• DocumentCode
    576436
  • Title

    Integration of X-band SAR and optical thermal data for retrieving snowpack parameters in mountain areas

  • Author

    Pasolli, Luca ; Callegari, Mattia ; Notarnicola, Claudia ; Bruzzone, Lorenzo ; Zebisch, Marc

  • Author_Institution
    Inst. for Appl. Remote Sensing, Eurac Res., Bolzano, Italy
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    7035
  • Lastpage
    7038
  • Abstract
    This paper presents a study on the retrieval of snowpack biophysical parameters in mountain areas from satellite remote sensing imagery. More in detail, the integration of new generation X-band Cosmo SkyMed SAR imagery and land surface temperature (LST) information derived from optical thermal remote sensing is investigated. First, a sensitivity analysis is carried out, in order to understand whether and to what extent the investigated remote sensing signals are sensitive to variations in different snowpack target parameters. Then, an advanced retrieval system based on the Support Vector Machine approach in a multilevel architecture is developed. Experiments carried out in a small valley in the eastern Alps during the winter 2010/11 point out the effectiveness of the combined use of X-band SAR and thermal satellite imagery for the characterization of snowpack parameters in terms of both accuracy on reference point measurements and capability to reproduce spatial patterns of the target variables.
  • Keywords
    geophysical image processing; geophysical techniques; land surface temperature; remote sensing by radar; sensitivity analysis; snow; support vector machines; synthetic aperture radar; X-band Cosmo SkyMed SAR imagery; advanced retrieval system; eastern Alps; land surface temperature information; mountain areas; multilevel architecture; optical thermal data; optical thermal remote sensing; reference point measurements; remote sensing signals; satellite remote sensing imagery; sensitivity analysis; snowpack biophysical parameters; snowpack target parameters; spatial patterns; support vector machine approach; target variables; thermal satellite imagery; Accuracy; Backscatter; Estimation; Remote sensing; Satellites; Snow; Synthetic aperture radar; Cosmo SkyMed; Land Surface Temperature; Retrieval; Snowpack Parameters;
  • 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.2012.6351951
  • Filename
    6351951