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dc.contributor.advisorSaleh, Muhamad Buce
dc.contributor.authorPertiwi, Dyah Ayu Putri
dc.date.accessioned2015-02-11T03:15:56Z
dc.date.available2015-02-11T03:15:56Z
dc.date.issued2014
dc.identifier.urihttp://repository.ipb.ac.id/handle/123456789/73949
dc.description.abstractLandsat 8 is new satelit has a sensor Operational Land imager (OLI) with a spatial resolution 30m x 30m and consist of eight spectral bands. Data and informations about comunity forest land cover is rarely done. The aims of this research are to identify comunity forest type and other land cover by use Landsat 8. The using method supervised classification in research are maximum likelihood and Support Vector Machine (SVM). Based on separability analysis using eight spectral bands, the type of comunity forest in APHR Wonosobo turned out not to be identified with either and acquired six land cover classes are residential, water body, shrub/dry land farming, rice field, open land, and mixed farm. The best method to classify land cover in APHR Wonosobo is maximum likelihood method with value of Kappa accuracy of 76.59% and has a high conformity by the visual image interpretation.en
dc.language.isoid
dc.subject.ddcWonosoboen
dc.subject.ddc2014en
dc.subject.ddcForest Managementen
dc.subject.ddcForestryen
dc.titleIdentifikasi Pola Hutan Rakyat dan Penutupan Lahan Lain Menggunakan Citra Landsat 8 OLI (Studi kasus di Asosiasi Petani Hutan Rakyat Wonosobo)en
dc.subject.keywordBogor Agricultural University (IPB)en
dc.subject.keywordmaximum likelihooden
dc.subject.keywordsupervised classificationen
dc.subject.keywordLandsat 8en
dc.subject.keywordLand coveren


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