Performance evaluation and sensitivity analysis of expert-based, statistical, machine learning, and hybrid models for producing landslide susceptibility maps

Pradhan, B

Seeni, MI Kalantar, B

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Publication Type:: Chapter
Citation:: Laser Scanning Applications in Landslide Assessment, 2017, pp. 193 - 232
Issue Date:: 2017-05-04

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Field	Value	Language
dc.contributor.author	Pradhan, B https://orcid.org/0000-0001-9863-2054	en_US
dc.contributor.author	Seeni, MI	en_US
dc.contributor.author	Kalantar, B	en_US
dc.date.issued	2017-05-04	en_US
dc.identifier.citation	Laser Scanning Applications in Landslide Assessment, 2017, pp. 193 - 232	en_US
dc.identifier.isbn	9783319553412	en_US
dc.identifier.uri	http://hdl.handle.net/10453/126289
dc.relation.ispartof	Laser Scanning Applications in Landslide Assessment	en_US
dc.relation.isbasedon	10.1007/978-3-319-55342-9_11	en_US
dc.title	Performance evaluation and sensitivity analysis of expert-based, statistical, machine learning, and hybrid models for producing landslide susceptibility maps	en_US
dc.type	Chapter
utslib.for	0907 Environmental Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

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