Paper
1 September 2005 Spectral red edge parameters for winter wheat under different nitrogen support levels
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Abstract
Hyperspectral remote sensing is not only an important technical method in observing global ecosystems and vegetation cover change, but also a main aspect of studies on precision agriculture. In order to monitor crop nutrient supply condition and to realize precision fertilization, spectral red edge parameter for winter wheat was studied. Experiments were carried out through 8 years since 1997 under four nitrogen support levels in Luancheng Station, Hebei province (e.g., 0, 100, 200 and 300 kg N ha-1). Canopy reflectance spectrum was measured by ASD HandHeld Spectroradiometer (325-1075 nm) during 2002 and 2004. The dynamics of red edge parameters for physiological stages of winter wheat canopy were calculated using first derivative curve. Analyses revealed that the red edge of the wheat canopy reflectance spectrum locates between 720-740 nm. All the different trial had distinct "red shift" trait, but higher N stress had shorter "red edge" wavelength. Position of red edge turned "blue shift" after pregnant period. Red edge swing is a first-order derivative spectrum when wavelength reached red edge position, red edge swing double peak shape showed that the pregnant period was the best stage to detect nitrogen deficiency. Red edge swing correlated with relative chlorophyll content and leaf N content. Area of red edge peak is the value of first-order derivative spectra accumulative total between 680 and 750 nm. These parameters can be used to estimate LAI and N accumulating quantities, and these results provide information needed for the development of variable-rate N application technology.
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Yisong Cheng, Chunsheng Hu, Hui Dai, and Yuping Lei "Spectral red edge parameters for winter wheat under different nitrogen support levels", Proc. SPIE 5884, Remote Sensing and Modeling of Ecosystems for Sustainability II, 58841A (1 September 2005); https://doi.org/10.1117/12.614759
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Cited by 4 scholarly publications.
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KEYWORDS
Nitrogen

Reflectivity

Vegetation

Agriculture

Ecosystems

Infrared radiation

Remote sensing

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