CN113869143A - Method for quickly identifying and extracting methane point source based on hyperspectral imager - Google Patents
Method for quickly identifying and extracting methane point source based on hyperspectral imager Download PDFInfo
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- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 title claims abstract description 169
- 238000000034 method Methods 0.000 title claims abstract description 34
- 230000005855 radiation Effects 0.000 claims abstract description 25
- 238000000862 absorption spectrum Methods 0.000 claims abstract description 13
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- 238000007781 pre-processing Methods 0.000 abstract 1
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 8
- 239000005431 greenhouse gas Substances 0.000 description 8
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Abstract
The invention discloses a method for quickly identifying and extracting a methane point source based on a hyperspectral imager, which comprises the following steps of: acquiring hyperspectral data covering a range of 2230nm-2330nm, performing preprocessing such as radiometric calibration and orthometric correction, and calculating a surface reflectivity correction factor (albedo factor) to eliminate the influence of different surface emissivity on results; calculating the mean value mu and covariance Cov of n wave bands of 2230nm-2330nm, simulating by utilizing radiation transmission according to the central wavelength and full width at half maximum (FWHM) of the wave band within the 2230nm-2330nm of the image to obtain a unit methane absorption spectrum, and obtaining a methane enhancement value image by utilizing a matched filtering method; the method comprises the steps of dividing a methane enhancement value image into a background part and a target part by using an maximum inter-class variance method (OSTU), and then eliminating isolated points by using connected domain area detection to finally obtain a binary image of a methane emission point source.
Description
Technical Field
The invention relates to the technical field of atmosphere, in particular to a method for quickly identifying and extracting a methane point source based on a hyperspectral imager.
Background
Methane (CH4) is second only to carbon dioxide (CO2) the most important contributor to the artificially enhanced greenhouse effect. The contribution rate to global warming is about one fourth, the greenhouse effect of a single methane molecule is 25 times that of CO2, and the accelerated increase of the atmospheric methane concentration in recent years again attracts high attention of the scientific community. Compared with other greenhouse gases, the methane emission reduction method has the advantages of low cost, quick response, obvious effect and the like. Therefore, the effective control of methane emission plays an important role in effectively coping with global climate change and realizing the net zero emission of greenhouse gases. Reports issued by the inter-government commission on climate change (IPCC) clearly indicate that deep abatement of non-carbon dioxide greenhouse gases such as methane is a necessary condition for global warming to be kept below 1.5 ℃. Coal mining and Oil and Gas industries (Oil and Gas) are main sources of artificial methane emission all over the world, and world energy prospect 2019 issued by the International Energy Agency (IEA) indicates that the methane leakage rate of coal mines all over the world in 2018 is 4000 ten thousand tons, and the methane leakage rate of Oil and Gas industries all over the world is 8000 ten thousand tons. In the supervision and treatment process of the ecological environmental protection department, an important premise is to know the accurate geographical position of a methane emission point source, and the current free open greenhouse gas satellite spatial resolution in on-orbit operation cannot meet the requirement.
As a supplement means of a greenhouse gas satellite, the hyperspectral imager has great potential in the aspect of methane hot spot detection, the hyperspectral imager covers the 2300nm absorption band of methane, the spatial resolution can reach 30m, and the typical spectral resolution is 7-15 nm. This spectral resolution, while not sufficient to accurately calculate the column abundance of methane, can presumably map out an enhancement map of methane, which is very helpful for accurate positioning of the point source.
Disclosure of Invention
The invention aims to solve the technical problem that the existing freely-disclosed greenhouse gas satellite spatial resolution cannot meet the defect of accurately positioning a methane point source, and provides an algorithm for quickly identifying and extracting the methane point source based on a hyperspectral imager.
