Dynamic changes of the Huizhou Coastline in nearly 50 years based on Landsat images and DSAS

  • role: First author第一作者
  • Affiliation:

    School of Earth Science and Engineering, Sun Yat-sen University, Zhuhai 519000, China

  • Email:wangth6@mail2.sysu.edu.cn
  • Introduction:E-mailwangth6@mail2.sysu.edu.cn
WANG Tonghao1,  
  • role: Corresponding author通信作者
  • Affiliation:

    School of Earth Science and Engineering, Sun Yat-sen University, Zhuhai 519000, China

    Guangdong Provincial Key Lab of Geodynamics and Geohazards, School of Earth Sciences and Engineering, Sun Yat-sen University, Guangzhou 510275, China

    Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519000, China

  • Email:zhgfang@mail.sysu.edu.cn
  • Introduction:RSGISE-mailzhgfang@mail.sysu.edu.cn
ZHANG Guifang123*,  
  • Affiliation:

    School of Earth Science and Engineering, Sun Yat-sen University, Zhuhai 519000, China

    Guangdong Provincial Key Lab of Geodynamics and Geohazards, School of Earth Sciences and Engineering, Sun Yat-sen University, Guangzhou 510275, China

    Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519000, China

ZHANG Ke123,  
  • Affiliation:

    School of Earth Science and Engineering, Sun Yat-sen University, Zhuhai 519000, China

FU Qiang1

résumé

Dynamic changes of the coastline reflect the transgression-regression process of the sea–land interaction, which is of great significance to the environmental protection and development planning of coastal areas. On the basis of six periods of Landsat satellite images from 1973 to 2019, this paper obtained coastline data of each period and calculated the changes in their length and type by means of human-machine interactive interpretation.Detailed analysis in terms of Net Shoreline Movement (NSM), End Point Rate (EPR), and Linear Regression Rate (LRR) in the Digital Shoreline Analysis System (DSAS) were conducted to explore the potential driving factors regarding the dynamic changes of the coastline.Results show that from 1973 to 2019, the total length of the Huizhou coastline increased from 224,565 m to 249,656 m, with an average NSM of 185.46 m and an average EPR of 4.04 m/a. The coastline was mainly characterized by erosion from 1973 to 1984 and showed an overall expansion trend afterwards. The expansion amplitude of the coastline exceeded the highest during 1984—1993, with the NSM reaching 100.2 m. In addition, the artificial coastline, which is mainly distributed in Daya Bay Petrochemical Zone, northern Fanhe Bay reclamation and aquaculture Section, Huizhou Port, western Kaozhou Bay reclamation and aquaculture section, and the vicinity of Huangbu Town section, showed the most remarkable change (8.27%—57.45%) among the different coastline types. The main reasons of coastline change include the development of a coastal aquaculture; the construction of ports, industrial areas, and coastal tourist areas; and the expansion of construction land due to population growth and economic development. Some coastline segments, such as the core area of Xunliao Bay and the east and west flanks of Shuangyue Bay, remained stable during the whole period.We conclude that human impact was the main driving factor and that natural factors have little influence in the coastline change during past nearly 50 years. Compared with other coastal zones in mainland China, the rate of change in Huizhou is less remarkable. Judging by the EPR (2.51%) from 2013 to 2019, the change of coastline in Huizhou remained stable. Thus, we estimate that there will be no significant expansion toward the sea in the future.

