Methane Plumes Detection on Prisma L1 Images with the Adjusted Spectral Matched Filter and Wind Data

E. Ouerghi; T. Ehret; G. Facciolo; E. Meinhardt; J.-M. Morel; C. de Franchis; T. Lauvaux

doi:10.1109/IGARSS52108.2023.10282211

Methane Plumes Detection on Prisma L1 Images with the Adjusted Spectral Matched Filter and Wind Data

E. Ouerghi
, T. Ehret
, G. Facciolo
, E. Meinhardt
, J.-M. Morel
, C. de Franchis
, T. Lauvaux

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

8 Citations (Scopus)

Abstract

Reducing methane emissions is essential to tackle climate change. Here, we address the problem of detecting automatically point source methane leaks using high resolution hyperspectral images from the PRISMA satellite. We use a variation of the Matched Filter (MF) called the Adjusted Spectral Matched Filter (ASMF) to detect methane plumes in satellite images. To remove false positives, the detected plumes are confirmed by comparing their orientation to the wind direction extracted from the standard meteorological reanalysis product ERA5. The ASMF reduces the fraction of false detections compared to the MF and without preventing the detection of plumes. To validate the method, we use a recently proposed dataset of manually annotated plumes on PRISMA images. We also compare our detection rate to the detection rate of methods using deep learning or the standard matched filter. We then show that our method outperforms those methods in terms of F1 score. © 2023 IEEE.

Original language	English
Title of host publication	IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
Publisher	IEEE
Pages	7598-7601
ISBN (Electronic)	979-8-3503-2010-7, 979-8-3503-2009-1
ISBN (Print)	979-8-3503-3174-5
DOIs	https://doi.org/10.1109/IGARSS52108.2023.10282211
Publication status	Published - 2023
Externally published	Yes
Event	43rd IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2023) - Pasadena Convention Center, Pasadena, United States Duration: 16 Jul 2023 → 21 Jul 2023 https://2023.ieeeigarss.org/index.php

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
ISSN (Print)	2153-6996
ISSN (Electronic)	2153-7003

Conference

Conference	43rd IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2023)
Place	United States
City	Pasadena
Period	16/07/23 → 21/07/23
Internet address	https://2023.ieeeigarss.org/index.php

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

Research Keywords

Anomaly detection
Hyperspectral images
Matched filter
Methane
Wind data

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10.1109/IGARSS52108.2023.10282211

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Cite this

Ouerghi, E., Ehret, T., Facciolo, G., Meinhardt, E., Morel, J.-M., de Franchis, C., & Lauvaux, T. (2023). Methane Plumes Detection on Prisma L1 Images with the Adjusted Spectral Matched Filter and Wind Data. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium - Proceedings (pp. 7598-7601). (International Geoscience and Remote Sensing Symposium (IGARSS)). IEEE. https://doi.org/10.1109/IGARSS52108.2023.10282211

@inproceedings{6996091b54a74222a452b718643b9eaf,

title = "Methane Plumes Detection on Prisma L1 Images with the Adjusted Spectral Matched Filter and Wind Data",

abstract = "Reducing methane emissions is essential to tackle climate change. Here, we address the problem of detecting automatically point source methane leaks using high resolution hyperspectral images from the PRISMA satellite. We use a variation of the Matched Filter (MF) called the Adjusted Spectral Matched Filter (ASMF) to detect methane plumes in satellite images. To remove false positives, the detected plumes are confirmed by comparing their orientation to the wind direction extracted from the standard meteorological reanalysis product ERA5. The ASMF reduces the fraction of false detections compared to the MF and without preventing the detection of plumes. To validate the method, we use a recently proposed dataset of manually annotated plumes on PRISMA images. We also compare our detection rate to the detection rate of methods using deep learning or the standard matched filter. We then show that our method outperforms those methods in terms of F1 score. {\textcopyright} 2023 IEEE.",

keywords = "Anomaly detection, Hyperspectral images, Matched filter, Methane, Wind data",

author = "E. Ouerghi and T. Ehret and G. Facciolo and E. Meinhardt and J.-M. Morel and \{de Franchis\}, C. and T. Lauvaux",

