平衡剖面模式下海岸线遥感提取中不同潮位校正方法对比研究*

doi:10.11978/2023009

热带海洋学报 ›› 2023, Vol. 42 ›› Issue (6): 52-62.doi: 10.11978/2023009CSTR: 32234.14.2023009

平衡剖面模式下海岸线遥感提取中不同潮位校正方法对比研究^*

巫统仁¹^,²(), 刘培²^,³(), 于吉涛²^,³, 文婷婷¹^,²

1.河南理工大学, 河南焦作 454003
2.海南省海洋与渔业科学院, 海南海口 571126
3.海南热带海洋学院崖州湾创新研究院, 海南三亚 572025

收稿日期:2023-01-24 修回日期:2023-03-23 出版日期:2023-11-10 发布日期:2023-04-07
作者简介:
巫统仁(1999—), 男, 湖南省浏阳市人, 硕士研究生, 从事遥感影像处理与海岸带遥感观测研究。email: wtw2021yjs@163.com
*论文在研究和写作过程中得到了海南省海洋与渔业科学院王道儒研究员的指导和帮助, 在此表示感谢！感谢海南高分数据与应用中心提供高分辨率遥感数据支撑！
基金资助:
国家自然科学基金(42071007); 海南热带海洋学院崖洲湾创新研究院开放课题重点项目(2022CXYKFKT03); 海南省自然科学基金(423MS120); 海南省海洋与渔业科学院省本级课题(KYL-2023-01)

Comparative study on different tide level correction methods in remote sensing extraction of coastline under balanced profile model^*

WU Tongren¹^,²(), LIU Pei²^,³(), YU Jitao²^,³, WEN Tingting¹^,²

1. Henan Polytechnic University, Jiaozuo 454003, China
2. Hainan Academy of Ocean and Fisheries Sciences, Haikou 571126, China
3. Yazhou Bay Innovation Institute, Hainan Tropical Ocean University, Sanya 572025, China

Received:2023-01-24 Revised:2023-03-23 Online:2023-11-10 Published:2023-04-07
Supported by:
National Natural Science Foundation of China(42071007); The Open project program of Yazhou Bay Innovation Research Institute of Hainan Tropical Ocean University(2022CXYKFKT03); Hainan Provincial Natural Science Foundation of China(423MS120); Foundation of Hainan Academy of Ocean and Fisheries Sciences(KYL-2023-01)

摘要/Abstract

摘要：

潮位校正是海岸线提取的重要步骤。针对当前基于遥感的海岸线提取多以瞬时水边线为主, 潮位校正方法多样且精度低等问题, 本文在分析平衡剖面模式的基础上, 引入改进的Bodge平衡剖面潮位校正的高分辨率遥感海岸线潮位校正新方法, 并对常见潮位校正方法作对比分析。选取广东省典型砂质岸滩海门湾和平海湾, 协同归一化水体指数、大津算法、数学形态学、边缘检测算子, 实现瞬时水边线的快速、自动化提取, 然后利用不同潮位校正方法获取真实岸线数据, 最后结合RTK(real-time kinematic)实测点位数据对基于平衡剖面模型的潮位校正、拟合线性潮位校正以及传统潮位校正方法提取结果进行对比分析。研究表明: (1)基于平衡剖面模式的潮位校正方法精度优于拟合线性潮位校正方法和传统潮位校正方法。(2)在同属基于平衡剖面模式的潮位校正方法中, 基于改进的Bodge平衡剖面模式的潮位校正方法相比较于Bruun-Dean平衡剖面模式潮位校正方法精度更高; 基于参考岸线数据, 利用断面法验证了所提取的岸线精度达到2m。研究结果可为海岸线精确提取和海岸规划提供参考案例和决策依据。

关键词: Bodge平衡剖面模式, 潮位校正, 海岸线提取, 高分影像

Abstract:

