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Remote Sensing for Land & Resources    2021, Vol. 33 Issue (2) : 141-152     DOI: 10.6046/gtzyyg.2020248
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Coastline extraction and spatial-temporal variations using remote sensing technology in Zhoushan Islands
CHEN Chao1,2,3(), CHEN Huixin1, CHEN Dong4, ZHANG Zili2(), ZHANG Xufeng1, ZHUANG Yue5, CHU Yanli6, CHEN Jianyu3, ZHENG Hong1
1. Marine Science and Technology College, Zhejiang Ocean University, Zhoushan 316022, China
2. Zhejiang Province Ecological Environment Monitoring Centre (Zhejiang Key Laboratory of Ecological and Environmental Monitoring, Forewarning and Quality Control), Hangzhou 310012, China
3. State Key Laboratory of Satellite Ocean Environment Dynamics (Second Institute of Oceanography, MNR), Hangzhou 310012, China
4. State Information Center, Beijing 100045, China
5. Xiamen Raw Water Investment Co., Ltd., Xiamen 361000, China
6. School of Economics and Management, Zhejiang Ocean University, Zhoushan 316022, China
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Abstract  

With a special geographical location and abundant marine resources, Zhoushan is the first prefecture-level city composed of islands in China. Therefore, the acquisition of dynamic information on the coastline is of great significance to this area. However, the large amount of suspended sediments, the tortuous coastline, the numerous tidal flats and some other factors have brought a lot of challenges to coastline extraction and the analysis of the spatial-temporal dynamics in Zhoushan Islands. In order to solve this problem, the authors have developed a method for extracting coastline remote sensing information based on the tasseled cap transformation and used long time series satellite remote sensing data to carry out the analysis of the temporal and spatial evolution of the coastline. The experimental results show that the proposed method can effectively remove the influence of suspended sediments, winding coastline and shoals on the extraction of coastline information, and make its position accurate. From 2000 to 2018, the total length of the coastline of Zhoushan Islands increased by about 327.36 km, the average growth length was 18.19 km, the average growth rate was 0.72%, the total area of Zhoushan Islands increased by about 112.26 km2, the average growth area was 6.24 km2, and the average growth rate was 0.49%. The constructions of reclamation and marine projects seem to have been the main reasons for Zhoushan’s coastline changes. This study is of great significance for improving the accuracy of coastline remote sensing information extraction as well as coastal development and protection in complex marine environments.

Keywords Zhoushan Islands      coastline      spatial-temporal variations      complex marine environment      precision evaluation     
ZTFLH:  TP79  
Corresponding Authors: ZHANG Zili     E-mail: chenchao@zjou.com;xjholieagle@163.com
Issue Date: 21 July 2021
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Chao CHEN
Huixin CHEN
Dong CHEN
Zili ZHANG
Xufeng ZHANG
Yue ZHUANG
Yanli CHU
Jianyu CHEN
Hong ZHENG
Cite this article:   
