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- W2213084061 abstract "Rice-planted area and production monitoring has significance for governments to formulate some food related policy. Remote sensing has an obvious advantage for the rice monitoring. As for the rice-planted area, the special growth raw shows different feature in the remote sensing image. In this paper, the multi-temporal Landsat-8 OLI image of Menghun and Mengzhe town in Xishuangbanna autonomous prefecture where planting a large number of rice was used as the test data, the corresponding changes of the difference between NDVI and NDWI was used as the diagnostic feature, and the SAM classification approach was introduced to extract rice-planted area. The experiments shows that the approach could acquire more than 95% of the extraction accuracy." @default.
- W2213084061 created "2016-06-24" @default.
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- W2213084061 date "2015-12-14" @default.
- W2213084061 modified "2023-09-23" @default.
- W2213084061 title "Rice-planted area extraction from multi-temporal remote sensing images" @default.
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- W2213084061 doi "https://doi.org/10.1117/12.2205681" @default.
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