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1st week of May

Streher, A. S., da Silva Torres, R., Morellato, L. P. C., & Silva, T. S. F. (2020). Accuracy and limitations for spectroscopic prediction of leaf traits in seasonally dry tropical environments. Remote Sensing of Environment, 244, 111828.
A spectral information projects its foliar traits, each of which exists with diverse proportion in a leaf. When LMA was over 300, model prediction didn't work well. In that region, other foliar traits must have contaminated LMA signals on reflectance. That uniqueness distinguishes savana from the other ecosystems.

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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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AGU 2019

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2nd Week of August

Schaepman-Strub, Gabriela, et al. Reflectance quantities in optical remote sensing—Definitions and case studies. Remote sensing of environment 103.1 (2006) 27-42. If a surface was not an ideal specular or diffuse surface, one could observe diffuse light as well as specular light reflected off the surface. Reflectance is affected by where the incident light comes from and where the light is observed, which is represented by an angular distribution function. So different reflectance concepts are possible, so it is needed to use the term reflectance practically.
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