Soil salinization is the main obstacle of agricultural production and development. At present,it is mainly based on remote sensing monitoring of soil salinization with low or middle resolution satellites, in addition to this, usual uses the traditional classification method based on pixels to monitor the salinization information, so, it is hard to get a detailed description and the monitoring precision is low. This paper use domestic GF-1 combining top-down multi-scale segmentation technology and object-oriented technology of information extraction, aimed at the field scale accurately extract, salinization information classification, and compared with the traditional classification methods. Results show that the object-oriented method and maximum likelihood classification accuracy of 92.72% and 84.31% respectively, in general, the Kappa coefficient was 0.90 and 0.78, respectively. The technology can accurately extract field scales salted information, in the future of farmland salinization high-precision monitoring has certain application value in the research and development potential.
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