• Spectroscopy and Spectral Analysis
  • Vol. 37, Issue 3, 829 (2017)
ZHANG Xu-zhou*, DU Peng-peng, HE Yong, and FANG Hui
Author Affiliations
  • [in Chinese]
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    DOI: 10.3964/j.issn.1000-0593(2017)03-0829-07 Cite this Article
    ZHANG Xu-zhou, DU Peng-peng, HE Yong, FANG Hui. Review of Research and Application for Vegetation BRDF[J]. Spectroscopy and Spectral Analysis, 2017, 37(3): 829 Copy Citation Text show less

    Abstract

    Plant leaves, as a vital organ of the plant photosynthesis, directly reflects the plant growth and nutrition status. Internal physicochemical property model, based on the reflection and transmission of plant leaf, indirectly reflects the information of matter and energy exchange in the process of plant growth information, which can be the premise and foundation of the plant growth process of fine management. The optical properties of plant leaves plays a great significant role in the field of crop nutrition diagnosis and plant morphological structure based on remote sensing, in the field of virtual plant light transmission simulation and computer graphics et al. BRDF (Bidirectional Reflectance Distribution Function) mainly focused on spatial distribution and spectral characteristics of the reflected light on the surface of the object characteristics. It can characterize crop growth parameters accurately and efficiently by acquiring optical properties information of plant leaves, which also has great advantages in the research and application of remote sensing in agriculture. In order to better apply BRDF technology in the agricultural remote sensing, this paper will focus on BRDF measurement and device, model development and classification and its application in the field of plants remote sensing. Eventually, although BRDF technology is still in early exploration stage and is facing many tough challenges, it has a promising future in terms of digital agriculture development.
    ZHANG Xu-zhou, DU Peng-peng, HE Yong, FANG Hui. Review of Research and Application for Vegetation BRDF[J]. Spectroscopy and Spectral Analysis, 2017, 37(3): 829
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