Estimation of winter wheat leaf area index at different growth stages using optimized red-edge hyperspectral vegetation indices

Leaf area index (LAI), as one of the most important indicators in vegetation growth monitoring, has been widely used in crop growth monitor and yield estimation. Previous studies focused on LAI retrieval for whole growth stages, this study inversed LAI at five main growth stages using widely-acknowledged vegetation indices and their optimized red-edge transformations. We used hyperspectral data to analyse relationships between LAI and vegetation indices. Partial least square discriminant analysis (PLS-DA) was used in this study to distinguish the best indices for distinct growth stages. The results show that LAI retrieval at various growth stages have distinct results. The best fitted indices for different growth stages are not fixed. The best indices for five stages are OSAVIre1, SRre1, SAVIre2, SAVIre2 and OSAVIre1 with R2 value of 0.20, 0.50, 0.49, 0.72 and 0.23, respectively. Most vegetation indices show better performance in milky stage than other four stages this may due to the high vegetation cover in this stage because leaves rise to maximum. Indices composed of red-edge exhibited better relationships with LAI with higher R2 and lower RMSE. Indices combined reflectance at 740 nm are capable of inversing LAI at stem elongation, anthesis and milk development stages. Indices with 705 nm showed better results in jointing and ripening stages. The results indicate that:1) specific vegetation indices for distinct growth stages lead to better estimation than inversing LAI for whole growth stages; 2) indices take advantage of red-edge showed better potentials in estimating high LAI than traditional visible wavelength.