Estimation Model of Leaf Area Index of Winter Wheat Based on Hyperspectral Reflectance at Different Sowing Dates

Leaf area index (LAI) is closely related to the photosynthetic ability of plants, and its measurement helps to evaluate crop growth status and forecast yield. Hyperspectral remote sensing can be used to acquire crop LAI in real time. This research aimed to establish the best hyperspectral monitoring model for winter wheat LAI under different sowing dates and to improve the forecast precision of the LAI estimation model. The experiments combined ground measurements of winter wheat LAI data with canopy hyperspectral data from four sowing dates. Eight kinds of vegetation indices were comparatively analyzed, then LAI monitoring models for different winter wheat sowing dates were constructed using correlation and regression analyses. The results showed that in comparison to LAI, spectrum monitoring models established for four different sowing dates and from all sowing dates together, the first and fourth sowing dates were better fitted using EVI2 and mNDVI, respectively. The second and third sowing dates and all sowing dates together were best fitted using NDGI. The determination coefficients (R²) for the first, second, third, fourth and all sowing dates together were 0.803, 0.823, 0.907, 0.819, and 0.798, respectively. The model was validated using experimentally collected LAI data and inversion LAI data. The root mean square errors for the fits of the first, second, third, fourth and all sowing dates together were 0.81, 0.78, 0.63, 0.82, and 0.91, respectively. Our results show that monitoring models from different plant stages with different sowing dates were better than a unified monitoring model with a mix of sowing dates, and the precision was higher.Therefore, the vegetation indices EVI2, NDGI, NDGI, and mNDVI were selected separately to establish the LAI monitoring models for the first, second, third and fourth sowing dates. This result provides technical support for growth monitoring of winter wheat at different sowing dates for farmers.