سابِق|تال

Research progress on methods of automatic coastline extraction based on remote sensing images

  • role： First author第一作者
  • Affiliation：

    College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

    State Key Laboratory of Computer Aided Design and Computer Graphics, Zhejiang University, Hangzhou 310058, China

  • Email：nuaaimage@163.com
  • Introduction：吴一全，1963年生，男，教授，研究方向为遥感图像处理、分析与理解，目标检测与识别。E-mail：nuaaimage@163.com
WU Yiquan12,  
  • Affiliation：

    College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

LIU Zhonglin1

ملخص

The coastline refers to the boundary line between land and sea. The coastline detection is an important part of studying the effects of land-sea interaction and human activities on coastal zones. It is also significant for the effective development, integrated management and sustainable exploitation of coastal resources and protection of coastal ecosystems. Therefore, it is critical to achieve the extraction of coastline quickly and accurately. Remote sensing technology has gradually become a way to detect the location of the coastline and monitor its dynamic changes with its wide range, high temporal resolution, high spatial resolution, multispectral, low cost and other prominent advantages, overcoming the shortcomings of traditional coastline detection methods of long time period, high intensity of labor and so on. This paper reviews the research progress on methods of automatic coastline extraction based on remote sensing images proposed in recent years. First, the definition and classification of the coastline are given. The two stages of extraction of the instantaneous waterline and the real coastline and the specific extraction process are clarified. Then, these methods are divided into eight categories: threshold segmentation, edge detection operator, active contour model, data mining, multiresolution analysis, object-oriented, polarization and other methods. And the basic ideas of the main methods of coastline extraction are elaborated. Finally, the advantages and disadvantages of all kinds of methods are analyzed and compared. The principle of tidal correction and the methods of accuracy evaluation are expounded, and the research work of the next step is prospected. The detailed feature description of main methods are as follows. Threshold segmentation method is simple and easy to implement. While the selection of appropriate threshold is a certain degree of difficulty, and the extraction accuracy needs to be improved. The edge detection operator method has a good effect on the extraction of edge. Simultaneously, this method is susceptible to noise and prone to detect pseudo edges, even the continuity of extracted coastline is poor. The extraction result of the active contour model is accurate. However, the model has high complexity and large computational burden. Data mining method utilizes intelligent means to achieve automatic extraction of coastline. But a variety of methods need to be combined to make the extraction accuracy higher. Although the multiresolution analysis method can obtain rich edge information, the mostly applied wavelets have a limitation of dealing with directional information. Object-oriented approach can achieve image segmentation of a higher level and reduce the influence of texture and other characteristics inside the cell. It cannot make full use of the implicit information of the image when the amount of data is large. And the polarization method is essentially a threshold segmentation method. The only difference is the selection method of threshold. The polarization method achieves threshold selection by usage of different polarization methods of SAR images. In the end, in view of the deficiency of currently existing methods, the following feasible research approaches and prominent research prospects of automatic coastline extraction based on remote sensing images are put forward: constructing dataset, utilizing hyperspectral data, employing deep learning method, adopting swarm intelligence algorithm to optimize the parameters in the method of active contour model, using multiscale transform which contains directional information to improve the extraction accuracy of multiresolution analysis method, combining various kinds of methods to synthesize their advantages and achieving the automatic extraction of coastline with subpixel precision.

مفهوم

remote sensing;coastline;remote sensing image;automatic extraction;waterline;accuracy evaluation

