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4th week of July


Exploring the potential of PROCOSINE and close-range hyperspectral imaging to study the effects of fungal diseases on leaf physiology


Symptoms of plant diseases just start to appear on only part of a leaf. To early detect them, sub-millimeter scale changes on a leaf need to be considered. Incorporating PROSPECT to leaf surface information, (specular parameter, incident light angle and leaf curved angle), PROCOSINE model well explains leaf physiology in close-range remote sensing.

Reference
Morel, J., Jay, S., Féret, J. B., Bakache, A., Bendoula, R., Carreel, F., & Gorretta, N. (2018). Exploring the potential of PROCOSINE and close-range hyperspectral imaging to study the effects of fungal diseases on leaf physiology. Scientific reports, 8(1), 1-13.

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AGU 2019

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4th week of june

Asner, G. P., Martin, R. E., Anderson, C. B., & Knapp, D. E. (2015). Quantifying forest canopy traits: Imaging spectroscopy versus field survey.  Remote Sensing of Environment ,  158 , 15-27. They use canopy sunlit reflectance at plot level and the trait samples from sunlit. The plot averaged refletance minimize canopy architectural effect. However actual field samples cover only 5% of a plot, the plot reflectance well explains canopy traits.
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1st Week of August

Jacquemoud, S., et al. "Estimating leaf biochemistry using the PROSPECT leaf optical properties model."  Remote sensing of environment  56.3 (1996): 194-202. Leaf reflectance is affected by leaf biochemicals as well as by pigments or water. Inspecting NIR reflectance, N which is highly correlated to protein and C which are highly correlated to  cellulose and lignin  can be detected.
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