4th week of september

Brodrick, P. G., Davies, A. B., & Asner, G. P. (2019). Uncovering Ecological Patterns with Convolutional Neural Networks. Trends in ecology & evolution.

When extracting foliar information from high resolution image, it would be quite hard work to detect the leaf, which one wants to know in the map. In the map, the pixel information varies depending on individual leaf angle. And it can change depending on solar zenith angle, which changes every observation. Though one is interested in just the information of a certain leaf, spatial pattern have to be considered.

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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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