The technical scheme of the invention is as follows: a method for quickly identifying and extracting a methane point source based on a hyperspectral imager comprises the following steps:
(1) acquiring hyperspectral data covering a certain range, performing radiometric calibration and orthorectification, setting a cloud place as a null value by using a cloud mask, setting a strip position as a null value to serve as a preprocessed image, calculating a surface reflectivity correction factor, and correcting the preprocessed image to serve as a to-be-processed image;
(2) calculating the mean value mu and covariance Cov of background radiation of n wave bands in a certain range according to the processed image in the step (1), simulating by utilizing radiation transmission according to the central wavelength and full width at half maximum FWHM of the wave bands in the certain range of the image to obtain a unit methane absorption spectrum, and obtaining a methane enhancement value image by utilizing a matched filtering method;
(3) and (3) for the methane enhancement value image obtained in the step (2), dividing the original image into a background part and a target part by using a maximum inter-class variance method, detecting and eliminating discrete points by using the area of a connected domain, and finally obtaining a binary image of a methane emission point source, wherein 1 represents that methane emission exists, and 0 represents that no methane emission exists.
Further, the high spectrum data in the step (1) comprise Hyperion of EO-1, PRISMA and AHSI of GF-5, and the high spectrum data of 2230nm-2330nm is obtained.
Further, the specific method for generating the preprocessed image in the step (1) is as follows;
according to the correlation coefficient provided in the header file or metadata of the satellite data, including a scale factor scaleFactor and a zero Offset, the DN value recorded by the sensor is converted into absolute radiance, then the image is orthorectified according to the DEM data to obtain accurate positioning, then the place with cloud is set as a null value according to the cloud mask provided by the satellite data, and the strip position is set as a null value to be used as a preprocessed image.
Further, in the step (1), calculating a surface reflectivity correction factor according to the radiance of each waveband from 2100nm to 2400nm in the step (1), wherein the specific calculation formula of the surface reflectivity correction factor is as follows;
x is the spectrum under analysis and μ is the mean value of the background radiation of n bands.
Further, the specific method for generating the methane enhancement value image in the step (2) is as follows;
the radiation brightness received by the satellite is reduced along with the increase of the concentration of the methane column, so that the methane enhancement value Δ CH4 can be calculated according to the change value of the radiation brightness and the radiation signal absorbed by unit methane, and Δ CH4 can be expressed as:
x is the spectrum under analysis, μ and Cov are the background radiation mean and covariance, respectively, for n bands, and k is the unit methane absorption spectrum calculated using radiation transmission simulations.
Further, a specific method for obtaining k is as follows: firstly, the HITRAN molecular absorption library is utilized to simulate to obtain 0.1cm-1The unit methane absorption spectrum k _ pre under the resolution ratio is used for simulating the spectral response function of the hyperspectral remote sensor wave band by using a Gaussian function according to the FWHM, as shown in a formula (3),
wherein γ is 2 times FWHM; and finally, convolving the k _ pre with the spectral response function of the corresponding position to obtain a unit methane absorption spectrum k suitable for the current satellite.
The invention has the following advantages:
(1) compared with the available greenhouse gas satellite, the resolution of the hyperspectral satellite can reach 30m, and the requirement of accurate positioning of a point source can be met.
(2) Compared with a methane column concentration inversion algorithm of greenhouse gas satellite data, the algorithm provided by the invention is simple in principle, greatly reduces the calculated amount, and can meet the requirement of quickly searching a methane point source in a large range.
(3) And 4, the emission or non-emission binary image can be directly obtained without manual interpretation.
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The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a general flow chart of the present invention;
FIG. 2 is a methane enhancement value image obtained in step (2) of the present invention;
FIG. 3 is a binary image of emissions or non-emissions obtained in step (3) of the present invention;
FIG. 4 is a match of a methane point source detected by the present invention with a satellite image.
Detailed Description
The technical solution of the present invention is further explained with reference to the drawings and the embodiments.
As shown in fig. 1, an algorithm for quickly identifying and extracting a methane point source based on a hyperspectral imager includes the following steps:
(1) the method comprises the steps of acquiring hyperspectral data (including but not limited to Hyperion of EO-1, PRISMA and AHSI of GF-5) covering a range of 2230nm-2330nm, carrying out radiometric calibration and orthometric correction, setting a cloud place to be a null value by using a cloud mask, setting a strip position to be a null value, taking the null value as a preprocessed image, calculating a surface reflectivity correction factor according to the radiance of each waveband of 2100nm-2400nm, and correcting an original image to be a to-be-processed image.
