The Classification of Land Cover Derived from High Resolution Remote Sensing Imagery
Remote sensing imagery is an attractive source of land cover information. High resolution sensing imagery provides more land cover detail than low resolution sensing imagery. Due to more complex and noisier spectral signatures for the former, new algorithms are needed to deal with high resolution imagery. Based on an integration of spectral and spatial information, a novel classification method is presented in this paper. Taking a city and countryside union region of Qingdao as the test area, a research was conducted to extract land cover information by applying classification. Five priori defined land cover classes in the classification scheme were construction, road, grassland, farmland, and water. The results show that the classification accuracy is satisfactory by the proposed method.
Remote Sensing Imagery Spectral Information Spatial Information Classification
Xia Jun Liu Jinmei Wang Guoyu Li Jizhong
School of Information Science and Engineering, Ocean University of China, 266100 School of Information Science and Engineering, Ocean University of China, 266100 School of Science a School of Science and Information, Agriculture University of Qingdao, 266109
国际会议
深圳
英文
742-744
2011-03-28（万方平台首次上网日期，不代表论文的发表时间）