Remote sensing detection data inversion method for overlapping of strong and weak absorption lines of greenhouse gas

Abstract

The invention relates to a remote sensing detection data inversion method for greenhouse gas strong and weak absorption line overlapping, and belongs to the technical field of satellite remote sensing. The method specifically comprises the following steps of 1, building an optical system which comprises a satellite platform, a camera 1 and a camera 2; the camera 1 and the camera 2 are mounted at the bottom of the satellite platform; the camera 1 and the camera 2 are arranged in a mirroring manner; the imaging spectrum band of the camera 1 is from a weak absorption spectrum band to a strong absorption spectrum band from the push-scan positive direction to the push-scan negative direction; the imaging spectrum directions of the camera 2 are opposite; the optical system horizontally moves from left to right to realize horizontal push-broom of greenhouse gas on the ground, and double-camera fusion imaging is obtained; carrying out inversion calculation on double-camera fusion imaging by adopting a double-camera differential absorption spectrum algorithm to obtain the concentration of the greenhouse gas column; the method is based on the spectral characteristics of strong and weak absorption lines of the greenhouse gas, adopts a detector focal plane segmentation form, realizes differential absorption and inversion in the same region through double cameras, and is used for guiding the design of a greenhouse gas detection micro-nano satellite load.

Description

Technical Field

[0001] The invention belongs to the technical field of satellite remote sensing and relates to a remote sensing detection data inversion method for overlapping strong and weak absorption lines of greenhouse gases. Background Art

[0002] Global greenhouse gas remote sensing has become a key research area in science and application. Greenhouse gas detection mainly uses optical hyperspectral imaging systems, including grating spectroscopy, Fourier interferometry, FP interferometry, etc. Many types of greenhouse gas hyperspectral detection payloads currently in orbit and under development use spotting or push-sweeping to achieve regional and local gas detection. The typical SCIAMACHY payload can detect greenhouse gases such as CO2, with a payload weight of 198kg and a power consumption of 122W. With the development of large-scale and high-density constellations, the design of lightweight and highly integrated payload platforms has become a trend in microsatellite technology. Therefore, traditional imaging modes and systems have large payload weights, high power consumption, and are not suitable for the integrated development of the research and application of greenhouse gas detection microsatellites. Summary of the invention

[0003] The technical problem solved by the present invention is: to overcome the shortcomings of the prior art and propose a remote sensing detection data inversion method for overlapping strong and weak absorption lines of greenhouse gases. Based on the spectral characteristics of the strong and weak absorption lines of greenhouse gases, the detector focal plane is segmented, and dual cameras are used to achieve differential absorption and inversion in the same area, which is used to guide the design of greenhouse gas detection micro-nano satellite payloads.

[0004] The solution of the present invention is:

[0005] A method for inverting remote sensing detection data of overlapping strong and weak absorption lines of greenhouse gases, comprising:

[0006] Build an optical system, including a satellite platform, camera 1 and camera 2; camera 1 and camera 2 are installed at the bottom of the satellite platform;

[0007] The optical system moves horizontally from left to right to achieve horizontal push scanning of greenhouse gases on the ground and obtain dual-camera fusion imaging;

[0008] The dual-camera differential absorption spectroscopy algorithm is used to invert the dual-camera fusion imaging to obtain the greenhouse gas column concentration.

[0009] In the above-mentioned remote sensing detection data inversion method for overlapping strong and weak absorption lines of greenhouse gases, the satellite platform is set horizontally; camera 1 and camera 2 are installed axially parallel, and the optical axes of camera 1 and camera 2 are both vertically pointed to the ground; the fields of view of camera 1 and camera 2 overlap on the ground.

[0010] In the above-mentioned remote sensing detection data inversion method for overlapping strong and weak absorption lines of greenhouse gases, the camera 1 and the camera 2 are arranged in a mirror image; the imaging spectrum of the camera 1 is from the weak absorption spectrum to the strong absorption spectrum along the positive direction of the push scan to the negative direction of the push scan; the imaging spectrum of the camera 2 is from the strong absorption spectrum to the weak absorption spectrum along the positive direction of the push scan to the negative direction of the push scan.

