期刊名称：International Research Journal of Earth Sciences
电子版ISSN：2321-2527
出版年度：2016
卷号：4
期号：4
页码：9-16
语种：English
出版社：International Science Community Association
摘要：LULC classification were performed using Rotational Principal component approach on multispectral Landsat8 OLI datasets to increase the spectral divergence among the classes, which result better classification accuracy. We adopted Quartimax Rotational criteriato perform rotation using PC layers, which were obtained by performing PCA transformation using multispectral bands. We observed that, Quartimax rotational criteria improved the level of classificationaccuracy by enhancing the spectral characteristics of the different spectral land cover classand satisfied higher classification accuracy than an ordinary PCA transformation approach over the same multispectral dataset.
关键词：Quartimax Rotational PCA;Land use and Land cover;Eigenvector;Eigen value;Factor loading Matrix.