References

  1. 1.
    Aktas Ü R, Can G and Vural F T Y. 2012. Edge-aware segmentation in satellite imagery: a case study of shoreline detection//Proceedings of the 7th IAPR Workshop on Pattern Recognition in Remote Sensing. Tsukuba, Japan: IEEE: 1-4 [DOI: 10.1109/PPRS.2012.6398319]
  2. 2.
    Alonso M T, López-Martínez C, Mallorqui J J and Salembier P. 2011. Edge enhancement algorithm based on the wavelet transform for automatic edge detection in SAR images. IEEE Transactions on Geoscience and Remote Sensing, 49(1): 222–235
  3. 3.
    Asaka T, Yamamoto Y, Aoyama S, Iwashita K and Kudou K. 2013. Automated method for tracing shorelines in L-band SAR images//Conference Proceedings of 2013 Asia-Pacific Conference on Synthetic Aperture Radar. Tsukuba, Japan: IEEE: 325-328
  4. 4.
    Baghdadi N, Pedreros R, Lenotre N, Dewez T and Paganini M. 2007. Impact of polarization and incidence of the ASAR sensor on coastline mapping: example of Gabon. International Journal of Remote Sensing, 28(17): 3841–3849
  5. 5.
    Baselice F and Ferraioli G. 2013. Unsupervised coastal line extraction from SAR images. IEEE Geoscience and Remote Sensing Letters, 10(6): 1350–1354
  6. 6.
    Bhaskar H. 2011. Coastline detection using coupled variational level-set formulation//Proceedings of the 4th International Conference on Imaging for Crime Detection and Prevention 2011. London, UK: IET: 1-6 [DOI: 10.1049/ic.2011.0107]
  7. 7.
    Boak E H and Turner I L. 2005. Shoreline definition and detection: a review. Journal of Coastal Research, 21(4): 688–703
  8. 8.
    Buono A, Nunziata F, Mascolo L and Migliaccio M. 2014. A multipolarization analysis of coastline extraction using X-band COSMO-SkyMed SAR data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(7): 2811–2820
  9. 9.
    Cao K, Fan J C, Wang X X, Wang X, Zhao J H and Zhang F S. 2016. Coastline automatic detection based on high resolution SAR images//Proceedings of the 4th International Workshop on Earth Observation and Remote Sensing Applications. Guangzhou, China: IEEE: 43-46 [DOI: 10.1109/EORSA.2016.7552763]
  10. 10.
    Caselles V, Kimmel R and Sapiro G. 1997. Geodesic active contours. International Journal of Computer Vision, 22(1): 61–79
  11. 11.
    Chan T F and Vese L A. 2001. Active contours without edges. IEEE Transactions on Image Processing, 10(2): 266–277
  12. 12.
    Chen X, Sun J, Yin K Y and Yu J M. 2014. Sea-land segmentation algorithm of SAR image based on Otsu method and statistical characteristic of sea area. Journal of Data Acquisition and Processing, 29(4): 603–608
  13. 13.
    Chen Y H, Feng T, Shi P J and Wang J F. 2006. Classification of remot sensing image based on object oriented and class rules. Geomatics and Information Science of Wuhan University, 31(4): 316–320
  14. 14.
    Chen Z H, Mao Z H and Chen J Y. 2011. Coastline change monitoring using 4 periods remote sensing data in Zhejiang Province from 1986 to 2009. Remote Sensing Technology and Application, 26(1): 68–73
  15. 15.
    Cheng D C, Meng G F, Cheng G L and Pan C H. 2017a. SeNet: structured edge network for sea–land segmentation. IEEE Geoscience and Remote Sensing Letters, 14(2): 247–251
  16. 16.
    Cheng D C, Meng G F, Xiang S M and Pan C M. 2017b. FusionNet: edge aware deep convolutional networks for semantic segmentation of remote sensing harbor images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(12): 5769–5783
  17. 17.
    Cheng G, Han J W and Lu X Q. 2017. Remote sensing image scene classification: benchmark and state of the art. Proceedings of the IEEE, 105(10): 1865–1883
  18. 18.
    Congalton R G and Green K. 2008. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. 2nd ed. Florida, USA: CRC Press
  19. 19.
    Dellepiane S, de Laurentiis R and Giordano F. 2004. Coastline extraction from SAR images and a method for the evaluation of the coastline precision. Pattern Recognition Letters, 25(13): 1461–1470
  20. 20.
    Descombes X, Moctezuma M, Maître H and Rudant J P. 1996. Coastline detection by a Markovian segmentation on SAR images. Signal Processing, 55(1): 123–132
  21. 21.
    Ding X W, Nunziata F, Li X F and Migliaccio M. 2015. Performance analysis and validation of waterline extraction approaches using single- and dual-polarimetric SAR data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(3): 1019–1027
  22. 22.
    Dong B G, Zhang L, Zhang G, Wu Z and Zhou L Y. 2012. Smooth shoreline extraction with topographic constraints using LiDAR point clouds. Journal of Geomatics Science and Technology, 29(2): 113–117
  23. 23.