[0011] In the above-mentioned remote sensing detection data inversion method for overlapping strong and weak absorption lines of greenhouse gases, the specific method of using the dual-camera differential absorption spectrum algorithm to perform inversion calculation on the imaging is as follows:

[0012] S1. Extract differential absorption spectrum from the detection spectrum of dual-camera fusion imaging;

[0013] S2. Fit the differential absorption spectrum to obtain the greenhouse gas column concentration.

[0014] In the above-mentioned remote sensing detection data inversion method for overlapping strong and weak absorption lines of greenhouse gases, in S1, the method for extracting the differential absorption spectrum is:

[0015] The emission spectrum of the solar light source is set to I0(λ); the spectrum received by the optical system after atmospheric absorption is I(i,λ); i is the spatial dimension number;

[0016] Calculate the natural logarithm R(i,λ) of the ratio of I(i,λ) to I0(λ); R(i,λ)=σ(i,λ)c i L+P(i,λ); where, σ(i,λ)c i L is the differential absorption spectrum; P(i,λ) is the extinction caused by the narrow-band absorption of the gas on the spectrum intensity, the Rayleigh scattering of the aerosol, and the Mie scattering;

[0017] The polynomial fitting method is used to eliminate P(i,λ) in the ratio spectrum R(i,λ);

[0018] After eliminating P(i,λ), the difference spectrum of R(i,λ) is recorded as A(i,λ), A(i,λ)=σ(i,λ)c i L.

[0019] In the above-mentioned remote sensing detection data inversion method for overlapping strong and weak absorption lines of greenhouse gases, the spectrum I(i,λ) absorbed by the atmosphere and received by the optical system is the integration of the detection spectra of machine 1 and camera 2 in the i-th spatial dimension, and includes both strong absorption spectral bands and weak absorption spectral bands.

[0020] In the above-mentioned remote sensing detection data inversion method for overlapping strong and weak absorption lines of greenhouse gases, the differential absorption spectrum σ(i,λ)c i In L, σ(i,λ) is the standard differential absorption cross section of greenhouse gases, indicating the absorption of light intensity per unit length by gas per unit concentration; ci is the greenhouse gas column concentration of the i-th spatial dimension to be solved; L represents the optical path, that is, the known orbital height; L is the optical path, that is, the known orbital height.

[0021] In the above-mentioned remote sensing detection data inversion method for overlapping strong and weak absorption lines of greenhouse gases, the differential absorption spectrum σ(i,λ)c i Compared with L, the extinction P(i,λ) caused by the narrow-band absorption of the gas on the spectral intensity, the Rayleigh scattering of the aerosol and the Mie scattering changes faster with wavelength.

[0022] In the above-mentioned remote sensing detection data inversion method for overlapping strong and weak absorption lines of greenhouse gases, a polynomial fitting is performed on the contrast spectrum R(i,λ) to obtain a fitting curve. The fitting curve subtracts the slow changes in the spectrum, including broadband absorption, Rayleigh scattering and Mie scattering of atmospheric molecules, as well as low-frequency background interference and system noise, and the remaining is the differential spectrum A(i,λ).

[0023] In the above-mentioned remote sensing detection data inversion method for overlapping strong and weak absorption lines of greenhouse gases, in S2, the specific method for fitting the differential absorption spectrum is:

[0024] The differential absorption spectrum A(i,λ) is fitted with the differential absorption cross section σ(i,λ) of the gas molecules, and the greenhouse gas column concentration c in the i-th spatial dimension is inverted. i .

[0025] The beneficial effects of the present invention compared with the prior art are:

[0026] (1) The present invention discloses a remote sensing detection payload imaging mode design for overlapping strong and weak absorption lines of greenhouse gases. The payload is light and small, and is suitable for micro-nano satellite mounting configuration;

[0027] (2) The present invention discloses a remote sensing payload imaging mode design for overlapping strong and weak absorption lines of greenhouse gases. Dual cameras can achieve differential absorption of strong and weak spectral lines in the same area, which is convenient for data inversion and application.

