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基于高空间分辨率遥感影像的水深反演有效性评估

王燕茹 张利勇 刘文 张凯 王鑫

王燕茹,张利勇,刘文,等. 基于高空间分辨率遥感影像的水深反演有效性评估[J]. 海洋学报,2023,45(3):136–146 doi: 10.12284/hyxb2023026
引用本文: 王燕茹,张利勇,刘文,等. 基于高空间分辨率遥感影像的水深反演有效性评估[J]. 海洋学报,2023,45(3):136–146 doi: 10.12284/hyxb2023026
Wang Yanru,Zhang Liyong,Liu Wen, et al. Evaluation of validity of bathymetry retrieval data based on high-spatial resolution remote sensing image[J]. Haiyang Xuebao,2023, 45(3):136–146 doi: 10.12284/hyxb2023026
Citation: Wang Yanru,Zhang Liyong,Liu Wen, et al. Evaluation of validity of bathymetry retrieval data based on high-spatial resolution remote sensing image[J]. Haiyang Xuebao,2023, 45(3):136–146 doi: 10.12284/hyxb2023026

基于高空间分辨率遥感影像的水深反演有效性评估

doi: 10.12284/hyxb2023026
基金项目: 山东省自然科学基金(ZR2020MD084);山东科技大学科研创新团队支持计划(2019TDJH103)。
详细信息
    作者简介:

    王燕茹(1998-),女,山东省济南市人,主要从事海洋水深反演研究。E-mail:920635744@qq.com

    通讯作者:

    张凯(1983-),男,副教授,主要从事海洋测绘相关研究。E-mail:zk0773@163.com

  • ① a图审图号为GS(2016)1585号。
  • 中图分类号: TP79

Evaluation of validity of bathymetry retrieval data based on high-spatial resolution remote sensing image

  • 摘要: 卫星遥感反演水深(Satellite Derived Bathymetry, SDB)是获取浅海水深信息的有效手段。然而,其有效范围只限于光学浅水区域,在深水区域呈现“伪浅海”的失真现象。因此,如何准确识别SDB数据的有效范围对其广泛应用至关重要。本文基于高空间分辨率多光谱卫星影像,在深入分析深/浅水辐射亮度统计分布特征差异的基础上,提出一种数据驱动的水深反演有效性评价方法。该方法以卫星影像辐亮度信息的局域标准差作为特征,基于K-S检验方法对光学深水区域统计特征进行模型优选,并使用假设检验方法对深水无效区域对应的SDB进行识别。甘泉岛水域实验结果表明,该方法通过统计分布划分光学浅水与深水区域边界,可以有效识别光学深水区域产生的无效水深反演数据。在剔除无效区域数据后,光学浅水有效区域内水深反演平均绝对误差(MAE)为1.01,均方根误差(RMSE)为1.52。实验结果表明,本文提出的方法可准确识别SDB结果的有效区域,进而为浅海地形解译提供方法支撑。
    1)  ① a图审图号为GS(2016)1585号。
  • 图  1  研究区域概况

    a. 永乐环礁地理位置;b. 永乐环礁卫星影像;c. 甘泉岛卫星影像

    Fig.  1  Overview of the study area

    a. Location of the Yongle Atoll; b. satellite image of Yongle Atoll; c. satellite image of Ganquan Island

    图  2  GeoEye-1遥感影像(a)、实测水深数据(b)和 Stumpf模型反演水深(c)

    Fig.  2  GeoEye-1 sensing image (a), in-situ bathymetry data (b) and satellite derived bathymetry based on Stumpf model (c)

    图  3  水深光学遥感示意图

    Fig.  3  Schematic diagram of optical bathymetry remote sensing

    图  4  光学深/浅水区域辐亮度统计分布特征图

    Fig.  4  Statistical distribution map of radiance in the optical shallow/deep water region

    图  5  算法整体流程图

    Fig.  5  The flow chart of the proposed algorithm

    图  6  蓝、绿波段辐亮度数据及对应标准差特征分布

    a. 蓝波段辐亮度;b. 绿波段辐亮度;c. 蓝波段辐亮度标准差特征分布;d. 绿波段辐亮度标准差特征分布

    Fig.  6  Radiance data of blue/green bands and distribution of associated standard deviation features

    a. Radiance of blue band; b. radiance of green band; c. distribution of radiance standard deviation feature of blue band; d. distribution of radiance standard deviation feature of green band

    图  7  辐亮度标准差统计分布

    Fig.  7  Radiance standard deviation statistical distribution

    图  8  不同波段深/浅水区域划分阈值及划定的光学深水区域

    a. 蓝波段划分阈值;b. 蓝波段确定深水区域;c. 绿波段划分阈值;d. 绿波段确定深水区域

    Fig.  8  Different waveband deep/shallow water region division thresholds and delineated optical deep water regions

    a. Blue band division threshold; b. blue band to determine deep water area; c. green band division threshold; d. green band to determine deep water area

    图  9  卫星遥感反演水深有效区域内信息分布

    Fig.  9  Information distribution in the effective area of satellite derived bathymetry

    图  10  边界区域统计信息

    Fig.  10  Statistics information about the boundary area

    表  1  5种候选统计分布的概率密度函数及标准差求解公式

    Tab.  1  Probability density functions and standard deviation computation formula of five candidate statistical distributions

    分布函数瑞利分布韦伯尔分布正态分布伽马分布对数正态分布
    概率密度函数${\dfrac{x}{v^2} {\rm{e}}^{-\frac{x^2}{2v^2} } }$${\dfrac{\sigma}{\lambda}x^{v-1}{\rm{e}}^{\frac{x^v}{\lambda} } }$${\dfrac{1}{\sqrt{2{\text{π}} v^2} }{\rm{e}}^{\frac{-(x-\lambda)^2}{2v^2} } }$$\dfrac{\lambda^vx^{v-1} }{\varGamma(v)}{\rm{e}}^{-\lambda x}$${\dfrac{1}{\sqrt{2{\text{π}}}xv}{\rm{e}}^{-\frac{({\rm{ln}}\;x-\lambda)^2}{2v^2} } }$
    标准差${\sqrt{4-{{\text{π}} }/2v} }$${\lambda^{\frac{1}{v}} }$1.482 6×MAD(xi)${\dfrac{1}{\lambda}\sqrt{v} }$1.482 6×MAD(ln xi)
     注:MAD为中位数的绝对偏差。
    下载: 导出CSV

    表  2  K-S检验的拟合优度检验结果

    Tab.  2  Test results of the goodness of fit of K-S test


    分布函数

    瑞利分布

    韦伯尔分布

    正态分布

    伽马分布

    对数正态分布
    蓝波段0.320.110.080.060.04
    绿波段0.420.100.060.040.03
     注:表中数据为最大偏差值,数值越小,拟合效果越好。
    下载: 导出CSV
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  • 收稿日期:  2022-05-10
  • 修回日期:  2022-08-25
  • 网络出版日期:  2022-09-05
  • 刊出日期:  2023-02-01

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