A light-weight multi-spectral aerial imaging system for nitrogen crop monitoring

A light-weight multi-spectral aerial imaging system for nitrogen crop monitoring Image-based remote sensing is one promising technique for precision crop management. In this study, the use of an ultra light aircraft (ULA) equipped with broadband imaging sensors based on commercial digital cameras was investigated to characterize crop nitrogen status in cases of combined nitrogen and water stress. The acquisition system was composed of two Canon® EOS 400D digital cameras: an original RGB camera measuring luminance in the Red, Green and Blue spectral bands, and a modified camera equipped with an external band-pass filter measuring luminance in the near-infrared. A 5 month experiment was conducted on a sugarcane (Saccharum officinarum) trial consisting of three replicates. In each replicate, two sugarcane cultivars were grown with two levels of water input (rainfed/irrigated) and three levels of nitrogen (0, 65 and 130 kg/ha). Six ULA flights, coupled with ground crop measurements, took place during the experiment. For nitrogen status characterisation, three indices were tested from the closed canopy: the normalised difference vegetation index (NDVI), the green normalised difference vegetation index (GNDVI), and a broadband version of the simple ratio pigment index (hereafter referred to as the SRPIb), calculated from the ratio between blue and red bands of the digital camera. The indices were compared with two nitrogen crop variables: leaf nitrogen content (NL) and canopy nitrogen content (NC). SRPIb showed the best correlation (R 2 = 0.7) with NL, independently of the water and the N treatment. NDVI and GNDVI were best correlated with NC values with correlation coefficients of 0.7 and 0.64 respectively, but the regression coefficients were dependent on the water and N treatment. These results showed that SRPIb could characterise the nitrogen status of sugarcane crop, even in the case of combined stress, and that such acquisition systems are promising for crop nitrogen monitoring. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

A light-weight multi-spectral aerial imaging system for nitrogen crop monitoring

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Publisher
Springer US
Copyright
Copyright © 2012 by Springer Science+Business Media, LLC
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-012-9262-9
Publisher site
See Article on Publisher Site

Abstract

Image-based remote sensing is one promising technique for precision crop management. In this study, the use of an ultra light aircraft (ULA) equipped with broadband imaging sensors based on commercial digital cameras was investigated to characterize crop nitrogen status in cases of combined nitrogen and water stress. The acquisition system was composed of two Canon® EOS 400D digital cameras: an original RGB camera measuring luminance in the Red, Green and Blue spectral bands, and a modified camera equipped with an external band-pass filter measuring luminance in the near-infrared. A 5 month experiment was conducted on a sugarcane (Saccharum officinarum) trial consisting of three replicates. In each replicate, two sugarcane cultivars were grown with two levels of water input (rainfed/irrigated) and three levels of nitrogen (0, 65 and 130 kg/ha). Six ULA flights, coupled with ground crop measurements, took place during the experiment. For nitrogen status characterisation, three indices were tested from the closed canopy: the normalised difference vegetation index (NDVI), the green normalised difference vegetation index (GNDVI), and a broadband version of the simple ratio pigment index (hereafter referred to as the SRPIb), calculated from the ratio between blue and red bands of the digital camera. The indices were compared with two nitrogen crop variables: leaf nitrogen content (NL) and canopy nitrogen content (NC). SRPIb showed the best correlation (R 2 = 0.7) with NL, independently of the water and the N treatment. NDVI and GNDVI were best correlated with NC values with correlation coefficients of 0.7 and 0.64 respectively, but the regression coefficients were dependent on the water and N treatment. These results showed that SRPIb could characterise the nitrogen status of sugarcane crop, even in the case of combined stress, and that such acquisition systems are promising for crop nitrogen monitoring.

Journal

Precision AgricultureSpringer Journals

Published: Apr 13, 2012

References

  • Estimation of sugarcane leaf nitrogen concentration using in situ spectroscopy
    Abdel-Rahman, EM; Ahmed, FB; Berg, M

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