Integrating UAV hyperspectral data and radiative transfer model simulation to quantitatively estimate maize leaf and canopy nitrogen content

Author:

Li JiatingORCID,Ge Yufeng,Puntel Laila A.,Heeren Derek M.ORCID,Bai Geng,Balboa Guillermo R.ORCID,Gamon John A.,Arkebauer Timothy J.ORCID,Shi Yeyin

Publisher

Elsevier BV

Reference53 articles.

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3. Bai, G., Ge, Y., Scoby, D., Leavitt, B., Stoerger, V., Kirchgessner, N., ... & Awada, T., 2019. NU-Spidercam: A large-scale, cable-driven, integrated sensing and robotic system for advanced phenotyping, remote sensing, and agronomic research. Comput. Electron. Agric. 160(October 2018), 71–81. Doi: 10.1016/j.compag.2019.03.009.

4. Barnes, E. M., Clarke, T. R., Richards, S. E., Colaizzi, P. D., Haberland, J., Kostrzewski, M., ... & Moran, M. S., 2000. Coincident detection of crop water stress, nitrogen status and canopy density using ground based multispectral data. In Proc. Fifth Int. Conf. Precis. Agric. Bloomington, MN, USA (Vol. 1619, p. 6).

5. Retrieval of aboveground crop nitrogen content with a hybrid machine learning method;Berger;Int. J. Appl. Earth Obs. Geoinf.,2020

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