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Vegetation Type and Degredation Classification on the Mongolian Steppe Using Random Forests

dc.contributor.authorLiu, Wei
dc.contributor.advisorBergen, Kathleen
dc.date.accessioned2013-08-16T15:11:18Z
dc.date.availableNO_RESTRICTIONen_US
dc.date.available2013-08-16T15:11:18Z
dc.date.issued2013-08
dc.date.submitted2013-08
dc.identifier.urihttps://hdl.handle.net/2027.42/99530
dc.description.abstractCreating consistent supervised vegetation classifications in different countries where training data are of different levels of quality and detail is challenging but important. For example, mapping steppe types and degradation of Mongolia and Inner Mongolia Autonomous Region (IMAR), China, using the same classification scheme would be helpful for doing comparative studies between the two regions and acquiring a better understanding of how country level differences affect vegetation on the Mongolian Plateau. Steppe and degradation maps, created through on-screen digitizing that combined image and ground information as input, were available in IMAR but not in Mongolia. We explored supervised classification using Random Forests (RF) to identify a reasonable sampling and training strategy and applied identical methods to classify remotely sensed images (Landsat Thematic Mapper 5) in IMAR and Mongolia using the same classification systems for the two countries in three ecological regions (meadow steppe, typical steppe and desert steppe). A number of challenges limit our ability to extend classifications trained in IMAR to Mongolia for creating consistent vegetation maps.en_US
dc.language.isoen_USen_US
dc.subjectRandom Foresten_US
dc.subjectSteppeen_US
dc.subjectMongoliaen_US
dc.subjectClassificationen_US
dc.titleVegetation Type and Degredation Classification on the Mongolian Steppe Using Random Forestsen_US
dc.typeThesisen_US
dc.description.thesisdegreenameMaster of Science (MS)en_US
dc.description.thesisdegreedisciplineNatural Resources and Environmenten_US
dc.description.thesisdegreegrantorUniversity of Michiganen_US
dc.contributor.committeememberBrown, Daniel
dc.identifier.uniqnamewillaliuen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/99530/1/Wei Liu Thesis August 2013.pdf
dc.owningcollnameDissertations and Theses (Ph.D. and Master's)


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