Skip to main content
SpringerLink
Log in

Spectral characteristics of plant communities from salt marshes: A case study from Chongming Dongtan, Yangtze estuary, China

  • Research Article
  • Published:
Frontiers of Environmental Science & Engineering in China Aims and scope Submit manuscript

Abstract

The spectral reflectance of recently formed salt marshes at the mouth of the Yangtze River, which are undergoing invasion by Spartina alterniflora, were assessed to determine the potential utility of remotely sensed data in assessing future invasion and changes in species composition. Following a review of published research on remote sensing of salt marshes, 53 locations along three transects were sampled for paired data on plant species composition and spectral reflectance using a FieldSpec™ Pro JR Field Portable Spectroradiometer. Spectral data were processed concerning reflectance, and the averaged reflectance values for each sample were reanalysed to correspond to a 12-waveband bandset of the Compact Airborne Spectral Imager. The spectral data were summarised using principal components analysis (PCA) and the relationships between the vegetation composition, and the PCA axes of spectral data were examined. The first PCA axis of the reflectance data showed a strong correlation with variability in near infrared reflectance and ‘brightness’, while the second axis was correlated with visible reflectance and ‘greenness’. Total vegetation cover, vegetation height, and mudflat cover were all significantly related to the first axis. The implications of this in terms of the ability of remote sensing to distinguish the various salt marsh species and in particular the invasive species S. alterniflora were discussed. Major differences in species with various physiognomies could be recognised but problems occurred in separating early colonising S. alterniflora from other species at that stage. Further work using multi-seasonal hyperspectral data might assist in solving these problems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Zhang R S, Shen Y M, Lu L S, Yan S G, Wang Y H, Li J L, Zhang Z L. Formation of Spartina alterniflora salt marshes on the coast of Jiangsu Province, China. Ecological Engineering, 2004, 23: 95–105

    Article  CAS  Google Scholar 

  2. Xu G W, Zhou R Z. Preliminary studies of introduced Spartina alterniflora Loisel in China. Journal of Nanjing University (Advances in Spartina Research), 1985, 212–225 (in Chinese)

  3. Gray A J, Marshall D F, Raybould A F. A century of evolution in Spartina anglica. Advances in Ecological Research, 1991, 21: 1–62

    Article  Google Scholar 

  4. Daehler C C, Strong D R. Status, prediction and prevention of introduced cordgrass Spartina sp. invasions in Pacific estuaries, USA. Biological Conservation, 1996, 78: 51–58

    Article  Google Scholar 

  5. Tessier M, Vivier J P, Ouin A, Gloaguen J C, Lefeuvre J C Vegetationdynamics and plant species interaction under grazed and ungrazed conditions in a western European salt marsh. Acta Oecologica 2003, 24: 103–111

    Article  Google Scholar 

  6. Roughgarden J, Running S, Matson P. What does remote sensing do for ecology? Ecology, 1991, 72(6): 918–1922

    Article  Google Scholar 

  7. Liu J Y, Zhuang D F, Ling Y R, Awaya Y. Vegetation integrated classification and mapping using remote sensing and GIS techniques in northeast China. Journal of Remote Sensing, 1998, 4(2): 285–291 (in Chinese)

    Google Scholar 

  8. Treitz P M, Howarth P J. Hyperspectral remote sensing for estimating biophysical parameters of forest ecosystems. Progress in Physical Geography, 1999, 23: 359–390

    Google Scholar 

  9. Yang C J, Liu J Y, Luo J C. Correlation analysis of landsat TM data and its derived data, meteorological data and topographic data with the biomass of different aged tropical forests. Acta Phytoecologica Sinica, 2004, 28: 862–867 (in Chinese)

    Google Scholar 

  10. Curran P J. The problems of remote sensing of vegetation canopies for biomass estimates. In: Fuller RM, ed. Ecological Mapping from Ground, Air and Space.Cambridge, UK: Institute of Terrestrial Ecology, 1983, 83–100

    Google Scholar 

  11. Morton A J. Moorland plant community recognition using Landsat MSS data. Remote Sensing of Environment, 1986, 20: 291–298

    Article  Google Scholar 

  12. Trodd N M. Analysis and representation of heathland vegetation from near-ground level remote sensing. Global Ecology and Biogeography Letters, 1996, 5: 206–216

    Article  Google Scholar 

  13. Blackburn G A, Pitman J I. Biophysical controls on the directional reflectance properties of bracken (Pteridium aquilinum) canopies: Results of field experiments. International Journal of Remote Sensing, 1999, 20: 2265–2282

    Article  Google Scholar 

  14. Thomas V, Treitz P, Jelinski D, Miller J, Lafleur P, McCaughey J H. Image classification of a northern peatland complex using spectral and plant community data. Remote Sensing of Environment, 2002, 84: 83–99

    Article  Google Scholar 

  15. Armitage R P, Kent M, Weaver R E. Identification of the spectral characteristics of British semi-natural upland vegetation using direct ordination: A case study from Dart moor, UK. International Journal of Remote Sensing, 2004, 25: 3369–3388