    Dong H Y, Xu P, Liu Q and Xu H L. 2015. The water coastline detection approaches based on USV vision//Proceedings of 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems. Shenyang, China: IEEE: 404-408 [DOI: 10.1109/CYBER.2015.7287971]
  24. 24.
    Dong Y, Zhang J F and Xu F J. 2014. Auto localization for coastal satellite imagery based on curve matching//Proceedings of 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems. Beijing, China: IEEE: 1-6 [DOI: 10.1109/MFI.2014.6997645]
  25. 25.
    Fan D, Guo H D, Yue H Y and Wang C L. 2002. Detection of lake shoreline in SAR image based on wavelet. Journal of Remote Sensing, 6(6): 511–516
  26. 26.
    Fan J C, Cao K, Zhao J H, Jiang D W and Tang X L. 2016. A hybrid particle swarm optimization algorithm for coastline SAR image automatic detection//Proceedings of the 12th World Congress on Intelligent Control and Automation. Guilin, China: IEEE: 822-825 [DOI: 10.1109/WCICA.2016.7578256]
  27. 27.
    Fan Y G, Zhang S Q, Hou C L and Zhang L. 2009. Study on method of coastline extraction from remote sensing - Taking Yellow River mouth reach and Diaokou reach of Yellow River Delta area as an example. Remote Sensing Information, (4): 67–70, 74
  28. 28.
    Feng L D, Sun X G and Xu K H. 2002. Edge detection of coastline based on wavelet transform method. Journal of Ocean University of Qingdao, 32(5): 777–781
  29. 29.
    Feng Y J and Han Z. 2012. Cellular automata approach to extract shoreline from remote sensing imageries and its application. Journal of Image and Graphics, 17(3): 441–446
  30. 30.
    Fugura A A, Billa L and Pradhan B. 2011. Semi-automated procedures for shoreline extraction using single RADARSAT-1 SAR image. Estuarine, Coastal and Shelf Science, 95(4): 395–400
  31. 31.
    Gao Y, Zhou C H, Su F Z and Wang H. 2014. Coastline extraction from remote sensing images based on multi-features approach. Engineering of Surveying and Mapping, 23(5): 1–5
  32. 32.
    Gao Z Q, Liu X Y, Ning J C and Lu Q S. 2014. Analysis on changes in coastline and reclamation area and its causes based on 30-year satellite data in China. Transactions of the Chinese Society of Agricultural Engineering, 30(12): 140–147
  33. 33.
    General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China. 2004. GB/T 18190-2000 Oceanological terminology--Marine geology. Beijing: Standards Press of China
  34. 34.
    Guo H T, Sun L, Shen J S, Chen X W and Zhang H W. 2016. An island and coastal image segmentation method based on quadtree and GAC model. Acta Geodaetica et Cartographica Sinica, 45(1): 65–72
  35. 35.
    Guo Q D, Pu R L, Zhang B and Gao L R. 2016. A comparative study of coastline changes at Tampa Bay and Xiangshan Harbor during the last 30 years//Proceedings of 2016 IEEE International Geoscience and Remote Sensing Symposium. Beijing, China: IEEE: 5185-5188 [DOI: 10.1109/IGARSS.2016.7730351]
  36. 36.
    Guo Y Y, Lu X and Shao F Q. 2009. Remote sensing information abstraction of Lianyungang coastal line based on wavelet transformation. Journal of Huaihai Institute of Technology (Natural Science Edition), 18(3): 86–89
  37. 37.
    Han M, Yang X and Jiang E D. 2016. An Extreme Learning Machine based on Cellular Automata of edge detection for remote sensing images. Neurocomputing, 198: 27–34
  38. 38.
    Hou B, Hu Y H and Jiao L C. 2010. Improved shearlet edge detection for waters of SAR images. Journal of Image and Graphics, 15(10): 1549–1554
  39. 39.
    Hu Q, Zhang F, Liu R Y and Du Z H. 2013. Land-sea boundary extraction based on gradient vector flow and active contour model. Journal of Zhejiang University (Science Edition), 40(6): 698–704
  40. 40.
    Huang K H and Zhang J. 2011. A coastline detection method using SAR images based on the local statistical active contour model. Journal of Remote Sensing, 15(4): 737–749
  41. 41.
    Jia M M, Liu D W, Wang Z M, Tang X G and Dong Z Y. 2013. Coastline changes in Hangzhou Bay based on object-oriented method using multi-source remote sensing data. Journal of Geo-Information Science, 15(2): 262–269
  42. 42.
    Jiang D W, Fan J C and Huang F R. 2016. SAR image coastline detection based on regional distance regularized geometric active contour models. Acta Geodaetica et Cartographica Sinica, 45(9): 1096–1103
  43. 43.
    Jiang X W. 2016. China Offshore Marine - Processing and Interpretation of Remote Sensing Image of Island Coastal Zone. Beijing: China Ocean Press
  44. 44.
