• DocumentCode
    3689932
  • Title

    Multitemporal polarimetric SAR images for urban areas

  • Author

    E. Colin Koeniguer;F. Weissgerber;N. Trouvé;J-M. Nicolas

  • Author_Institution
    Onera Palaiseau, Chemin de la Huniere et des Joncherettes, FR-91123 Palaiseau, France
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    231
  • Lastpage
    234
  • Abstract
    In the context of rapid global urbanization, urban environments represent one of the most dynamic regions on earth. Even in developed countries the yearly conversion of natural or agricultural space into residential, industrial or transport areas frequently exceeds 100 ha. The current increase in population has resulted in widespread spatial changes, particularly rapid development of built-up areas, in the city and its environs. Due to these rapid changes, up-to-date spatial information is requisite for the effective management and mitigation of the effects of built-up dynamics. Various studies have shown the potential of high resolution optical satellite data for the detection and classification of urban area. Nevertheless optical satellite imagery is characterized by a high dependency in weather conditions and daytime. Thus, particularly in case of regional and national surveys within a short period of time, disaster management, or when data have to be acquired at specific dates, radar systems are more valuable. Thus, the new generation of civil space borne Synthetic Aperture Radar (SAR)-Systems with short revisit can serve as a valuable instrument. Furthermore, there is today a growing access to available data, with revisit times shorter and shorter, improved available resolutions, and a diversification of polarimetric modes. Thus, promising approaches towards the classification of urban area include the analysis of multipolarized image analysis.
  • Keywords
    "Entropy","Polarimetry","Coherence","Synthetic aperture radar","Urban areas","Context","Image resolution"
  • 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.2015.7325742
  • Filename
    7325742