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3rd Week of June 2019

Kokaly, Raymond F., et al. Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies. Remote Sensing of Environment 113 (2009) S78-S91.
Reflectance spectra for a single leaf is different from that for a stake of leaves or a canopy in near infrared because, in the range, reflectance is mainly affected by photon scattering, not photon absorption. Canopy scale reflectance, attributed to the structure such as height, would be shown much higher than the others. Thus understanding refectance spectra at canopy scale, it is needed to consider leaf transmittance or canopy structure which is possible to detect in LiDAR sensing.

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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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