Newly-developed multi-band spectral ratio index for estimating leaf SPAD content at different angles of HSL

Hyperspectral LiDAR (HSL) is a new type of active detection equipment, which can combine high-resolution spectral data and 3D spatial information into one system. However, the process of collecting data with HSL is susceptible to the effects of incident angle, which in turn affects the ability to monitor chlorophyll, requiring correction measures. In this paper, we analyzed the theoretical basis of using multiple band spectral ratios to overcome the influence of incident angles and proposed four types of multi-band spectral ratio indices for chlorophyll inversion. Next, HSL was used to collect leaf sample data at different angles and their SPAD values, the index forms were optimized with kernel functions, and index construction was completed based on correlation coefficients and variation coefficients. Finally, SPAD inversion was conducted at multiple angles using Partial Least Squares Regression (PLSR) as the prediction model. The results show that the average R² of inversion with the new spectral index in the public dataset (ANGERS) and HSL data are 0.908 and 0.916, RMSE are 6.041 and 3.318, which is better than conventional spectral indices. It indicates that the new multi-band spectral ratio index can correct the incident angle and improve the accuracy of chlorophyll inversion of HSL data.