(2) Calculating the mean value mu and covariance Cov of background radiation of n wave bands of 2230nm-2330nm according to the processed image in (1), obtaining a unit methane absorption spectrum by utilizing radiation transmission simulation according to the central wavelength and full width at half maximum (FWHM) of the wave band in the 2230nm-2330nm range of the image, and obtaining a methane enhancement value image by utilizing a matched filtering method.
(3) And (3) for the methane enhancement value image obtained in the step (2), dividing the original image into a background part and a target part by using an maximum inter-class variance method (OSTU), and then detecting and eliminating discrete points by using the area of a connected domain to finally obtain a binary image of a methane emission point source, wherein 1 represents that methane emission exists, and 0 represents that no methane emission exists.
Further, the specific method for generating the preprocessed image in the step (1) is as follows:
the DN value recorded by the sensor is converted into absolute radiance according to the correlation coefficient (usually scale factor and zero Offset) provided in the header file or metadata of the satellite data, and then the image is orthorectified according to the DEM data to obtain accurate positioning. And setting the cloud place as a null value according to a cloud mask provided by satellite data, and setting the strip position as a null value to serve as a preprocessed image.
Calculating a surface reflectivity correction factor according to the radiance of each waveband from 2100nm to 2400nm in the step (1), wherein the specific calculation formula of the surface reflectivity correction factor is as follows;
x is the spectrum under analysis and μ is the mean value of the background radiation of n bands.
Further, the specific method for generating the methane enhancement value image in the step (2) is as follows:
the radiation intensity received by the satellite decreases with the increase of the concentration of the methane column, so the methane enhancement value (change of concentration) Δ CH4 can be calculated according to the change value of the radiation intensity and the radiation signal absorbed by unit methane, and Δ CH4 can be expressed as:
x is a spectrum under analysis, mu and Cov are respectively a background radiation mean value and a covariance of n wave bands, k is a unit methane absorption spectrum calculated by using radiation transmission simulation, and a specific method for obtaining k is as follows: firstly, the HITRAN molecular absorption library is utilized to simulate to obtain 0.1cm-1And simulating a spectral response function of a hyperspectral remote sensor waveband by using a Gaussian function according to the FWHM of a unit methane absorption spectrum k _ pre under the resolution, wherein gamma is 2 times of FWHM in the formula (2). Finally, convolving k _ pre with the spectral response function of the corresponding position to obtainThe unit methane absorption spectrum k is adapted to the current satellite.
Further, the specific method for generating the binary image of the methane emission point source in the step (3) is as follows:
firstly, the methane enhancement value image generated in the step (2) is converted into a gray level image, then the image is divided into a background part and a target part by utilizing a maximum inter-class variance method (OSTU), according to the prior knowledge, the position with methane point source emission usually shows that the concentration of the central position is high, and the concentration is gradually reduced along with the increase of the distance from the central position, so that some isolated points in the obtained methane enhancement value image are probably caused by the problem of data per se, and the points are not the point sources to be extracted. And then, a connected domain area detection method is used, a proper area threshold value is set, isolated points are eliminated, and a final binary image of the methane emission point source is obtained.
FIG. 4 shows the matching between the detected methane point source and the satellite image, and the result is judged to be a coal mine according to the satellite image, and the result is more reliable.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (6)
1. A method for rapidly identifying and extracting a methane point source based on a hyperspectral imager is characterized by comprising the following steps:
(1) firstly, acquiring hyperspectral data covering a certain range, carrying out radiometric calibration and orthometric correction, setting a cloud place as a null value by using a cloud mask, setting a strip position as a null value to serve as a preprocessed image, then calculating a surface reflectivity correction factor, and correcting the preprocessed image to serve as a to-be-processed image;
(2) calculating the mean value mu and covariance Cov of background radiation of n wave bands in a certain range according to the processed image in the step (1), simulating by utilizing radiation transmission according to the central wavelength and full width at half maximum FWHM of the wave bands in the certain range of the image to obtain a unit methane absorption spectrum, and obtaining a methane enhancement value image by utilizing a matched filtering method;
(3) and (3) for the methane enhancement value image obtained in the step (2), dividing the original image into a background part and a target part by using a maximum inter-class variance method, detecting and eliminating discrete points by using the area of a connected domain, and finally obtaining a binary image of a methane emission point source, wherein 1 represents that methane emission exists, and 0 represents that no methane emission exists.