Chao CHEN,Huixin CHEN,Dong CHEN, et al. Coastline extraction and spatial-temporal variations using remote sensing technology in Zhoushan Islands[J]. Remote Sensing for Land & Resources, 2021, 33(2): 141-152.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020248     OR     https://www.gtzyyg.com/EN/Y2021/V33/I2/141
Fig.1  Location of the study area
卫星 传感器 成像时间 卫星 传感器 成像时间
Landsat5 TM 2000.05.14,2000.06.06,
2003.08.27,2003.08.02,
2007.01.26,2006.04.20,
2009.08.27,2009.07.17,
2012.08.16,2012.11.17 		Landsat8 OLI 2015.04.22,
2015.03.12,
2018.06.01,
2018.07.26
Tab.1  Landsat image data
Fig.2  Flowchart of the study
Fig.3  Scatter plot of typical feature in study area (greeness-wetness)
年份 生产者精度 用户精度 漏分误差 错分误差
2000年 86.82 89.30 13.18 10.70
2003年 95.89 98.10 4.11 1.90
2006年 95.74 98.02 4.26 1.98
2009年 93.55 98.42 6.45 1.58
2012年 93.47 97.52 6.53 2.48
2015年 93.69 95.42 6.31 4.58
2018年 96.21 96.26 3.79 3.74
平均值 93.62 96.15 6.38 3.85
Tab.2  Accuracy assessment of coastline information (%)
Fig.4  Contrast map of land range from 2000 to 2018
岛屿 长度/km 面积/km2
2000年 2003年 2006年 2009年 2012年 2015年 2018年 2000年 2003年 2006年 2009年 2012年 2015年 2018年
舟山本岛 185.80 202.50 179.42 180.88 215.88 208.25 209.40 485.79 483.16 497.51 501.54 515.76 518.18 515.02
金塘 55.53 58.80 55.26 52.26 65.88 60.54 65.88 79.04 78.75 79.88 80.91 80.09 86.09 84.71
岱山 99.13 93.84 91.92 90.90 114.54 101.10 113.04 109.00 104.30 112.17 113.40 110.70 113.41 110.85
衢山 109.48 119.52 113.22 110.41 116.58 107.40 111.93 61.18 61.68 63.22 65.48 65.72 65.58 65.56
嵊泗 66.12 72.24 70.28 69.99 79.69 76.36 70.50 22.36 23.35 23.67 23.55 23.87 23.95 25.33
六横 100.31 104.65 104.34 101.40 115.47 122.71 134.84 97.42 95.01 100.22 101.79 105.03 105.47 106.54
朱家尖 92.41 93.18 92.46 93.47 99.32 104.82 98.58 62.00 62.41 63.35 65.39 65.80 65.78 68.47
桃花岛 59.46 63.66 63.12 63.84 62.70 62.16 62.88 41.99 41.05 41.62 41.24 41.24 41.16 41.37
秀山 40.07 43.26 40.68 42.48 43.08 43.08 48.00 24.27 23.36 24.44 24.56 24.42 24.31 24.14
其他岛屿 1 725.88 1 818.18 1 798.99 1 806.46 1 824.81 1 946.14 1 946.50 315.21 312.45 329.89 346.89 343.19 361.78 368.53
总计 2 534.19 2 669.83 2 609.69 2 612.09 2 737.95 2 832.56 2 861.55 1 298.26 1 285.52 1 335.97 1 364.75 1 375.82 1 405.71 1 410.52
Tab.3  Coastline length and area of different islands during 2000 to 2018
Fig.5  Changes of coastal line length and area in Zhoushan from 2000 to 2018
Fig.6  Coastline change in Donggang of the Zhoushan island during 2000 to 2018
Fig.7  Coastline change in Beichan of the Zhoushan island during 2000 to 2018
Fig.8  Coastline change in Cengang of the Zhoushan island during 2000 to 2018
Fig.9-1  Coastline change in Changzhi island and Xiaogan island during 2000 to 2018
Fig.9-2  Coastline change in Changzhi island and Xiaogan island during 2000 to 2018
Fig.10  Coastline change in Zhujiajian island during 2000 to 2018
Fig.11  Coastline change in Shengsi island during 2000 to 2018
Fig.12  Coastline change in Daishan island during 2000 to 2018
Fig.13  Coastline change in Yushan island during 2000 to 2018
Fig.14  Coastline change in Jintang island during 2000 to 2018
Fig.15  Coastline change in Qushan island during 2000 to 2018
Fig.16  Coastline Change in Yangshan during 2000 to 2018
Fig.17  Coastline change in Liuheng island during 2000 to 2018
[1] 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.
[1] 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.
