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Journal of Applied Remote Sensing

Leaf nitrogen spectral reflectance model of winter wheat (<italic<Triticum aestivum</italic<) based on PROSPECT: simulation and inversion
Author(s): Guijun Yang; Chunjiang Zhao; Ruiliang Pu; Haikuan Feng; Zhenhai Li; Heli Li; Chenhong Sun
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Paper 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.

Paper Details

Date Published: 23 December 2015
PDF: 14 pages
J. Appl. Remote Sens. 9(1) 095976 doi: 10.1117/1.JRS.9.095976
Published in: Journal of Applied Remote Sensing Volume 9, Issue 1
Show Author Affiliations
Guijun Yang, National Engineering Research Ctr. for Information Technology in Agriculture (China)
Beijing Academy of Agriculture and Forestry Sciences (China)
Chunjiang Zhao, Beijing Academy of Agriculture and Forestry Sciences (China)
National Engineering Research Ctr. for Information Technology in Agriculture (China)
Ruiliang Pu, Univ. of South Florida (United States)
Haikuan Feng, National Engineering Research Ctr. for Information Technology in Agriculture (China)
Zhenhai Li, National Engineering Research Ctr. for Information Technology in Agriculture (China)
Heli Li, National Engineering Research Ctr. for Information Technology in Agriculture (China)
Chenhong Sun, National Engineering Research Ctr. for Information Technology in Agriculture (China)


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