mots-clés

Huizhou City;coastline;remote sensing;DSAS;dynamic change

References

  1. 1.
    Amrouni O, Hzami A and Heggy E. 2019. Photogrammetric assessment of shoreline retreat in North Africa: anthropogenic and natural drivers. ISPRS Journal of Photogrammetry and Remote Sensing, 157: 73-92
  2. 2.
    Ding X S, Shan X J, Chen Y L, Jin X S, Yuan Z H and Yang T. 2018. Study on the change rate of shoreline based on Digital Coastal Analysis System (DSAS): taking the shoreline of the Yellow River Delta and Laizhou Bay as an example. Marine Science Bulletin, 37(5): 565-575
  3. 3.
    Feng Y J, Yuan J Y, Song L J and Jiang F. 2015. Coastline mapping and change detection along Hangzhou Bay using remotely sensed imagery. Remote Sensing Technology and Application, 30(2): 345-352
  4. 4.
    Gao Y, Wang H, Su F Z and Liu G M. 2013. The analysis of spatial and temporal changes of the continental coastlines of China in recent three decades. Acta Oceanologica Sinica, 35(6): 31-42
  5. 5.
    Ghosh M K, Kumar L and Roy C. 2015. Monitoring the coastline change of Hatiya Island in Bangladesh using remote sensing techniques. ISPRS Journal of Photogrammetry and Remote Sensing, 101: 137-144
  6. 6.
    Hakkou M, Maanan M, Belrhaba T, El Khalidi K, El Ouai D and Benmohammadi A. 2018. Multi-decadal assessment of shoreline changes using geospatial tools and automatic computation in Kenitra coast, Morocco. Ocean and Coastal Management, 163: 232-239
  7. 7.
    Himmelstoss E, Henderson R E, Kratzmann M G and Farris A S. 2018. Digital Shoreline Analysis System (DSAS) version 5.0 user guide. Reston: U.S. Geological Survey
  8. 8.
    Hou X Y, Wu T, Hou W, Chen Q, Wang Y D and Yu L J. 2016. Characteristics of coastline changes in mainland China since the early 1940s. Science China Earth Sciences, 59(9): 1791-1802
  9. 9.
    Huizhou Municipal Bureau of Statistics and Survey Office of National Bureau of Statistics in Huizhou. 2020. Huizhou Statistical Yearbook 2020. Beijing: China Statistics Press
  10. 10.
    Jia K, Chen S S and Jiang W G. 2022. Long time-series remote sensing monitoring of mangrove forests in the Guangdong-Hong Kong-Macao Greater Bay Area. National Remote Sensing Bulletin, 26(6): 1096-1111
  11. 11.
    Kabir M A, Salauddin M, Hossain K T, Tanim I A, Saddam M M H and Ahmad A U. 2020. Assessing the shoreline dynamics of Hatiya Island of Meghna estuary in Bangladesh using multiband satellite imageries and hydro-meteorological data. Regional Studies in Marine Science, 35: 101167
  12. 12.
    Kang B, Lin N, Xu W B, Wang N and Liu Q Q. 2017. Spatial-temporal changes of the coastline in five south island of Long Island in recent three decades on RS and GIS. Marine Science Bulletin, 36(5): 585-593
  13. 13.
    Li G, Sun G H, Yao Y J, Zhu B Q and Zhang Y M. 2019. Spatial-temporal evolution of the Sansha Bay coastline. Journal of Jilin University (Earth Science Edition), 49(1): 196-205
  14. 14.
    Li L C, Lu D S, Zhang X L, Zhu C M and Deng L. 2015. Coastline change in the Beibu gulf of South China Sea using time series Landsat images. Transactions of Oceanology and Limnology, (4): 132-142
  15. 15.
    Li M N, Chen X Y, Liu J Q, Wu Z and Song W. 2016. Coastline change in Weihai based on remote sensing. Marine Geology and Quaternary Geology, 36(6): 79-84
  16. 16.
    Li Q Q, Lu Y, Hu S B, Hu Z W, Li H Z, Liu P, Shi T Z, Wang C S, Wang J J and Wu G F. 2016. Review of remotely sensed geo-environmental monitoring of coastal zones. Journal of Remote Sensing, 20(5): 1216-1229
  17. 17.
    Li Y, Wang Y L, Peng J, Wu J S and Lü X F. 2009. Research on dynamic changes of coastline in Shenzhen City based on Landsat image. Resources Science, 31(5): 875-883
  18. 18.
    Moussa R M, Fogg L, Bertucci F, Calandra M, Collin A, Aubanel A, Polti S, Benet A, Salvat B, Galzin R, Planes S and Lecchini D. 2019. Long-term coastline monitoring on a coral reef island (Moorea, French Polynesia). Ocean and Coastal Management, 180: 104928
  19. 19.
    Muskananfola M R, Supriharyono and Febrianto S. 2020. Spatio-temporal analysis of shoreline change along the coast of Sayung Demak, Indonesia using Digital Shoreline Analysis System. Regional Studies in Marine Science, 34: 101060
