• DocumentCode
    2929553
  • Title

    Wetland vegetation biomass estimation using Landsat-7 ETM+ data

  • Author

    Tan, Qulin ; Shao, Yun ; Yang, Songlin ; Wei, Qingzhao

  • Author_Institution
    Sch. of Civil Eng. & Archit., Northern Jiaotong Univ., Beijing, China
  • Volume
    4
  • fYear
    2003
  • fDate
    21-25 July 2003
  • Firstpage
    2629
  • Abstract
    At present, monitoring, conservation and wise use of wetlands has become an international trend. Using Landst-7 ETM+ data acquired on Oct. 2000, we conducted a digital and rapid estimation of wetland vegetation biomass in the Poyang wetland natural conservation area, which is one of the seven international importance wetlands in China. Firstly, using the ETM band 4, 3 and 2 false color composite as one of the main references, we planned a reasonable sampling biomass field route. Based on geometric co-registration of both the field GPS positioning data and the ETM data, the linear relationships among the field biomass data and some transformed data derived from the ETM data were analyzed statistically. The results show that the sampling biomass data have the best positive correlation to DVI vegetation index data with a coefficient of 0.8546. Therefore, a linear regression model established between the sampling data and DVI data, was applied to estimate the total biomass of the whole Poyang Lake natural conservation area. The resultant total biomass is 10.98×104t.
  • Keywords
    Global Positioning System; lakes; regression analysis; vegetation mapping; AD 2000 10; China; DVI data; DVI vegetation index data; ETM band; ETM data; GPS positioning data; Poyang Lake natural conservation area; Poyang wetland natural conservation area; field biomass data; linear regression; sampling biomass; wetland vegetation biomass estimation; Bioinformatics; Biomass; Data analysis; Global Positioning System; Monitoring; Page description languages; Remote sensing; Sampling methods; Satellites; Vegetation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International
  • Print_ISBN
    0-7803-7929-2
  • Type

    conf

  • DOI
    10.1109/IGARSS.2003.1294532
  • Filename
    1294532