[2] Ai B, Zhang R, Zhang H, et al. Dynamic process and artificial mechanism of coastline change in the Pearl River Estuary[J]. Regional Studies in Marine Science, 2019, 30:100715.
doi: 10.1016/j.rsma.2019.100715 url: https://linkinghub.elsevier.com/retrieve/pii/S2352485518306911
[3] Cao W, Zhou Y, Li R, et al. Mapping changes in coastlines and tidal flats in developing islands using the full time series of Landsat images[J]. Remote Sensing of Environment, 2020, 239:111665.
doi: 10.1016/j.rse.2020.111665 url: https://linkinghub.elsevier.com/retrieve/pii/S0034425720300341
[4] Kelly J T, Gontz A M. Using GPS-surveyed intertidal zones to determine the validity of shorelines automatically mapped by Landsat water indices[J]. International Journal of Applied Earth Observation and Geoinformation, 2018, 65:92-104.
doi: 10.1016/j.jag.2017.10.007 url: https://linkinghub.elsevier.com/retrieve/pii/S030324341730226X
[5] 梁立, 刘庆生, 刘高焕, 等. 基于遥感影像的海岸线提取方法综述[J]. 地球信息科学学报, 2018, 20(12):1745-1755.
doi: 10.12082/dqxxkx.2018.180152
[5] Liang L, Liu Q S, Liu G H, et al. Review of coastline extraction methods based on remote sensing images[J]. Journal of Geo-information Science, 2018, 20(12):1745-1755.
[6] 王志华, 杨晓梅, 苏奋振, 等. 我国海岸带海岛礁遥感研究进展及建议[J]. 中国工程科学, 2019, 21(6):59-63.
[6] Wang Z H, Yang X M, Su F Z, et al. Remote sensing application in China’s coastal zones and islands:Recent progress and some suggestions[J]. Strategic Study of CAE, 2019, 21(6):59-63.
[7] Almonacid-Caballer J, Sánchez-García E, Pardo-Pascual J E, et al. Evaluation of annual mean shoreline position deduced from Landsat imagery as a mid-term coastal evolution indicator[J]. Marine Geology, 2016, 372:79-88.
doi: 10.1016/j.margeo.2015.12.015 url: https://linkinghub.elsevier.com/retrieve/pii/S0025322715300864
[8] 李加林, 王丽佳. 围填海影响下东海区主要海湾形态时空演变[J]. 地理学报, 2020, 75(1):126-142.
doi: 10.11821/dlxb202001010
[8] Li J L, Wang L J. Spatial and temporal evolutions of the major bays in the East China Sea under the influence of reclamataion[J]. Acta Geographica Sinica, 2020, 75(1):126-142.
[9] 隋燕, 张丽, 穆晓东, 等. 海南岛海岸线变迁遥感监测与分析[J]. 海洋学研究, 2018, 36(3):36-43.
[9] Sui Y, Zhang L, Mu X D, et al. Coastline change detection and analysis with remote sensing in Hainan Island[J]. Journal of Marine Sciences, 2018, 36(3):36-43.
[10] 毋亭, 侯西勇. 海岸线变化研究综述[J]. 生态学报, 2016, 36(4):1170-1182.
[10] Wu T, Hou X Y. Review of research on coastline changes[J]. Acta Ecologica Sinica, 2016, 36(4):1170-1182.
[11] Sun W, Peng J, Yang G, et al. Correntropy-based sparse spectral clustering for hyperspectral band selection[J]. IEEE Geoscience and Remote Sensing Letters, 2020, 17(3):484-488.
doi: 10.1109/LGRS.8859 url: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8859
[12] Sun W, Yang G, Peng J, et al. Lateral-slice sparse tensor robust principal component analysis for hyperspectral image classification[J]. IEEE Geoscience and Remote Sensing Letters, 2020, 17(1):107-111.
doi: 10.1109/LGRS.8859 url: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8859
[13] 孙伟伟, 杨刚, 陈超, 等. 中国地球观测遥感卫星发展现状及文献分析[J]. 遥感学报, 2020, 24(5):479-510.
[13] Sun W W, Yang G, Chen C, et al. Development status and literature analysis of China’s earth observation remote sensing satellites[J]. Journal of Remote Sensing, 2019, 24(5):479-510.
[14] 张兵. 遥感大数据时代与智能信息提取[J]. 武汉大学学报(信息科学版), 2018, 43(12):1861-1871.
