Articles | Volume 17, issue 4
https://doi.org/10.5194/amt-17-1333-2024
https://doi.org/10.5194/amt-17-1333-2024
Research article
 | 
26 Feb 2024
Research article |  | 26 Feb 2024

Exploiting the entire near-infrared spectral range to improve the detection of methane plumes with high-resolution imaging spectrometers

Javier Roger, Luis Guanter, Javier Gorroño, and Itziar Irakulis-Loitxate

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Cited articles

Ayasse, A. K., Thorpe, A. K., Roberts, D. A., Funk, C. C., Dennison, P. E., Frankenberg, C., Steffke, A., and Aubrey, A. D.: Evaluating the effects of surface properties on methane retrievals using a synthetic airborne visible/infrared imaging spectrometer next generation (AVIRIS-NG) image, Remote Sens. Environ., 215, 386–397, https://doi.org/10.1016/j.rse.2018.06.018, 2018. a
Ayasse, A. K., Thorpe, A. K., Cusworth, D. H., Kort, E. A., Negron, A. G., Heckler, J., Asner, G., and Duren, R. M.: Methane remote sensing and emission quantification of offshore shallow water oil and gas platforms in the Gulf of Mexico, Environ. Res. Lett., 17, 084039, https://doi.org/10.1088/1748-9326/ac8566, 2022. a
Copernicus Climate Change Service, Climate Data Store: Carbon dioxide data from 2002 to present derived from satellite observations, Copernicus Climate Change Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/cds.f74805c8, 2018. a
Cusworth, D., Thorpe, A., Miller, C., Ayasse, A., Jiorle, R., Duren, R., Nassar, R., Mastrogiacomo, J.-P., and Nelson, R.: Two years of satellite-based carbon dioxide emission quantification at the world’s largest coal-fired power plants, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-1408, 2023. a
Cusworth, D. H., Jacob, D. J., Varon, D. J., Chan Miller, C., Liu, X., Chance, K., Thorpe, A. K., Duren, R. M., Miller, C. E., Thompson, D. R., Frankenberg, C., Guanter, L., and Randles, C. A.: Potential of next-generation imaging spectrometers to detect and quantify methane point sources from space, Atmos. Meas. Tech., 12, 5655–5668, https://doi.org/10.5194/amt-12-5655-2019, 2019. a
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Short summary
Methane emissions can be identified using remote sensing, but surface-related structures disturb detection. In this work, a variation of the matched filter method that exploits a large fraction of the near-infrared range (1000–2500 nm) is applied. In comparison to the raw matched filter, it reduces background noise and strongly attenuates the surface-related artifacts, which leads to a greater detection capability. We propose this variation as a standard methodology for methane detection.
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