Simultaneous Extraction of Plant 3-D Biochemical and Structural Parameters Using Hyperspectral LiDAR

Abstract

Hyperspectral light detection and ranging (LiDAR) (HSL) can be used to acquire backscattered full-waveform data with abundant spectral information, providing a new technique for the remote sensing of plant 3-D properties monitoring. HSL 3-D point cloud of two Kniphofia uvaria plants was acquired by HSL scanning and data processing. Then, chlorophyll concentration could be retrieved at any 3-D position using a constructed partial least squares regression (PLSR) model. At the same time, the vegetation canopy structural parameters (canopy height, maximum canopy width, and projected canopy area) were retrieved based on the geometric information of the HSL data. The results of this study showed that the HSL system could be used to realize the simultaneous extraction of both the 3-D biochemical and structural parameters, which has great potential in the field of quantitative remote sensing.