基于高分一号遥感影像的水体提取方法对比分析与改进
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(1.河海大学水灾害防御全国重点实验室,江苏 南京 210098;2.河海大学长江保护与绿色发展研究院,江苏 南京 210098;3.河海大学水文水资源学院,江苏 南京 210098;4.中国气象局水文气象重点开放实验室,江苏 南京 210098;5.水利部水利大数据重点实验室,江苏 南京 210098 )

作者简介:

张珂(1979—),男,教授,博士,主要从事水文水资源及水文气象研究。E-mail:kzhang@hhu.edu.cn 通信作者:吴星宇(2000—),男,硕士研究生,主要从事水文水资源研究。E-mail:1317707157@qq.com

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基金项目:

国家重点研发计划项目(2023YFC3006500);中央高校基本科研业务费专项资金资助项目(B240203007);水灾害防御全国重点实验室自主研究项目(524015222)


Comparative analysis and improvement of water body extraction methods based on GF-1 remote sensing images
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(1.The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing 210098, China;2.Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, China;3.College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China;4.China Meteorological Administration Hydro-Meteorology Key Laboratory, Nanjing 210098, China;5.Key Laboratory of Water Big Data Technology of Ministry of Water Resources, Nanjing 210098, China)

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    摘要:

    以高分一号遥感影像为数据源,以安徽省黄山市屯溪流域内的东方红水库为研究对象,采用单波段阈值法、两波段差值法、波段比值法、归一化差分水体指数(NDWI)法、归一化差分植被指数(NDVI)法共5种水陆像元度量方法,分别应用平均值法和最大类间方差迭代法两种阈值选取方法对东方红水库进行水体提取,探索最大类间方差迭代法在水体提取变量上的改进效果,在此基础上提出了一种改进的最大类间方差联合水体提取法,并对比了改进前后的水体提取效果。结果表明:改进后的水体提取方法可以很好地降低影像提取中产生的噪点,提高水体提取的精度,提取成果的平均相对误差为4.69%,决定系数为0.8579,相比于改进前平均相对误差降低了0.68%,决定系数提高了0.0539。

    Abstract:

    Taking the GF1 remote sensing image as the data source and the Dongfanghong Reservoir in Tunxi Watershed, Huangshan City, Anhui Province as the research object, five kinds of water and land pixel measurement methods, including single band threshold method, two band difference method, band ratio method, normalized difference water index (NDWI) method, and normalized difference vegetation index (NDVI) method, were used to extract water body of the Dongfanghong Reservoir, respectively, using the average method and the maximum interclass variance iteration method, to explore the improvement effect of the maximum interclass variance iteration method on water body extraction variables. On this basis, an improved maximum interclass variance joint water extraction method was proposed, and the water extraction effects before and after the improvement were compared. The results show that the improved water body extraction method can effectively reduce the noise generated in image extraction and improve the accuracy of water body extraction. The average relative error of the extraction results is 4.69%, with a determination coefficient of 0.8579. Compared with before improvement, the average relative error is reduced by 0.68%, and the determination coefficient is increased by 0.0539.

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张珂,吴星宇,吴南,等.基于高分一号遥感影像的水体提取方法对比分析与改进[J].水资源保护,2024,40(4):9-16.(ZHANG Ke, WU Xingyu, WU Nan, et al. Comparative analysis and improvement of water body extraction methods based on GF-1 remote sensing images[J]. Water Resources Protection,2024,40(4):9-16.(in Chinese))

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  • 收稿日期:2023-11-28
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  • 在线发布日期: 2024-08-02
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