[14] Zhang B. Remotely sensed big data era and intelligent information extraction[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12):1861-1871.
[15] Dai C, Howat I M, Larour E, et al. Coastline extraction from repeat high resolution satellite imagery[J]. Remote Sensing of Environment, 2019, 229:260-270.
doi: 10.1016/j.rse.2019.04.010 url: https://linkinghub.elsevier.com/retrieve/pii/S0034425719301531
[16] Sagar S, Roberts D, Bala B, et al. Extracting the intertidal extent and topography of the Australian coastline from a 28 year time series of Landsat observations[J]. Remote Sensing of Environment, 2017, 195:153-169.
doi: 10.1016/j.rse.2017.04.009 url: https://linkinghub.elsevier.com/retrieve/pii/S0034425717301591
[17] Ghosh M K, Kumar L, Roy C. Monitoring the coastline change of Hatiya island in Bangladesh using remote sensing techniques[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015, 101:137-144.
doi: 10.1016/j.isprsjprs.2014.12.009 url: https://linkinghub.elsevier.com/retrieve/pii/S0924271614002846
[18] Li W, Gong P. Continuous monitoring of coastline dynamics in Western Florida with a 30-year time series of Landsat imagery[J]. Remote Sensing of Environment, 2016, 179:196-209.
doi: 10.1016/j.rse.2016.03.031 url: https://linkinghub.elsevier.com/retrieve/pii/S0034425716301249
[19] Liu C, Wu X, Cao X, et al. Analysis of coastline changes and the socio-economic driving mechanisms in Shenzhen,China[J]. Marine Geodesy, 2017, 40(6):378-403.
doi: 10.1080/01490419.2017.1319447 url: https://www.tandfonline.com/doi/full/10.1080/01490419.2017.1319447
[20] Wu T, Hou X, Xu X. Spatio-temporal characteristics of the mainland coastline utilization degree over the last 70 years in China[J]. Ocean & Coastal Management, 2014, 98:150-157.
[21] 张云芝, 张千力, 胡云锋. 2010—2017年珠江河口海岸线遥感监测和动态变化分析[J]. 海洋通报, 2019, 38(2):217-224.
[21] Zhang Y Z, Zhang Q L, Hu Y F. Remote sensing monitoring and dynamic analysis of the Pearl River Estuary coastline during 2010—2017[J]. Marine Science Bulletin, 2019, 38(2):217-224.
[22] Hsiao Y S, Hwang C, Cheng L C, et al. High-resolution depth and coastline over major atolls of South China Sea from satellite altimetry and imagery[J]. Remote Sensing of Environment, 2016, 176:69-83.
doi: 10.1016/j.rse.2016.01.016 url: https://linkinghub.elsevier.com/retrieve/pii/S0034425716300177
[23] Mulcahy N, Kennedy D M, Blanchon P. Hurricane-induced shoreline change and post-storm recovery:Northeastern Yucatan Peninsula,Mexico[J]. Journal of Coastal Research, 2016, 75(s1):1192-1196.
doi: 10.2112/SI75-239.1 url: http://www.bioone.org/doi/10.2112/SI75-239.1
[24] Hou X, Wu T, Hou W, et al. Characteristics of coastline changes in Mainland China since the early 1940s[J]. Science China Earth Sciences, 2016, 59,1791-1802.
doi: 10.1007/s11430-016-5317-5 url: http://link.springer.com/10.1007/s11430-016-5317-5
[25] Maglione P, Parente C, Vallario A. Coastline extraction using high resolution WorldView-2 satellite imagery[J]. European Journal of Remote Sensing, 2014, 47(1),685-699.
doi: 10.5721/EuJRS20144739 url: https://www.tandfonline.com/doi/full/10.5721/EuJRS20144739
[26] Pillet V, Duvat V K E, Krien Y, et al. Assessing the impacts of shoreline hardening on beach response to hurricanes:Saint-Barthélemy,Lesser Antilles[J]. Ocean & Coastal Management, 2019, 174:71-91.
