Wetlands

, Volume 29, Issue 4, pp 1255–1261 | Cite as

Dynamic changes in Tangxunhu wetland over a period of rapid development (1953–2005) in Wuhan, China

  • Kai Xu
  • Chunfang Kong
  • Chonglong Wu
  • Gang Liu
  • Hongbin Deng
  • and Yi Zhang
Article
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Accepted:

Abstract

Tangxunhu wetland is one of China’s largest freshwater lakes and plays a significant role in the sustainable development of the city of Wuhan. Based on terrain maps, TM images, and statistical data from 1953 to 2005, the spatial characters and changing features of Tangxunhu wetland were quantitatively assessed by calculating the landscape metrics of shape index (SI), fractal dimension (D), and stability index (S). The results showed that Tangxunhu wetland had meandrous development over the past 53 years, withSI, D, and S decreasing from 1953 to 1967, increasing from 1967 to 2000, and then decreasing again from 2000 to 2005.SI, D, andS were lowest in 1967, indicating maximuminstability, but highest in 2000, indicating maximum stability. These changes in Tangxunhu wetland were associated with various natural, social, and economic factors.

Key Words

fractal dimension Geographic Information System (GIS) landscape ecology shape index stability index sustainable development 
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Literature Cited

  1. Baker, C., R. Lawrence, C. Montagne, and D. Patten. 2006. Mapping wetlands and riparian areas using Landsat ETM+ imagery and decision-tree-based models. Wetlands 26:465–74.CrossRefGoogle Scholar
  2. Baker, C., R. Lawrence, C. Montagne, and D. Patten. 2007. Change detection of wetland ecosystems using Landsat imagery and change vector analysis. Wetlands 27:610–19.CrossRefGoogle Scholar
  3. Burbridge, P. R. 1994. Integrated planning and management of freshwater habitats, including wetlands. Hydrobiologia 285:311–22.CrossRefGoogle Scholar
  4. Cai, S. M. and Y. Du. 2000. The characteristics of lake resources and its development and protection on the Jianghan Lakes region. Journal of Central China Normal University (Natural Sciences) 34:476–81.Google Scholar
  5. Cedffldt, P. T., M. C. Watzin, and B. D. Richardson. 2000. Using GIS to identify functionally significant wetland in the northeastern United States. Environmental Management 26:13–24.CrossRefGoogle Scholar
  6. Chen, F. Q. and J. M. Hartman. 2004. The ecological restoration and management of degraded wetlands ecosystem. Journal of Natural Resources 19:217–23.Google Scholar
  7. Craft, C., J. Reader, J. N. Succo, and S. W. Broome. 1999. Twenty-five years of ecosystem development of constructedSpartina alterniflora (Loisel) marshes. Ecological Applications 9:1405–19.CrossRefGoogle Scholar
  8. De Cola, L. 1989. Fractal analysis of a classified Landsat scene. Photogrammetric Engineering and Remote Sensing 55:601–10.Google Scholar
  9. De Roeck, E. R., N. E. C. Verhoest, M. H. Mtemi, H. Lievens, O. Batalaan, T. Abraham, and L. Brendonck. 2008. Remote sensing and wetlands ecology: a South African case study. Sensors 8:3542–56.CrossRefGoogle Scholar
  10. Deng, H. B., S. M. Cai, Y. Du, H. P. Xue, and X. H. Wei. 2006. Quantitative analysis on the evolution of Jianghan lakes region over the last 50 years. Resources and Environment in the Yangtze Basin 15:244–48.Google Scholar
  11. Detenbeck, N. E., D. L. Taylor, A. Lima, and C. Hagley. 1996. Temporal and spatial variability in water quality of wetlands in the Minneapolis/St. Paul, MN metropolitan area: implications for monitoring strategies and designs. Monitoring & Assessment 40:11–40.CrossRefGoogle Scholar
