Land cover classification using interval type-2 fuzzy clustering for multi-spectral satellite imagery
Long Thanh Ngo, Dzung Dinh Nguyen · 2012
Land cover classification have been developed for specially surveillance of change of land and generating update information. The paper introduces an approach to classification of land cover from multi-spectral satellite imagery using interval type-2 c-means clustering. Two channels (Near Infrared - NIR and Visible Red - NR) are used to generate NDVI image of study area. Then IT2-FCM is used to classify NDVI into six sub-classes presenting for six types of land cover. The method is implemented for two study areas in comparing with ISODATA algorithm and FCM.