    Karantzalos K G, Argialas D and Georgopoulos A. 2002. Towards automatic detection of coastlines from satellite imagery//Proceedings of the 14th International Conference on Digital Signal Processing Proceedings. Santorini, Greece: IEEE: 897-900 [DOI: 10.1109/ICDSP.2002.1028235]
  45. 45.
    Kass M, Witkin A and Terzopoulos D. 1988. Snakes: active contour models. International Journal of Computer Vision, 1(4): 321–331
  46. 46.
    Latini D, del Frate F, Palazzo F and Minchella A. 2012. Coastline extraction from SAR COSMO-SkyMed data using a new neural network algorithm//Proceedings of 2012 IEEE International Geoscience and Remote Sensing Symposium. Munich, Germany: IEEE: 5975-5977 [DOI: 10.1109/IGARSS.2012.6352247]
  47. 47.
    Li C L, Li Y and Lan G X. 2011. New method of the fast narrow brand C-V level set model for image segmentation. Computer Science, 38(12): 17–19, 35
  48. 48.
    Li C L, Li Y and Ma L. 2010. A new method of coastline detection for remote sensing image. Computer Simulation, 27(8): 212–214, 254
  49. 49.
    Li C P and Yang G. 2014. Fast sea-land segmentation method based on maritime boundary tracking. Computer Science, 41(10): 84–86, 100
  50. 50.
    Li M and Zheng X S. 2016. A second modified normalized difference water index (SMNDWI) in the case of extracting the shoreline. Marine Science Bulletin, 18(2): 15–27
  51. 51.
    Li R R, Liu W J, Yang L, Sun S H, Hu W, Zhang F and Li W. 2017. DeepUNet: A deep fully convolutional network for pixel-level sea-land segmentation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(11): 3954–3962
  52. 52.
    Li X M, Yuan C Z and Li Y Y. 2013. Remote sensing monitoring and spatial-temporal variation of Bohai Bay coastal zone. Remote Sensing for Land and Resources, 25(2): 156–163
  53. 53.
    Li Y, Li J and Lu Y. 2007. A fuzzy segmentation-based approach to extraction of coastlines from IKONOS imagery. Geomatica, 62(4): 407–417
  54. 54.
    Li Z M, Luo Y Z, Man W and Sun F Q. 2017. Extraction and analysis of coastline of Fujian province based on RS and GIS. Journal of Applied Oceanography, 36(1): 125–134
  55. 55.
    Liu C, Xiao Y Y and Yang J. 2017. A coastline detection method in polarimetric SAR images mixing the region-based and edge-based active contour models. IEEE Transactions on Geoscience and Remote Sensing, 55(7): 3735–3747
  56. 56.
    Liu C, Yang J, Yin J J and An W T. 2016. Coastline detection in SAR images using a hierarchical level set segmentation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(11): 4908–4920
  57. 57.
    Liu C, Yin J J and Yang J. 2016. Coastline detection in polarimetric SAR images based on mixed edge detection. Systems Engineering and Electronics, 38(6): 1262–1267
  58. 58.
    Liu H and Jezek K C. 2004. Automated extraction of coastline from satellite imagery by integrating Canny edge detection and locally adaptive thresholding methods. International Journal of Remote Sensing, 25(5): 937–958
  59. 59.
    Liu P C. 2015. Feature extraction of coastline contour based on level set theory. Remote Sensing for Land and Resources, 27(2): 75–79
  60. 60.
    Liu S W, Zhang J, Ma Y and Sun W F. 2011. Coastline extraction method based on remote sensing and DEM. Remote Sensing Technology and Application, 26(5): 613–618
  61. 61.
    Liu X Y, Gao Z Q, Ning J C, Yu X and Zhang Y Y. 2016. An improved method for mapping tidal flats based on remote sensing waterlines: A case study in the Bohai Rim, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(11): 5123–5129
  62. 62.
    Liu Y, Huang H J and Yan L W. 2013. Remote sensing applications in extraction of Shijiutuo Island coastline based on different spatial scales. Remote Sensing Technology and Application, 28(1): 144–149
  63. 63.
    Liu Y X, Huang H J, Qiu Z F and Fan J Y. 2013. Detecting coastline change from satellite images based on beach slope estimation in a tidal flat. International Journal of Applied Earth Observation and Geoinformation, 23: 165–176
  64. 64.
    Liu Z L, Li F, Li N, Wang R and Zhang H. 2016. A novel region-merging approach for coastline extraction from Sentinel-1A IW mode SAR imagery. IEEE Geoscience and Remote Sensing Letters, 13(3): 324–328
  65. 65.
    Ma X F, Zhao D Z, Xing X G, Zhang F S, Wen S Y and Yang F. 2007. Means of withdrawing coastline by remote sensing. Marine Environmental Science, 26(2): 185–189
  66. 66.
    Ma X F, Zhao D Z, Zhang F S, Wen S Y and Yang F. 2007. An overview of means of withdrawing coastline by remote sensing. Remote Sensing Technology and Application, 22(4): 575–580
  67. 67.
    McFeeters S K. 1996. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17(7): 1425–1432
  68. 68.
