• DocumentCode
    2962981
  • Title

    The Remote Sensing Dynamic Monitoring of Land Sandy Desertification in Duolun County

  • Author

    Jian, Wu ; Dao-li, Peng

  • Author_Institution
    Key Lab. for Silviculture & Conservation of Minist. of Educ., Beijing Forestry Univ., Beijing, China
  • Volume
    2
  • fYear
    2011
  • fDate
    28-29 March 2011
  • Firstpage
    281
  • Lastpage
    285
  • Abstract
    To monitor the land sandy desertification dynamic change accurately in Duolun, the desertification was classified and evaluated based on the land use point of view and the evaluation index system based on land use was set up. TM image was decomposed by linear spectral mixture mode and the vegetation component of TM image was amended by the high-resolution satellite image to extract the information of vegetation. The occupation ratio of bare sandy land was obtained using linear spectrum mixed model. Soil moisture was retrieved by thermal inertia according to land use types. The substitute index of remote sensing was used to obtain the content of iron oxide. And the code of soil texture was obtained by view interpretation. Based on the current desertification assessment method, quantitative remote sensing information model on the basis of the pixel was developed. The results shows that the area of moderate desertification increases 37272hm2, and the area of mild, strong and extremely strong desertification reduces 18594hm2, 5399.1hm2, 15210.2hm2 respectively. The area with on desertification increases 3237.9 hm2. The desertification of the whole county has been eased and the ecological environment has been improved.
  • Keywords
    ecology; geomorphology; geophysical image processing; remote sensing; soil; terrain mapping; vegetation mapping; China; Duolun county; TM image; desertification assessment method; ecological environment; evaluation index system; high-resolution satellite image; land sandy desertification dynamic change; land use; linear spectral mixture mode; linear spectrum mixed model; occupation ratio; remote sensing dynamic monitoring; remote sensing information model; soil moisture; soil texture; substitute index; thermal inertia; vegetation component; Biological system modeling; Indexes; Monitoring; Remote sensing; Soil moisture; Vegetation mapping; desertification evaluation; land use; quantitative retrieval; remote sensing information model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
  • Conference_Location
    Shenzhen, Guangdong
  • Print_ISBN
    978-1-61284-289-9
  • Type

    conf

  • DOI
    10.1109/ICICTA.2011.356
  • Filename
    5750881