Extraction of the vertical distribution of biochemical parameters using hyperspectral LiDAR

The vertical distribution of plant physiological composition plays an important role in vegetation growth and carbon stock. The hyperspectral LiDAR was thought to be the most promising solution to assess the vertical distribution of vegetation physiological parameters, such as LAI (Leaf Area Index) and chlorophyll content. However, the instrument was not fully feasible, so the simulation and experiment of its response to these parameters was necessary. In this paper, the hyperspectral LiDAR waveform was simulated with the consideration of single scatter of plant radiative transfer model. The variation of LAI and chlorophyll along plant height was investigated and tree scenarios were assumed in the simulation. The hyperspectral lidar data experiment was also carried out to validate the simulation and method. The result showed that the hyperspectral LiDAR waveform could reflect the variation of plant physiological composition and facilitate the inversion algorithm design and it could play a significant role in parameter estimation and precision agriculture application in future.