Embedded Files
California Greenhouse Gas Emission Measurements
CALGEM-AI
CALGEM-AI
Artificial Intelligence for Estimating Dairy Methane Emissions
Artificial Intelligence for Estimating Dairy Methane Emissions
Training Dataset for Jeong et al. (2022, ES&T)
Includes: aerial images and masks for training the AI (deep learning) model.
Data: link (130 MB)
This dataset is available to the public; if the data are used in a publication, please let us know at sjeong@lbl.gov.
Paper: Jeong, S., M. L. Fischer, H. Breunig, A. R. Marklein, F. M. Hopkins, S. C. Biraud. Artificial Intelligence Approach for Estimating Dairy Methane Emissions (2022), Environmental Science & Technology, https://pubs.acs.org/doi/full/10.1021/acs.est.1c08802.
Gaussian Process (GP) Machine Learning Atmospheric Inverse Modeling
Gaussian Process (GP) Machine Learning Atmospheric Inverse Modeling
Paper: Jeong et al. (2025), Applying Gaussian Process Machine Learning and Modern Probabilistic Programming to Satellite Data to Infer CO2 Emissions, Environmental Science & Technology, https://pubs.acs.org/doi/10.1021/acs.est.4c09395
See GP Inverse Modeling for data and code.
Paper: Johnson, M. S., Hamilton, S. D., Jeong, S., Cui, Y. Y., Wu, D., Turner, A., & Fischer, M. (2025). State-wide California 2020 carbon dioxide budget estimated with OCO-2 and OCO-3 satellite data. Atmospheric Chemistry and Physics, 25(15), 8475–8492. https://doi.org/10.5194/acp-25-8475-2025
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