[27] Quang T N, Cong T H, Quang D L, et al. Historical monitoring of shoreline changes in the Cua Dai Estuary,Central Vietnam using multi-temporal remote sensing data[J]. Geosciences, 2017, 7(3):7030072.
[28] Sun Y, Gao C, Li J, et al. Evaluating urban heat island intensity and its associated determinants of towns and cities continuum in the Yangtze River Delta urban agglomerations[J]. Sustainable Cities and Society, 2019, 50:101659.
doi: 10.1016/j.scs.2019.101659 url: https://linkinghub.elsevier.com/retrieve/pii/S2210670719302276
[29] Bera R, Maiti R. Quantitative analysis of erosion and accretion (1975—2017) using DSAS:A study on Indian Sundarbans[J]. Regional Studies in Marine Science, 2019, 28:100583.
doi: 10.1016/j.rsma.2019.100583 url: https://linkinghub.elsevier.com/retrieve/pii/S2352485518302044
[30] Bronstein M M, Bruna J, Lecun Y, et al. Geometric deep learning:Going beyond euclidean data[J]. IEEE Singnal Processing Magazine, 2017, 34(4):18-42.
[31] Li J, Ye M, Pu R, et al. Spatiotemporal change patterns of coastlines in Zhejiang Province,China,over the last twenty-five years[J]. Sustainability, 2018, 10(2):477.
doi: 10.3390/su10020477 url: http://www.mdpi.com/2071-1050/10/2/477
[32] Liu C, Xiao Y, Yang J. A coastline detection method in polarimetric SAR images mixing the region-based and edge-based active contour models[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(7):3735-3747.
doi: 10.1109/TGRS.2017.2679112 url: http://ieeexplore.ieee.org/document/7887745/
[33] 朱长明, 张新, 骆剑承, 等. 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, 2013, 25(2):69-74.doi; 10.6046/gtzyyg.2013.02.13.
doi: 10.6046/gtzyyg.2013.02.13
[33] Zhu C M, Zhang X, Luo J C, et al. Automatic extraction of coastline by remote sensing technology based on SVM and auto-selection of training samples[J]. Remote Sensing for Land and Resources, 2013, 25(2):69-74.doi; 10.6046/gtzyyg.2013.02.13.
doi: 10.6046/gtzyyg.2013.02.13
[34] 胡亚斌, 任广波, 马毅, 等. 基于多时相GF-1和Landsat影像的连云港市44年海岸线遥感监测与演变分析[J]. 海洋技术学报, 2019, 38(6):9-16.
[34] Hu Y B, Ren G B, Ma Y, et al. Remote sensing monitoring and evolution analysis of the coastline in the Lianyungang City based on multi-temporal GF-1 and Landsat images during 44 years[J]. Ocean Technology, 2019, 38(6):9-16.
[35] Tsokos A, Kotsi E, Petrakis S, et al. Combining series of multi-source high spatial resolution remote sensing datasets for the detection of shoreline displacement rates and the effectiveness of coastal zone protection measures[J]. Journal of Coastal Conservation, 2018, 22:431-441.
doi: 10.1007/s11852-018-0591-3 url: https://doi.org/10.1007/s11852-018-0591-3
[36] Wu W, Yang Z, Tian B, et al. Impacts of coastal reclamation on wetlands:Loss,resilience,and sustainable management[J]. Estuarine,Coastal and Shelf Science, 2018, 210:153-161.
doi: 10.1016/j.ecss.2018.06.013 url: https://linkinghub.elsevier.com/retrieve/pii/S0272771417307503
[37] Xu N, Gong P. Significant coastline changes in China during 1991—2015 tracked by Landsat data[J]. Science Bulletin, 2018, 63(14):883-886.
doi: 10.1016/j.scib.2018.05.032 url: https://linkinghub.elsevier.com/retrieve/pii/S2095927318302548
[38] Liu Y, Li J, Yuan Q, et al. Comparative research on the impact of human activities on changes in coastline and landscape in bay areas:A case study with Xiangshangang bay,China and Tampa bay,USA[J]. Acta Geographica Sinica, 2016, 71(1):86-103.
