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1st week of june

Feilhauer, H., Asner, G. P., Martin, R. E., & Schmidtlein, S. (2010). Brightness-normalized partial least squares regression for hyperspectral data. Journal of Quantitative Spectroscopy and Radiative Transfer, 111(12-13), 1947-1957.
Leaf spectra varies with canopy structure, such as leaf angel, LAI etc. They affects the magnitude of spectra. Brightness normalization is one option to alleviate canopy effects. In doing so, spectral magnitude is normalized without any changes in the shape. It could improve model performance by reducing shade heterogeneity within canopy.

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4th Week of August

Farquhar, G. D., von Caemmerer, S. V., & Berry, J. A. (1980). A biochemical model of photosynthetic CO 2 assimilation in leaves of C 3 species.  Planta ,  149 (1), 78-90. Carbon assimilation is mainly controlled by electron, light which is reducing electron from water molecule, O2 and CO2. They consist of the model.
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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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