Estimating wheat biochemical concentration from field reflectance spectra

Liangyun Liu; Bing Zhang; Lanfen Zheng; Qingxi Tong

doi:10.1117/12.466720

16 June 2003 Estimating wheat biochemical concentration from field reflectance spectra

Liangyun Liu, Bing Zhang, Lanfen Zheng, Qingxi Tong

Proceedings Volume 4897, Multispectral and Hyperspectral Remote Sensing Instruments and Applications; (2003) https://doi.org/10.1117/12.466720
Event: Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, 2002, Hangzhou, China

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, λ_p, absorption peak position λ_o 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 λ_p, λ_o in winter wheat’s tillering, jointing, booting and heading stages; Blue-shifted was found with a late decrease in the value of λ_p, λ_o 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.

Citation Download Citation

Liangyun Liu, Bing Zhang, Lanfen Zheng, and Qingxi Tong "Estimating wheat biochemical concentration from field reflectance spectra", Proc. SPIE 4897, Multispectral and Hyperspectral Remote Sensing Instruments and Applications, (16 June 2003); https://doi.org/10.1117/12.466720

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KEYWORDS

Reflectivity

Biological research

Nitrogen

Absorption

Data modeling

Vegetation

Agriculture

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