[0028] (3) During data processing, the present invention uses a dual-camera differential absorption spectroscopy algorithm to achieve inversion calculation of greenhouse gas column concentrations. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a flow chart of greenhouse gas data inversion in the present invention;

[0030] Figure 2 Schematic diagram of the optical system of the present invention. DETAILED DESCRIPTION

[0031] The present invention will be further described below in conjunction with the embodiments.

[0032] The present invention provides a remote sensing detection data inversion method for overlapping strong and weak absorption lines of greenhouse gases. Based on the spectral characteristics of strong and weak absorption lines of greenhouse gases, the detector focal plane segmentation form is adopted, and dual cameras realize differential absorption and inversion in the same area, which is used to guide the design of greenhouse gas detection micro-nano satellite payloads.

[0033] The dual-camera greenhouse gas data inversion method based on the detector mirror distribution, such as Figure 1 The method specifically comprises the following steps:

[0034] Step 1. Build an optical system, including a satellite platform, camera 1 and camera 2; camera 1 and camera 2 are installed at the bottom of the satellite platform. The satellite platform is set horizontally; camera 1 and camera 2 are installed axially parallel, and the optical axes of camera 1 and camera 2 are both vertically pointing to the ground; the fields of view of camera 1 and camera 2 overlap on the ground. Camera 1 and camera 2 are set in mirror image; the imaging spectrum of camera 1 is from the weak absorption spectrum to the strong absorption spectrum along the positive direction of push-scan to the negative direction of push-scan; the imaging spectrum of camera 2 is from the strong absorption spectrum to the weak absorption spectrum along the positive direction of push-scan to the negative direction of push-scan, such as Figure 2 shown.

[0035] The optical system moves horizontally from left to right to achieve horizontal push-scanning of greenhouse gases on the ground and obtain dual-camera fusion imaging.

[0036] The dual-camera differential absorption spectroscopy algorithm is used to invert the dual-camera fusion imaging to obtain the greenhouse gas column concentration.

[0037] The specific method of using the dual-camera differential absorption spectroscopy algorithm to perform inversion calculation on imaging is as follows:

[0038] S1. Extract the differential absorption spectrum from the detection spectrum of dual-camera fusion imaging.

[0039] The extraction method of differential absorption spectrum is:

[0040] Assume that the emission spectrum of the solar light source is I0(λ); the spectrum absorbed by the atmosphere and received by the optical system is I(i,λ); i is the spatial dimension number; the spectrum absorbed by the atmosphere and received by the optical system I(i,λ) is the integration of the detection spectra of camera 1 and camera 2 in the i-th spatial dimension, including both strong absorption spectral bands and weak absorption spectral bands.

[0041] Calculate the natural logarithm R(i,λ) of the ratio of I(i,λ) to I0(λ); R(i,λ)=σ(i,λ)c i L+P(i,λ); where, σ(i,λ)c i L is the differential absorption spectrum; P(i,λ) is the extinction caused by the narrow-band absorption of the gas on the spectrum intensity, Rayleigh scattering of the aerosol, and Mie scattering.

[0042] Differential absorption spectrum σ(i,λ)c i In L, σ(i,λ) is the standard differential absorption cross section of greenhouse gases, indicating the absorption of light intensity per unit length by gas per unit concentration; c i is the greenhouse gas column concentration of the i-th spatial dimension to be solved; L represents the optical path, that is, the known orbital height; L is the optical path, that is, the known orbital height.

[0043] Differential absorption spectrum σ(i,λ)c i Compared with L, the extinction P(i,λ) caused by the narrow-band absorption of the gas on the spectral intensity, the Rayleigh scattering of the aerosol and the Mie scattering changes faster with wavelength.

