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Feizizadeh, Bakhtiar, Roodposhti, Majid Shadman, Blaschke, Thomas, Aryal, Jagannath (2017) Comparing GIS-based support vector machine kernel functions for landslide susceptibility mapping. Arabian Journal of Geosciences, 10 (5) doi:10.1007/s12517-017-2918-z

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Reference TypeJournal (article/letter/editorial)
TitleComparing GIS-based support vector machine kernel functions for landslide susceptibility mapping
JournalArabian Journal of Geosciences
AuthorsFeizizadeh, BakhtiarAuthor
Roodposhti, Majid ShadmanAuthor
Blaschke, ThomasAuthor
Aryal, JagannathAuthor
Year2017 (March)Volume10
Issue5
PublisherSpringer Science and Business Media LLC
DOIdoi:10.1007/s12517-017-2918-zSearch in ResearchGate
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Mindat Ref. ID959245Long-form Identifiermindat:1:5:959245:6
GUID0
Full ReferenceFeizizadeh, Bakhtiar, Roodposhti, Majid Shadman, Blaschke, Thomas, Aryal, Jagannath (2017) Comparing GIS-based support vector machine kernel functions for landslide susceptibility mapping. Arabian Journal of Geosciences, 10 (5) doi:10.1007/s12517-017-2918-z
Plain TextFeizizadeh, Bakhtiar, Roodposhti, Majid Shadman, Blaschke, Thomas, Aryal, Jagannath (2017) Comparing GIS-based support vector machine kernel functions for landslide susceptibility mapping. Arabian Journal of Geosciences, 10 (5) doi:10.1007/s12517-017-2918-z
In(2017, March) Arabian Journal of Geosciences Vol. 10 (5) Springer Science and Business Media LLC

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Feizizadeh, Bakhtiar, Shadman Roodposhti, Majid, Jankowski, Piotr, Blaschke, Thomas (2014) A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping. Computers & Geosciences, 73. 208-221 doi:10.1016/j.cageo.2014.08.001
Shadman Roodposhti, Majid, Aryal, Jagannath, Shahabi, Himan, Safarrad, Taher (2016) Fuzzy Shannon Entropy: A Hybrid GIS-Based Landslide Susceptibility Mapping Method. Entropy, 18 (10). 343pp. doi:10.3390/e18100343
Feizizadeh, Bakhtiar, Blaschke, Thomas (2013) GIS-multicriteria decision analysis for landslide susceptibility mapping: comparing three methods for the Urmia lake basin, Iran. Natural Hazards, 65. 2105-2128 doi:10.1007/s11069-012-0463-3
Feizizadeh, Bakhtiar, Blaschke, Thomas (2014) An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping. International Journal of Geographical Information Science, 28 (3). 610-638 doi:10.1080/13658816.2013.869821
Naboureh, Amin, Rezaei Moghaddam, Mohammad Hossein, Feizizadeh, Bakhtiar, Blaschke, Thomas (2017) An integrated object-based image analysis and CA-Markov model approach for modeling land use/land cover trends in the Sarab plain. Arabian Journal of Geosciences, 10 (12) doi:10.1007/s12517-017-3012-2
Feizizadeh, Bakhtiar, Blaschke, Thomas, Nazmfar, Hossein (2014) GIS-based ordered weighted averaging and Dempster–Shafer methods for landslide susceptibility mapping in the Urmia Lake Basin, Iran. International Journal of Digital Earth, 7 (8). 688-708 doi:10.1080/17538947.2012.749950
Roodposhti, Majid Shadman, Rahimi, Saeed, Beglou, Mansour Jafar (2014) PROMETHEE II and fuzzy AHP: an enhanced GIS-based landslide susceptibility mapping. Natural Hazards, 73. 77-95 doi:10.1007/s11069-012-0523-8
Roodposhti, Majid Shadman, Safarrad, Taher, Shahabi, Himan (2017) Drought sensitivity mapping using two one-class support vector machine algorithms. Atmospheric Research, 193. 73-82 doi:10.1016/j.atmosres.2017.04.017
Patel, Ashok Kumar, Chatterjee, Snehamoy, Gorai, Amit Kumar (2017) Development of machine vision-based ore classification model using support vector machine (SVM) algorithm. Arabian Journal of Geosciences, 10 (5) doi:10.1007/s12517-017-2909-0
Bai, Zhigang, Liu, Qimeng, Liu, Yu (2021) Landslide susceptibility mapping using GIS-based machine learning algorithms for the Northeast Chongqing Area, China. Arabian Journal of Geosciences, 14 (24) doi:10.1007/s12517-021-08871-w
Ghorbanzadeh, Omid, Didehban, Khalil, Rasouli, Hamid, Kamran, Khalil, Feizizadeh, Bakhtiar, Blaschke, Thomas (2020) An Application of Sentinel-1, Sentinel-2, and GNSS Data for Landslide Susceptibility Mapping. ISPRS International Journal of Geo-Information, 9 (10) 561pp. doi:10.3390/ijgi9100561
 
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