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
章敏1,2,3(), 吴文挺1,2,3,*(
), 汪小钦1,2,3, 孙玉1,2,3
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:
ZHANG Min1,2,3(), WU Wenting1,2,3,*(
), WANG Xiaoqin1,2,3, SUN Yu1,2,3
Received:
2021-07-27
Revised:
2021-09-01
Online:
2022-03-25
Published:
2022-05-25
Contact:
WU Wenting
Supported by:
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。
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
[1] | 韩倩倩, 牛振国, 吴孟泉, 等. 基于潮位校正的中国潮间带遥感监测及变化[J]. 科学通报, 2019, 64(4):456-473. |
[ Han Q Q, Niu Z G, Wu M Q, et al. Remote-sensing monitoring and analysis of China intertidal zone changes based on tidal correction[J]. Chinese Science Bulletin, 2019, 64(4):456-473. ] DOI: 10.1360/N972018-00723 | |
[2] |
Salameh E, Frappart F, Turki I, et al. Intertidal topography mapping using the waterline method from Sentinel-1 & -2 images: The examples of Arcachon and Veys Bays in France[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 163(5):98-120. DOI: 10.1016/j.isprsjprs.2020.03.003
doi: 10.1016/j.isprsjprs.2020.03.003 |
[3] |
Mason D C, Davenport I J, Robinson G J, et al. Construction of an inter-tidal digital elevation model by the 'Water-Line' method[J]. Geophysical Research Letters, 1995, 22(23):3187-3190. DOI: 10.1029/95GL03168
doi: 10.1029/95GL03168 |
[4] | Xu Z, Kim D J, Kim S H, et al. Estimation of seasonal topographic variation in tidal flats using waterline method: A case study in Gomso and Hampyeong Bay, South Korea[J]. Estuarine Coastal & Shelf Science, 2016, 183(Part A):213-220. DOI: 10.1016/j.ecss.2016.10.026 |
[5] | Zhang Z G, Wu F, Li T Q, et al. Building digital topography model of the intertidal zone between Caofeidian Nanpu town and Tanggu district using multi-period remote sensing data[C]. Xiamen: IOP Publishing, 2018:12061.DOI: 10.1088/1755-1315/146/1/012061 |
[6] |
McFEETERS S K. The use of the normalized difference water index (NDWI) in the delineation of open water features[J]. International Journal of Remote Sensing, 1996, 17(7):1425-1432. DOI: 10.1080/01431169608948714
doi: 10.1080/01431169608948714 |
[7] |
Xu H Q. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery[J]. International Journal of Remote Sensing, 2006, 27(14):3025-3033. DOI: 10.1080/01431160600589179
doi: 10.1080/01431160600589179 |
[8] |
Qi Y L, Liu D Z, Huang X, et al. Topographical mapping of a bare tidal flat outside a mangrove area based on the waterline method and an iterative hydrodynamic model: A case study of Yingluo Bay, South China[J]. Marine Geodesy, 2019, 42(3):263-285. DOI: 10.1080/01490419.2019.1583617
doi: 10.1080/01490419.2019.1583617 |
[9] | 吴一全, 刘忠林. 遥感影像的海岸线自动提取方法研究进展[J]. 遥感学报, 2019, 23(4):582-602. |
[ Wu Y Q, Liu Z L. Research progress on methods of automatic coastline extraction based on remote sensing images[J]. Journal of Remote Sensing, 2019, 23(4):582-602. ] DOI: 10.11834/jrs.20197410 | |
[10] | 李天祺, 王建超, 吴芳, 等. 基于多算法水边线提取的潮滩DEM构建[J]. 国土资源遥感, 2021, 33(1):38-44. |
[ Li T Q, Wang J C, Wu F, et al. Construction of tidal flat DEM based on multi-algorithm waterline extraction[J]. Remote Sensing for Land & Resources, 2021, 2021, 33(1):38-44.]DOI: 10.6046/gtzyyg.2019337 | |
