Land use classification based on RS object-oriented method in coastal spectral confusion region

Land use and land cover information acquisition in coastal spectral confusion region is one of the difficulties for remote sensing information extraction. In this paper, image segmentation and support vector machine classification method were used in order to extract the information of land use/cover with object-oriented technology, based on TM image of March 11, 2007 in Kenli County. The results were compared with that of traditional pixel-based classification. Our results showed that the precision of classification reached 84.83% basing on object-oriented method, which increased by 5.94% and 19.53% respectively in comparison with maximum likelihood method and spectral angle mapper method. It also avoided the “salt and pepper” problem effectively. This study indicated that classification accuracy and efficiency of remote sensing image were improved with object-oriented method, which also provided an effective technological means for fast and accurate information extraction of Land use/cover in coastal spectral confusion region.