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1st Week of July 2019

Cho, Moses Azong, et al. Discriminating species using hyperspectral indices at leaf and canopy scales. The International Archives of the Spatial Information Sciences (2008) 369-376.
At canopy scale, PRI(Petrochemical Reflectance Index) was the best indicator for classifying plant species. It means, because PRI may influenced by soil background, PRI was well defined to detect leaf area and leaf angle information. REP(Red Edge Position), however, had no difference among both scales. It means that REP was well defined to detect leaf traits, so it was identical at canopy scale which probably had another information, such as lignin, leaf area, leaf angle, solar zenith, etc.

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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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2nd week of december

El Alem, A., Chokmani, K., Agili, H., Poulin, J., Laurion, I., Venkatesan, A. E., & Dedieu, J. P. (2019, December). Potential of a Drone Hyperspectral Data-Based Model to Remote Estimate Chlorophyll-a Concentration from Sentinel 2A and 2B Sensors Data. In  AGU Fall Meeting 2019 . AGU. As for ocean chlorophyll contents, they are not distributed evenly. Rather, their amounts are polarized. The author harmonized two models, the one is classifying model and the other is retrieving model.
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