基于SPOT-5多光谱影像的矿区塌塘水体提取方法研究

Research of Water Body Extraction Methods of Mining Area Collapsed Pond Based on SPOT-5 Multispectral Image

  • 摘要: 针对基于遥感影像的水体提取方法存在水体提取不完整和误提的现象,提出了一种基于SPOT-5多光谱影像的矿区塌塘水体提取方法。在利用波段合成增加一个可用波段的基础上对已有的水体提取方法进行适当的改进,并基于决策树分类器和改进后的方法进行矿区水体的四级提取,保证了水体提取的完整性,同时减少了误提率;最后利用实测数据对水体提取的精度进行了评定。试验结果表明,基于决策树分类器的水体提取方法具有较高的精度,能满足矿区实际应用的需要。

     

    Abstract: For phenomenon of incomplete water extraction and false extraction in existing water extraction method based on remote sensing images, a water extraction method of mining area collapsed pond based on SPOT-5 multispectral images was proposed.On the basis of adding a available band by use of band synthetic, existing water extraction method was improved appropriately, and mining area water body was extracted by decision tree classifier and improved method with four-level extraction, so as to ensure the water body extraction integrity and reduce error rate. Finally, accuracy of the water body extraction was assessed by the extracted data. The test results showed that the water body extraction method based on decision tree classifier has higher accuracy and can meet with demand of practical application in mining area.

     

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