, Volume 33, Issue 5, pp 871–886 | Cite as

Seasonal Pattern of Tidal-Flat Topography along the Jiangsu Middle Coast, China, Using HJ-1 Optical Images

  • Yongxue Liu
  • Manchun Li
  • Liang Mao
  • Liang Cheng
  • Kefeng Chen


Seasonal topographical changes in the intertidal zone are of high interest in many parts of the world. Due to existing challenges in mapping this dynamics, little is known about the seasonal pattern of tidal flats. This research aims to fill the knowledge gap by using optical images from the Chinese HJ-1 satellites constellation. A case study was conducted at the Jiangsu middle coast, a typical tidal flat region in China. Firstly, 455 optical images from the HJ-1 Satellites were collected to construct seasonal tidal flat Digital Elevation Models (DEMs). Next, synchronous Light Detection and Ranging (LiDAR) DEM and ground survey data were collected to validate the accuracy of the seasonal tidal flat DEMs. Finally, seasonal pattern of the tidal flats was demonstrated based on a time series of DEM volume comparison. The results show: (1) the HJ-1 images are qualified data source to produce satisfactory tidal flat DEMs with high spatio-temporal resolution and acceptable vertical accuracy. (2) In general, there are apparent erosion-and-deposition cycles in the Jiangsu middle coast, with deposition during the Winter and erosion during the Summer. Furthermore, the derived seasonal patterns differ notably among the five major sandbanks.


Tidal flats Coastal morphology Digital elevation model Seasonal pattern HJ-1 satellites constellation 



This research is supported by the National Natural Science Foundation of China (NO. 41171325, NO. 40701117, NO. 41230751, and NO. J1103408), the Program for New Century Excellent Talents in University (NCET-12-0264), the National Key Project of Scientific and Technical Supporting Programs funded by the Ministry of Science & Technology of China (NO. 2012BAH28B02), the Fundamental Research Funds for the Central Universities and PAPD (Priority Academic Program Development of Jiangsu Higher Education Institutions). The authors are grateful to the China Center for Resource Satellite Data and Applications (CRESDA) for providing the CBERS CCD, HJ-1A/B optical images, to the Center for Earth Observation and Digital Earth (CEODE, China) for providing the IRS-P6 LiSS/AWiFS images, and to the Earth Resources Observation and Science Center (EROS, USA) for providing the EO-1 ALI images. The authors are also grateful for the valuable tidal flat transects data provided by Dr. Xianrong Ding (Hohai University, HHU). Any errors or shortcoming in the paper are the responsibility of the authors.


