regression, and artificial neural network models using ASTER images and GIS” by Choi et al. (2012), Engineering Geology, 124, 12–23. Engineering Geology, 129. 104-105 doi:10.1016/j.enggeo.2012.01.008
Lee, S. (2007) Landslide susceptibility mapping using an artificial neural network in the Gangneung area, Korea. International Journal of Remote Sensing, 28 (21). doi:10.1080/01431160701264227
Melchiorre, C., Matteucci, M., Azzoni, A., Zanchi, A. (2008) Artificial neural networks and cluster analysis in landslide susceptibility zonation. Geomorphology, 94 (3) 379-400 doi:10.1016/j.geomorph.2006.10.035
Booth, Adam M., Roering, Josh J., Perron, J. Taylor (2009) Automated landslide mapping using spectral analysis and high-resolution topographic data: Puget Sound lowlands, Washington, and Portland Hills, Oregon. Geomorphology, 109 (3) 132-147 doi:10.1016/j.geomorph.2009.02.027
Yilmaz, Işık (2009) Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat—Turkey) Computers & Geosciences, 35 (6) 1125-1138 doi:10.1016/j.cageo.2008.08.007
Crozier, M.J. (2017) A proposed cell model for multiple-occurrence regional landslide events: Implications for landslide susceptibility mapping. Geomorphology, 295. 480-488 doi:10.1016/j.geomorph.2017.07.032
Saito, Hitoshi, Nakayama, Daichi, Matsuyama, Hiroshi (2009) Comparison of landslide susceptibility based on a decision-tree model and actual landslide occurrence: The Akaishi Mountains, Japan. Geomorphology, 109 (3) 108-121 doi:10.1016/j.geomorph.2009.02.026
 
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