面向对象的无人机影像水体变化监测方法
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P208

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江苏省水利科技项目“基于无人机航空影像的水域变化自动监测研究”(2015035);江苏省测绘地理信息科研项目面向地理国情的卷积神经网络遥感影像分类研究(JSCHKY201618)


Water Change Monitoring by Object-oriented Detection Based on Unmanned Aerial Vehicle Image
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    摘要:

    [目的]针对大多无人机影像仅有红、绿、蓝3个波段的特点,提出一种利用纹理特征提取水体并进行变化监测的方法,为水利部门了解水体面积变化情况提供技术支持。[方法]首先利用易康软件对无人机影像进行多尺度分割,形成影像像斑,再计算影像像斑的角二阶矩、均值、熵等纹理特征,将这些纹理特征作为影像波段进行组合,从而突出水体,最后通过ISO分类的方法提取出水体,将不同时期提取的水体进行叠置分析,得到水体的变化区域。[结果]通过选择不同的区域进行试验,水体的提取精度和变化检测精度均达90%以上。[结论]面向对象的无人机影像水体变化监测方法可有效提高水体变化监测的效率,节约人工作业量。

    Abstract:

    [Objective] Due to the fact that there are only three bands (red, green and blue) in most UAV(unmanned aerial vehicle)images, a method of extracting water body and monitoring water changes based on texture feature is proposed in order to provide technical support for water conservancy department.[Methods] We used eCognition software to divide the UAV images into multiple scales, and from the image object firstly. The angular second-order moment, mean, entropy and other texture features of the image object was then calculated. These texture features was combined as the image band to highlight the water body. Finally, the water body was extracted by ISO classification method, and the water body extracted from different periods was analyzed to obtain the change area of the water body.[Results] By testing in different regions, the accuracy of the water extraction and detection for water change was above 90%.[Conclusion] The proposed method can effectively improve the efficiency of the water body change monitoring, and reduce the amount of manual labor.

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秦慧杰,高磊,梁文广,欧阳晓.面向对象的无人机影像水体变化监测方法[J].水土保持通报,2018,38(5):256-260

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  • 收稿日期:2018-03-29
  • 最后修改日期:2018-04-16
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  • 在线发布日期: 2018-11-10
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