    Article  Google Scholar 

  16. Armitage R P, Weaver R E, Kent M. Remote sensing of seminatural upland vegetation: The relationship between species composition and spectral response. In: Alexander R, Millington A, eds.Vegetation Mapping: Patch to Planet. Chichester: John Wiley and Sons, 2000, 83–102

    Google Scholar 

  17. Cochrane M A. Using vegetation reflectance variability for species level classification of hyperspectral data. International Journal of Remote Sensing, 2000, 21: 2075–2087

    Article  Google Scholar 

  18. Artigras F J, Yang J. Hyperspectral remote sensing of habitat heterogeneity between tide-restricted and tide-open areas in the New Jersey Meadowlands. Urban Habitats, 2004, 2: 112–129

    Google Scholar 

  19. Silvestri S, Defina A, Marani M. Tidal regime, salinity and salt marsh plant zonation. Estuarine, Coastal and Shelf Sciences, 2005, 62: 119–130

    Article  CAS  Google Scholar 

  20. Schmidt K S, Skidmore A K. Spectral discrimination of vegetation types in a coastal wetland. Remote Sensing of Environment, 2003, 85: 92–108

    Article  Google Scholar 

  21. Thomson A G, Fuller R M, Yates M G, Brown S L, Cox R, Wadsworth R A. The use of airborne remote sensing for extensive mapping of intertidal sediments and salt marshes in eastern England. International Journal of Remote Sensing, 2003, 24: 2717–2737

    Article  Google Scholar 

  22. Zhang M, Pinzon J, Rejmankova S L, Sanderson E W. Differentiating salt marsh species using foreground/background analysis. In: Proceedings of ERIM 2nd Annual Airborne Remote Sensing Conference, Volume 1. San Francisco, USA, 1996, 83–92

  23. Silvestri S, Marani M, Marani A. Hyperspectral remote sensing of salt marsh vegetation, morphology and soil topography. Physics and Chemistry of the Earth, 2003, 28: 15–25

    Google Scholar 

  24. Salvitori R, Grignetti A, Casacchia R, Mandrone S. The role of spatial resolution in vegetation studies by hyperspectral airborne images. In: Proceedings of Spectral Remote Sensing of Vegetation Conference. Las Vegas, USA, 2003

  25. Brown K. Increasing classification accuracy of coastal habitats using integrated airborne remote sensing. EARSEL eProccedings, 2004, 1: 34–42

    Google Scholar 

  26. Thomson A G, Fuller R M, Huiskes A, Cox R, Wadsworth R A, Boorman L A. Short-term vegetation succession and erosion identified by airborne remote sensing of Westerschelde salt marshes, The Netherlands. International Journal of Remote Sensing, 2004, 25: 4151–4176

    Article  Google Scholar 

  27. Thomson A G, Fuller R M, Sparks T H, Yates M G, Eastwood J A. Ground and airborne radiometry over intertidal surfaces: Waveband selection for cover classification. International Journal of Remote Sensing, 1998a, 19: 1189–1205

    Article  Google Scholar 

  28. Rocchini D, Chiarucci A, Loiselle S A. Testing the spectral hypothesis by using satellite multispectral images. Acta Oecologica, 2004, 26: 117–120

    Article  Google Scholar 

  29. Malthus T J, Mumby P J. Remote sensing of the coastal zone: An overview and priorities for future research. International Journal of Remote Sensing, 2003, 24: 2805–2815

    Article  Google Scholar 

  30. Thomson A G, Fuller R M, Eastwood J A. Supervised and unsupervised methods for classification of coasts and river corridors using airborne remote sensing. International Journal of Remote Sensing, 1998b, 19: 3423–3431

    Article  Google Scholar 

  31. Cracknell A P. Remote sensing techniques in estuaries and coastal zones: An update. International Journal of Remote Sensing, 1999, 20: 485–496

    Article  Google Scholar 

  32. Gray A J. Salt marsh plant ecology: Zonation and succession revisited. In: Allen J R L, Pye K, eds. Salt Marshes: Morphodynmics, Conservation and Engineering Significance. Cambridge, UK: Cambridge University Press, 1992, 63–79

    Google Scholar 

  33. Silvestri S, Marani M, Settle J, Benvenuto F, Marani A. Salt marsh vegetation radiometry: Data analysis and scaling. Remote Sensing of Environment, 2002, 80: 473–482

    Article  Google Scholar 

  34. Zhang L Q, Yong X K. Studies on phenology and spatial distribution of Scirpus mariqueter population. Acta Phytoecologica Sinica, 1992, 16: 43–51 (in Chinese)

    Google Scholar 

  35. Huang H M, Zhang L Q, Gao Z G. A study into the vegetation resource at the intertidal zone in Shanghai using remote sensing. Acta Ecologica Sinica, 2005, 25(10): 2686–2693 (in Chinese)

    Google Scholar 

  36. Eastwood J A, Yates M G, Thomon A G, Fuller R M. The reliability of vegetation indices for monitoring saltmarsh vegetation cover. International Journal of Remote Sensing, 1997, 18: 3901–3907