[0044] The polynomial fitting method is used to eliminate P(i,λ) in the ratio spectrum R(i,λ).

[0045] The contrast spectrum R(i,λ) is fitted with a polynomial to obtain a fitting curve, which subtracts the slow changes in the spectrum, including broadband absorption, Rayleigh scattering and Mie scattering of atmospheric molecules, as well as low-frequency background interference and system noise. The remaining is the differential spectrum A(i,λ).

[0046] After eliminating P(i,λ), the difference spectrum of R(i,λ) is recorded as A(i,λ), A(i,λ)=σ(i,λ)c i L.

[0047] S2. Fit the differential absorption spectrum to obtain the greenhouse gas column concentration.

[0048] The specific method for fitting the differential absorption spectrum is:

[0049] The differential absorption spectrum A(i,λ) is fitted with the differential absorption cross section σ(i,λ) of the gas molecules, and the greenhouse gas column concentration c in the i-th spatial dimension is inverted. i .

[0050] Example

[0051] The greenhouse gas in this embodiment is CH4. Take the continuous spectrum of the spectral absorption band of CH4 gas 1635-1664nm (weak) and 1664-1670nm (strong) as an example.

[0052] By selecting the focal plane of the detector, the design of the hyperspectral imaging system of camera 1 and camera 2 can be realized. The spectrum of ground projection camera 1 is from weak absorption spectrum to strong absorption spectrum along the positive direction to the negative direction of push scanning, that is, 1635-1670nm, and the spectrum of camera 2 is from strong absorption spectrum to weak absorption spectrum along the positive direction to the negative direction of push scanning, that is, 1670-1635nm.

[0053] Camera 1 and Camera 2 are configured on a micro-nano satellite platform, with their optical axes facing the ground and installed in parallel to ensure that the image projections of the two cameras overlap on the ground. Figure 2 ①②③ indicate the ground application positions, which represent a certain position in the positive direction of the push-scan, the center position of the detector's ground projection, and a certain position in the negative direction of the push-scan. As can be seen from the figure, the ground position ① has both weak absorption spectrum data from camera 1 and strong absorption data from camera 2. Similarly, the ground position ③ has both strong absorption spectrum data from camera 1 and weak absorption data from camera 2.

[0054] In data processing, the dual-camera differential absorption spectrum algorithm is used to realize the inversion calculation of CH4 concentration. It is mainly divided into two parts: first, the differential absorption spectrum is extracted from the detection spectrum fused by the dual cameras, and then the differential absorption spectrum is fitted.

[0055] (1) Differential absorption spectrum extraction

[0056] Set the emission spectrum of the solar light source I0(λ); the spectrum received by the detector after atmospheric absorption I(i,λ): it is the integration of the spectra detected by camera 1 and camera 2 in the i-th spatial dimension, including both strong absorption spectral bands and weak absorption spectral bands.

[0057] Compute the natural logarithm R(i,λ) of the ratio of I(i,λ) to I0(λ).

[0058] According to the Beer-Lambert atmospheric extinction law, the ratio spectrum R(i,λ) can be decomposed into two parts:

[0059] R(i,λ)=σ(i,λ)c i L+P(i,λ) (1)

[0060] One part changes rapidly with wavelength, and is caused by the narrow-band absorption of the gas, i.e., the differential absorption spectrum, expressed as σ(i,λ)c i L. Where σ(i,λ) is the standard differential absorption cross section of CH4 molecules, indicating the absorption of light intensity per unit length by gas per unit concentration; c i is the CH4 concentration of the i-th spatial dimension to be solved; L represents the optical path, that is, the known orbital height. A part changes slowly, which is caused by the narrow band absorption of the gas on the spectral intensity, the Rayleigh scattering and Mie scattering of the aerosol, expressed as P(i,λ). The Mie scattering extinction of the aerosol is inversely proportional to the wavelength, and the Rayleigh scattering extinction is inversely proportional to the fourth power of the wavelength. Both are low-order functions of the wavelength, and the scattering changes slowly with the wavelength.

