Estimation of Leaf Nitrogen Content in Wheat Using New Hyperspectral Indices and a Random Forest Regression Algorithm

@article{Liang2018EstimationOL,
  title={Estimation of Leaf Nitrogen Content in Wheat Using New Hyperspectral Indices and a Random Forest Regression Algorithm},
  author={Liang Liang and Liping Di and Ting Huang and Jiahui Wang and Li Lin and Lijuan Wang and Minhua Yang},
  journal={Remote Sensing},
  year={2018},
  volume={10},
  pages={1940}
}
Novel hyperspectral indices, which are the first derivative normalized difference nitrogen index (FD-NDNI) and the first derivative ratio nitrogen vegetation index (FD-SRNI), were developed to estimate the leaf nitrogen content (LNC) of wheat. The field stress experiments were conducted with different nitrogen and water application rates across the growing season of wheat and 190 measurements were collected on canopy spectra and LNC under various treatments. The inversion models were… CONTINUE READING

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