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Tropical and temperate forest characterization by parametric P-band SAR tomography with low dimensional models

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اقرأ أكثر حفظ في قائمتي
  • معلومة اضافية
    • Contributors:
      DEMR, ONERA, Université de Toulouse Toulouse; ONERA-Communauté d'universités et établissements de Toulouse (Comue de Toulouse); Centre d'études spatiales de la biosphère (CESBIO); Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3); Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Communauté d'universités et établissements de Toulouse (Comue de Toulouse)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Institut Supérieur de l'Aéronautique et de l'Espace (ISAE-SUPAERO); DEMR, ONERA, Université Paris Saclay Palaiseau; ONERA-Université Paris-Saclay; Météo-France
    • بيانات النشر:
      CCSD
    • الموضوع:
      2024
    • Collection:
      ONERA: HAL (Centre français de recherche aérospatiale / French Aerospace Lab)
    • الموضوع:
      Athènes; Greece
    • نبذة مختصرة :
      International audience ; Synthetic Aperture Radar (SAR) tomography has been successfully applied to the characterization of forest using 3D imaging. Nevertheless, the information content extracted by this technique is limited by the resolution in range and elevation. Also, it is demonstrated that a small number of parameters allows the reconstruction of tomograms that are close to the measured ones. In this paper, forest tomograms are reconstructed by an inversion method using forest scattering models with few parameters. Key forest parameters, such as ground position z g , forest height h v and the ratio between ground intensity and volume are determined using mono-polarized P-band data. These results are compared for different types of forest scattering models with verification data from the TropiSAR and TomoSense campaigns.
    • الدخول الالكتروني :
      https://hal.science/hal-04747759
      https://hal.science/hal-04747759v1/document
      https://hal.science/hal-04747759v1/file/DEMR2024-051.pdf
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.63169452