3rd week of december

Gitelson, A.A., Zur, Y., Chivkunova, O.B. and Merzlyak, M.N., 2002. Assessing carotenoid content in plant leaves with reflectance spectroscopy. Photochem Photobiol, 75(3): 272-81.

Carotenoid content is lower than leaf chlorophyll content. But the seasonal decrease is much lower than that of chlorophyll. Namely, in green leaves, the strong chlorophyll effect in visible range obscures carotenoid signal. On the other hand, in yellowish leaves, the effect is little. Before estimating carotenoid content, it can be useful to classify leaves by carotenoid proportion.

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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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