• DocumentCode
    1502622
  • Title

    Assessment of TerraSAR-X Products with a New Feature Extraction Application: Monitoring of Cylindrical Tanks

  • Author

    Guida, Raffaella ; Iodice, Antonio ; Riccio, Daniele

  • Author_Institution
    Surrey Space Centre, Univ. of Surrey, Guildford, UK
  • Volume
    48
  • Issue
    2
  • fYear
    2010
  • Firstpage
    930
  • Lastpage
    938
  • Abstract
    There is no doubt that retrieving observed scene features is one of the most interesting and challenging activities in all fields of remote sensing: The successful extraction of scene parameters may not only mean the success of the adopted procedure but also the success of a prediction model, an image product, a sensor project, or even an entire mission. This paper is partly concerned with this. The mission, the sensor, and the products at issue are the TerraSAR-X; the feature retrieval approach is the deterministic model-based approach already tested on E-SAR images and now in phase of improvement and testing on high-resolution TerraSAR-X images. Together with assessing the performances of TerraSAR-X products, this paper deals with a new application which, until now, has not received enough attention even if being worth of it: monitoring of big tanks in suburban or urban areas. Detailed discussion concerning the most suitable product for this kind of application is accompanied by retrieval results carried out on recently acquired TerraSAR-X images.
  • Keywords
    geophysical image processing; geophysical techniques; radar imaging; remote sensing by radar; synthetic aperture radar; E-SAR images; TerraSAR-X products; cylindrical tanks monitoring; feature extraction; high-resolution TerrasSAR-X images; image product; inverse problems; prediction model; remote sensing; scene parameters; sensor project; Feature extraction; inverse problems; synthetic aperture radar (SAR); urban areas;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2009.2029233
  • Filename
    5290029