    Modava M and Akbarizadeh G. 2017. Coastline extraction from SAR images using spatial fuzzy clustering and the active contour method. International Journal of Remote Sensing, 38(2): 355–370
  69. 69.
    Mumford D and Shah J. 1989. Optimal approximations by piecewise smooth functions and associated variational problems. Communications on Pure and Applied Mathematics, 42(5): 577–685
  70. 70.
    Niedermeier A, Lehner S and van der Sanden J. 2001. Monitoring big river estuaries using SAR images//Proceedings of IGARSS 2001. Scanning the Present and Resolving the Future. IEEE 2001 International Geoscience and Remote Sensing Symposium. Sydney, NSW, Australia: IEEE: 1756-1758 [DOI: 10.1109/IGARSS.2001.977061]
  71. 71.
    Niedermeier A, Romaneessen E and Lehner S. 2000. Detection of coastlines in SAR images using wavelet methods. IEEE Transactions on Geoscience and Remote Sensing, 38(5): 2270–2281
  72. 72.
    Nunziata F, Buono A, Migliaccio M and Benassai G. 2016. Dual-polarimetric C- and X-band SAR data for coastline extraction. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(11): 4921–4928
  73. 73.
    Nunziata F and Migliaccio M. 2013. Coherent dual-pol HH-HV SAR data to extract coastline//Proceedings of 2013 IEEE International Geoscience and Remote Sensing Symposium. Melbourne, VIC, Australia: IEEE: 3215-3218 [DOI: 10.1109/IGARSS.2013.6723511]
  74. 74.
    Nunziata F, Migliaccio M and Li X. 2012. Dual-polarized COSMO-SkyMed SAR data for coastline detection//Proceedings of 2012 IEEE International Geoscience and Remote Sensing Symposium. Munich, Germany: IEEE: 5109-5112 [DOI: 10.1109/IGARSS.2012.6352461]
  75. 75.
    Nunziata F, Migliaccio M, Li X F and Ding X W. 2014. Coastline extraction using dual-polarimetric COSMO-SkyMed PingPong mode SAR data. IEEE Geoscience and Remote Sensing Letters, 11(1): 104–108
  76. 76.
    Onana V P, Ngono J M, Trebossen H, Rudant J P and Tonye E. 2001. Coastline detection in SAR images using texture analysis in textural or geometrical multi-resolution//Proceedings of IGARSS 2001. Scanning the Present and Resolving the Future. IEEE 2001 International Geoscience and Remote Sensing Symposium. Sydney, NSW, Australia: IEEE: 1549-1551 [DOI: 10.1109/IGARSS.2001.976907]
  77. 77.
    Otsu N. 1979. A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 9(1): 62–66
  78. 78.
    Ouyang Y, Chong J S and Wu Y R. 2010. Two coastline detection methods in Synthetic Aperture Radar imagery based on Level Set Algorithm. International Journal of Remote Sensing, 31(17/18): 4957–4968
  79. 79.
    Paes R L, Nunziata F and Migliaccio M. 2015. Coastline extraction and coastal area classification via SAR hybrid-polarimetry architecture//Proceedings of 2015 IEEE International Geoscience and Remote Sensing Symposium. Milan, Italy: IEEE: 3798-3801 [DOI: 10.1109/IGARSS.2015.7326651]
  80. 80.
    Pardo-Pascual J E, Almonacid-Caballer J, Ruiz L A and Palomar-Vázquez J. 2012. Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision. Remote Sensing of Environment, 123: 1–11
  81. 81.
    Qiao X J, Wang Q, Zhan C, Wang X, Wang H Y, Du G Y and Li X Y. 2016. Study on automatic extraction of coastline in the Yellow River Delta based on multi-spectral data. Haiyang Xuebao, 38(7): 59–71
  82. 82.
    Qu G Z, Yu Q Z and Wang Y F. 2013. An improved method for SAR image coastline detection based on despeckling and SVM//Proceedings of the IET International Radar Conference 2013. Xi'an, China: IET: 1-6 [DOI: 10.1049/cp.2013.0268]
  83. 83.
    Qu J S, Wang C and Wang Z Z. 2003. A multi-threshold based morphological approach for extracting coastal line feature from remote sensed images. Journal of Image and Graphics, 8(7): 805–809
  84. 84.
    Ryan T W, Sementilli P J, Yuen P and Hunt B R. 1991. Extraction of shoreline features by neural nets and image processing. Photogrammetric Engineering and Remote Sensing, 57(7): 947–955
  85. 85.
    Sabuncu A, Dogru A, Ozener H and Turgut B. 2016. Detection of coastline deformation using remote sensing and geodetic surveys. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B8: 1169-1174 [DOI: 10.5194/isprs-archives-XLI-B8-1169-2016]
  86. 86.
    Sekovski I, Stecchi F, Mancini F and del Rio L. 2014. Image classification methods applied to shoreline extraction on very high-resolution multispectral imagery. International Journal of Remote Sensing, 35(10): 3556–3578
  87. 87.
    Shan Z L, Wang C, Zhang H and Zhang B. 2010. Ocean-land segmentation based on active contour model for SAR imagery//Proceedings of 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering. Chengdu, China: IEEE: 215-218 [DOI: 10.1109/CCTAE.2010.5545332]
