Articles | Volume 19, issue 14
https://doi.org/10.5194/amt-19-4637-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-4637-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Jul 2026
Research article |
| 21 Jul 2026
| 21 Jul 2026
Automatic methane plume masking based on wavelet transform image processing: application to MethaneAIR and MethaneSAT data
Environmental Defense Fund, Washington, DC, USA
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Maryann Sargent
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Ethan Manninen
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Jack D. Warren
Environmental Defense Fund, Washington, DC, USA
Apisada Chulakadabba
Professorship of Environmental Sensing and Modeling, Technical University of Munich, Munich, Germany
Marcus Russi
Environmental Defense Fund, Washington, DC, USA
Sasha Ayvazov
Environmental Defense Fund, Washington, DC, USA
Joshua Benmergui
Environmental Defense Fund, Washington, DC, USA
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Marvin Knapp
Environmental Defense Fund, Washington, DC, USA
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Ethan Kyzivat
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Christopher C. Miller
Environmental Defense Fund, Washington, DC, USA
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
Sébastien Roche
Environmental Defense Fund, Washington, DC, USA
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
Bingkun Luo
Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
David J. Miller
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Maya Nasr
Environmental Defense Fund, Washington, DC, USA
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Manuel Perez-Carrasco
Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
Department of Civil, Structural and Environmental Engineering, University at Buffalo, Buffalo, NY, USA
James P. Williams
Environmental Defense Fund, Washington, DC, USA
Katlyn MacKay
Environmental Defense Fund, Washington, DC, USA
Mark Omara
Environmental Defense Fund, Washington, DC, USA
Professorship of Environmental Sensing and Modeling, Technical University of Munich, Munich, Germany
Luis Guanter
Environmental Defense Fund, Washington, DC, USA
University of Valencia, Valencia, Spain
Ritesh Gautam
Environmental Defense Fund, Washington, DC, USA
Jonathan Franklin
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Xiong Liu
Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
Steven C. Wofsy
CORRESPONDING AUTHOR
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
Model code and software
zhanzhangqq/wavelet_plume_finder_public: License Update: Added MIT License (Version v1.0.1) Zang Zhang https://doi.org/10.5281/zenodo.21286248
Short summary
Methane released into the atmosphere is often difficult to detect in satellite imagery because the signals can be weak and hidden by background noise. We developed an automated method that improves the visibility of methane plumes while reducing false detections, decreasing the need for time-consuming manual inspection. The method identifies more small emission sources across different instruments, helping build a more complete understanding of methane emissions and their impacts.
Methane released into the atmosphere is often difficult to detect in satellite imagery because...