  1. Blott SJ, Pye K (2004) Application of lidar digital terrain modelling to predict intertidal habitat development at a managed retreat site: Abbotts Hall, Essex, UK. Earth Surface Processes and Landforms 29:893–905CrossRefGoogle Scholar
  2. Cai WW, Song JL, Wang JD, Xiao ZQ (2011) High spatial-and temporal-resolution NDVI produced by the assimilation of MODIS and HJ-1 data. Canadian Journal of Remote Sensing 37:612–627CrossRefGoogle Scholar
  3. Chen LC, Rau JY (1998) Detection of shoreline changes for tideland areas using multi-temporal satellite images. International Journal of Remote Sensing 19:3383–3397CrossRefGoogle Scholar
  4. Chen JY, Cheng HQ, Dai ZJ, Eisma D (2008) Harmonious development of utilization and protection of tidal flats and wetlands - a case study in shanghai area. China Ocean Engineering 22:649–662Google Scholar
  5. Chen KF, Wang YH, Lu PD, Zheng JH (2009) Effects of coastline changes on tide system of Yellow Sea off Jiangsu coast, China. China Ocean Engineering 23:741–750Google Scholar
  6. Gao S, Wang YP, Gao JH (2011) Sediment retention at the Changjiang sub-aqueous delta over a 57 year period, in response to catchment changes. Estuarine, Coastal and Shelf Science 95:29–38CrossRefGoogle Scholar
  7. Heygster G, Dannenberg J, Notholt J (2010) Topographic mapping of the German tidal flats analyzing SAR images with the waterline method. IEEE Transactions on Geoscience and Remote Sensing 48:1019–1030CrossRefGoogle Scholar
  8. Jaakkola O, Oksanen J (2000) Creating DEMs from contour lines: Interpolation techniques which save terrain morphology. GIM International 14:46–49Google Scholar
  9. Lemke A, Lunau M, Stone J, Dellwig O, Simon M (2009) Spatio-temporal dynamics of suspended matter properties and bacterial communities in the back-barrier tidal flat system of Spiekeroog Island. Ocean Dynamics 59:277–290CrossRefGoogle Scholar
  10. Liu YX, Li MC, Cheng L, Li FX, Shu YM (2010) A DEM inversion method for inter-tidal zone based on MODIS dataset: a case study in the Dongsha Sandbank of Jiangsu Radial Tidal Sand-Ridges, China. China Ocean Engineering 24:735–748Google Scholar
  11. Liu XJ, Gao S, Wang YP (2011) Modeling profile shape evolution for accreting tidal flats composed of mud and sand: A case study of the central Jiangsu coast, China. Continental Shelf Research 31:1750–1760CrossRefGoogle Scholar
  12. Liu YX, Li MC, Cheng L, Li FX, Chen KF (2012) Topographic mapping of offshore sandbank tidal flats using the waterline detection method: a case study on the Dongsha Sandbank of Jiangsu Radial Tidal Sand Ridges, China. Marine Geodesy 35:362–378CrossRefGoogle Scholar
  13. Liu YX, Li MC, Mao L, Cheng L, Li FX (2013) Toward a method of constructing tidal flat digital elevation models with MODIS and medium-resolution satellite images. Journal of Coastal Research 29:438–448CrossRefGoogle Scholar
  14. Lohani B, Mason DC (1999) Construction of a digital elevation model of the Holderness coast using the waterline method and airborne thematic mapper Data. International Journal of Remote Sensing 20:593–607CrossRefGoogle Scholar
  15. Mason DC, Davenport IJ, Robinson GJ, Flather RA, McCartney BS (1995) Construction of an intertidal digital elevation model by the ‘water-line’ method. Geophysical Research Letters 22:3187–3190CrossRefGoogle Scholar
  16. Mason DC, Davenport IJ, Flather RA, Gurney C (1998) A digital elevation model of the inter-tidal areas of the Wash, England, produced by the waterline method. International Journal of Remote Sensing 19:1455–1460CrossRefGoogle Scholar
  17. Mason DC, Gurney C, Kennett M (2000) Beach topography mapping: a comparison of techniques. Journal of Coastal Conservation 6:113–124CrossRefGoogle Scholar
  18. Mason DC, Scott TR, Dance SL (2010) Remote sensing of intertidal morphological change in Morecambe Bay, UK, between 1991 and 2007. Estuarine, Coastal and Shelf Science 87:487–496CrossRefGoogle Scholar
