A method and system for improving the resolution of methane emission concentration inversion

Abstract

This invention relates to the field of greenhouse gas remote sensing monitoring technology, specifically to a method and system for retrieving and improving the resolution of methane emission concentrations. The method includes: acquiring high-resolution satellite data and low-resolution satellite data, wherein the high-resolution satellite data includes image data, and the low-resolution satellite data includes methane concentration data corresponding to the image data; upscaling the high-resolution satellite data and calculating a weighted spectral curve by combining it with the low-resolution satellite data; determining pixel feature weights based on the weighted spectral curve and the spectral curves of pixels in the high-resolution satellite data to obtain a reweighted spectral curve; and performing matched filtering on the reweighted spectral curve to obtain high-resolution methane concentration data. This invention combines high-resolution satellite data with corresponding low-resolution methane concentration data to retrieve methane concentrations, meeting the requirements for improved data resolution while avoiding data loss due to low concentrations.

Description

Technical Field

[0001] This invention relates to the field of greenhouse gas remote sensing monitoring technology, specifically to a method and system for improving the resolution of methane emission concentration retrieval. Background Technology

[0002] Satellite remote sensing, as a novel monitoring technology, has become a significant driving force for improving the transparency of methane emission sources. It offers advantages such as a large observation area and short revisit cycles, providing crucial information for determining the scale and duration of large-scale methane leaks. With the continuous development of remote sensing technology, several methane satellites have been launched internationally, capable of directly monitoring methane concentrations in the Earth's atmosphere, such as Sentinel-5, GOSAT, and GHGSat. Simultaneously, both domestic and international efforts are accelerating the development of more methane monitoring satellites to monitor methane gas at different scales. However, currently, most satellites provide images with low resolution, which is insufficient to meet the requirements for methane monitoring in mining areas. Summary of the Invention

[0003] Therefore, the present invention aims to overcome the technical problems required in the prior art, thereby providing a method and system for improving the inversion resolution of methane emission concentration.

[0004] In a first aspect, the present invention provides a method for improving the inversion resolution of methane emission concentration, comprising:

[0005] Acquire high-resolution satellite data and low-resolution satellite data, where high-resolution satellite data includes image data and low-resolution satellite data includes methane concentration data corresponding to the image data;

[0006] The high-resolution satellite data is upscaled and then combined with the low-resolution satellite data to calculate a weighted spectral curve.

[0007] Based on the weighted spectral curves and the spectral curves of pixels in high-resolution satellite data, the pixel feature weights are determined, and the reweighted spectral curves are obtained.

[0008] Matched filtering was applied to the weighted spectral curves to obtain high-resolution methane concentration data.

[0009] Furthermore, the upscaling process for the high-resolution satellite data includes:

[0010] Reduce the resolution of high-resolution satellite data to make the methane concentration data from high-resolution satellite data consistent with the methane concentration data from low-resolution satellite data;

[0011] The spectral curves of each pixel in the high-resolution satellite data after resolution reduction are obtained and defined as the reference spectral curves.

[0012] Furthermore, the calculation of the weighted spectral curve by combining the low-resolution satellite data includes:

[0013] Based on the low-resolution satellite data and the corresponding atmospheric profile data, the spectral curve of methane is obtained and defined as the simulated spectral curve.

[0014] The simulated spectral curve and the reference spectral curve of any pixel are weighted and calculated to obtain the weighted spectral curve of each pixel.

[0015] Furthermore, the process of determining pixel feature weights and obtaining reweighted spectral curves based on weighted spectral curves and pixel spectral curves in high-resolution satellite data includes:

[0016] Obtain the spectral curves of each pixel in high-resolution satellite data;

[0017] At a specific wavelength, the ratio of the peak value of the spectral curve of any pixel in high-resolution satellite data to the peak value of the weighted spectral curve of the corresponding pixel is calculated. This ratio is the pixel feature weight.

[0018] The obtained pixel feature weights are multiplied by the weighted spectral curves of each pixel to obtain the reweighted spectral curves of each pixel.

