Next Article in Journal
Unmanned Aircraft Systems in Remote Sensing and Scientific Research: Classification and Considerations of Use
Previous Article in Journal
Categorizing Wetland Vegetation by Airborne Laser Scanning on Lake Balaton and Kis-Balaton, Hungary
Article Menu

Export Article

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

Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy

Remote Sensing and GIS, School of Engineering and Technology, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
Department of Survey Engineering, Chulalongkorn University, Thailand 254 Phayathai Road, Pathumwan, Bangkok 10330, Thailand
IRD, UMR 190, 44 Bd de Dunkerque, F-13572 Marseille Cedex 02, France
Author to whom correspondence should be addressed.
Received: 25 April 2012 / Revised: 28 May 2012 / Accepted: 30 May 2012 / Published: 6 June 2012
View Full-Text   |   Download PDF [827 KB, uploaded 19 June 2014]   |  


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. View Full-Text
Keywords: hyperspectral; imaging spectroscopy; nitrogen concentration; sugarcane; canopy architecture; first derivative spectrum; absorption feature hyperspectral; imaging spectroscopy; nitrogen concentration; sugarcane; canopy architecture; first derivative spectrum; absorption feature

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

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.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top