Comparison of Machine Learning Methods for Potential Active Landslide Hazards Identification with Multi-Source Data

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datacite.relatedItem.firstPage253
datacite.relatedItem.issue4
datacite.relatedItem.relatedIdentifierTypeISSN
datacite.relatedItem.relatedItemIdentifier2220-9964
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datacite.relatedItem.titleIJGI
datacite.relatedItem.volume10
dc.contributor.authorXiangxiang Zheng
dc.contributor.authorGuojin He
dc.contributor.authorShanshan Wang
dc.contributor.authorYi Wang
dc.contributor.authorGuizhou Wang
dc.contributor.authorZhaoying Yang
dc.contributor.authorJunchuan Yu
dc.contributor.authorNing Wang
dc.date.accessioned2025-05-14T12:25:31Z
dc.date.available2025-05-14T12:25:31Z
dc.date.issued2021
dc.identifier.doihttps://doi.org/10.3390/ijgi10040253
dc.identifier.otherjz000145-0251
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/20790
dc.publisherMDPI AG
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc550
dc.titleComparison of Machine Learning Methods for Potential Active Landslide Hazards Identification with Multi-Source Data
dc.typeArticle
dcat.distribution.pdfhttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/20791
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