  12. Dugan, P. 1993. Wetlands in Danger. Oxford University Press, New York, NY, USA.Google Scholar
  13. Forman, R. T. T. and M. Godron. 1986. Landscape Ecology. John Wiley & Sons, New York, NY, USA.Google Scholar
  14. Fuller, D. O. 2001. Forest fragmentation in Loudoun County, Virginia, USA evaluated with multi-temporal Landsat imagery. Landscape Ecology 16:627–42.CrossRefGoogle Scholar
  15. Jensen, J., S. Narumaiani, O. Weatherbee, and H. Mackey. 1993. Measurement of seasonal and yearly cattail and waterlily change using multidata SPOT panchromatic data. Photogrammetric Engineering and Remote Sensing 59:519–25.Google Scholar
  16. Kevin, F. N. 1996. A model of created wetland primary succession. Landscape and Urban Planning 34:97–123.CrossRefGoogle Scholar
  17. Krummel, J. R., R. H. Gardner, G. Sugihara, R. V. O’Neill, and P. R. Coleman. 1987. Landscape patterns in a disturbed environment. Oikos 48:321–24.CrossRefGoogle Scholar
  18. Liu, A. J. and G. N. Cameron. 2001. Analysis of landscape patterns in coastal wetlands of Galveston Bay, Texas (USA). Landscape Ecology 16:581–95.CrossRefGoogle Scholar
  19. Liu, H. L., D. H. Li, and X. L. Han. 2005. Review of ecological infrastructure: concept and development. City Planning Review 29:70–75.Google Scholar
  20. Lunetta, R. S. and C. Elvidge. 1998. Remote Sensing Change Detection. Ann Arbor Press, Chelsea, MI, USA.Google Scholar
  21. Lunetta, R. S. and M. E. Balogh. 2003. Application of multi-temporal Landsat TM imagery for wetlands identification. Photogrammetric Engineering & Remote Sensing 65:1303–10.Google Scholar
  22. Olsen, E. R., R. D. Ramsey, and D. S. Winn. 1999. A modified fractal dimension as a measure of landscape diversity. Photogrammetric Engineering and Remote Sensing 59:1517–20.Google Scholar
  23. O’Neill, R. V., K. H. Riitters, J. D. Wichham, and K. B. Jones. 1999. Landscape pattern metrics and regional assessment. Ecosystem Health 5:225–33.CrossRefGoogle Scholar
  24. Ozesmi, S. L. and M. E. Bauer. 2002. Satellite remote sensing of wetlands. Wetlands Ecology and Management 10:381–402.CrossRefGoogle Scholar
  25. Patton, D. R. 1975. A diversity index for quantifying habitat ‘edge’. Wildlife Society Bulletin 3:171–73.Google Scholar
  26. Ramsey, E. and J. Jensen. 1996. Remote sensing of mangrove wetlands: relating canopy spectra to site-specific data. Photogrammetric Engineering and Remote Sensing 62:939–48.Google Scholar
  27. Read, J. M. and N. S-. N. Lam. 2002. Spatial methods for characterizing land cover and detecting land-cover changes for the tropics. International Journal of Remote Sensing 23:2457–74.CrossRefGoogle Scholar
  28. Rex, K. D. and G. P. Malanson. 1990. The fractal shape of riparian forests. Landscape Ecology 4:249–58.CrossRefGoogle Scholar
  29. Schmid, T., M. Koch, and J. Gumuzzio. 2005. Multisensor approach to determine changes of wetland characteristics in semiarid environments (central Spain). IEEE Transactions on Geoscience and Remote Sensing 43:2516–25.CrossRefGoogle Scholar
  30. Schumaker, N. H. 1996. Using landscape indices to predict habitat connectivity. Ecology 17:1210–25.CrossRefGoogle Scholar
  31. Shanmugam, P., Y. H. Ahn, and S. Sanjeevi. 2006. A comparison of the classification of wetland characteristics by linear spectral mixture modeling and traditional hard classifiers on multispectral remotely sensed imagery in southern India. Ecological Modelling 194:379–94.CrossRefGoogle Scholar
  32. Shuman, C. S. and R. F. Ambrose. 2003. A comparison of remote sensing and ground based methods for monitoring wetlands restoration. Restoration Ecology 11:325–33.CrossRefGoogle Scholar
