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Lookup NU author(s): Dr Zhenhai Li, Dr Hao Yang, Beth Clark, Professor Zhenhong Li
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Plant nitrogen (N) information has widely been estimated through empirical techniques using hyperspectral data. However, the physical model inversion approach on N spectral response has seldom developed and remains a challenge. In this study, an N-PROSAIL model based on the N-based PROSPECT model and the SAIL model canopy model was constructed and used for retrieving crop N status both at leaf and canopy scales. The results show that the third parameter (3rd-par) retrieving strategy (leaf area index (LAI) and leaf N density (LND) optimized where other parameters in the N-PROSAIL model are set at different values at each growth stage) exhibited the highest accuracy for LAI and LND estimation, which resulted in R2 and RMSE values of 0.80 and 0.69, and 0.46 and 21.18 µg·cm−2, respectively. It also showed good results with R2 and RMSE values of 0.75 and 0.38% for leaf N concentration (LNC) and 0.82 and 0.95 g·m−2 for canopy N density (CND), respectively. The N-PROSAIL model retrieving method performed better than the vegetation index regression model (LNC: RMSE = 0.48 − 0.64%; CND: RMSE = 1.26 − 1.78 g·m−2). This study indicates the potential of using the N-PROSAIL model for crop N diagnosis on leaf and canopy scales in wheat.
Author(s): Li Z, Jin X, Yang G, Drummond J, Yang H, Clark B, Li Z, Zhao C
Publication type: Article
Publication status: Published
Journal: Remote Sensing
Year: 2018
Volume: 10
Issue: 9
Online publication date: 13/09/2018
Acceptance date: 10/09/2018
Date deposited: 18/09/2018
ISSN (electronic): 2072-4292
Publisher: M D P I AG
URL: https://doi.org/10.3390/rs10091463
DOI: 10.3390/rs10091463
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