Remote Sens. 2012, 4(6), 1651-1670; doi:10.3390/rs4061651
Article

Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy

1 Remote Sensing and GIS, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand 2 Department of Survey Engineering, Chulalongkorn University, Thailand 254 Phayathai Road, Pathumwan, Bangkok 10330, Thailand 3 IRD, UMR 190, 44 Bd de Dunkerque, F-13572 Marseille Cedex 02, France
* Author to whom correspondence should be addressed.
Received: 25 April 2012; in revised form: 28 May 2012 / Accepted: 30 May 2012 / Published: 6 June 2012
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Abstract: The retrieval of nutrient concentration in sugarcane through hyperspectral remote sensing is widely known to be affected by canopy architecture. The goal of this research was to develop an estimation model that could explain the nitrogen variations in sugarcane with combined cultivars. Reflectance spectra were measured over the sugarcane canopy using a field spectroradiometer. The models were calibrated by a vegetation index and multiple linear regression. The original reflectance was transformed into a First-Derivative Spectrum (FDS) and two absorption features. The results indicated that the sensitive spectral wavelengths for quantifying nitrogen content existed mainly in the visible, red edge and far near-infrared regions of the electromagnetic spectrum. Normalized Differential Index (NDI) based on FDS(750/700) and Ratio Spectral Index (RVI) based on FDS(724/700) are best suited for characterizing the nitrogen concentration. The modified estimation model, generated by the Stepwise Multiple Linear Regression (SMLR) technique from FDS centered at 410, 426, 720, 754, and 1,216 nm, yielded the highest correlation coefficient value of 0.86 and Root Mean Square Error of the Estimate (RMSE) value of 0.033%N (n = 90) with nitrogen concentration in sugarcane. The results of this research demonstrated that the estimation model developed by SMLR yielded a higher correlation coefficient with nitrogen content than the model computed by narrow vegetation indices. The strong correlation between measured and estimated nitrogen concentration indicated that the methods proposed in this study could be used for the reliable diagnosis of nitrogen quantity in sugarcane. Finally, the success of the field spectroscopy used for estimating the nutrient quality of sugarcane allowed an additional experiment using the polar orbiting hyperspectral data for the timely determination of crop nutrient status in rangelands without any requirement of prior cultivar information.
Keywords: hyperspectral; imaging spectroscopy; nitrogen concentration; sugarcane; canopy architecture; first derivative spectrum; absorption feature

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MDPI and ACS Style

Miphokasap, P.; Honda, K.; Vaiphasa, C.; Souris, M.; Nagai, M. Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy. Remote Sens. 2012, 4, 1651-1670.

AMA Style

Miphokasap P, Honda K, Vaiphasa C, Souris M, Nagai M. Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy. Remote Sensing. 2012; 4(6):1651-1670.

Chicago/Turabian Style

Miphokasap, Poonsak; Honda, Kiyoshi; Vaiphasa, Chaichoke; Souris, Marc; Nagai, Masahiko. 2012. "Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy." Remote Sens. 4, no. 6: 1651-1670.

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