  88. 88.
    Shen J S, Guo H T, Li H B, Qiu F G and Zhang Z P. 2013. A water edge extraction method from images based on Canny operator and GAC model. Journal of Geomatics Science and Technology, 30(3): 264–268
  89. 89.
    Shen Q, Wang C Y and Zhao B. 2012. Automatic waterline extraction in VHR imagery using geometric active contour model. Journal of Fudan University (Natural Science), 51(1): 77–82, 104
  90. 90.
    Sheng G F, Yang W, Deng X P, He C, Cao Y F and Sun H. 2012. Coastline detection in synthetic aperture radar (SAR) images by integrating watershed transformation and controllable gradient vector flow (GVF) Snake model. IEEE Journal of Oceanic Engineering, 37(3): 375–383
  91. 91.
    Shu Y M, Li J and Gomes G. 2010. Shoreline extraction from RADARSAT-2 intensity imagery using a narrow band level set segmentation approach. Marine Geodesy, 33(2/3): 187–203
  92. 92.
    Silveira M and Heleno S. 2008. Water/land segmentation in SAR images using level sets//Proceedings of the 15th IEEE International Conference on Image Processing. San Diego, CA, USA: IEEE: 1896-1899 [DOI: 10.1109/ICIP.2008.47121507]
  93. 93.
    Silveira M and Heleno S. 2009a. Classification of water regions in SAR images using level sets and non-parametric density estimation//Proceedings of the 16th IEEE International Conference on Image Processing. Cairo, Egypt: IEEE: 1685-1688 [DOI: 10.1109/ICIP.2009.5413391]
  94. 94.
    Silveira M and Heleno S. 2009b. Separation between water and land in SAR images using region-based level sets. IEEE Geoscience and Remote Sensing Letters, 6(3): 471–475
  95. 95.
    Su F Z. 2015. Assessment of Remote Sensing of the Coastal Zone. Beijing: Science Press
  96. 96.
    Sukcharoenpong A, Yilmaz A and Li R X. 2015. An integrated active contour approach to shoreline mapping using HSI and DEM. IEEE Transactions on Geoscience and Remote Sensing, 54(3): 1586–1597
  97. 97.
    Sun F Q, Hua L Z, Li H, Wang Y T and Chen Y Q. 2015. Detecting and analysis of coast changes of Xiamen Island by RS and GIS//Proceedings of the 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services. Fuzhou, China: IEEE: 197-201 [DOI: 10.1109/ICSDM.2015.7298053]
  98. 98.
    Sun R C, Shao F J, Wu S Y and Li S J. 2012. Study on coastline changes of Yellow River estuary using semi-supervised clustering//Proceedings of the International Conference on Automatic Control and Artificial Intelligence. Xiamen, China: IET: 1952-1955 [DOI: 10.1049/cp.2012.1376]
  99. 99.
    Sun W F, Ma Y, Zhang J, Liu S W and Ren G B. 2011. Study of remote sensing interpretation keys and extraction technique of different types of shoreline. Bulletin of Surveying and Mapping, (3): 41–44
  100. 100.
    Tarmizi N M, Samad A M and Yusop M S M. 2014. Shoreline data extraction from QuickBird satellite image using semi-automatic technique//Proceedings of the IEEE 10th International Colloquium on Signal Processing and its Applications. Kuala Lumpur, Malaysia: IEEE: 157-162 [DOI: 10.1109/CSPA.2014.6805739]
  101. 101.
    Tello M, Lopez-Martinez C, Mallorqui J J and Bonastre R. 2006. Automatic detection of spots and extraction of frontiers in SAR images by means of the wavelet transform: Application to ship and coastline detection//Proceedings of 2006 IEEE International Symposium on Geoscience and Remote Sensing. Denver, CO, USA: IEEE: 383-386 [DOI: 10.1109/IGARSS.2006.103]
  102. 102.
    The State Bureau of Quality and Technical Supervision. 2004a. GB 12327-1998 Specifications for hydrographic survey. Beijing: Standards Press of China
  103. 103.
    The State Bureau of Quality and Technical Supervision. 2004b. GB 12319-1998 Symbols, abbreviations and terms used on Chinese nautical charts. Beijing: Standards Press of China
  104. 104.
    Tochamnanvita T and Muttitanon W. 2014. Investigation of coastline changes in three provinces of Thailand using remote sensing. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-8: 1079-1083 [DOI: 10.5149/isprsarchives-XL-8-1079-2014]
  105. 105.
    Tseng K H, Shum C K, Kim J W, Wang X W, Zhu K F and Cheng X. 2016. Integrating Landsat imageries and digital elevation models to infer water level change in Hoover Dam. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(4): 1696–1709
  106. 106.
    Tzeng Y C, Chen D N and Chen K S. 2008. Integration of spatial chaotic model and type-2 fuzzy sets to coastline detection in SAR images//Proceedings of 2008 IEEE International Geoscience and Remote Sensing Symposium. Boston, MA, USA: IEEE: I-430-I-433 [DOI: 10.1109/IGARSS.2008.4778887]
