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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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3rd week of october

Wang, Z., et al. (2010). "Large variations in Southern Hemisphere biomass burning during the last 650 years." Science 330(6011): 1663-1666. Biomass burning and methane oxidation affect the amount of CO. C derived from biomass burning has higher delta C-13 than methane oxidized C. Also, there is fraction between O-16 and O-18. Using delta C-13 and delta O-18, CO amounts and their relative source can be retrieved.

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.

AGU 2019