Application Study on Remote Sensing Classification Based on RBF Network and Spectral Indexes
Abstract: In this paper, spectral indexes NDWI, NDVI, NDBI were inversed from TM images as the key aux-iliary information in the classification of city land use. On this basis, the city remote sensing classi-fication model was put forward based on RBF network and the normalized indexes. Finally, taking the Sichuan Nanchong city as the study area, using TM image as data source, the city classification model proposed in this paper was experimented. The experimental results show that RBF network has a certain advantage in the integration of learning parameters. The overall accuracy using RBF neural network and the surface indexes can reach to 95.02%, which is improved by 7.05 percentage points than only using the band information.
文章引用: 黄三军 , 郝莹莹 , 罗小波 (2014) 结合RBF网络与光谱指数的遥感分类应用研究。 无线通信， 4， 136-142. doi: 10.12677/HJWC.2014.46021
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