Tide level correction is an important step in coastline extraction. Regarding to the current problems of remote sensing based coastline extraction, such as the predominance of instantaneous water boundary line, the diversity of tidal level correction methods, and low accuracy, this paper introduces a new high-resolution remote sensing coastline tidal level correction method based on the improved Bodge balanced profile tidal level correction, and makes a comparative analysis of common tidal level correction methods. The research selects typical sandy beaches, Haimen Bay and Pinghai Bay in Guangdong Province, and coordinates with normalized difference water index, Otsu algorithm, mathematical morphology and edge detection operator to realize fast and automatic extraction of instantaneous water boundary line, then, different tidal level correction methods are used to obtain real coastline data. Finally, combined with real-time kinematic (RTK) measured point data, the results of tidal level correction based on the balanced profile model, fitting linear tidal level correction, and traditional tidal level correction methods are compared and analyzed. The results show that: (1) The accuracy of the tidal level correction method based on the balanced profile model is superior to the fitting linear tidal level correction method and the traditional tidal level correction method. (2) Among the tidal level correction methods that are both based on the balanced profile model, the tidal level correction method based on the improved Bodge balanced profile model has higher accuracy than the tidal level correction method based on the Bruun-Dean balanced profile model; based on the reference coastline data, the accuracy of the extracted shoreline is verified to be 2 meters using the cross-sectional method. The research results can provide cases and decision-making basis for accurate coastline extraction and coastal planning.

Key words: Bodge balanced profile model, tidal correction, coastline extraction, high resolution image

巫统仁, 刘培, 于吉涛, 文婷婷. 平衡剖面模式下海岸线遥感提取中不同潮位校正方法对比研究^*[J]. 热带海洋学报, 2023, 42(6): 52-62.

WU Tongren, LIU Pei, YU Jitao, WEN Tingting. Comparative study on different tide level correction methods in remote sensing extraction of coastline under balanced profile model^*[J]. Journal of Tropical Oceanography, 2023, 42(6): 52-62.

