• DocumentCode
    576227
  • Title

    Wetland vegetation biomass inversion using polarimetric RADARSAT-2 data

  • Author

    Shen, Guozhuang ; Liao, Jingjuan ; Guo, Huadong ; Liu, Ju ; Zhang, Lu ; Chen, Jie

  • Author_Institution
    Key Lab. of Digital Earth, Center for Earth Obs. & Digital Earth, Beijing, China
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    750
  • Lastpage
    753
  • Abstract
    Biomass, as an indicator of vegetation productivity, can evaluate the contribution of wetland vegetation to carbon sink and carbon source. Long time and quantitative biomass study can help to acknowledge and understand the global carbon balance and carbon cycle. RADAR, which can work all day/weather and can penetrate vegetation in some extent, can be used to retrieve vegetation structure information, even the biomass. Here, the RADARSAT-2 data was used to retrieve vegetation biomass in Poyang Lake wetland. Based on the canopy scattering model, which is based on radioactive transfer model, the vegetation backscatter characteristics at C band were studied and good relationship between simulation results and backscatter in RADATSAT-2 image were achieved. Using the backscatter model, pairs of training data (backscatter coefficients in HH, VV, HV polarization mode and polarization decomposed components) were built and were used to train the Back Propagation (BP) artificial neural network (ANN). The biomass was inversed using this ANN, and compared to the field survey. It shows that the combination of the canopy scatter model and polarimetric decomposition components can improve the inversion precision efficiently.
  • Keywords
    lakes; neural nets; remote sensing by radar; vegetation; Poyang Lake wetland; back propagation artificial neural network; canopy scattering model; carbon sink; carbon source; global carbon balance; global carbon cycle; polarimetric RADARSAT-2 data; polarimetric decomposition components; radioactive transfer model; vegetation productivity indicator; vegetation structure information; wetland vegetation biomass inversion; Artificial neural networks; Backscatter; Biological system modeling; Biomass; Lakes; Remote sensing; Vegetation mapping; BP ANN; biomass; canopy scatter model; polarimetric SAR; polarimetric decomposition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6351456
  • Filename
    6351456