  33. Wang, X. L., L. M. Ning, J. Yu, R. Xiao, and T. Li. 2008. Changes of urban wetland landscape pattern and impacts of urbanization on wetland in Wuhan city. Chinese Geographical Science 18:47–53.CrossRefGoogle Scholar
  34. Wang, Y., H. L. Gong, W. J. Zhao, X. J. Li, Z. F. Zhang, and W. Zhao. 2005. The change of Yeyahu wetlands resources in Beijing. Acta Geographica Sinica 6:656–64.Google Scholar
  35. Welch, R., M. Remillard, and J. Alberts. 1992. Integration of GPS, remote sensing, and GIS techniques for coastal resource management. Photogrammetric Engineering and Remote Sensing 58:1571–78.Google Scholar
  36. Wickham, T. J., E. J. Filardo, D. A. Cheresh, and G. R. Nemerow. 1994. Integrin αVβ5 selectively promotes adenovirus mediated cell membrane permeabilization. Journal of Cell Biology 127:257–64.CrossRefPubMedGoogle Scholar
  37. Wu, J. and J. David. 2002. A spatially explicit hierarchical approach to modeling complex ecological systems: theory and applications. Ecological Modelling 153:7–26.CrossRefGoogle Scholar
  38. Wu, J. and O. L. Loucks. 1995. From balance-of-nature to hierarchical patch dynamics: A paradigm shift in ecology. The Quarterly Review of Biology 70:439–66.CrossRefGoogle Scholar
  39. Xu, J. H., N. S. Ai, J. Jin, and S. Y. Fan. 2001. A fractal study on the mosaic structure of the landscape of Northwest China: Taking the drainage area of Heihe River as an example. Arid Zone Research 18:35–39.Google Scholar
  40. Yang, Y. X. 2002. New knowledge on the progress of international wetland science research and priority field and prospect of Chinese wetland science research. Advance in Earth Sciences 17:508–14.Google Scholar
  41. Yuan, L. 2007. Dynamic change and driving force of landscape pattern based on RS and GIS: a case study of Zhalong wetland. Journal of Northeast Forestry University 35:25–28.Google Scholar
  42. Yuan, X. Y. and Y. X. Tao. 2001. Impacts of urbanization on lake and bay. Volcanology and Mineral Resource 22:102–14.Google Scholar
  43. Zhang, Y. and H. B. Deng. 2005. Discussion of the evolution and use of the lakes in Wuhan. Journal of Central China Normal University (Natural Sciences) 39:559–63.Google Scholar
  44. Zhang, Z. F., H. L. Gong, W. J. Zhao, and R. H. Fu. 2004. Fractal research on dynamic change of the Beijing Wild Duck lake wetland resources based on GIS and RS. Remote Sensing for Land & Resources 3:42–45.Google Scholar
  45. Zheng, C. H., C. S. Zeng, Z. Q. Chen, and M. C. Lin. 2006. A study on the changes of landscape pattern of estuary wetlands of the Minjiang River. Wetland Science 4:29–34.Google Scholar
  46. Zou, S. H. 1987. Study of modern vicissitudes of the Jianghan lake group by using remote sensing techniques. Oceanologia et Limnologia Sinica 5:469–76.Google Scholar

Copyright information

© Society of Wetland Scientists 2009

Authors and Affiliations

  • Kai Xu
    • 1
    • 3
    • 2
  • Chunfang Kong
    • 3
  • Chonglong Wu
    • 3
  • Gang Liu
    • 3
  • Hongbin Deng
    • 4
  • and Yi Zhang
    • 5
  1. 1.Research Center for Remote Sensing and GIS School of Geography State Key Laboratory of Remote Sensing ScienceBeijing Normal UniversityBeijingChina
  2. 2.Department of Earth and Atmospheric SciencesPurdue UniversityWest LafayetteUSA
  3. 3.Faculty of Earth ResourcesChina University of GeosciencesWuhanChina
  4. 4.Faculty of Humanity and EconomyChina University of GeosciencesWuhanChina
  5. 5.College of Urban and Environmental ScienceCentral China Normal UniversityWuhanChina

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