• DocumentCode
    86564
  • Title

    A Methodology to Determine Radio-Frequency Interference in AMSR2 Observations

  • Author

    de Nijs, Anne H. A. ; Parinussa, Robert M. ; de Jeu, Richard A. M. ; Schellekens, Jaap ; Holmes, Thomas R. H.

  • Author_Institution
    Earth & Climate Cluster, VU Univ. Amsterdam, Amsterdam, Netherlands
  • Volume
    53
  • Issue
    9
  • fYear
    2015
  • fDate
    Sept. 2015
  • Firstpage
    5148
  • Lastpage
    5159
  • Abstract
    A study to determine radio-frequency interference (RFI) in low-frequency passive microwave observations of the Advanced Microwave Scanning Radiometer-2 (AMSR2) is performed. RFI detection methods, such as the spectral difference method, have already been applied on microwave satellite sensors. However, these methods may result in false RFI detection, particularly in zones with extreme environmental conditions. To overcome this problem, this paper proposes an approach that uses the additional 7.3-GHz channel of the AMSR2 sensor in a new RFI detection method. This method uses calculated standard errors of estimate to detect RFI contamination in 6.9- and 7.3-GHz observations. It was found that 6.9-GHz observations are mainly contaminated in the USA, India, Japan, and parts of Europe. The 7.3-GHz observations are contaminated in South America, Ukraine, the Middle East, Southeast Asia, and Russia. The fact that these channels are not affected by RFI in exactly the same regions is useful for studies that prefer C-band brightness temperature observations (e.g., soil moisture retrieval algorithms). Therefore, a decision tree approach was set up to determine RFI and to select reliable brightness temperature observations in the lowest frequency free of any man-made contamination. The result is a reduction of the total contaminated pixels in the 6.9-GHz observations of 66% for horizontal observations and even 85% for vertical observations when 7.3 and 10.7 GHz are used. By linking RFI maps with civilization maps, this paper further shows that RFI sources at the C-band frequency are mainly located in urbanized areas.
  • Keywords
    decision trees; radiofrequency interference; radiometry; remote sensing by radar; AMSR2 observation; AMSR2 sensor channel; C-band brightness temperature observation; C-band frequency; Europe; India; Japan; Middle East; RFI contamination; RFI detection method; RFI source; Russia; South America; Southeast Asia; USA; Ukraine; advanced microwave scanning radiometer-2; decision tree approach; frequency 6.9 GHz; frequency 7.3 GHz; low-frequency passive microwave observation; man-made contamination; microwave satellite sensor; radiofrequency interference determination; soil moisture retrieval algorithm; spectral difference method; urbanized area; Brightness temperature; Contamination; Indexes; Microwave radiometry; Microwave theory and techniques; Soil moisture; Standards; Advanced Microwave Scanning Radiometer-2 (AMSR2); RFI detection; quality control methods; radio-frequency interference (RFI);
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2015.2417653
  • Filename
    7116527