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融合潮位影像与分位数特征的滩涂结构动态提取方法研究

杨振华, 赵铜铁钢, 严林, 陈文龙, 郭成超, 陈晓宏, 刘双元

杨振华, 赵铜铁钢, 严林, 陈文龙, 郭成超, 陈晓宏, 刘双元. 融合潮位影像与分位数特征的滩涂结构动态提取方法研究[J]. 应用基础与工程科学学报, 2024, 32(5): 1238-1252. DOI: 10.16058/j.issn.1005-0930.2024.05.003
引用本文: 杨振华, 赵铜铁钢, 严林, 陈文龙, 郭成超, 陈晓宏, 刘双元. 融合潮位影像与分位数特征的滩涂结构动态提取方法研究[J]. 应用基础与工程科学学报, 2024, 32(5): 1238-1252. DOI: 10.16058/j.issn.1005-0930.2024.05.003
YANG Zhenhua, ZHAO Tongtiegang, YAN Lin, CHEN Wenlong, GUO Chengcao, CHEN Xiaohong, LIU Shuangyuan. Study on Dynamic Extraction of Tidal Flat Structure Based on Tidal Level Image and Quantile Feature[J]. Journal of Basic Science and Engineering, 2024, 32(5): 1238-1252. DOI: 10.16058/j.issn.1005-0930.2024.05.003
Citation: YANG Zhenhua, ZHAO Tongtiegang, YAN Lin, CHEN Wenlong, GUO Chengcao, CHEN Xiaohong, LIU Shuangyuan. Study on Dynamic Extraction of Tidal Flat Structure Based on Tidal Level Image and Quantile Feature[J]. Journal of Basic Science and Engineering, 2024, 32(5): 1238-1252. DOI: 10.16058/j.issn.1005-0930.2024.05.003

融合潮位影像与分位数特征的滩涂结构动态提取方法研究

基金项目: 

国家重点研发计划项目(2021YFC3001000);广东省“珠江人才计划”青年创新团队项目(2019ZT08G090);广州市科技计划项目(2023A04J1029)

详细信息
    作者简介:

    杨振华(1991-),男,博士研究生.E-mail:yangzhh63@mail2.sysu.edu.cn

    通讯作者:

    赵铜铁钢(1986-),男,教授.E-mail:zhaottg@mail.sysu.edu.cn

  • 中图分类号: TP751

Study on Dynamic Extraction of Tidal Flat Structure Based on Tidal Level Image and Quantile Feature

  • 摘要: 为解决周期性潮位与长序列人类活动影响下滩涂结构动态提取的难题,融合潮位信息与光谱指数分位数特征,构建了一种滩涂结构与转化动态监测方法,借助单张Landsat影像训练样本的MNDWI和NDWI均值排序,采用云量、中值融合算法和分位数特征将影像栈融合成潮位影像,进一步利用随机森林分类算法识别1988~2021年深圳湾滩涂时空转化过程.研究结果表明,滩涂监测算法的平均总体精度和Kappa系数分别为0.85和0.78,实现了滩涂结构与转化动态的同步提取.整体上,深圳湾滩涂呈“北窄南宽、西缩东扩”的动态格局,北部因填海造陆区建设用地和人工绿地导致大规模潮上带和潮间带扩展,东部生态保护区滩涂发育促使光滩、红树林的海向延伸,南部潜在开发区光滩、水体呈此消彼长的波动变化.
    Abstract: To solve the problem of dynamic extraction for tidal-flat structure caused by periodic tide level and long sequences of human activities,the paper combines the tide level with the spectral index quartile features to construct an algorithm for monitoring the dynamics of tidal-flat structure.With utilization of MNDWI and NDWI mean ordering of the training samples for Landsat images,the quality mosaic and medium mosaic are used to fuse the image stacks into tide level images,and utilized the Random Forest classification algorithm to identify the spatio-temporal dynamics of tidal-flat in Bay from 1988 to 2021.The results shown that the average overall accuracy and Kappa coefficient of the algorithm are 0.85 and 0.78,respectively,realizing the simultaneous extraction of the dynamic structure and transitions of tidal-flat.On the whole,the tidal-flat in Shenzhen Bay show a dynamic pattern of "narrow in the north and wide in the south,shrinking in the west and expanding in the east"; the northern construction land in the reclaimed land area and the artificial greenland are massively expanded to the supratidal and intertidal zones; the eastern development of tidal-flat in the ecological protection zone has prompted the seaward extension of the beaches and the mangroves; and the southern beaches in the potential development zone and the water bodies show a fluctuating change pattern.The development of beaches and water bodies in the southern potential development zone showed trade-off dynamics.
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出版历程
  • 收稿日期:  2023-04-17
  • 修回日期:  2023-10-08

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