2. The method for rapidly identifying and extracting the methane point source based on the hyperspectral imager as claimed in claim 1, wherein: the high spectrum data in the step (1) comprise Hyperion of EO-1, PRISMA and AHSI of GF-5, and the high spectrum data of 2230nm-2330nm is obtained.
3. The method for rapidly identifying and extracting the methane point source based on the hyperspectral imager as claimed in claim 1, wherein: the specific method for generating the preprocessed image in the step (1) is as follows;
according to the correlation coefficient provided in the header file or metadata of the satellite data, including a scale factor scaleFactor and a zero Offset, the DN value recorded by the sensor is converted into absolute radiance, then the image is orthorectified according to the DEM data to obtain accurate positioning, then the place with cloud is set as a null value according to the cloud mask provided by the satellite data, and the strip position is set as a null value to be used as a preprocessed image.
4. The method for rapidly identifying and extracting the methane point source based on the hyperspectral imager as claimed in claim 1, wherein: calculating a surface reflectivity correction factor according to the radiance of each waveband from 2100nm to 2400nm in the step (1), wherein the specific calculation formula of the surface reflectivity correction factor is as follows;
x is the spectrum under analysis and μ is the mean value of the background radiation of n bands.
5. The method for rapidly identifying and extracting the methane point source based on the hyperspectral imager as claimed in claim 1, wherein: the specific method for generating the methane enhancement value image in the step (2) is as follows;
the radiation brightness received by the satellite is reduced along with the increase of the concentration of the methane column, so that the methane enhancement value Δ CH4 can be calculated according to the change value of the radiation brightness and the radiation signal absorbed by unit methane, and Δ CH4 can be expressed as:
x is the spectrum under analysis, μ and Cov are the background radiation mean and covariance, respectively, for n bands, and k is the unit methane absorption spectrum calculated using radiation transmission simulations.
6. The method for rapidly identifying and extracting the methane point source based on the hyperspectral imager as claimed in claim 5, wherein: the specific method for obtaining k is as follows;
firstly, the HITRAN molecular absorption library is utilized to simulate to obtain 0.1cm-1The unit methane absorption spectrum k _ pre under the resolution ratio is used for simulating the spectral response function of the hyperspectral remote sensor wave band by using a Gaussian function according to the FWHM, as shown in a formula (3),
wherein γ is 2 times FWHM; and finally, convolving the k _ pre with the spectral response function of the corresponding position to obtain a unit methane absorption spectrum k suitable for the current satellite.
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| CN115452822A (en) * | 2022-08-24 | 2022-12-09 | 武汉大学 | Method and device for acquiring rice field methane emission flux based on remote sensing and farmland information |
| CN115830472A (en) * | 2023-01-12 | 2023-03-21 | 北京英视睿达科技股份有限公司 | Urban complex underlying surface methane emission source identification method |
| CN117765407A (en) * | 2023-12-22 | 2024-03-26 | 南京大学 | Method for rapidly detecting and quantifying abnormal methane emission under complex terrain condition |
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- 2021-09-09 CN CN202111056130.3A patent/CN113869143A/en active Pending
Cited By (4)
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| CN115452822A (en) * | 2022-08-24 | 2022-12-09 | 武汉大学 | Method and device for acquiring rice field methane emission flux based on remote sensing and farmland information |
| CN115452822B (en) * | 2022-08-24 | 2024-04-09 | 武汉大学 | Method and device for obtaining paddy field methane emission flux based on remote sensing and farmland information |
| CN115830472A (en) * | 2023-01-12 | 2023-03-21 | 北京英视睿达科技股份有限公司 | Urban complex underlying surface methane emission source identification method |
| CN117765407A (en) * | 2023-12-22 | 2024-03-26 | 南京大学 | Method for rapidly detecting and quantifying abnormal methane emission under complex terrain condition |
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