Classification of Land Use/Cover with OMIS-I Images Based on Segmentation Control and Multi-layer Information Extraction
Based on OMIS-Ⅰ hyperspectral remote sensing data oi 128 bands lor Yixing area, a decision tree has been built lor both plain and mountainous area. With this method, the first level in land use/cover (forest land, garden plots, water area, cultivated land )can be classified automatically with an accuracy oi 88.15% and the Kappa Coefficient is 0. 82 .20.23% of garden plots and 2.24% oi cultivated land are left out in the classification respectively .Error in classification for cultivated land is 21.87% , forest land 21.98% , garden plots 0.66% , water area 0. Classification ior land use/cover types in the second level can also be carried out automatically with an accuracy of 86.16% and the Kappa Coefficient is 0.81 .Better results can be achieved by interpretation with the aid of vector map oi land use. Study in the area shows that the integrated decision tree method based on segmentation control and multi - layer information extraction is operational and results in a good accuracy in classification of land use/cover with OMIS - Ⅰ hyperspectral data.
NETL
NSTL
万方数据
维普
