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岸外沙洲潮间带地形的增强型遥感构建方法

周永 张东 邓慧丽 徐南 张慧铭 郝昕 沈永明

周永,张东,邓慧丽,等. 岸外沙洲潮间带地形的增强型遥感构建方法[J]. 海洋学报,2021,43(7):1–11
引用本文: 周永,张东,邓慧丽,等. 岸外沙洲潮间带地形的增强型遥感构建方法[J]. 海洋学报,2021,43(7):1–11
Zhou Yong,Zhang Dong,Deng Huili, et al. The enhanced construction method for intertidal terrain of offshore sandbanks by remote sensing[J]. Haiyang Xuebao,2021, 43(7):1–11
Citation: Zhou Yong,Zhang Dong,Deng Huili, et al. The enhanced construction method for intertidal terrain of offshore sandbanks by remote sensing[J]. Haiyang Xuebao,2021, 43(7):1–11

岸外沙洲潮间带地形的增强型遥感构建方法

基金项目: 国家自然科学基金项目(41771447;U1609203);江苏省海洋科技创新专项项目(HY2018-3)
详细信息
    作者简介:

    周永(1989-),男,江苏省南京市人,主要从事海岸带遥感应用研究。E-mail:451985335@qq.com

    通讯作者:

    张东(1975-),男,江苏省南通市人,博士,副教授,研究方向为海洋信息技术与海岸带资源开发管理。E-mail:zhangdong@njnu.edu.cn

The enhanced construction method for intertidal terrain of offshore sandbanks by remote sensing

  • 摘要: 水边线法是潮间带地形遥感反演的重要方法。针对常规水边线方法在应用于地形多变的岸外沙洲潮间带数字高程模型(DEM)构建中出现的水边线交叉和缺乏表现潮沟微地形特征的问题,本文提出了一种增强型地形遥感构建方法:首先通过潮位排序,筛选出具有正确高程变化趋势、空间分离的水边线;然后对筛选过程中水边线位置相近的影像组按像元计算改进的归一化差值水体指数(MNDWI)并进行均值序列合成,提取出合成海陆边界线,二者共同构建出初始的潮间带DEM;进一步利用低潮期的潮沟边界线和中线生成潮沟DEM,通过潮沟镶嵌处理,最终获得可表达滩面微地形起伏的潮滩DEM。该方法在江苏岸外辐射沙洲中部核心区域的模拟应用表明,对比4条验证剖面的平均结果,高程平均绝对误差(MAE)为0.43 m,均方根误差(RMSE)为0.54 m,相关系数(r)为0.75,模拟高程与验证高程在剖面起伏形态变化方面具有良好的一致性,同时模拟DEM的空间破碎度小,能够反映更多的细节地形特征。该方法可为利用多源遥感数据构建考虑微地形变化的高精度潮间带地形DEM提供新的思路。
  • 图  1  研究区概况

    Fig.  1  Sketch map of the study area

    图  2  影像成像时间分布

    Fig.  2  Image acquisition time

    图  3  基于遥感水边线的增强型地形构建方法技术流程图

    Fig.  3  Flowchart of enhanced terrain construction method based on waterlines

    图  4  各潮位站点在不同排序条件下影像成像时刻的潮位分布和线性拟合

    a−c. 以大丰港、弶港、洋口港为潮位基准站点的排序结果

    Fig.  4  Tide level distribution and linear fitting diagram of imaging time at various tide stations under different sequencing conditions

    a−c. The tide level sequencing results by taking Dafeng Port, Jianggang Port, and Yangkou Port stations as the tidal level ranking benchmarks respectively

    图  5  影像组HC-4的MNDWI序列合成与海陆边界线提取过程

    a. 原始影像;b. MNDWI结果;c. 序列合成;d. 阈值分割;e. 5组合成影像提取的海陆边界线

    Fig.  5  MNDWI sequence synthesis and sea-land boundary extraction of image group HC-4

    a. original images; b. images of MNDWI; c. sequential synthesis result map; d. threshold segmentation map; e. border lines extracted from 5 groups of synthetic images

