2nd Week of August

Schaepman-Strub, Gabriela, et al. Reflectance quantities in optical remote sensing—Definitions and case studies. Remote sensing of environment 103.1 (2006) 27-42.

If a surface was not an ideal specular or diffuse surface, one could observe diffuse light as well as specular light reflected off the surface. Reflectance is affected by where the incident light comes from and where the light is observed, which is represented by an angular distribution function. So different reflectance concepts are possible, so it is needed to use the term reflectance practically.

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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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