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Estimation of leaf biochemical content using a novel hyperspectral full-waveform LiDAR system

A novel hyperspectral full-waveform light detection and ranging (LiDAR) system was proposed in this study. First, the optical set-up of this system was introduced. Second, the spectral reflectance of two kinds of leaves was measured using this system as well as a common spectrometer. A workflow was proposed to show how to calculate spectral reflectance from the LiDAR data. Three vegetation indices (VIs) – simple ratio index, normalized difference vegetation index and photochemical reflectance index – were calculated using the reflectance derived from the data collected by these two instruments. Finally, the LiDAR-derived VIs were used to test for the estimation of leaf biochemical contents. Results show that: (1) LiDAR reflectance is different from that measured by spectrometer, but the LiDAR and spectrometer spectral shapes are clearly similar; (2) leaf biochemical contents can be successfully estimated by LiDAR-derived VIs with a root mean square error of 0.46–0.55% for nitrogen content, 1.42–2.98 mg g−1 for chlorophyll content and 0.35–0.56 mg g−1 for carotenoid content. These results demonstrate the possibilities for estimating leaf biochemical contents using the new hyperspectral full-waveform LiDAR data.