[0061] The polynomial fitting method is used to eliminate the slow-changing spectrum P(i,λ) in the ratio spectrum R(i,λ). The polynomial fitting of the ratio spectrum R(i,λ) is used to obtain a fitting curve. The fitting curve is considered to be a slow change in the spectrum, including broadband absorption, Rayleigh scattering and Mie scattering of atmospheric molecules, as well as some low-frequency background interference and system noise. Subtract it from the ratio spectrum, and the remaining is the differential absorption spectrum.

[0062] (a) The differential spectrum A(i,λ) after R(i,λ) is fitted with a polynomial to remove the slowly varying spectrum. Formula (1) can be written as:

[0063] A(i,λ)=σ(i,λ)c i L (2)

[0064] (2) Differential absorption spectrum fitting

[0065] By fitting the differential absorption spectrum A(i,λ) with the differential absorption cross section σ(i,λ) of the gas molecules, the concentration c of these gas molecules can be inverted. i .

[0066] The differential absorption cross section σ(i,λ) of gas molecules is obtained by using the atmospheric radiation transfer simulation software SICATRAN. Based on the observation parameters and the standard differential absorption cross section provided by the HITRAN library, the differential absorption cross section for the observation condition is obtained.

[0067] Since the attenuation of the spectral intensity of each wavelength includes the influence of differential absorption of multiple atmospheric molecules, in order to remove the interference of other gas molecules, their concentrations need to be inverted at the same time, and the least squares method is used to achieve concentration inversion through data fitting. Assume that the methane detection band is interfered by n gases, that is, the differential absorption spectrum A(i,λ) is a linear combination of the absorption cross sections σ(i,λ) of these n gases, as shown in formula (3). Assume that the number of data points in the spectrum is m (m>n), the value A(i,λ) of the i-th data point in the spectrum should be a linear combination of the absorption cross sections of these n gases at that point, that is

[0068] A(i,λ)=u1σ1(i,λ)+u2σ2(i,λ)+...+u n σ n (i,λ) (3)

[0069] Where: u1, u2, …, u n are the fitting coefficients; for all data points, they can be expressed in a matrix as:

[0070]

[0071] Since m>n, the equations are overdetermined. By solving the overdetermined equations, we can get the fitting coefficients u1, u2,…, un , and then according to the fitting coefficient, we can finally get the concentration c of the jth gas at the ith data point i,j =u i,j / L, L is the orbit height.

[0072] The present invention discloses a remote sensing detection payload imaging mode design for overlapping strong and weak absorption lines of greenhouse gases. The payload is light and small, and is suitable for micro-nano satellite mounting configuration. The present invention discloses a remote sensing detection payload imaging mode design for overlapping strong and weak absorption lines of greenhouse gases. Dual cameras can realize differential absorption of strong and weak spectral lines in the same area, which is convenient for data inversion and application.

[0073] The present invention adopts a dual-camera differential absorption spectroscopy algorithm during data processing to achieve inversion calculation of greenhouse gas column concentrations.

[0074] Although the present invention has been disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications to the technical solution of the present invention by using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for inverting remote sensing detection data of overlapping strong and weak absorption lines of greenhouse gases, characterized by: include: Build the optical system, including the satellite platform, camera 1 and camera 2; Camera 1 and Camera 2 are installed on the bottom of the satellite platform; The optical system moves horizontally from left to right to achieve horizontal push scanning of greenhouse gases on the ground and obtain dual-camera fusion imaging; The dual-camera differential absorption spectroscopy algorithm is used to invert the dual-camera fusion imaging to obtain the greenhouse gas column concentration.

2. The method for inverting remote sensing detection data of overlapping strong and weak absorption lines of greenhouse gases according to claim 1, characterized in that: The satellite platform is set horizontally; the cameras 1 and 2 are installed axially parallel, and the optical axes of the cameras 1 and 2 are both vertically pointed to the ground; the fields of view of the cameras 1 and 2 overlap on the ground.