  19. Otsu N (1979) Threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics 9:62–66CrossRefGoogle Scholar
  20. Pino M, Busquets T, Brummer R (1999) Temporal and spatial variability in the sediments of a tidal flat, Queule River Estuary, south-central Chile. Revista Geologica De Chile 26:187–204Google Scholar
  21. Ryu JH, Won JS, Min KD (2002) Waterline extraction from Landsat TM data in a tidal flat - A case study in Gomso Bay, Korea. Remote Sensing of Environment 83:442–456CrossRefGoogle Scholar
  22. Ryu JH, Kim CH, Lee YK, Won JS, Chun SS, Lee S (2008) Detecting the intertidal morphologic change using satellite data. Estuarine, Coastal and Shelf Science 78:623–632CrossRefGoogle Scholar
  23. Sezgin M, Sankur B (2004) Survey over image thresholding techniques and quantitative performance evaluation. Journal of Electronic Imaging 13:146–168CrossRefGoogle Scholar
  24. Wang Q (2012) Technical system design and construction of China’s HJ-1 satellites. International Journal of Digital Earth 5:202–216CrossRefGoogle Scholar
  25. Wang QA, Wu CQ, Li Q, Li JS (2010) Chinese HJ-1A/B satellites and data characteristics. Science China-Earth Sciences 53:51–57CrossRefGoogle Scholar
  26. Wang Y, Zhang YZ, Zou XQ, Zhu DK, Piper D (2012a) The sand ridge field of the South Yellow Sea: origin by river-sea interaction. Marine Geology 291:132–146CrossRefGoogle Scholar
  27. Wang YP, Gao S, Jia JJ, Thompson CEL, Gao JH, Yang Y (2012b) Sediment transport over an accretional intertidal flat with influences of reclamation, Jiangsu coast, China. Marine Geology 291:147–161CrossRefGoogle Scholar
  28. Wimmer C, Siegmund R, Schwabisch M, Moreira J (2000) Generation of high precision DEMs of the Wadden Sea with airborne interferometric SAR. IEEE Transactions on Geoscience and Remote Sensing 38:2234–2245CrossRefGoogle Scholar
  29. Woolard JW, Colby JD (2002) Spatial characterization, resolution, and volumetric change of coastal dunes using airborne LIDAR: Cape Hatteras, North Carolina. Geomorphology 48:269–287CrossRefGoogle Scholar
  30. Xing F, Wang YP, Wang HV (2012) Tidal hydrodynamics and fine-grained sediment transport on the radial sand ridge system in the southern Yellow Sea. Marine Geology 291:192–210CrossRefGoogle Scholar
  31. Zhang RS (1995) Equilibrium state of tidal mud flat, a case coastal area of central Jiangsu, China. Chinese Science Bulletin 40:1363–1368Google Scholar
  32. Zhang RS, Chen CJ (1992) Study of the evolution of Jiangsu offshore sandbanks and the prospects for tiaozini sandbanks merging into land. China Ocean Press, Beijing, pp 40–42Google Scholar
  33. Zhang RS, Shen YM, Lu LY, Yan SG, Wang YH, Li JL, Zhang ZL (2004) Formation of Spartina alterniflora salt marshes on the coast of Jiangsu Province, Spain. Ecological Engineering 23:95–105CrossRefGoogle Scholar
  34. Zhao B, Guo H, Yan Y, Wang Q, Li B (2008) A simple waterline approach for tidelands using multi-temporal satellite images: a case study in the Yangtze Delta. Estuarine, Coastal and Shelf Science 77:134–142CrossRefGoogle Scholar
  35. Zhou HX, Liu JE, Qin P (2009) Impacts of an alien species (Spartina alterniflora) on the macrobenthos community of Jiangsu coastal inter-tidal ecosystem. Ecological Engineering 35:521–528CrossRefGoogle Scholar

Copyright information

© Society of Wetland Scientists 2013

Authors and Affiliations

  • Yongxue Liu
    • 1
  • Manchun Li
    • 2
  • Liang Mao
    • 3
  • Liang Cheng
    • 4
  • Kefeng Chen
    • 5
  1. 1.Jiangsu Provincial Key Laboratory of Geographic Information Science and TechnologyNanjing UniversityNanjingPeople’s Republic of China
  2. 2.School of Geographic and Oceanographic SciencesNanjing UniversityNanjingPeople’s Republic of China
  3. 3.Department of GeographyUniversity of FloridaGainesvilleUSA
  4. 4.Department of Geographic Information ScienceNanjing UniversityNanjingPeople’s Republic of China
  5. 5.Nanjing Hydraulic Research InstituteNanjingPeople’s Republic of China

Personalised recommendations