图/表 13

图1

图2

图3

图4

图5

图6

图7

图8

图9

图10

表1

表2

图11

参考文献 34

[1]	陈玮彤, 张东, 施顺杰, 等, 2017. 江苏中部淤泥质海岸岸线变化遥感监测研究[J]. 海洋学报, 39(5): 138-148.
	CHEN WEITONG, ZHANG DONG, SHI SHUNJIE, et al, 2017. Research on monitoring coastline changes by remote sensing in muddy coast, central Jiangsu coast[J]. Haiyang Xuebao, 39(5): 138-148 (in Chinese with English abstract).
[2]	陈子燊, 1997. 海滩剖面形态与地形动态研究的进展[J]. 海洋通报, (1): 86-91.
	CHEN ZISHEN, 1997. Progress in studies on the shapes and dynamics of beach profiles[J]. Marine Science Bulletin, (1): 86-91 (in Chinese with English abstract).
[3]	贾明明, 刘殿伟, 王宗明, 等, 2013. 面向对象方法和多源遥感数据的杭州湾海岸线提取分析[J]. 地球信息科学学报, 15(2): 262-269. doi: 10.3724/SP.J.1047.2013.00262
	JIA MINGMING, LIU DIANWEI, WANG ZONGMING, et al, 2013. Coastline changes in Hangzhou Bay based on object-oriented method using multi-source remote sensing data[J]. Journal of Geo-Information Science, 15(2): 262-269 (in Chinese with English abstract). doi: 10.3724/SP.J.1047.2013.001262
[4]	李志强, 陈子燊, 2002. 海滩平衡剖面形态研究进展[J]. 海洋通报, (5): 82-89.
	LI ZHIQIANG, CHEN ZISHEN, 2002. Progress in the studies on beach profile shapes[J]. Marine Science Bulletin, (5): 82-89 (in Chinese with English abstract).
[5]	李志强, 陈子燊, 2009. 海滩平衡剖面模型中参数意义及相互关系探讨[J]. 海洋工程, 27(4): 108-115.
	LI ZHIQIANG, CHEN ZISHEN, 2009. Analysis on the parameters’ meanings and relations in equilibrium beach profile models[J]. Ocean Engineering, 27(4): 108-115 (in Chinese with English abstract).
[6]	林松, 俞晓牮, 庄小冰, 等, 2020. 厦门岛海岸线分形特性演变规律的研究[J]. 海洋科学进展, 38(1): 121-129.
	LIN SONG, YU XIAOJIAN, ZHUANG XIAOBING, et al, 2020. Fractal characteristics evolution of coastline of the Xiamen Island[J]. Advances in Marine Science, 38(1): 121-129 (in Chinese with English abstract).
[7]	刘百桥, 孟伟庆, 赵建华, 等, 2015. 中国大陆1990—2013年海岸线资源开发利用特征变化[J]. 自然资源学报, 30(12): 2033-2044.
	LIU BAIQIAO, MENG WEIQING, ZHAO JIANHUA, et al, 2015. Variation of coastline resources utilization in China from 1990 to 2013[J]. Journal of Natural Resources, 30(12): 2033-2044 (in Chinese with English abstract).
[8]	刘善伟, 张杰, 马毅, 等, 2011. 遥感与DEM相结合的海岸线高精度提取方法[J]. 遥感技术与应用, 26(5): 613-618.
	LIU SHANWEI, ZHANG JIE, MA YI, et al, 2011. Coastline extraction method based on remote sensing and DEM[J]. Remote Sensing Technology and Application, 26(5): 613-618 (in Chinese with English abstract).
[9]	马小峰, 赵冬至, 张丰收, 等, 2007. 海岸线卫星遥感提取方法研究进展[J]. 遥感技术与应用, 22(4): 575-580.
	MA XIAOFENG, ZHAO DONGZHI, ZHANG FENGSHOU, et al, 2007. An overview of means of withdrawing coastline by remote sensing[J]. Remote sensing Technology and Application, 22(4): 575-580 (in Chinese with English abstract).
[10]	邱志伟, 刘晓霞, 章铭诚, 2021. 基于星载SAR影像的苏北地区海岸线提取研究[J]. 地理空间信息, 19(1): 4-7, 141.
	QIU ZHIWEI, LIU XIAOXIA, ZHANG MINGCHENG, 2021. Research on extraction of coastline in north Jiangsu based on spaceborne SAR image[J]. Geospatial Information, 19(1): 4-7, 141 (in Chinese with English abstract).
[11]	沈琦, 汪承义, 赵斌, 2012. 几何活动轮廓模型用于高分辨率遥感影像海岸线自动提取[J]. 复旦学报(自然科学版), 51(1): 77-82, 104.
	SHEN QI, WANG CHENYI, ZHAO BIN, 2012. Automatic waterline extraction in VHR imagery using geometric active contour model[J]. Journal of Fudan University (Natural Science), 51(1): 77-82, 104 (in Chinese with English abstract).
[12]	盛辉, 张驰, 万剑华, 2021. 基于多时相遥感数据的海岸线自动提取方法[J]. 海洋科学, 45(5): 16-22.
	SHENG HUI, ZHANG CHI, WAN JIANHUA, 2021. Automatic coastline extraction method based on multi-temporal remote sensing data[J]. Marine Science, 45(5): 16-22 (in Chinese with English abstract).
[13]	孙孟昊, 蔡玉林, 顾晓鹤, 等, 2019. 基于潮汐规律修正的海岸线遥感监测[J]. 遥感信息, 34(6): 105-112.
	SUN MENGHAO, CAI YULIN, GU XIAOHE, et al, 2019. Coastline remote sensing monitoring based on tidal level correction[J]. Remote Sensing Information, 34(6): 105-112 (in Chinese with English abstract).
[14]	王常颖, 王志锐, 初佳兰, 等, 2017. 基于决策树与密度聚类的高分辨率影像海岸线提取方法[J]. 海洋环境科学, 36(4): 590-595.
	WANG CHANGYING, WANG ZHIRUI, CHU JIALAN, et al, 2017. Coastline extraction from high-resolution image based on decision tree and density clustering algorithms[J]. Marine Environmental Science, 36(4): 590-595 (in Chinese with English abstract).
[15]	王靖雯, 牛振国, 2017. 基于潮位校正的盐城滨海潮间带遥感监测及变化分析[J]. 海洋学报, 39(5): 149-160.
	WANG JINGWEN, NIU ZHENGUO, 2017. Remote-sensing analysis of Yancheng intertidal zones based on tidal correction[J]. Haiyang Xuebao, 39(5): 149-160 (in Chinese with English abstract).
[16]	毋亭, 侯西勇, 2016. 海岸线变化研究综述[J]. 生态学报, 36(4): 1170-1182.
	WU TING, HOU XIYONG, 2016. Review of research on coastline changes[J]. Acta Ecologica Sinica, 36(4): 1170-1182 (in Chinese with English abstract).
[17]	吴一全, 刘忠林, 2019. 遥感影像的海岸线自动提取方法研究进展[J]. 遥感学报, 23(4): 582-602.
