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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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1st week of december

Féret, J.B. et al., 2019. Estimating leaf mass per area and equivalent water thickness based on leaf optical properties: Potential and limitations of physical modeling and machine learning. Remote Sensing of Environment, 231. Physical model has more ability to generalize itself then empirical or statistical models. But the calibration and the inversion algorithm can be essential and complicated step.
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4th week of may

Jain, V., Biesinger, M. C., & Linford, M. R. (2018). The Gaussian-Lorentzian Sum, Product, and Convolution (Voigt) functions in the context of peak fitting X-ray photoelectron spectroscopy (XPS) narrow scans.  Applied Surface Science ,  447 , 548-553. Spectral peaks are generally assumed to be Gaussian function. The width of its half maximum defines spectral resolution of the sensor. When interpolating spectral signal, linear one is risky especially near the peak wavelength.
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4th week of october

Dechant, B., et al. (2017). "Estimation of photosynthesis traits from leaf reflectance spectra: Correlation to nitrogen content as the dominant mechanism." Remote Sensing of Environment 196: 279-292. Photosynthetic traits has its mechanism by leaf internal components. Comparing the spectroscopic absorption of causing components and their traits, they can be detected and correlation. In the case of Vcmax, N dominantly controls it.
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