Comparison of Two Classification Methods (MLC and SVM) to Extract Land Use and Land Cover in Johor Malaysia

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dc.contributor.authorB Rokni Deilmai
dc.contributor.authorB Bin Ahmad
dc.contributor.authorH Zabihi
dc.coverage.publicationMalaysia
dc.date.accessioned2024-05-15T01:44:11Z
dc.date.available2024-05-15T01:44:11Z
dc.date.issued2014
dc.description.abstractIn this study, we have analyzed multispectral data using two different classifiers including Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM). To pursue this aim, Landsat Thematic Mapper data and identical field-based training sample datasets in Johor Malaysia used for each classification method, which results indicate in five land cover classes forest, oil palm, urban area, water, rubber.
dc.identifier.citationDeilmai, B. R., Ahmad, B. B., & Zabihi, H. (2014). Comparison of two classification methods (MLC and SVM) to extract land use and land cover in Johor Malaysia. In IOP conference series: Earth and environmental science (Vol. 20, No. 1, p. 012052). IOP Publishing.
dc.identifier.urihttps://repoemc.ukm.my/handle/123456789/734
dc.languageen
dc.publisherIOP Publishing
dc.publisher.alternativeIOP Conference Series: Earth and Environmental Science
dc.titleComparison of Two Classification Methods (MLC and SVM) to Extract Land Use and Land Cover in Johor Malaysia

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