    Article  Google Scholar 

  37. Milton E J, Rollin E M, Emmery D R. Advances in field spectroscopy. In: Danson F M, Plummer S E, eds. Advances in Environmental Remote Sensing. Chichester: John Wiley and Son, 1995, 9–32

    Google Scholar 

  38. Crist E P, Cicone R J. A physical-based transformation of Thematic Mapper data-the Tasselled Cap. IEEE Transaction on Geosciences and Remote Sensing, 1984a, GE22: 256–263

    Article  Google Scholar 

  39. Crist E P, Cicone R J. Application of the Tasselled Cap concept to simulated Thematic Mapper data. Photogrammetric Engineering and Remote Sensing, 1984b, 50: 343–352

    Google Scholar 

  40. Crist E P, Kauth R J. The Tasselled Cap de-mystified. Photogrammetric Engineering and Remote Sensing, 1986, 52: 81–86

    Google Scholar 

  41. Canas A D D, Barnett M E. The generation and interpretation of false colour composite principal component images. International Journal of Remote Sensing, 1985, 6: 867–881

    Article  Google Scholar 

  42. McCune B, Mefford M J. PC-ORD. Multivariate Analysis of Ecological Data. Version 4. Gleneden Beach, Oregon, USA: MjM Software Design, 1999

    Google Scholar 

  43. Atkinson M D, Plummer S E. The influence of percentage cover and biomass of clover on the reflectance of mixed pasture. International Journal of Remote Sensing, 1993, 14: 1439–1444

    Article  Google Scholar 

  44. Sims D A, Gamon J A. Relationship between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and development stages. Remote Sensing of Environment, 2002, 81: 337–354

    Article  Google Scholar 

  45. Wang Y R, Yong S P. The use of multitemporal near-ground spectral reflectance to discriminate among degraded grasslands. Acta Phytoecologica Sinica, 2004, 28: 406–413 (in Chinese)

    Google Scholar 

  46. Tucker C J, Maxwell E L. Sensor design for monitoring vegetation canopies. Photogrammetric Engineering and Remote Sensing, 1976, 42: 1399–1410

    Google Scholar 

  47. Filella I, Penuelas J. The red edge position and shape as an indicator of plant chlorophyll content, biomass and hydric status. International Journal of Remote Sensing, 1994, 15: 1459–1470

    Article  Google Scholar 

  48. Bowers S A, Hanks R J. Reflection of radiant energy from soils. Soil Science, 1965, 2: 130–138

    Article  Google Scholar 

  49. Hoffer R M, Johannsen J. Ecological potentials in spectral signature analysis. In: Johnson P L, eds. Remote Sensing in Ecology. Athens, Georgia, USA: Athens University of Georgia Press, 1969, 1–29

    Google Scholar 

  50. Price J C. Variability of high resolution crop reflectance spectra. International Journal of Remote Sensing, 1992, 14: 2593–2610

    Article  Google Scholar 

  51. Price J C. How unique are spectral signatures? Remote Sensing of Environment, 1994, 49: 181–186

    Article  Google Scholar 

  52. Davidson D A, Watson A I. Spatial variability in soil moisture as predicted from Airborne Thematic Mapper (ATM) data. Earth Surface Processes, 1995, 20: 219–230

    Article  Google Scholar 

  53. Muller E, Décamps H. Modeling soil moisture reflectance. Remote Sensing of Environment, 2000, 76: 173–180

    Article  Google Scholar 

  54. Bork E W, West N E, Price K P. Calibration of broad-and narrow-band spectral variables for rangeland cover component quantification. International Journal of Remote Sensing, 1999, 20: 3641–3662

    Article  Google Scholar 

  55. Chavez A Y, Kwarteng P S. Change detection study of Kuwait City and environs using multi-temporal Landsat Thematic Mapper data. International Journal of Remote Sensing, 1998, 19: 1651–1662

    Article  Google Scholar 

  56. Pu R L, Gong P. Hyperspectral Remote Sensing and Its Applications. Beijing: Higher Education Press, 2000, 81–86 (in Chinese)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, 200062, China

    Liquan Zhang & Zhanguo Gao

  2. Environment Monitoring Center of Ningbo, Ningbo, 315012, China

    Zhanguo Gao

  3. Research Institute for the Built and Human Environment, School of Environment and Life Science, University of Salford, Salford, M5 4WT, UK

    Richard Armitage

  4. School of Geography, University of Plymouth, Plymouth, PL4 8AA, UK

    Martin Kent

Authors
  1. Liquan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhanguo Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Richard Armitage
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Martin Kent
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Liquan Zhang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhang, L., Gao, Z., Armitage, R. et al. Spectral characteristics of plant communities from salt marshes: A case study from Chongming Dongtan, Yangtze estuary, China. Front. Environ. Sci. Eng. China 2, 187–197 (2008). https://doi.org/10.1007/s11783-008-0004-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11783-008-0004-1

Keywords

Search

Navigation