Remote Sensing Applications and Decision Support

Leaf nitrogen spectral reflectance model of winter wheat (Triticum aestivum) based on PROSPECT: simulation and inversion

[+] Author Affiliations
Guijun Yang, Chunjiang Zhao

Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Shuguang Hua Yuan Middle Road No. 11, Haidian District, Beijing, China

National Engineering Research Center for Information Technology in Agriculture, Shuguang Hua Yuan Middle Road No. 11, Haidian District, Beijing, China

Ruiliang Pu

University of South Florida, School of Geosciences, 4202 E. Fowler Avenue, NES 107, Tampa, Florida 33620, United States

Haikuan Feng, Zhenhai Li, Heli Li

National Engineering Research Center for Information Technology in Agriculture, Shuguang Hua Yuan Middle Road No. 11, Haidian District, Beijing, China

Chenhong Sun

Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Shuguang Hua Yuan Middle Road No. 11, Haidian District, Beijing, China

J. Appl. Remote Sens. 9(1), 095976 (Dec 23, 2015). doi:10.1117/1.JRS.9.095976
History: Received July 6, 2015; Accepted November 25, 2015
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Abstract.  Through its association with proteins and plant pigments, leaf nitrogen (N) plays an important regulatory role in photosynthesis, leaf respiration, and net primary production. However, the traditional methods of measurement leaf N are rooted in sample-based spectroscopy in laboratory. There is a big challenge of deriving leaf N from the nondestructive field-measured leaf spectra. In this study, the original PROSPECT model was extended by replacing the absorption coefficient of chlorophyll in the original PROSPECT model with an equivalent N absorption coefficient to develop a nitrogen-based PROSPECT model (N-PROSPECT). N-PROSPECT was evaluated by comparing the model-simulated reflectance values with the measured leaf reflectance values. The validated results show that the correlation coefficient (R) was 0.98 for the wavelengths of 400 to 2500 nm. Finally, N-PROSPECT was used to simulate leaf reflectance using different combinations of input parameters, and partial least squares regression (PLSR) was used to establish the relationship between the N-PROSPECT simulated reflectance and the corresponding leaf nitrogen density (LND). The inverse of the PLSR-based N-PROSPECT model was used to retrieve LND from the measured reflectance with a relatively high accuracy (R2=0.77, RMSE=22.15  μgcm2). This result demonstrates that the N-PROSPECT model established in this study can accurately simulate nitrogen spectral contributions and retrieve LND.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Guijun Yang ; Chunjiang Zhao ; Ruiliang Pu ; Haikuan Feng ; Zhenhai Li, et al.
"Leaf nitrogen spectral reflectance model of winter wheat (Triticum aestivum) based on PROSPECT: simulation and inversion", J. Appl. Remote Sens. 9(1), 095976 (Dec 23, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.095976


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