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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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AGU 2019

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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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1st week of August

The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography The paper mapped above ground biomass using satellite radar and LiDAR fusion. Satellite radar systems provides global data, as it passes through clouds. However, radar cannot produce vertical profile. Satellite LiDAR system, the paper targeting, provides accurate canopy point clouds. On the contrary, clouds occlude LiDAR incident wave. As the author mentioned, it only covered only 4% of the surface for 2 years. To combine LiDAR with radar, LiDAR data was compared to radar and then extended to radar. Validation was done plots where the coverage of LiDAR and radar overlapped. Reference Dubayah, R., Blair, J. B., Goetz, S., Fatoyinbo, L., Hansen, M., Healey, S., ... & Armston, J. (2020). The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography. Science of Remote Sensing, 1, 100002.
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