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

Timely and accurate quantification of aerial nitrogen (N) uptake in crops is important for the calculation of regional N balances and the study of the N budget in agro-ecosystems. Experiments in the present study were conducted from 2007 to 2011 to remotely estimate the aerial N uptake of diverse winter wheat cultivars grown in contrasting climatic and geographic zones in China and Germany. Potentials and limitations of hyperspectral indices obtained from (i) optimized algorithms and (ii) 15 representative indices reported in the literature were tested for stability in estimating the aerial N uptake of winter wheat across different growth stages, cultivars, sites and years. Growth stage, cultivar, N application rates, site and year greatly influenced the relationship between hyperspectral indices and aerial N uptake. The optimized hyperspectral indices generally had more robust aerial N uptake prediction abilities than the published indices. Compared with the algorithms of all possible two-band combinations and red-edge position-based algorithms, area-based algorithms for a three-band optimized combination were more stable in deriving the aerial N uptake of winter wheat. Optimized algorithms can potentially be implemented in future aerial N uptake monitoring by hyperspectral sensing.