基于SAR卫星的内陆水体信息提取方法研究 ——以华阳河湖泊群流域为例
作者:
作者单位:

1.安徽省·水利部淮河水利委员会水利科学研究院,安徽 合肥 230088 2.河海大学水文水资源学院,江苏 南京 210098

作者简介:

孙金彦(1988—),女,硕士,工程师,主要从事水文及水资源,遥感解译技术等方面研究工作。 E-mail:sjy@ahwrri.org.cn

通讯作者:

孙金彦 E-mail:sjy@ahwrri.org.cn

中图分类号:

TV211;TP751

基金项目:

安徽省重点研究与开发计划(202104b11020046);安徽省·水利部淮河水利委员会水利科学研究院科技攻关计划项目(KJGG202201);水利水资源安徽省重点实验室青年科技创新基金项目(KY202001)


Research on extraction method of inland water body information based on SAR satellite ——The case for Huayang River Lake Group Basin
Author:
Affiliation:

1.Anhui and Huaihe River Institute of Hydraulic Research, Hefei 230088, China 2.College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China

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    摘要:

    为快速准确的提取SAR卫星数据中的水体信息,采用2020年汛期SAR卫星过境华阳河湖泊群流域获取的雷达数据,提出了一种自适应迭代水体OTSU-SDWI阈值分割方法(简称“AIOS 阈值法”),并从定性和定量两种角度与VV阈值法、VH阈值法和SDWI阈值法进行了对比分析。从定性角度,VV阈值法难以识别河湖藻华区域的水体信息,VH阈值法和SDWI阈值法存在将潮湿的滩地、池塘等识别为地表水体,易引起水体监测结果偏大,AIOS 阈值法的提取结果与实际情况更为相符;从定量角度,AIOS阈值法的提取结果精确率和准确率高于其他三种方法,但完整度低于SDWI阈值法。实验表明AIOS阈值法可以识别藻华区域的水体信息,具有自动化程度强、检测精度高的优势,对于提升内陆水体信息分布监测的速度和精度具有重要参考意义。

    Abstract:

    To quickly and accurately extract surface water information from SAR satellite data, an adaptive iterative OTSU-SDWI threshold method (hereinafter referred to as "AIOS threshold method") is proposed based on the radar data, which obtained by SAR satellite passing through Huayang River Lake Group Basin in the flood season of 2020. It is compared with VV threshold method, VH threshold method and SDWI threshold method from both qualitative and quantitative perspectives:(1)VV threshold method is difficult to identify the water information in the algal bloom area. VH threshold method and SDWI threshold method may identify wet beaches, ponds, etc. as surface water bodies, which is easy to cause the surface water extraction result to be larger. Correspondingly, the extraction results of the AIOS threshold method are more consistent with the actual situation; (2) For testing samples, the precision and accuracy of the AIOS threshold method are higher than those of the other three methods, but the completeness is lower than that of the SDWI threshold method. The experimental results verify the effectiveness of the AIOS threshold method, which can identify the water information of algal bloom area, and offer the advantage of strong automation and high reliability.

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引用本文

孙金彦,黄祚继,王春林.基于SAR卫星的内陆水体信息提取方法研究 ——以华阳河湖泊群流域为例[J].江淮水利科技,2023,(1):39-43

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  • 收稿日期:2023-01-03
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  • 在线发布日期: 2023-04-11
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