Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-12T22:24:58.396Z Has data issue: false hasContentIssue false

A spectral correction method for multi-scattering effects in close range hyperspectral imagery of vegetation scenes: application to nitrogen content assessment in wheat

Published online by Cambridge University Press:  01 June 2017

G. Rabatel*
Affiliation:
IRSTEA, UMR ITAP, 361 rue Jean-François Breton, 34196 Montpellier Cedex 05, France
N. Al Makdessi
Affiliation:
IRSTEA, UMR ITAP, 361 rue Jean-François Breton, 34196 Montpellier Cedex 05, France
M. Ecarnot
Affiliation:
INRA, UMR AGAP, 2 place Pierre Viala, 34060 Montpellier Cedex 02, France
P. Roumet
Affiliation:
INRA, UMR AGAP, 2 place Pierre Viala, 34060 Montpellier Cedex 02, France
*
E-mail: [email protected]
Get access

Abstract

A method able to overcome multiple scattering effects in close range hyperspectral imagery of vegetation scenes is presented. It has been developed using canopy and light propagation simulation tools and evaluated on real crop plants in the context of nitrogen content assessment.

Type
Precision Nitrogen
Copyright
© The Animal Consortium 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Chelle, M and Andrieu, B 1998. The nested radiosity model for the distribution of light within plant canopies. Ecological Modelling 111, 7591.CrossRefGoogle Scholar
Ecarnot, M, Compan, F and Roumet, P 2013. Assessing leaf nitrogen content and leaf mass per unit area of wheat in the field throughout plant cycle with a portable spectrometer. Field Crops Research 140, 4450.CrossRefGoogle Scholar
Fournier, C, Andrieu, B, Ljutovac, S and Saint-Jean, S 2003. ADEL-wheat: a 3D architectural model of wheat development. Plant Growth Modeling and Applications (eds B-G Hu and M Jaeger), 5466.Google Scholar
Roger, J.M, Chauchard, F and Bellon Maurel, V 2003. EPO-PLS external parameter orthogonalisation of PLS application to temperature-independent measurement of sugar content of intact fruits. Chemometrics and Intelligent Laboratory Systems, Elsevier, 2003 66 (2), 191204.Google Scholar
Vigneau, N, Ecarnot, M, Rabatel, G and Roumet, P 2011. Potential of field hyperspectral imaging as a non destructive method to assess leaf nitrogen content in Wheat. Field Crops Research 122, 2531.CrossRefGoogle Scholar
Wold, S, Sjöström, M and Eriksson, L 2001. PLS-regression: a basic tool of chemometrics. Chemometrics and intelligent laboratory systems 58, 109130.CrossRefGoogle Scholar