• DocumentCode
    143838
  • Title

    To derive BRDF archetypes from POLDER-3 BRDF database

  • Author

    Ziti Jiao ; Yadong Dong ; Hu Zhang ; Xiaowen Li

  • Author_Institution
    Sch. of Geogr., Beijing Normal Univ., Beijing, China
  • fYear
    2014
  • fDate
    13-18 July 2014
  • Firstpage
    3586
  • Lastpage
    3589
  • Abstract
    In this study, based on kernel-driven linear BRDF model, a new spectral vegetation index named anisotropic flat index (AFX) and a hotspot kernel function are described. Anisotropic Flat Index (AFX), which is created by normalization of net scattering magnitude with the isotropic scattering, can summarize the variability of basic dome-bowl anisotropic reflectance pattern of the terrestrial surface. The hotspot kernel function is modified with the exponential approximation to generate a so-called RossThickChen kernel (KRTC). Using the POLDER-3 multi-angular observations, a classification scheme for BRDF typology is created and a BRDF archetype data is established. The results show that the AFX effectively summarizes BRDF archetypes that provide additional information on vegetation structures and other anisotropic reflectance characteristics of the land surface. The RTCLSR model can significantly capture the hotspot signatures, the BRDF archetypes derived in this way provides a significantly different hotspot signatures from those derived from the MODIS BRDF product.
  • Keywords
    radiometry; vegetation; AFX; BRDF archetype data; BRDF typology classification scheme; KRTC; MODIS BRDF product; POLDER-3 BRDF database; POLDER-3 multiangular observation; RTCLSR model; RossThickChen kernel; anisotropic flat index; basic dome-bowl anisotropic reflectance pattern variability; exponential approximation; hotspot kernel function; hotspot signature; isotropic scattering; kernel-driven linear BRDF model; land surface anisotropic reflectance characteristic; net scattering magnitude normalization; spectral vegetation index; terrestrial surface; vegetation structure; Biological system modeling; Databases; Kernel; Land surface; Scattering; Shape; Vegetation mapping; Albedo; BRDF archetype; bayes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
  • Conference_Location
    Quebec City, QC
  • Type

    conf

  • DOI
    10.1109/IGARSS.2014.6947258
  • Filename
    6947258