[11] | Arthur D, Vassilvitskii S. K-means++: The advantages of careful seeding[C]. New Orleans, Louisiana: Society for Industrial and Applied Mathematics, 2007:1027-1035. DOI: 10.1145/1283383.1283494 |
[12] | 刘杰, 程海峰, 韩露, 等. 流域水沙变化和人类活动对长江口河槽演变的影响[J]. 水利水运工程学报, 2021(2):1-9. |
[ Liu J, Cheng H F, Han L, et al. New trends of river channel evolution of the Yangtze River estuary under the influences of inflow and sediment variations and human activities[J]. Hydro-Science and Engineering, 2021(2):1-9. ] DOI: 10.12170/20200313001 | |
[13] | 陈吉余, 沈焕庭, 恽才兴. 长江河口动力过程和地貌演变[M]. 上海: 上海科学技术出版社, 1988. |
[ Chen J Y, Shen H T, Yun C X. Dynamic process and geomorphic evolution of the Yangtze River Estuary[M]. Shanghai: Shanghai Scientific & Technical Publishers, 1988. ] | |
[14] | 王浩斌. 风暴对长江口悬沙浓度的影响及其动力机制[D]. 上海:华东师范大学, 2018. |
[ Wang H B. A study of the suspended sediment concentration in response to the typhoon in the Yangtze Estuary and its dynamic mechanism[D]. Shanghai: East China Normal University, 2018. ] | |
[15] | 袁爽. 近35年长江口潮滩演变遥感研究——以崇明东滩与九段沙为例[D]. 南昌:江西理工大学, 2018. |
[ Yuan S. Remote sensing study on tidal flat evolution in the Yangtze River Estuary in recent 35 years: A case study of Chongming Dongtan and Jiuduansha[D]. Nanchang: Jiangxi University of Science and Technology, 2018. ] | |
[16] | 中华人民共和国水利部. 中国河流泥沙公报(2019)[M]. 北京: 中国水利水电出版社,2020. |
[ Ministry of Water Resources of China. China river water and sediment bulletin (2019)[M]. Beijing: China Water Resources and Hydropower Press, 2020. ] | |
[17] | 范吉庆. 台风对长江口潮间带湿地沉积动力过程的影响[D]. 上海:华东师范大学, 2019. |
[ Fan J Q. Influence of typhoon on sedimentary dynamic process of intertidal wetland in Yangtze Estuary[D]. Shanghai: East China Normal University, 2019. ] | |
[18] | 欧洲航天局. 哥白尼开放存取中心[EB/OL]. https://scihub.copernicus.eu/dhus/#/home/ , 2021-03-03. |
[ European Space Agency. Copernicus Open Access Hub[EB/OL]. https://scihub.copernicus.eu/dhus/#/home/ , 2021-03-03.] | |
[19] | 美国地质勘探局.地球探索者平台[EB/OL]. http://earthexplorer.usgs.gov/ , 2021-03-09. |
[ United States Geological Survey. Earth Explorer[EB/OL]. http://earthexplorer.usgs.gov/ , 2021-03-09.] | |
[20] | 刘向阳. 基于遥感水边线的环渤海地区潮滩研究[D]. 烟台:中国科学院烟台海岸带研究所, 2016. |
[ Liu X Y. Study on tidal flats in the Bohai Rim based on remote sensing waterlines[D]. Yantai: University of Chinese Academy of Sciences, 2016. ] | |
[21] | Erofeeva S, Padman L, Howard S L. Tide Model Driver (TMD)[CP]. GitHub, 2020. https://www.github.com/EarthAndSpaceResearch/TMD_Matlab_Toolbox_v2.5 . |
[22] | 沈芳, 郜昂, 吴建平, 等. 淤泥质潮滩水边线提取的遥感研究及DEM构建——以长江口九段沙为例[J]. 测绘学报, 2008, 37(1):102-107. |
[ Shen F, Gao A, Wu J P, et al. A remotely sensed approach on waterline extraction of silty tidal flat for DEM construction: A case study in Jiuduansha Shoal of Yangtze River[J]. Acta Geodaetica Et Cartographica Sinica, 2008, 37(1):102-107. ] DOI: 10.3321/j.issn:1001-1595.2008.01.018 | |
[23] | MacQueen J. Some methods for the classification and analysis of multivariate observations[C]. Oakland, CA: California Press, 1967:281-297. |
[24] |
Murray N J, Phinn S R, DeWitt M, et al. The global distribution and trajectory of tidal flats[J]. Nature, 2019, 565(7738):222-225. DOI: 10.1038/s41586-018-0805-8
doi: 10.1038/s41586-018-0805-8 |
[25] |
