基于潮汐动态淹没过程的长江口潮滩地形信息反演研究

doi:10.12082/dqxxkx.2022.210429

地球信息科学学报 ›› 2022, Vol. 24 ›› Issue (3): 583-596.doi: 10.12082/dqxxkx.2022.210429

• 遥感科学与应用技术 • 上一篇

基于潮汐动态淹没过程的长江口潮滩地形信息反演研究

章敏¹^,²^,³(), 吴文挺¹^,²^,³^,^*(), 汪小钦¹^,²^,³, 孙玉¹^,²^,³

1.福州大学数字中国研究院（福建）,福州 350108
2.空间数据挖掘与信息共享教育部重点实验室,福州 350108
3.卫星空间信息技术综合应用国家地方联合工程研究中心,福州 350108

收稿日期:2021-07-27 修回日期:2021-09-01 出版日期:2022-03-25 发布日期:2022-05-25
通讯作者: *吴文挺（1990— ）,男,福建福州人,博士,助理研究员,研究方向为海岸带遥感。E-mail: wuwt@fzu.edu.cn
*吴文挺（1990— ）,男,福建福州人,博士,助理研究员,研究方向为海岸带遥感。E-mail: wuwt@fzu.edu.cn
作者简介:章敏（1997— ）,男,安徽铜陵人,硕士生,研究方向为海岸带遥感。E-mail: N195527044@fzu.edu.cn
基金资助:
国家自然科学基金项目(41801393);中央引导地方发展专项(2017L3012)

Topographic Retrieval of the Tidal Flats in the Yangtze Estuary based on the Dynamic Tidal Submergence

ZHANG Min¹^,²^,³(), WU Wenting¹^,²^,³^,^*(), WANG Xiaoqin¹^,²^,³, SUN Yu¹^,²^,³

1. The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350108, China
2. Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou 350108, China
3. National ＆ Local Joint Engineering Research Center of Satellite Geospatial Information Technology, Fuzhou 350108, China

Received:2021-07-27 Revised:2021-09-01 Online:2022-03-25 Published:2022-05-25
Contact: WU Wenting
Supported by:
National Natural Science Foundation of China(41801393);Special Project of Central Government Guiding Local Development(2017L3012)

摘要/Abstract

摘要：

潮滩是陆地与海洋之间重要的生态过渡地带,具有复杂的生态过程和重要的服务功能。受陆海交互作用及人类活动的影响,潮滩处于高度动态变化过程中,而传统测绘技术受到潮滩可达性影响无法快速获取潮滩地形信息。为解决潮滩高程数据获取困难的问题,本文提出一种基于潮汐动态淹没过程和时序遥感影像的潮滩地形信息提取算法,利用K-means++聚类方法实现水域提取,并通过时序淹没特征计算潮滩淹没频率提取潮滩范围信息,最终综合区域潮汐特征反演潮滩地形。研究以崇明东滩为例,利用2016—2020年所有可用Sentinel-2和Landsat-8时序遥感影像,实现潮滩范围提取与高程反演,并通过实测高程数据进行精度验证。研究结果表明,潮滩范围提取总体精度为97.73%,F1_score为0.98;高程反演平均绝对误差为0.15 m,潮滩高程的反演精度与可用影像的数量呈正相关。研究利用该算法进一步反演长江口地区主要潮滩地形特征,结果表明区域内潮滩面积为346.93 km²,高程范围为1.00~3.84 m,且与现有潮滩范围数据集相比,本研究提取的长江口潮滩范围更为完整。该算法为潮滩地形的快速反演提供了可能,对潮滩资源动态监测和管理具有重要意义。

关键词: 潮滩, 时序遥感影像, K-means++, 潮滩淹没频率, Sentinel-2, Landsat-8, 潮滩范围提取, 地形反演, 长江口

Abstract:

Tidal flats are important transitional zones between terrestrial and marine ecosystems and have complicated ecological processes and essential ecosystem services. Tidal flats are highly dynamic under the influences of land-sea interactions and anthropogenic activities. Limited by the accessibility, it is difficult to map the tidal flat using traditional survey. To solve the difficulty in obtaining tidal flat elevation data, a tidal flat elevation inversion model suitable for large-scale with high accuracy is needed. In this study, we proposed an algorithm incorporating tidal submergence and time-series Remote Sensing (RS) data to map the topography of tidal flats. We used Chongming Dongtan as an example and further extended the results to the whole Yangtze Estuary. Firstly, the K-means++ clustering was employed to extract the inundation extent of tidal. Then, the frequency of tidal inundation of each pixel was calculated from the time series RS data. Finally, the tidal flat topography was retrieved based on the regional tidal frequency. All available Sentinel-2 and Landsat-8 images from 2016 to 2020 were used to build the time-series dynamic of tidal flats to map the topography. Verified by the in-situ data, the results showed that the total accuracy and F1-score of the inundation extent extraction of the tidal flats were 97.73% and 0.98, respectively. The average absolute error of elevation inversion was 0.15 m. The accuracy of tidal flat elevation was positively correlated with the number of available images. The total area of tidal flats was 346.93 km² with an elevation range of 1.00~3.84 m. The tidal flats in the Yangtze Estuary were mainly distributed in Chongming Dongtan, Jiuduansha, Hengsha Dongtan, Nanhui Biantan, and Tuanjiesha. Among them, Nanhui beach had the largest area (107.44 km²), while Chongming east beach had the largest elevation difference (2.84 m). The distribution status of tidal flat was mainly affected by sediment hydrodynamics, vegetation, and human engineering activities. Compared with the existing dataset, our results showed a more robust capacity in the inundation extent extraction of tidal flats. With the increasing number of effective observations and tidal level information from time-series RS images in coastal areas, the extraction accuracy of tidal flat information could be further improved. The proposed algorithm has a great potential in rapid mapping of tidal flat topography and is of great significance for the dynamic monitoring and management of tidal flat resources.

Key words: tidal flats, time-series remote sensing images, K-means++, frequency of tidal inundation, Sentinel-2, Landsat-8, tidal flats area extraction, topographic retrieval, Yangtze Estuary

章敏, 吴文挺, 汪小钦, 孙玉. 基于潮汐动态淹没过程的长江口潮滩地形信息反演研究[J]. 地球信息科学学报, 2022, 24(3): 583-596.DOI:10.12082/dqxxkx.2022.210429

ZHANG Min, WU Wenting, WANG Xiaoqin, SUN Yu. Topographic Retrieval of the Tidal Flats in the Yangtze Estuary based on the Dynamic Tidal Submergence[J]. Journal of Geo-information Science, 2022, 24(3): 583-596.DOI:10.12082/dqxxkx.2022.210429

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区域	数量/景	相对最高潮/m	相对最低潮/m
A1	115	3.94	0.92
A2	101	3.95	1.08
A3	81	3.39	1.33
A4	90	3.18	1.41
A5	111	3.21	1.37
A6	104	3.34	1.39
A7	86	3.47	1.41

类别	潮滩	非潮滩	合计	用户精度/%	F1_score	总体精度/%
潮滩	300	1	301	99.67	0.98	97.73
非潮滩	12	261	273	95.60	0.97
合计	312	262	574
生产精度/%	96.15	99.62

潮滩区域	面积/km²	高程范围/m
崇明岛	97.59	1.00~3.84
团结沙	34.56	1.36~2.66
横沙岛	29.94	1.48~3.11
九段沙	68.72	1.48~3.25
江亚南沙	8.68	1.48~3.13
南汇东滩	107.44	1.49~3.39
合计	346.93	1.00~3.84

高程范围/m	面积/km²	高程范围/m	面积/km²
1.00~1.20	4.61	2.60~2.80	23.05
1.20~1.40	21.69	2.80~3.00	26.14
1.40~1.60	39.66	3.00~3.20	29.33
1.60~1.80	44.76	3.20~3.40	15.80
1.80~2.00	39.40	3.40~3.60	5.79
2.00~2.20	32.35	3.60~3.80	9.50
2.20~2.40	28.02	3.80~3.84	3.42
2.40~2.60	23.92

影像数量/景	R²	RMSE/m
101	0.92	0.19
60	0.86	0.21
32	0.83	0.32

基于潮汐动态淹没过程的长江口潮滩地形信息反演研究

Topographic Retrieval of the Tidal Flats in the Yangtze Estuary based on the Dynamic Tidal Submergence

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