  107. 107.
    Wan J H, Wang K, Zhao S L and Zhang J S. 2011. Fast automatic coastline extraction algorithm based on graphics morphology. Yellow River, 33(10): 126–127, 130
  108. 108.
    Wang H W, Chen K S, Li Z L and Liu Y. 2016. Quantitative analysis of shoreline changes in western Taiwan coast using time-series SAR images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(11): 4898–4907
  109. 109.
    Wang J, Wu Z F, Li S Y, Wang S S, Zhang X S and Gao Q. 2016. Coastline and land use change detection and analysis with remote sensing in the Pearl River Estuary Gulf. Scientia Geographica Sinica, 36(12): 1903–1911
  110. 110.
    Wang J B, Zhang J, Chen J Y, Sun W F and Ma Y. 2015. Analysis of the Liaohe Estuary coastline changes basing on the remote sensing image in the past thirty years. Marine Environmental Science, 34(1): 86–92
  111. 111.
    Wang J N, Meng Y H and Zhang L X. 2016. Remote sensing monitoring and change analysis of Yellow River Estuary coastline in the past 42 years. Remote Sensing for Land and Resources, 28(3): 188–193
  112. 112.
    Wang L J, Niu Z, Zhao D G, Li Y X, Wang Z B and Kuang D. 2010. The study of coastline extraction and validation using ETM remote sensing image. Remote Sensing Technology and Application, 25(2): 235–239
  113. 113.
    Wang Y F, Yu Q Z, Lv W T and Yu W X. 2011. Coastline detection in SAR images using multi-feature and SVM//Proceedings of the 4th International Congress on Image and Signal Processing. Shanghai, China: IEEE: 1227-1230 [DOI: 10.1109/CISP.2011.6100487]
  114. 114.
    Wang Y X, Liu Y X, Li M C, Yan S, Ma X W, Zhang S and Zhang J. 2011. Extraction of sandbank shoreline of Jiangsu based on wavelet transformation//Proceedings of the 19th International Conference on Geoinformatics. Shanghai, China: IEEE: 1-4 [DOI: 10.1109/Geoinformatics.2011.5980914]
  115. 115.
    Wei D L and Cao X C. 2015. Using satellite remote sensing image data to research the north coastline extraction based on Matlab - A case study of Changxing Island, Dalian city. Bulletin of Surveying and Mapping, (5): 80–83
  116. 116.
    Wu T and Hou X Y. 2016. Review of research on coastline changes. Acta Ecologica Sinica, 36(4): 1170–1182
  117. 117.
    Wu X J, Xiao C C, Cui Z Y and Liu X J. 2015. Coastline extraction based on object-oriented method using GF-2 satellite data. Spacecraft Recovery and Remote Sensing, 36(4): 84–92
  118. 118.
    Wu X L, Liu C X and Wu G F. 2018. Spatial-temporal analysis and stability investigation of coastline changes: a case study in Shenzhen, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(1): 45–56
  119. 119.
    Wu Y Q, Meng T L and Wu S H. 2015. Research progress of image thresholding methods in recent 20 years (1994-2014). Journal of Data Acquisition and Processing, 30(1): 1–23
  120. 120.
    Xia G S, Hu J W, Hu F, Shi B G, Bai X, Zhong Y F, Zhang L P and Lu X Q. 2017. AID: a benchmark data set for performance evaluation of aerial scene classification. IEEE Transactions on Geoscience and Remote Sensing, 55(7): 3965–3981
  121. 121.
    Xie M H, Zhang Y F and Fu K. 2007. Algorithm of detection coastline from SAR images based on seeds growing. Journal of Graduate School of the Chinese Academy of Sciences, 24(1): 93–98
  122. 122.
    Xu C Y and Prince J L. 1997. Gradient vector flow: a new external force for snakes//Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Juan, Puerto Rico, USA: IEEE: 66-71 [DOI: 10.1109/CVPR.1997.609299]
  123. 123.
    Xu H Q. 2005. A study on information extraction of water body with the modified normalized difference water index (MNDWI). Journal of Remote Sensing, 9(5): 589–595
  124. 124.
    Yan H B, Li B B and Chen M D. 2009. Progress of researches in coastline extraction based on RS technique. Areal Research and Development, 28(1): 101–105
  125. 125.
    Yang H, Guo H D and Wang C L. 2001. Coast line dynamic inspect and land cover classification at Yellow River mouth using TM-SAR data fusion method. Geography and Territorial Research, 17(4): 15–19
  126. 126.
    Yin J Z and He F Q. 2011. Researching the method of coastline extracted by remote sensing image//Proceedings of 2011 International Conference on Remote Sensing, Environment and Transportation Engineering. Nanjing, China: IEEE: 3441-3444 [DOI: 10.1109/RSETE.2001.5965052]
  127. 127.
    Yousef A and Iftekharuddin K. 2014. Shoreline extraction from the fusion of LiDAR DEM data and aerial images using mutual information and genetic algrithms//Proceedings of 2014 International Joint Conference on Neural Networks. Beijing, China: IEEE: 1007-1014 [DOI: 10.1109/IJCNN.2014.6889863]
