• DocumentCode
    479808
  • Title

    Automated Estimation of Vegetation Fraction Based on Landsat TM/ETM+ Imagery

  • Author

    Yang, Shengmei ; Zhang, Qiuwen ; Li, Wenbo

  • Author_Institution
    Hubei Key Lab. of Digital Watershed Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan
  • Volume
    1
  • fYear
    2008
  • fDate
    12-14 Dec. 2008
  • Firstpage
    891
  • Lastpage
    894
  • Abstract
    Vegetation fraction is mainly associated with the living environment of human being. Forest canopy density (FCD) model and sub-pixel model are applied to automatically estimate the vegetation fraction in Qingjiang river basin. FCD model uses the vegetation bare-soil shadow index (VBSI). The sub-pixel model method applies the normalized difference vegetation index (NDVI) based on the dimidiate pixel algorithm. The vegetation fraction of Qingjiang river area is estimated based on the Landsat enhanced thematic mapper (ETM+) imagery with the ENVI 4.0 and the EARDAS 8.7 image software. Results indicate that the estimate accuracy of two models exceeds 75%. Both the FCD model and the sub-pixel model are reliable to extract the vegetation fraction. The information of this study is useful for further study on the vegetation fraction automated estimation, especially in mountainous area.
  • Keywords
    satellite communication; vegetation mapping; EARDAS 8.7 image software; ENVI 4.0; FCD model; Landsat TM-ETM+ imagery; Qingjiang river basin; automated vegetation fraction estimation; dimidiate pixel algorithm; enhanced thematic mapper; forest canopy density model; normalized difference vegetation index; subpixel model; vegetation bare-soil shadow index; Biological system modeling; Bismuth; Computer science; Infrared spectra; Large-scale systems; Remote sensing; Rivers; Satellites; Soil; Vegetation mapping; Qingjiang River Basin; automated estimation; image-processing; landsat TM/ETM+; remote sensing; vegetation fraction; vegetation index;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Software Engineering, 2008 International Conference on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3336-0
  • Type

    conf

  • DOI
    10.1109/CSSE.2008.1337
  • Filename
    4721893