Volume 43 Issue 6
Dec.  2023
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Article Navigation >  Chinese Journal of Space Science  > 2023  >  43(6): 1160-1175 Open Access
HU Ronghai, XING Yuzhen. Retrieval methods for Tree Leaf Area Parameters Based on Terrestrial Laser Scanning (in Chinese). Chinese Journal of Space Science, 2023, 43(6): 1160-1175 doi: 10.11728/cjss2023.06.2023-0078
Citation: HU Ronghai, XING Yuzhen. Retrieval methods for Tree Leaf Area Parameters Based on Terrestrial Laser Scanning (in Chinese). Chinese Journal of Space Science, 2023, 43(6): 1160-1175 doi: 10.11728/cjss2023.06.2023-0078
shu

Retrieval methods for Tree Leaf Area Parameters Based on Terrestrial Laser Scanning

doi: 10.11728/cjss2023.06.2023-0078 cstr: 32142.14.cjss2023.06.2023-0078

  • College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049

  • Beijing Yanshan Earth Critical Zone National Research Station, Beijing 101408

  • Received Date: 2023-06-20
  • Rev Recd Date: 2023-08-11
    • Available Online: 2023-11-29
    Abstract
  • Leaf Area Index (LAI) is a key parameter that characterizes the structure of vegetation canopies, and the indirect measurement of LAI has always been an important research topic in vegetation remote sensing. Terrestrial Laser Scanning (TLS), with its efficient and precise three-dimensional observation capability, has been widely used for LAI estimation. At the same time, TLS provides possibilities for the inversion of more refined leaf area parameters, such as the three-dimensional distribution of Foliage Area Volume Density (FAVD). This paper reviews the main methods for retrieving leaf area parameters based on TLS from a methodological perspective, discussing their advantages, limitations, and influencing factors. The indirect measurement of leaf area parameters based on TLS can be classified into four categories: the gap fraction-based method, the contact frequency-based method, the computer graphics theory-based method, and the ecophysiological model-based method. These methods differ in theoretical foundations, data organization, etc., and are suitable for the retrieval of various leaf area parameters at different scales. Among them, the mainstream approach currently relies on the measurement and analysis of gap fraction, and it has evolved into three categories based on different forms of point cloud organization: 2D images, pulses, and voxels. Methods based on contact frequency, computer graphics theory, and ecophysiological models are also emerging, providing new avenues for leaf area parameter inversion and can be further optimized to improve the accuracy and efficiency of LAI estimation. Existing methods have basically covered the inversion of various leaf area parameters at different scales. From stand-scale LAI to more refined individual-tree-scale Vertical Foliage Profile (VFP) and voxel-scale FAVD, leaf area parameter inversion based on TLS continues to advance in a refined and three-dimensional direction. In this process, clumping effects, non-uniform path lengths, and occlusion effects are important factors that affect measurement accuracy and require further research and calibration.

     

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