  128. 128.
    Yu C X, Wang J Y, Bao J Y, Xu J and Chen H R. 2015a. A binary image optimization method of extracting coastline based on LiDAR data. Journal of Geomatics Science and Technology, 32(2): 187–191, 196
  129. 129.
    Yu C X, Wang J Y, Huang W Q and Xu J. 2017. An improved binary image method of extracting shoreline based on LiDAR data. Geomatics and Information Science of Wuhan University, 42(7): 897–903
  130. 130.
    Yu C X, Wang J Y, Xu J, Peng R C, Cheng Y and Wang M. 2014. Advance of coastline extraction technology. Journal of Geomatics Science and Technology, 31(3): 305–309
  131. 131.
    Yu C X, Xu J, Xu J, Zheng Y D and Li G X. 2015. A new method of extracting coastlines from LiDAR point clouds. Bulletin of Surveying and Mapping, (5): 66–68
  132. 132.
    Yu J, Chen P M, Jia X P, Tang Z C and Qin C X. 2012. Research progress on coastline extraction based on remote sensing and GIS technique. Journal of Anhui Agricultural Sciences, 40(32): 15989–15991
  133. 133.
    Yu J, Du F Y, Chen G B, Huang H H and Li Y Z. 2009. Research on coastline change of Daya Bay using remote sensing technology. Remote Sensing Technology and Application, 24(4): 512–516
  134. 134.
    Yu J T, Guo H T, Li C G, Lu J and Jiang C X. 2016. A waterline extraction method from remote sensing image based on quad-tree and multiple active contour model. Acta Geodaetica et Cartographica Sinica, 45(9): 1104–1114
  135. 135.
    Yu L S, Li Z Y, Wen G J and Du C. 2011. Application of intertidal zone extraction based on remote sensing images fusion technique. Acta Geodaetica et Cartographica Sinica, 40(5): 551–554, 562
  136. 136.
    Yu Y and Acton S T. 2004. Automated delineation of coastline from polarimetric SAR imagery. International Journal of Remote Sensing, 25(17): 3423–3438
  137. 137.
    Zhan Y T, Zhu L, Sun Y H, Su X B and Hou H Q. 2017. Automatic extraction of coastline via spectral angle-distance similarity growth model. Journal of Remote Sensing, 21(3): 458–469
  138. 138.
    Zhang M, Jiang X Z, Zhang J R and Tian B. 2008. Progress of study on characteristic collection of coastline through remote sensing images. Yellow River, 30(6): 7–9
  139. 139.
    Zhang P. 2010. Coastline Detection in SAR Images Based on Stationary Wavelet Transform. Qingdao: Ocean University of China
  140. 140.
    Zhang X, Zhuang Z, Zhang X K and Yang B H. 2014. Coastline extraction and change monitoring by remote sensing technology in Qinhuangdao city. Remote Sensing Technology and Application, 29(4): 625–630
  141. 141.
    Zhang X K, Zhang X, Lan Q Q and Baig M H A. 2012. Automated detection of coastline using Landsat TM based on water index and edge detection methods//Proceedings of 2012 Second International Workshop on Earth Observation and Remote Sensing Applications. Shanghai, China: IEEE: 153-156 [DOI: 10.1109/EORSA.2012.6261155]
  142. 142.
    Zhang X K, Zhang X, Yang B H, Zhuang Z and Shang K. 2013. Coastline extraction using remote sensing based on coastal type and tidal correction. Remote Sensing for Land and Resources, 25(4): 91–97
  143. 143.
    Zhang Z Y, Feng W F and Zhang J H. 2005. A coastline-detection method based on the color difference for the RS image. Journal of Institute of Surveying and Mapping, 22(4): 259–262
  144. 144.
    Zhao Y L. 2017. Remote sensing dynamic monitoring of the shoreline and the mangrove wetland in the Lingdingyang Estuary in the past 40 years. Remote Sensing for Land and Resources, 29(1): 136–142
  145. 145.
    Zhou Y N, Zhu Z W, Shen Z F and Cheng X. 2012. Automatic extraction of coastline from TM image integrating texture and spatial relationship. Acta Scientiarum Naturalium Universitatis Pekinensis, 48(2): 273–279
  146. 146.
    Zhu C M, Zhang X, Luo J C, Li W Q and Yang J W. 2013. Automatic extraction of coastline by remote sensing technology based on SVM and auto-selection of training samples. Remote Sensing for Land and Resources, 25(2): 69–74
  147. 147.
    Zhu J F, Wang G M, Zhang J L and Huang T L. 2013. Remote sensing investigation and recent evolution analysis of Pearl River delta coastline. Remote Sensing for Land and Resources, 25(3): 130–137
  148. 148.
    Zhu X G. 2002. Remote sensing monitoring of coastline changes in Pearl River Estuary. Marine Environmental Science, 21(2): 19–22
  149. 149.
    Zhuang C R. 2009. Remote-sensing dynamic monitoring of Xiamen coastline. Marine Geology Letters, 25(4): 13–17

قراءة النص الكامل

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website