APA   Click to copy
Madani, N., Parazoo, N. C., Manizza, M., Chatterjee, A., Carroll, D., Menemenlis, D., … Miller, C. E. (2024). A machine learning approach to produce a continuous solar-induced chlorophyll fluorescence dataset for understanding Ocean productivity. Journal of Geophysical Research: Machine Learning and Computation, 1(e2024JH000215). https://doi.org/ https://doi.org/10.1029/2024JH000215

Chicago/Turabian   Click to copy
Madani, Nima, Nicholas C Parazoo, Manfredi Manizza, Abhishek Chatterjee, Dustin Carroll, Dimitris Menemenlis, Vincent le Fouest, et al. “A Machine Learning Approach to Produce a Continuous Solar-Induced Chlorophyll Fluorescence Dataset for Understanding Ocean Productivity.” Journal of Geophysical Research: Machine Learning and Computation 1, no. e2024JH000215 (2024).

MLA   Click to copy
Madani, Nima, et al. “A Machine Learning Approach to Produce a Continuous Solar-Induced Chlorophyll Fluorescence Dataset for Understanding Ocean Productivity.” Journal of Geophysical Research: Machine Learning and Computation, vol. 1, no. e2024JH000215, 2024, doi: https://doi.org/10.1029/2024JH000215.

@article{madani2024a,
  title = {A machine learning approach to produce a continuous solar-induced chlorophyll fluorescence dataset for understanding Ocean productivity},
  year = {2024},
  issue = {e2024JH000215},
  journal = {Journal of Geophysical Research: Machine Learning and Computation},
  volume = {1},
  doi = { https://doi.org/10.1029/2024JH000215},
  author = {Madani, Nima and Parazoo, Nicholas C and Manizza, Manfredi and Chatterjee, Abhishek and Carroll, Dustin and Menemenlis, Dimitris and Fouest, Vincent le and Matsuoka, Atsushi and Luis, Kelly and Serra-Pompei, Camila and Miller, Charles E.},
  howpublished = {}
}