Wavelength selection of the multispectral lidar system for estimating leaf chlorophyll and water contents through the PROSPECT model

Abstract The estimation of leaf biochemical constituents is of high interest for the physiological and ecological applications of remote sensing. The multispectral lidar (MSL) system emerges as a promising active remote sensing technology with the ability to acquire both three-dimensional and spectral characteristics of targets. The detection wavelengths of the MSL system can be geared toward the specific application purposes. Therefore, it’s important to conduct the wavelength selection work to maximize the potential of the MSL system in vegetation monitoring. Traditional strategies of wavelength selection attempt to establish an empirical relationship between large quantities of observed reflectance and foliar biochemical constituents. By contrast, this study proposed to select wavelengths through the radiative transfer model PROSPECT. A five-wavelength combination was established to estimate leaf chlorophyll and water contents: 680, 716, 1104, 1882 and 1920 nm. The consistency of the wavelengths selected were tested by running different versions of PROSPECT model. Model inversion using simulated and experimental datasets showed that the selected wavelengths have the ability to retrieve leaf chlorophyll and water contents accurately. Overall, this study demonstrated the potential of the MSL system in vegetation monitoring and can serve as a guide in the design of new MSL systems for the application community.