CS-E407519 - Special Course in Machine Learning, Data Science and Artificial Intelligence: Machine Learning for Climate Action, Lectures, 8.1.2024-15.2.2024
This course space end date is set to 15.02.2024 Search Courses: CS-E407519
Research papers for lectures II-VI
Completion requirements
- Lecture II: D. P. Finch, P. I. Palmer, and T. Zhang (2022). Automated detection of atmospheric NO2 plumes from satellite data: a tool to help infer anthropogenic combustion emissions. Atmospheric Measurement Techniques, 15(3):721–733, 2022.
- Lecture III: Schuit, B. J., Maasakkers, J. D., Bijl, P., Mahapatra, G., Van den Berg, A. W., Pandey, S., Aben, I. (2023). Automated detection and monitoring of methane super-emitters using satellite data. Atmospheric Chemistry and Physics Discussions, 1-47.
- Lecture IV: Paolo, F., Kroodsma, D., Raynor, J. et al. Satellite mapping reveals extensive industrial activity at sea. Nature 625, 85–91 (2024). https://doi.org/10.1038/s41586-023-06825-8
- Lecture V: Oh, Jin Woo, et al. "Using deep-learning to forecast the magnitude and characteristics of urban heat island in Seoul Korea." Scientific reports 10.1 (2020): 3559.
- Lecture VI: Zhu, Xiao Xiang et al. "The urban morphology on our planet -- Global perspectives from space". Remote Sensing of Environment, vol. 269, p. 112794 (2022)
Last modified: Friday, 2 February 2024, 4:55 PM