3. The method for inverting remote sensing detection data of overlapping strong and weak absorption lines of greenhouse gases according to claim 2, characterized in that: The camera 1 and the camera 2 are arranged in a mirror image, so that the imaging spectrum of the camera 1 is from the weak absorption spectrum to the strong absorption spectrum along the positive direction of the push scan to the negative direction of the push scan; and the imaging spectrum of the camera 2 is from the strong absorption spectrum to the weak absorption spectrum along the positive direction of the push scan to the negative direction of the push scan.

4. The method for inverting remote sensing detection data of overlapping strong and weak absorption lines of greenhouse gases according to claim 3, characterized in that: The specific method of using the dual-camera differential absorption spectroscopy algorithm to perform inversion calculation on imaging is as follows: S1. Extract differential absorption spectrum from the detection spectrum of dual-camera fusion imaging; S2. Fit the differential absorption spectrum to obtain the greenhouse gas column concentration.

5. The method for inverting remote sensing detection data of overlapping strong and weak absorption lines of greenhouse gases according to claim 4, characterized in that: In S1, the method for extracting the differential absorption spectrum is: The emission spectrum of the solar light source is set to I0(λ); the spectrum received by the optical system after atmospheric absorption is I(i,λ); i is the spatial dimension number; Calculate the natural logarithm R(i,λ) of the ratio of I(i,λ) to I0(λ); R(i,λ)=σ(i,λ)c i L+P(i,λ); where, σ(i,λ)c i L is the differential absorption spectrum; P(i,λ) is the extinction caused by the narrow-band absorption of the gas on the spectrum intensity, the Rayleigh scattering of the aerosol, and the Mie scattering; The polynomial fitting method is used to eliminate P(i,λ) in the ratio spectrum R(i,λ); After eliminating P(i,λ), the difference spectrum of R(i,λ) is recorded as A(i,λ), A(i,λ)=σ(i,λ)c i L.

6. The method for inverting remote sensing detection data of overlapping strong and weak absorption lines of greenhouse gases according to claim 5, characterized in that: The spectrum I(i,λ) absorbed by the atmosphere and received by the optical system is the integration of the spectrum detected by the camera 1 and the camera 2 in the i-th spatial dimension, and includes both strong absorption spectrum bands and weak absorption spectrum bands.

7. The method for inverting remote sensing detection data of overlapping strong and weak absorption lines of greenhouse gases according to claim 5, characterized in that: Differential absorption spectrum σ(i,λ)c i In L, σ(i,λ) is the standard differential absorption cross section of greenhouse gases, indicating the absorption of light intensity per unit length by gas per unit concentration; c i is the greenhouse gas column concentration of the i-th spatial dimension to be solved; L represents the optical path, that is, the known orbital height; L is the optical path, that is, the known orbital height.

8. The method for inverting remote sensing data of overlapping strong and weak absorption lines of greenhouse gases according to claim 7, characterized in that: The differential absorption spectrum σ(i,λ)c i Compared with L, the extinction P(i,λ) caused by the narrow-band absorption of the gas on the spectral intensity, the Rayleigh scattering of the aerosol and the Mie scattering changes faster with wavelength.

9. The method for inverting remote sensing detection data of overlapping strong and weak absorption lines of greenhouse gases according to claim 8, characterized in that: The contrast spectrum R(i,λ) is fitted with a polynomial to obtain a fitting curve, which subtracts the slow changes in the spectrum, including broadband absorption, Rayleigh scattering and Mie scattering of atmospheric molecules, as well as low-frequency background interference and system noise. The remaining is the differential spectrum A(i,λ).

10. The method for inverting remote sensing detection data of overlapping strong and weak absorption lines of greenhouse gases according to claim 4, characterized in that: In S2, the specific method for fitting the differential absorption spectrum is: The differential absorption spectrum A(i,λ) is fitted with the differential absorption cross section σ(i,λ) of the gas molecules, and the greenhouse gas column concentration c in the i-th spatial dimension is inverted. i .

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