• DocumentCode
    3690188
  • Title

    Robust assessment of an operational algorithm for the retrieval of soil moisture from AMSR-E data in central Italy

  • Author

    E. Santi;S. Paloscia;S. Pettinato;L. Brocca;L. Ciabatta

  • Author_Institution
    Institute of Applied Physics - National Research Council, Florence, Italy
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    1288
  • Lastpage
    1291
  • Abstract
    In this work, the surface soil moisture (SMC) derived from the AMSR-E acquisitions by using Artificial Neural Networks (ANN) is compared with simulated data obtained from the application of a soil water balance model in central Italy. All the overpasses available for the 9-years lifetime of AMSR-E have been considered for the comparison, which was carried out point by point over a grid of 91 nodes spaced at 0.1×0.1°, roughly corresponding to the Umbria region. The main purpose of this study is to exploit the potential of AMSR-E sensors for hydrological studies, and in particular, for SMC monitoring at regional scale in heterogeneous environments.
  • Keywords
    "Artificial neural networks","Soil moisture","Orbits","Data models","Radiometers","Training"
  • 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.2015.7326010
  • Filename
    7326010