Jia M M, Wang Z M, Mao D H, et al. Rapid, robust, and automated mapping of tidal flats in China using time series Sentinel-2 images and Google Earth Engine[J]. Remote Sensing of Environment, 2021, 255(5):112285. DOI: 10.1016/j.rse.2021.112285
doi: 10.1016/j.rse.2021.112285 |
[26] |
Wang X X, Xiao X M, Zou Z H, et al. Mapping coastal wetlands of China using time series Landsat images in 2018 and Google Earth Engine[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 163(5):312-326. DOI: 10.3969/j.issn.1000-0690.2005.05.017
doi: 10.1016/j.isprsjprs.2020.03.014 |
[27] | 张长宽, 徐孟飘, 周曾, 等. 潮滩剖面形态与泥沙分选研究进展[J]. 水科学进展, 2018, 29(2):269-282. |
[ Zhang Z K, Xu M P, Zhou C, et al. Advances in cross-shore profile characteristics and sediment sorting dynamics of tidal flats[J]. Advances in Water Science, 2018, 29(2):269-282. ] DOI: 10.14042/j.cnki.32.1309.2018.02.015 | |
[28] |
Roberts W, Le Hir P, Whitehouse R J S. Investigation using simple mathematical models of the effect of tidal currents and waves on the profile shape of intertidal mudflats[J]. Continental Shelf Research, 2000, 20(10):1079-1097. DOI: 10.1016/S0278-4343(00)00013-3
doi: 10.1016/S0278-4343(00)00013-3 |
[29] | 龚政, 白雪冰, 靳闯, 等. 基于植被和潮动力作用的潮滩剖面演变数值模拟[J]. 水科学进展, 2018, 29(6):877-886. |
[ Gong Z, Bai X B, Jin C, et al. A numerical model for the cross-shore profile evolution of tidal flats based on vegetation growth and tidal processes[J]. Advances in Water Science, 2018, 29(6):877-886. ] DOI: 10.14042/j.cnki.32.1309.2018.06.013 | |
[30] | 戴志军, 陈吉余, 程和琴, 等. 南汇边滩的沉积特征和沉积物输运趋势[J]. 长江流域资源与环境, 2005, 14(6):63-67. |
[ Dai Z J, Chen J Y, Cheng H Q, et al. Sediment characteristics and transport patterns in Nanhui joint area[J]. Resources and Environment in the Yangtze Basin, 2005, 14(6):63-67. ] DOI: 10.3969/j.issn.1004-8227.2005.06.013 | |
[31] | 罗锋, 蒋冰, 董冰洁, 等. 潮滩剖面形态特征及演变[J]. 科技导报, 2018, 36(14):35-41. |
[ Luo F, Jiang B, Dong B J, et al. Characteristics and evolution of tidal flat profile[J]. Science & Technology Review, 2018, 36(14):35-41. ] DOI: 10.3981/j.issn.1000-7857.2018.14.006 | |
[32] | 吴小根, 王爱军. 人类活动对苏北潮滩发育的影响[J]. 地理科学, 2005, 25(5):614-620. |
[ Wu X G, Wang A J. Impacts of human beings' activities on north Jiangsu tidal flat[J]. Scientia Geographica Sinica, 2005, 25(5):614-620.] DOI: 10.3969/j.issn.1000-0690.2005.05.017 | |
[33] | 路兵, 蒋雪中. 滩涂围垦对崇明东滩演化影响的遥感研究[J]. 遥感学报, 2013, 17(2):335-349. |
[ Lu B, Jiang X Z. Reclamation impacts on the evolution of the tidal flat at Chongming Eastern Beach in Changjiang estuary[J]. Journal of Remote Sensing, 2013, 17(2):335-349. ] DOI: 10.11 834/jrs.20132017 | |
[34] | 朱绳祖, 张国安, 张卫国, 等. 近期长江口崇明岛周边岸滩沉积特征及影响机制[J]. 长江流域资源与环境, 2019, 28(10):2441-2451. |
[ Zhu S Z, Zhang G A, Zhang W G, et al. Recent sedimentary characteristics and impact mechanism of tidal flats in Chongming Island, the Yangtze Estuary[J]. Resources and Environment in the Yangtze Basin, 2019, 28(10):2441-2451. ] DOI: 10.11870/cjlyzyyhj201910016 | |
[35] |
Catalao J, Nico G. Multitemporal backscattering logistic analysis for intertidal bathymetry[J]. IEEE Transactions On Geoscience and Remote Sensing, 2017, 55(2):1066-1073. DOI: 10.1109/TGRS.2016.2619067
doi: 10.1109/TGRS.2016.2619067 |
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