Comparing hyperspectral index optimization algorithms to estimate aerial N uptake using multi-temporal winter wheat datasets from contrasting climatic and geographic zones in China and Germany.

Highlights: [•] Hyperspectral indices obtained from algorithms designed to optimize a combination of wavebands were explored. [•] Multi-temporal winter wheat datasets of China and Germany were used to assess aerial N uptake. [•] Optimized hyperspectral indices were generally more robust than published indices. [•] Optimized waveband combinations provided a promising algorithm to improve the prediction of aerial N uptake. [•] Implementation for future aerial N uptake monitoring applications by hyperspectral sensors is possible. [Copyright &y& Elsevier]