Extraction of Water Body Based on LandSat TM5 Imagery – A Case Study in the Yangtze River

Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 393)


A improved method named vegetation normalized difference water index (VNDWI) has been proposed in this paper based on NEW of Xiao Yun-fang(2010), which uses Band 1 and Band 7 and the normalized difference vegetation index (NDVI) in TM5 imagery to construct the VNDWI. This method has been tested in the Yangtze River Basin, and compares the results with other methods is the best. Due to the reflection characteristics differences between water and cloud, NEW method cannot distinguish the differences effectively. However, joins the NDVI parameter, VNDWI can enhance the difference between water and cloud, so it can remove clouds and its shadow noise from water body information without using complicated procedures, which is particular difficult work should be done in pretreatment.


Extraction of Water Body Imagery Processing Binarization 


  1. 1.
    Jensen, O.: Knowledge based classification of an urban area using texture and context information in Landsat TM imagery. Photogrammetric Engineering and Remote Sensing 56 (1990)Google Scholar
  2. 2.
    Mc Feeters, S.K.: The use of the Normalized Difference Water Index (NDWI) in the delineation of open water feature. International Journal of Sensing (1996)Google Scholar
  3. 3.
    Xu, H.-Q.: A Study on Information Extraction of Water Body with the Modified Normalized Difference Water Index. Journal of Remote Sensing (2005)Google Scholar
  4. 4.
    Yang, C.-J., Xu, M., et al.: Remote sensing information mechanism of water extraction method. Geography Research, 86–89 (1998)Google Scholar
  5. 5.
    Xiao, Y.-F., Zhu, L.: A study on information extraction of water body using band1 and band7 of TM imagery. Surveying and Mapping (2010)Google Scholar
  6. 6.
    Zhao, S.-Y.: Principles and methods of Remote Sensing Applications. Science Press, Beijing (2003)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2013

Authors and Affiliations

  1. 1.3S CenterTsinghua UniversityBeijingChina

Personalised recommendations