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2nd Week of July 2019

Gara, Tawanda W., et al. Leaf to canopy upscaling approach affects the estimation of canopy traits. GIScience & remote sensing 56.4 (2019) 554-575.
In remotely sensing, upper-most leaves are dominantly detected so they are usually measured for upscaling, assuming that sunlit leaves are representing the whole canopy. Short plants or plants with sparse leaves, however, cannot be seen dominated by sunlit leaves because of canopy vertical diversity. In that case, it is significantly better to measure sunlit and mid-layer leaves(approach B,D and E) more than to measure only sunlit leaves(C). Though r square in remotely sensing canopy chlorophyll was higher at C, there was no significant difference between 2-leaf and 1-leaf approach.

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AGU 2019

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.

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.