	WU YIQUAN, LIU ZHONGLIN, 2019. Research progress on methods of automatic coastline extraction based on remote sensing images[J]. Journal of Remote Sensing, 23(4): 582-602 (in Chinese with English abstract).
[18]	徐涵秋, 2005. 利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J]. 遥感学报, (5): 589-595.
	XU HANQIU, 2005. A study on information extraction of water body with the modified Normalized Difference Water Index (MNDWI)[J]. Journal of Remote Sensing, (5): 589-595 (in Chinese with English abstract).
[19]	尹航, 戚洪帅, 蔡锋, 等, 2022. 高分影像砂质海岸线精细提取及校正方法[J]. 海洋学报, 44(4): 143-152.
	YIN HANG, QI HONGSHUAI, CAI FENG, et al, 2022. Sandy coastline fine extraction and correction method based on high resolution image[J]. Haiyang Xuebao, 44(4): 143-152 (in Chinese with English abstract).
[20]	袁欣智, 江洪, 陈芸芝, 等, 2016. 一种应用大津法的自适应阈值水体提取方法[J]. 遥感信息, 31(5): 36-42.
	YUAN XINZHI, JIANG HONG, CHEN YUNZHI, et al, 2016. Extraction of water body information using adaptive threshold value and OTSU algorithm[J]. Remote Sensing Information, 31(5): 36-42 (in Chinese with English abstract).
[21]	张锦, 赖祖龙, 孙杰, 2020. Otsu法、区域生长法及形态学相结合的遥感图像海岸线提取[J]. 测绘通报, (10): 89-92. doi: 10.13474/j.cnki.11-2246.2020.0325
	ZHANG JIN, LAI ZULONG, SUN JIE, 2020. Coastline extraction of remote sensing image by combining Otsu, regional growth method with morphology[J]. Bulletin of Surveying and Mapping, (10): 89-92 (in Chinese with English abstract). doi: 10.13474/j.cnki.11-2246.2020.0325
[22]	张翔, 王霄鹏, 黄安齐, 等, 2021. 基于遥感影像提取山东半岛复杂海岸线及海岸线多年变迁研究[J]. 海洋湖沼通报, 43(2): 171-181.
	ZHANG XIANG, WANG XIAOPENG, HUANG ANQI, et al, 2021. Extraction of complex coastline feature and its multi-year changes in Shandong Peninsula Based on remote sensing image[J]. Transactions of Oceanology and limnology, 43(2): 171-181 (in Chinese with English abstract).
[23]	张旭凯, 张霞, 杨邦会, 等, 2013. 结合海岸类型和潮位校正的海岸线遥感提取[J]. 国土资源遥感, 25(4): 91-97.
	ZHANG XUKAI, ZHANG XIA, YANG BANGHUI, 2013. Coastline extraction using remote sensing based on coastal type and tidal correction[J]. Remote Sensing of Land Resources, 25(4): 91-97 (in Chinese with English abstract).
[24]	郑修诚, 周斌, 雷惠, 等, 2022. 基于GEE的杭州湾慈溪段潮滩提取及时空变化分析[J]. 自然资源遥感, 34(1): 18-26.
	ZHENG XIUCHENG, ZHOU BIN, LEI HUI, 2022. Extraction and spatio-temporal change analysis of the tidal flat in Cixi section of Hangzhou Bay based on Google Earth Engine[J]. Remote Sensing for Natural Resources, 34(1): 18-26 (in Chinese with English abstract).
[25]	朱长明, 张新, 骆剑承, 等, 2013. 基于样本自动选择与SVM结合的海岸线遥感自动提取[J]. 国土资源遥感, 25(2): 69-74.
	ZHU CHANGMING, ZHANG XIN, LUO JIANCHENG, et al, 2013. Automatic extraction of coastline by remote sensing technology based on SVM and auto-selection of training samples[J]. Remote Sensing for Land and Resources, 25(2): 69-74 (in Chinese with English abstract).
[26]	朱萝云, 刘婷婷, 凡仁福, 等, 2022. 1986-2019年粤东企望湾砂质海岸线演变过程与驱动机制研究[J]. 海洋学报, 44(7): 20-32.
	ZHU LUOYUN, LIU TINGTING, FAN RENFU, et al, 2022. Study on the evolution process and driving mechanism of the sandy shoreline of the Qiwang Bay in eastern Guangdong from 1986 to 2019[J]. Haiyang Xuebao, 44(7): 20-32 (in Chinese with English abstract).
[27]	BODGE K R, 1992. Representing equilibrium beach profiles with an exponential expression[J]. Journal of coastal research, 8(1): 47-55.
[28]	LI JIALIN, YE MENGYAO, PU RUILIANG, et al, 2018. Spatiotemporal change patterns of coastlines in Zhejiang Province, China, over the last twenty-five years[J]. Sustainability, 10(2): 477. doi: 10.3390/su10020477
[29]	LIU H, JEZEK K C, 2004. Automated extraction of coastline from satellite imagery by integrating Canny edge detection and locally adaptive thresholding methods[J]. International Journal of Remote Sensing, 25(5): 937-958. doi: 10.1080/0143116031000139890
[30]	SUN WEIHUA, CHEN BIN, MESSINGER D W, 2014. Nearest-neighbor diffusion-based pan-sharpening algorithm for spectral images[J]. Optical Engineering, 53(1): 13107-13108. doi: 10.1117/1.OE.53.1.013107
[31]	TANG WEI, ZHAO CHENGYI, LIN JING, et al, 2022. Improved spectral water index combined with Otsu algorithm to extract muddy coastline data[J]. Water, 14(6): 855. doi: 10.3390/w14060855
[32]	VOS K, HARLEY M D, SPLINTER K D, et al, 2019. Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery[J]. Coastal Engineering, 150: 160-174. doi: 10.1016/j.coastaleng.2019.04.004
[33]	YU JITAO, DING YUANTING, CHENG HUANGXIN, et al, 2016. Typical equilibrium beach profile models and their significances from different segments of a headland-bay beach[J]. China Ocean Engineering, 30(4): 637-650. doi: 10.1007/s13344-016-0041-7
[34]	ZHANG YAOWEN, LIN HAOLI, YE GUANQIONG, 2022. Long-term benefits of coastline ecological restoration in China[J]. Journal of Marine Science and Engineering, 10(4): 541. doi: 10.3390/jmse10040541

