Improving Methane Point Sources Detection Over Heterogeneous Land Surface for Satellite Hyperspectral Imagery

Hyperspectral imaging for satellites is currently an important tool for global monitoring of methane point sources, and it can be used to retrieve methane concentration to enable source location and “top-down” emission estimation. The matched filter (MF) is the main method used...

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Main Authors: Erchang Sun, Xianhua Wang, Shichao Wu, Hanhan Ye, Hailiang Shi, Yuan An, Chao Li, Yun Jiang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Online Access:https://ieeexplore.ieee.org/document/10720881/
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author Erchang Sun
Xianhua Wang
Shichao Wu
Hanhan Ye
Hailiang Shi
Yuan An
Chao Li
Yun Jiang
author_facet Erchang Sun
Xianhua Wang
Shichao Wu
Hanhan Ye
Hailiang Shi
Yuan An
Chao Li
Yun Jiang
author_sort Erchang Sun
collection DOAJ
description Hyperspectral imaging for satellites is currently an important tool for global monitoring of methane point sources, and it can be used to retrieve methane concentration to enable source location and &#x201C;top-down&#x201D; emission estimation. The matched filter (MF) is the main method used to retrieve methane enhancement from hyperspectral imaging. However, many false positive retrievals occur over heterogeneous land surfaces because of the confusion between methane absorption and surface reflectance spectra. This hinders the accurate quantification of methane point source emissions from hyperspectral imaging. To overcome this hindrance, we present an improved matched filter that includes background filtering to mitigate the reflectance spectra mismatch between the target and background. By analyzing the land cover shortwave-infrared spectral library, we found that wideband spectral slopes can be used to distinguish between surface types. Based on this, we designed the background sample filtering process and verified its performance using simulation and the advanced hyperspectral imager data. The results show that the improved matched filter can effectively reduce false retrievals over heterogeneous land surfaces and obtain a more realistic methane plume. For example, near an emission source with a <inline-formula><tex-math notation="LaTeX">$\Delta$</tex-math></inline-formula>XCH<inline-formula><tex-math notation="LaTeX">$_{4}$</tex-math></inline-formula> of 1000 ppb, the simulated retrieval bias can be less than 1.3&#x0025; using a 1&#x0025; filter threshold. Our method can enhance the ability of satellites to quantify methane concentrations on complex land surfaces.
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spelling doaj-art-d71f94c2defa43ef890a3026457cd95a2025-08-20T01:54:11ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-011869971110.1109/JSTARS.2024.348227810720881Improving Methane Point Sources Detection Over Heterogeneous Land Surface for Satellite Hyperspectral ImageryErchang Sun0https://orcid.org/0009-0002-5059-7733Xianhua Wang1https://orcid.org/0009-0004-2860-4399Shichao Wu2https://orcid.org/0009-0003-6599-1079Hanhan Ye3Hailiang Shi4https://orcid.org/0000-0001-5235-2698Yuan An5https://orcid.org/0009-0004-9739-8306Chao Li6https://orcid.org/0000-0001-8852-8448Yun Jiang7Hefei Institutes of Physical Science, Chinese Academy of Sciences, Anhui Institute of Optics and Fine Mechanics, Hefei, ChinaHefei Institutes of Physical Science, Chinese Academy of Sciences, Anhui Institute of Optics and Fine Mechanics, Hefei, ChinaHefei Institutes of Physical Science, Chinese Academy of Sciences, Anhui Institute of Optics and Fine Mechanics, Hefei, ChinaHefei Institutes of Physical Science, Chinese Academy of Sciences, Anhui Institute of Optics and Fine Mechanics, Hefei, ChinaHefei Institutes of Physical Science, Chinese Academy of Sciences, Anhui Institute of Optics and Fine Mechanics, Hefei, ChinaHefei Institutes of Physical Science, Chinese Academy of Sciences, Anhui Institute of Optics and Fine Mechanics, Hefei, ChinaHefei Institutes of Physical Science, Chinese Academy of Sciences, Anhui Institute of Optics and Fine Mechanics, Hefei, ChinaSchool of Electronic Engineering, Chaohu Universtiy, Hefei, ChinaHyperspectral imaging for satellites is currently an important tool for global monitoring of methane point sources, and it can be used to retrieve methane concentration to enable source location and &#x201C;top-down&#x201D; emission estimation. The matched filter (MF) is the main method used to retrieve methane enhancement from hyperspectral imaging. However, many false positive retrievals occur over heterogeneous land surfaces because of the confusion between methane absorption and surface reflectance spectra. This hinders the accurate quantification of methane point source emissions from hyperspectral imaging. To overcome this hindrance, we present an improved matched filter that includes background filtering to mitigate the reflectance spectra mismatch between the target and background. By analyzing the land cover shortwave-infrared spectral library, we found that wideband spectral slopes can be used to distinguish between surface types. Based on this, we designed the background sample filtering process and verified its performance using simulation and the advanced hyperspectral imager data. The results show that the improved matched filter can effectively reduce false retrievals over heterogeneous land surfaces and obtain a more realistic methane plume. For example, near an emission source with a <inline-formula><tex-math notation="LaTeX">$\Delta$</tex-math></inline-formula>XCH<inline-formula><tex-math notation="LaTeX">$_{4}$</tex-math></inline-formula> of 1000 ppb, the simulated retrieval bias can be less than 1.3&#x0025; using a 1&#x0025; filter threshold. Our method can enhance the ability of satellites to quantify methane concentrations on complex land surfaces.https://ieeexplore.ieee.org/document/10720881/Advanced hyperspectral imager (AHSI)Gaofen-5heterogeneous land surfacehyperspectral imagerymatched filtermethane (CH<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX">$_{4}$</tex-math> </inline-formula> </named-content>)
spellingShingle Erchang Sun
Xianhua Wang
Shichao Wu
Hanhan Ye
Hailiang Shi
Yuan An
Chao Li
Yun Jiang
Improving Methane Point Sources Detection Over Heterogeneous Land Surface for Satellite Hyperspectral Imagery
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Advanced hyperspectral imager (AHSI)
Gaofen-5
heterogeneous land surface
hyperspectral imagery
matched filter
methane (CH<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX">$_{4}$</tex-math> </inline-formula> </named-content>)
title Improving Methane Point Sources Detection Over Heterogeneous Land Surface for Satellite Hyperspectral Imagery
title_full Improving Methane Point Sources Detection Over Heterogeneous Land Surface for Satellite Hyperspectral Imagery
title_fullStr Improving Methane Point Sources Detection Over Heterogeneous Land Surface for Satellite Hyperspectral Imagery
title_full_unstemmed Improving Methane Point Sources Detection Over Heterogeneous Land Surface for Satellite Hyperspectral Imagery
title_short Improving Methane Point Sources Detection Over Heterogeneous Land Surface for Satellite Hyperspectral Imagery
title_sort improving methane point sources detection over heterogeneous land surface for satellite hyperspectral imagery
topic Advanced hyperspectral imager (AHSI)
Gaofen-5
heterogeneous land surface
hyperspectral imagery
matched filter
methane (CH<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX">$_{4}$</tex-math> </inline-formula> </named-content>)
url https://ieeexplore.ieee.org/document/10720881/
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