[0019] Furthermore, the step of performing matched filtering on the weighted spectral curves to obtain high-resolution methane concentration data includes:

[0020] Based on satellite observation of shortwave infrared band data, the spectral radiance values ​​of each pixel are obtained;

[0021] Calculate the average spectral radiance, and then use the average spectral radiance to calculate the background covariance matrix;

[0022] High-resolution methane concentration data were obtained using matched filtering.

[0023] Furthermore, the method of obtaining high-resolution methane concentration data using matched filtering includes:

[0024] The spectral radiance value is decomposed into the background radiance value of the pixel without methane enhancement and the radiative perturbation caused by the increased methane concentration. The enhancement effect of methane is approximated by the following formula:

[0025]

[0026] Where α is the methane concentration, s is the methane absorption spectral characteristic, L0 is the background radiance value without methane enhancement, and t is the target characteristic spectrum based on the methane absorption spectral characteristic s. The average spectral radiance value approximately replaces L0.

[0027] Performing a Gaussian log-likelihood calculation on the above formula and taking its minimum value yields high-resolution methane column concentration data, which is expressed by the following formula:

[0028]

[0029] In the formula, L i Let be the spectral radiance value of the i-th pixel, μ be the average spectral radiance, and C be the background covariance matrix. It is the target spectral radiation perturbation. This represents the perturbation value relative to background radiation caused by the increase in methane concentration.

[0030] Furthermore, the method also includes a step of optimizing the obtained high-resolution methane column concentration data;

[0031] The step of optimizing the obtained high-resolution methane column concentration data includes:

[0032] The dichroic reflection characteristics of the Earth's surface are expressed using the following formula:

[0033]

[0034] in, These are the observed radiance values ​​after terrain correction. This represents the original observed radiance value at the Earth's surface. It is the cosine of the angle of incidence at the zenith. Let be the cosine of the solar incident zenith angle relative to the slope, represent the cosine of the solar incident zenith angle relative to the slope, and k be the Minnaert coefficient;

[0035] Calculate the scalar albedo factor and construct the scalar albedo matrix. The scalar albedo factor is expressed by the following formula:

[0036]

[0037] in, Here, μ is the scalar albedo factor, and μ is the average spectral radiance. The radiance value of the i-th pixel observed below a flat surface;

[0038] Based on the scalar albedo factor, the objective function is calculated, and the objective function matrix is ​​constructed. The objective function is expressed by the following formula:

[0039]

[0040] in,

[0041] In the formula, Let C be the objective function, and C be the background covariance matrix. For the number of iterations, Scalar albedo factor To apply regularization weights to each row vector for the p-th iteration, Let be the radiance value of the i-th pixel observed below a flat surface; where,

[0042]

[0043] The objective function matrix was optimized to obtain the optimized high-resolution methane column concentration, using the following calculations:

[0044]

[0045] In the formula, and Recalculation is performed in each reweighting iteration.

[0046] Secondly, the present invention provides a system for improving the resolution of methane emission concentration retrieval, characterized in that it comprises:

[0047] The acquisition module is used to acquire high-resolution satellite data and low-resolution satellite data. The high-resolution satellite data includes image data, and the low-resolution satellite data includes methane concentration data corresponding to the image data.

[0048] The weighting module is used to upscale the high-resolution satellite data and combine it with the low-resolution satellite data to calculate the weighted spectral curve.

[0049] The reweighting module is used to determine the pixel feature weights and obtain the reweighted spectral curve based on the weighted spectral curve and the spectral curve of pixels in high-resolution satellite data.

[0050] The matched filtering module is used to perform matched filtering on the weighted distribution spectral curve to obtain high-resolution methane concentration data.

[0051] Thirdly, the present invention provides a terminal device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method for improving the inversion resolution of methane emission concentration as described in any of the first aspects.

[0052] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for improving the inversion resolution of methane emission concentration as described in any of the first aspects.

[0053] The technical solution of this invention has the following advantages:

[0054] This invention combines high-resolution satellite data with corresponding low-resolution methane concentration data to retrieve methane concentration, meeting the requirements for improved data resolution while avoiding data loss due to low concentrations. As satellite data continues to be updated and added, this approach can be extended to other satellite data combinations, and the weights can be flexibly adjusted according to the importance of the actual data to obtain more accurate and higher-resolution methane concentration results, demonstrating sustainable innovation.

