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Proceedings Paper

Estimating wheat biochemical concentration from field reflectance spectra
Author(s): Liangyun Liu; Bing Zhang; Lanfen Zheng; Qingxi Tong
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Paper Abstract

The shift of the reflectance red edge parameters is a known phenomenon documenting changes in the biological status and biochemical concentration of plants. In this paper, firstly, the inverted-gaussian (IG) reflectance model was analyzed, and the related reflectance red edge parameters, such as red edge position, λp, absorption peak position λo and absorption width σ, were derived. It is absolutely reliable to simulate wheat canopy reflectance red edge by IG model, because the coefficients of determination, R2, between the 403 reflectance red edges (sampled from winter wheat tillering stage to milking satage) and the fitted IG models are large than 0.98. Secondly, red-shifted was found with an early slow increase in the value of λp, λo in winter wheat’s tillering, jointing, booting and heading stages; Blue-shifted was found with a late decrease in the value of λp, λo in the seed forming and milking stage. Finally, strong correlations were observed between the reflectance red edge parameters and foliar biochemical contents, such as chlorophyll, total nitrogen, sugar, water, from field spectra. The results demonstrated the use of remotely sensed estimates of red edge parameters for estimating biochemical contents, and also indicated the potential of hyperspectral data for precision agriculture.

Paper Details

Date Published: 16 June 2003
PDF: 8 pages
Proc. SPIE 4897, Multispectral and Hyperspectral Remote Sensing Instruments and Applications, (16 June 2003); doi: 10.1117/12.466720
Show Author Affiliations
Liangyun Liu, Institute of Remote Sensing Applications (China)
Bing Zhang, Institute of Remote Sensing Applications (China)
Lanfen Zheng, Institute of Remote Sensing Applications (China)
Qingxi Tong, Institute of Remote Sensing Applications (China)


Published in SPIE Proceedings Vol. 4897:
Multispectral and Hyperspectral Remote Sensing Instruments and Applications
Allen M. Larar; Qingxi Tong; Makoto Suzuki, Editor(s)

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