• DocumentCode
    3691158
  • Title

    Multifrequency microwave vegetation indexes for estimating vegetation biomass

  • Author

    E. Santi;S. Paloscia;P. Pampaloni

  • Author_Institution
    IFAC-CNR, Florence (Italy)
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    5186
  • Lastpage
    5189
  • Abstract
    The polarization capabilities in estimating vegetation biomass on both global and local scales by using passive and active microwave satellite data (AMSR-E/2, ENVISAT and COSMO-SkyMed) were investigated. Two algorithms that are based on Artificial Neural Networks (ANN) and are able to ingest data from different frequency channels have been implemented. The algorithm validation, carried out on the available experimental data, confirmed that the two polarizations and related indices can be legitimately used to produce vegetation maps on a global and local scale by separating at least 3-4 levels of biomass, without any need of further information from other sensors.
  • Keywords
    "Vegetation mapping","Biomass","Indexes","Artificial neural networks","Microwave radiometry","Satellites","Remote sensing"
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
  • ISSN
    2153-6996
  • Electronic_ISBN
    2153-7003
  • Type

    conf

  • DOI
    10.1109/IGARSS.2015.7327002
  • Filename
    7327002