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High resolution remote sensing classification of coral reef substrate, base on SVM—Taken XiSha Zhaoshu island as an example

机译:基于支持向量机的珊瑚礁基质高分辨率遥感分类-以西沙兆树岛为例

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Coral resources in global are facing a huge threat under climate change and increasing human activities. In this paper, at first, combined with Support Vector Machine (SVM), WorldView-3 satellite data (October 10, 2014) with high spatial resolution (1.2 m) and eight spectral bands are used to research classification of Zhao Shu island coral reef substrate. Coral reef, coral bleaching, coral sand and seawater are identified. Then training and checking samples are built artificially and label types from in situ data and finished classification result accuracy test. The results show that the total classification accuracy and Kappa coefficient are 95.28% and 0.90 respectively. These results demonstrate that high resolution images can provide more detailed information and are suitable to monitor the health of coral reefs. High resolution remote sensing classification results of coral reef can provide the important information for environment protection.
机译:全球的珊瑚资源在气候变化和人类活动增加的情况下面临着巨大的威胁。本文首先结合支持向量机(SVM),高分辨率(1.2 m)和8个光谱带的WorldView-3卫星数据(2014年10月10日)研究赵树岛珊瑚礁的分类。基质。确定了珊瑚礁,珊瑚漂白,珊瑚沙和海水。然后人为地建立训练和检查样本,并根据现场数据和完成的分类结果准确性测试来标记标签类型。结果表明,总分类准确率和Kappa系数分别为95.28%和0.90。这些结果表明,高分辨率图像可以提供更详细的信息,并且适合监视珊瑚礁的健康。高分辨率的珊瑚礁遥感分类结果可为环境保护提供重要信息。

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