• DocumentCode
    2215705
  • Title

    Microwave vegetation index from SMOS

  • Author

    Shi, Jiancheng ; Li, Yunqing

  • Author_Institution
    State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    194
  • Lastpage
    197
  • Abstract
    Monitoring global vegetation can be of importance in understanding land surface processes and their interactions with the atmosphere, biogeochemical cycle, and primary productivity. Previous research has shown that vegetation indices have become essential tools in this field. In this study, we will explore and demonstrate a new technique for deriving Microwave Vegetation Indices (MVIs) using the passive microwave radiometer SMOS data. It provides the global microwave brightness temperature observations at L-band (1.4 GHz) with dual polarizations (V, H) and a range of viewing angles [2]. The SMOS MVIs A parameter was negatively related to NDVI while the B parameter is positively related to NDVI. Compared with WindSat MVIs, SMOS MVIs have similar global distribution patterns but can indicate different vegetation information mainly because of penetrability and incidence angle variation. Based on analysis using BARC 1980 data, SMOS MVI_B is linearly related to LAI.
  • Keywords
    atmospheric temperature; microwave measurement; radiometers; vegetation; vegetation mapping; BARC data; L-band observation data; NDVI; SMOS MVI; WindSat MVI; biogeochemical cycle; dual polarizations; frequency 1.4 GHz; global distribution patterns; global microwave brightness temperature; global vegetation monitoring; incidence angle variation; land surface process; microwave vegetation index; passive microwave radiometer SMOS data; Brightness temperature; Indexes; Microwave measurements; Microwave radiometry; Microwave theory and techniques; Soil; Vegetation mapping; L-band; Microwave vegetation index; Multi-angle; SMOS;
  • 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.2012.6351604
  • Filename
    6351604