[39] Naser H A. The role of environmental impact assessment in protecting coastal and marine environments in rapidly developing islands:The case of Bahrain,Arabian Gulf[J]. Ocean & Coastal Management, 2015, 104:159-169.
[40] 陈超, 何新月, 傅姣琪, 等. 基于缨帽变换的农田洪水淹没范围遥感信息提取[J]. 武汉大学学报(信息科学版), 2019, 44(10):1560-1566.
[40] Chen C, He X Y, Fu J Q, et al. A method of flood submerging area extracting for farmland based on tasseled cap transformation from remote sensing images[J]. Geomatics and Information Science of Wuhan University, 2019, 44(10):1560-1566.
[41] 沙宏杰, 张东, 崔丹丹, 等. 剖面形态自适应的海岸线遥感推算方法[J]. 海洋学报, 2019, 41(9):170-180.
[41] Sha H J, Zhang D, Cui D D, et al. Remote sensing prediction method of coastline based on self-adaptive profile morphology[J]. Haiyang Xuebao, 2019, 41(9):170-180.
[42] 鲁旭, 陈超. 基于遥感数据的舟山市土地利用时空格局研究[J]. 浙江科技学院学报, 2018, 30(5):404-411.
[42] Lu X, Chen C. Research on spatial-temporal pattern of land use in Zhoushan City by using remote sensing images[J]. Journal of Zhejiang University of Science and Technology, 2018, 30(5):404-411.
[43] Qiao G, Mi H, Wang W, et al. 55-year (1960—2015) spatiotemporal shoreline change analysis using historical DISP and Landsat time series data in Shanghai[J]. International Journal of Applied Earth Observation and Geoinformation, 2018, 68:238-251.
doi: 10.1016/j.jag.2018.02.009 url: https://linkinghub.elsevier.com/retrieve/pii/S0303243418301466
[44] Zhang B, Chen Z, Peng D, et al. Remote sensed big data:Evolution in model development for information extraction[J]. Proceedings of the IEEE, 2019, 107(12):2294-2301.
doi: 10.1109/JPROC.2019.2948454
[45] Tian B, Wu W, Yang Z, et al. Drivers,trends,and potential impacts of long-term coastal reclamation in China from 1985 to 2010[J]. Estuarine,Coastal and Shelf Science, 2016, 170:83-90.
doi: 10.1016/j.ecss.2016.01.006 url: https://linkinghub.elsevier.com/retrieve/pii/S0272771416300063
[46] Tran T V, Tien T, Xuan A, Phan N H, et al. Application of remote sensing and GIS for detection of long-term mangrove shoreline changes in Mui Ca Mau,Vietnam[J]. Biogeosciences, 2014, 11:3781-3795.
doi: 10.5194/bg-11-3781-2014 url: https://bg.copernicus.org/articles/11/3781/2014/
[47] 李加林, 田鹏, 邵姝遥, 等. 中国东海区大陆海岸线变迁及其开发利用强度分析[J]. 自然资源学报, 2019, 34(9),1886-1901.
[47] Li J L, Tian P, Shao S Y, et al. The changes of continental coastline and its development and utilization intensity in the East China Sea[J]. Journal of Natural Resources, 2019, 34(9):1886-1901.
[48] Chen C, Bu J, Zhang Y, et al. The application of the tasseled cap transformation and feature knowledge for the extraction of coastline information from remote sensing images[J]. Advances in Space Research, 2019, 64(9):1780-1791.
doi: 10.1016/j.asr.2019.07.032 url: https://linkinghub.elsevier.com/retrieve/pii/S0273117719305381
[49] Chen C, Fu J, Zhang S, et al. Coastline information extraction based on the tasseled cap transformation of Landsat-8 OLI images[J]. Estuarine,Coastal and Shelf Science, 2019, 217:281-291.
doi: 10.1016/j.ecss.2018.10.021 url: https://linkinghub.elsevier.com/retrieve/pii/S0272771418306139
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