• DocumentCode
    1986846
  • Title

    The Study of Soil Moisture Retrieval Algorithm from GNSS-R

  • Author

    Kebiao, Mao ; Mengyang, Zhang ; Jianming, Wang ; Huajun, Tang ; Qingbo, Zhou

  • Author_Institution
    Bejing Inst. of Satellite Inf. Eng., Beijing
  • Volume
    1
  • fYear
    2008
  • fDate
    21-22 Dec. 2008
  • Firstpage
    438
  • Lastpage
    442
  • Abstract
    The L1 band (1.58 GHz)on board GPS satellite is very suitable for monitoring the change of soil moisture. The research for retrieval of soil moisture from GNSS-R is just beginning. This paper makes an analysis by using simulation data from AIEM model and experiment data from SMEX02. The analysis for simulation data from AIEM model shows that scattering signal of GPS is influenced much by angle and roughness, so the retrieval algorithm should consider the angle and roughness. The analysis of experiment data in SMEX02 indicates that the average correlation coefficient is above 0.85 between soil moisture and GNSS-R SNR for a single field site, so the soil moisture can be accurately retrieved by GNSS-R for single site, and the retrieval algorithm should be built for single site under considering incidence angle.
  • Keywords
    Global Positioning System; geophysical signal processing; moisture; remote sensing; soil; AIEM model; GNSS-R; L1 band on board GPS satellite; SMEX02 experiment data; frequency 1.58 GHz; global navigation satellite system-reflection; global positioning system; scattering signal; soil moisture retrieval algorithm; Algorithm design and analysis; Analytical models; Data analysis; Global Positioning System; Information retrieval; Monitoring; Satellites; Scattering; Signal analysis; Soil moisture; AIEM Model; GNSS-R; SMEX02; Soil Moisture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Education Technology and Training, 2008. and 2008 International Workshop on Geoscience and Remote Sensing. ETT and GRS 2008. International Workshop on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3563-0
  • Type

    conf

  • DOI
    10.1109/ETTandGRS.2008.12
  • Filename
    5070190