地区	拟合模型	确定系数	相关系数	误差平方和
海门湾	Bodge剖面模型	0.95	0.98	3.95
海门湾	Bruun-Dean剖面模型	0.90	0.97	8.05
海门湾	线性拟合模型	0.43	0.92	45.16
平海湾	Bodge剖面模型	0.93	0.87	3.02
平海湾	Bruun-Dean剖面模型	0.92	0.80	4.72
平海湾	线性拟合模型	0.90	0.71	9.76

潮位校正方法	最大偏移量/m	最小偏移量/m	平均偏移量/m	标准差/m
Bodge模型潮位校正	6.7	0.1	2.0	1.2
Bruun-Dean模型潮位校正	8.2	0	2.6	1.8
线性模型潮位校正	9.6	2.6	3.9	2.1
传统潮位校正	8.9	1.0	3.1	2.0

平衡剖面模式下海岸线遥感提取中不同潮位校正方法对比研究^*

Comparative study on different tide level correction methods in remote sensing extraction of coastline under balanced profile model^*

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 13

参考文献 34

相关文章 0

Metrics

本文评价

推荐阅读 0

平衡剖面模式下海岸线遥感提取中不同潮位校正方法对比研究*

Comparative study on different tide level correction methods in remote sensing extraction of coastline under balanced profile model*

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 13

参考文献 34

相关文章 0

Metrics

本文评价

推荐阅读 0

平衡剖面模式下海岸线遥感提取中不同潮位校正方法对比研究^*

Comparative study on different tide level correction methods in remote sensing extraction of coastline under balanced profile model^*