    图  6  地形构建结果对比

    a. 常规水边线方法DEM构建结果;b. 增强型潮滩构建方法DEM构建结果

    Fig.  6  Comparison of terrain construction results

    a. DEM by conventional waterline method; b. DEM by enhanced tidal flat construction method

    图  7  各剖面实测地形与模拟地形的精度和趋势相关性对比

    Fig.  7  Comparison of the accuracy and trend correlation between the measured and simulated terrain at each section

    图  8  剖面形态对比图 a–d分别为JJS-H、JJS-Z、ZGS-H、ZGS-Z剖面形态对比

    Fig.  8  Morphology comparison of each section. a−d are the morphological comparison of JJS-H, JJS-Z, ZGS-H, ZGS-Z section

    表  1  不同排序基准下各站点的潮位变化拟合决定系数与斜率

    Tab.  1  The coefficient of determination and slope for fitting tide level changes at different tide stations

    排序基准大丰港站弶港站洋口港站
    R2斜率R2斜率R2斜率
    大丰港站0.96–0.130.01–0.010.74–0.11
    弶港站0.06–0.020.77–0.080.32–0.06
    洋口港站0.70–0.110.31–0.070.93–0.13
    下载: 导出CSV

    表  2  各影像组中的影像与成像时刻潮位高度表

    Tab.  2  Images and their correspondent tide levels for each image group

    影像组名称成像日期成像时间潮位高度/m(国家1985高程)
    大丰港弶港洋口港
    HC-12017–10–3110:38:190.281.421.27
    2018–07–2810:35:491.87–0.761.18
    2017–10–2110:37:091.56–0.961.14
    合成后1.24–0.101.20
    HC-22018–11–1010:39:211.01–1.510.31
    2019–05–2910:35:51–0.430.700.27
    2017–12–2110:30:590.58–1.67–0.08
    合成后0.39–0.830.17
    HC-32019–01–2410:40:090.85–1.89–0.46
    2018–04–1910:35:491.09–1.82–0.51
    2018–04–0910:35:49–1.22–0.27–0.58
    2018–10–1610:36:59–0.95–1.15–0.86
    合成后–0.06–1.28–0.60
    HC-42018–10–3111:38:31–1.22–1.25–1.42
    2018–10–0110:35:51–0.95–1.39–1.44
    2018–06–0310:36:51–0.43–1.97–1.46
    2018–01–2210:30:46–0.88–1.86–1.58
    2018–01–0910:40:49–1.86–1.08–1.58
    合成后–1.07–1.51–1.50
    HC-52017–12–1010:40:59–1.67–1.39–1.69
    2017–12–2510:41:21–1.52–1.75–1.70
    2018–02–0710:30:38–1.88–1.15–1.71
    2019–02–2610:30:29–1.91–1.04–1.72
    2018–02–2310:30:32–1.99–1.02–1.77
    2018–02–2310:37:11–1.96–1.07–1.79
    合成后–1.82–1.24–1.73
    未参与合成的原始影像2018–05–1410:35:511.691.322.50
    2018–05–1410:29:491.711.172.44
    2017–12–0510:41:011.31–0.921.03
    2018–11–2510:40:291.42–1.090.80
    2018–12–2410:30:401.32–1.220.80
    2017–12–2010:41:091.01–1.240.66
    2018–03–1010:35:39–1.43–0.40–0.80
    2018–02–0810:38:39–1.72–0.65–1.21
    2018–05–0410:35:51–0.06–1.97–1.13
    2018–07–1710:29:58–0.65–1.73–2.12
    2018–07–1810:35:49–1.52–1.75–2.48
    2019–06–0810:35:51–1.12–1.87–2.31
    下载: 导出CSV
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