year = "2023",

doi = "10.1109/IGARSS52108.2023.10282211",

language = "English",

isbn = "979-8-3503-3174-5",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

publisher = "IEEE",

pages = "7598--7601",

booktitle = "IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium - Proceedings",

address = "United States",

note = "43rd IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2023) ; Conference date: 16-07-2023 Through 21-07-2023",

url = "https://2023.ieeeigarss.org/index.php",

}

Ouerghi, E, Ehret, T, Facciolo, G, Meinhardt, E, Morel, J-M, de Franchis, C & Lauvaux, T 2023, Methane Plumes Detection on Prisma L1 Images with the Adjusted Spectral Matched Filter and Wind Data. in IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium - Proceedings. International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, pp. 7598-7601, 43rd IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2023), Pasadena, California, United States, 16/07/23. https://doi.org/10.1109/IGARSS52108.2023.10282211

Methane Plumes Detection on Prisma L1 Images with the Adjusted Spectral Matched Filter and Wind Data. / Ouerghi, E.; Ehret, T.; Facciolo, G. et al.
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium - Proceedings. IEEE, 2023. p. 7598-7601 (International Geoscience and Remote Sensing Symposium (IGARSS)).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Methane Plumes Detection on Prisma L1 Images with the Adjusted Spectral Matched Filter and Wind Data

AU - Ouerghi, E.

AU - Ehret, T.

AU - Facciolo, G.

AU - Meinhardt, E.

AU - Morel, J.-M.

AU - de Franchis, C.

AU - Lauvaux, T.

PY - 2023

Y1 - 2023

N2 - Reducing methane emissions is essential to tackle climate change. Here, we address the problem of detecting automatically point source methane leaks using high resolution hyperspectral images from the PRISMA satellite. We use a variation of the Matched Filter (MF) called the Adjusted Spectral Matched Filter (ASMF) to detect methane plumes in satellite images. To remove false positives, the detected plumes are confirmed by comparing their orientation to the wind direction extracted from the standard meteorological reanalysis product ERA5. The ASMF reduces the fraction of false detections compared to the MF and without preventing the detection of plumes. To validate the method, we use a recently proposed dataset of manually annotated plumes on PRISMA images. We also compare our detection rate to the detection rate of methods using deep learning or the standard matched filter. We then show that our method outperforms those methods in terms of F1 score. © 2023 IEEE.

AB - Reducing methane emissions is essential to tackle climate change. Here, we address the problem of detecting automatically point source methane leaks using high resolution hyperspectral images from the PRISMA satellite. We use a variation of the Matched Filter (MF) called the Adjusted Spectral Matched Filter (ASMF) to detect methane plumes in satellite images. To remove false positives, the detected plumes are confirmed by comparing their orientation to the wind direction extracted from the standard meteorological reanalysis product ERA5. The ASMF reduces the fraction of false detections compared to the MF and without preventing the detection of plumes. To validate the method, we use a recently proposed dataset of manually annotated plumes on PRISMA images. We also compare our detection rate to the detection rate of methods using deep learning or the standard matched filter. We then show that our method outperforms those methods in terms of F1 score. © 2023 IEEE.

KW - Anomaly detection

KW - Hyperspectral images

KW - Matched filter

KW - Methane

KW - Wind data

UR - https://www.scopus.com/pages/publications/85178325915

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85178325915&origin=recordpage

U2 - 10.1109/IGARSS52108.2023.10282211

DO - 10.1109/IGARSS52108.2023.10282211

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 979-8-3503-3174-5

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 7598

EP - 7601

BT - IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium - Proceedings

PB - IEEE

T2 - 43rd IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2023)

Y2 - 16 July 2023 through 21 July 2023

ER -

Ouerghi E, Ehret T, Facciolo G, Meinhardt E, Morel JM, de Franchis C et al. Methane Plumes Detection on Prisma L1 Images with the Adjusted Spectral Matched Filter and Wind Data. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium - Proceedings. IEEE. 2023. p. 7598-7601. (International Geoscience and Remote Sensing Symposium (IGARSS)). Epub 2023 Oct 20. doi: 10.1109/IGARSS52108.2023.10282211

Methane Plumes Detection on Prisma L1 Images with the Adjusted Spectral Matched Filter and Wind Data

Abstract

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UN SDGs

Research Keywords

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