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

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19_Comparison_of_Two_Classification_Methods_MLC_and_SVM_to_Extract_Land_Use_and_Land_Cover_in_Johor_Malaysia.pdf (1.21 MB)

Date

2014

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Publisher

IOP Publishing

Abstract

In 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.

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Citation

Deilmai, 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.

URI

https://repoemc.ukm.my/handle/123456789/734

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Land Use