  20. 20.
    Pardo-Pascual J E, Sánchez-García E, Almonacid-Caballer J, Palomar-Vázquez J M, de los Santos E P, Fernández-Sarría A and Balaguer-Beser Á. 2018. Assessing the accuracy of automatically extracted shorelines on microtidal beaches from Landsat 7, Landsat 8 and Sentinel-2 imagery. Remote Sensing, 10(2): 326
  21. 21.
    Saleem A and Awange J L. 2019. Coastline shift analysis in data deficient regions: exploiting the high spatio-temporal resolution Sentinel-2 products. Catena, 179: 6-19
  22. 22.
    Shen K M, Li A L, Jiang Y B and Liu C X. 2020. Time-space velocity analysis of coastline based on digital shoreline analysis system: a case study of the Haizhou Bay. Haiyang Xuebao, 42(5): 117-127
  23. 23.
    Sun X Y, Lü T T, Gao Y and Fu M. 2014. Driving force analysis of Bohai bay coastline change from 2000 to 2010. Resources Science, 36(2): 413-419
  24. 24.
    Tang C L, You D W, Chen T G, Chen H M and Yu K F. 2009. Sea-level changes along the coast of Guangdong Province during 1986-2008. Tropical Geography, 29(5): 423-428
  25. 25.
    Thieler E R, Himmelstoss E A, Zichichi J L and Ayhan E. 2009. Digital Shoreline Analysis System (DSAS) version 4.3. U.S. Geological Survey Open-File Report 2008-1278
  26. 26.
    Wang Y X, Liu Y X, Jin S, Sun C and Wei X L. 2019. Evolution of the topography of tidal flats and sandbanks along the Jiangsu coast from 1973 to 2016 observed from satellites. ISPRS Journal of Photogrammetry and Remote Sensing, 150: 27-43
  27. 27.
    Xia Z, Chen T H and Zhao Q X. 2000. Study on the shoreline changes by multiseasonal satellite remote sensing data--take Dayawan Bay as a pilot. South China Sea Geology, (12): 102-108
  28. 28.
    Yan X L, Zhong J Q, Han Z L, Sun C Z and Liu M. 2019. Driving forces analysis and landscape succession features of coastal wetland both outside and inside reclamation areas in the northern Liaodong Bay, China in recent 40 years. Scientia Geographica Sinica, 39(7): 1155-1165
  29. 29.
    Yang C C, Gan H Y, Wan R S and Zhang Y M. 2021. Spatiotemporal evolution and influencing factors of coastline in the Guangdong-Hong Kong-Macao Greater Bay Area from 1975 to 2018. Geology in China, 48(3): 697-707
  30. 30.
    Yang Y X, Liu X J, Qiu R F and Yang W. 2017. The analysis of shoreline changes respond to artificial island project of Dongjiao Coco Forest based on DSAS and SMC. Periodical of Ocean University of China, 47(10): 162-168
  31. 31.
    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
  32. 32.
    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
  33. 33.
    Yu J, Chen G B, Huang Z R and Chen Z Z. 2014. Changes in the coastline of three typical bays in Guangdong during recent 10 years revealed by satellite image. Transactions of Oceanology and Limnology, (3): 91-96
  34. 34.
    Zhang H T. 2016. Monitoring of coastline change in Zhuhai based on high resolution remote sensing. Bulletin of Surveying and Mapping, 11: 55-59, 71
  35. 35.
    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
  36. 36.
    Zhang X X, Wang W W, Yan C Q, Yan W B, Dai Y X, Xu P and Zhu C X. 2014. Historical coastline spatio-temporal evolution analysis in Jiangsu coastal area during the past 1 000 years. Scientia Geographica Sinica, 34(3): 344-351
  37. 37.
    Zhang Y Z, Zhang Q L and Hu Y F. 2019. Remote sensing monitoring and dynamic analysis of the Pearl River Estuary coastline during 2010-2017. Marine Science Bulletin, 38(2): 217-224
  38. 38.
    Zhao Y L. 2010. The remote sensing dynamic monitoring of the evolution of shoreline and mangrove wetlands in the Zhujiang River estuary in the past 30 years. Remote Sensing for Land and Resources, (S1): 178-184
  39. 39.
    Zhong R, Liu C S and Chen X X. 2021. Fractal characteristics and spatial heterogenicity of continental coastline in Guangdong Province. Journal of Guangdong Ocean University, 41(4): 70-76
  40. 40.
    Zhu J F, Wang G M, Zhang J L and Huang J L. 2013. Remote sensing investigation and recent evolution analysis of Pearl River delta coastline. Remote Sensing for Land and Resources, 25(3): 130-137

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