• DocumentCode
    85399
  • Title

    Improving Backscatter Intensity Calibration for Multispectral LiDAR

  • Author

    Shuo Shi ; Shalei Song ; Wei Gong ; Lin Du ; Bo Zhu ; Xin Huang

  • Author_Institution
    State Key Lab. of Inf. Eng. in Surveying, Mapping, & Remote Sensing, Wuhan Univ., Wuhan, China
  • Volume
    12
  • Issue
    7
  • fYear
    2015
  • fDate
    Jul-15
  • Firstpage
    1421
  • Lastpage
    1425
  • Abstract
    A wavelength-dependent light detection and ranging (LiDAR) backscatter intensity calibration method was developed to maximize the advantages of a multispectral LiDAR system. We established a spectral ratio calibration method for multispectral LiDAR and investigated the effective calibration procedure for the mixed measurement of the effect of incident angle and surface roughness. Experiment results showed that the proposed LiDAR spectral ratio is insensitive to sensor-related factors and advantageous in calibrating the effect of incidence angle and surface roughness. As the product of the LiDAR calibration procedure based on spectral ratio, extended vegetation indexes significantly improve the classification accuracy.
  • Keywords
    backscatter; calibration; optical radar; remote sensing by radar; surface roughness; surface topography measurement; vegetation mapping; LiDAR spectral ratio; classification accuracy improvement; extended vegetation index; incident angle effect measurement; light detection and ranging; multispectral LiDAR backscatter intensity calibration method; spectral ratio calibration method; surface roughness measurement; Backscatter; Calibration; Indexes; Laser radar; Remote sensing; Rough surfaces; Vegetation mapping; Calibration; light detection and ranging (LiDAR) spectral ratio; multispectral LiDAR; remote sensing; vegetation index;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2015.2405573
  • Filename
    7053915