[0055] This invention makes full use of spectral curve data and generates more accurate methane spectral curves by combining atmospheric profile data and other information. This not only provides richer spectral information for subsequent methane data inversion using spectral curve differences, but also significantly improves the reliability and accuracy of remote sensing inversion, providing new possibilities and higher data quality for inverting methane concentration from remote sensing data. At the same time, using the peak values ​​of the methane spectral curve at specific wavelengths as the weights of each pixel provides a foundation for improving resolution.

[0056] This invention improves the matched filtering method. Based on the consideration that the actual ground is not a Lambertian surface and that there may be noise interference in the data, it introduces the empirical Minnaert coefficient k and L2,1 norm, which can effectively suppress irrelevant features and noise, and better avoid the impact of complex terrain on the reflectivity of remote sensing image pixels, thus making it more adaptable to complex terrain.

[0057] This invention addresses the potential data gaps in low-concentration methane regions. In these regions, traditional methods may struggle to accurately invert methane concentration due to the small difference between the spectral curve and the background spectral curve. This invention calculates all methane data by using the ratio of spectral characteristics of different combinations of methane spectral curves at specific wavelengths to the methane concentration, thereby further improving the completeness and reliability of the data. Attached Figure Description

[0058] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0059] Figure 1 This is a schematic diagram of the process for improving the resolution of methane emission concentration inversion provided by the present invention.

[0060] Figure 2 This is a schematic diagram of the second step in the process of improving the resolution of methane emission concentration inversion provided by the present invention.

[0061] Figure 3 A schematic diagram of the process for improving the resolution of methane emission concentration inversion provided by the present invention;

[0062] Figure 4 A schematic diagram of the process for improving the resolution of methane emission concentration inversion provided by the present invention;

[0063] Figure 5 A schematic diagram of the process for improving the resolution of methane emission concentration inversion provided by the present invention (Figure 5).

[0064] Figure 6 A schematic diagram of the process for improving the resolution of methane emission concentration inversion provided by the present invention (Figure 6).

[0065] Figure 7 This is a schematic diagram of the methane emission concentration inversion resolution enhancement system provided by the present invention;

[0066] Figure 8 This is a schematic diagram of the structure of the terminal device provided by the present invention;

[0067] Figure 9 A schematic diagram of the computer structure to which the methane emission concentration inversion resolution improvement method provided by the present invention is applicable. Detailed Implementation

[0068] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0069] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0070] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0071] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0072] Example

[0073] Most methane monitoring satellites have a large monitoring range, typically at the kilometer level, but their image resolution is relatively low, making them suitable for monitoring large-scale methane leaks. However, when mining areas need to be designated as key areas for methane emissions, the low resolution of methane monitoring satellites is insufficient to meet the monitoring requirements.

[0074] To address the aforementioned issues, this invention provides a method for improving the resolution of methane emission concentration retrieval. This method involves acquiring high-resolution satellite data and low-resolution satellite data, where the high-resolution satellite data includes image data and the low-resolution satellite data includes methane concentration data corresponding to the image data. The high-resolution satellite data is upscaled, and a weighted spectral curve is calculated by combining it with the low-resolution satellite data. Based on the weighted spectral curve and the spectral curves of pixels in the high-resolution satellite data, pixel feature weights are determined to obtain a reweighted spectral curve. Finally, matched filtering is applied to the weighted spectral curve to obtain high-resolution methane concentration data, thereby improving the resolution of methane concentration data within the monitoring range of the mining area.

[0075] To enable those skilled in the art to better understand the present invention, the following will be combined with... Figure 1 The technical solutions in the embodiments of this application are clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this invention.

[0076] like Figure 1 As shown, the present invention provides a method for improving the inversion resolution of methane emission concentration, comprising:

[0077] Step 101: Acquire high-resolution and low-resolution satellite data. The high-resolution satellite data includes image data, and the low-resolution satellite data includes methane concentration data corresponding to the image data. It should be noted that the acquisition dates of the high-resolution and low-resolution satellite data should be close, and the monitoring area of ​​the high-resolution satellite image should correspond to the monitoring area of ​​the low-resolution satellite data's methane concentration. The high-resolution and low-resolution satellite data each correspond to spectral curves. High-resolution data can be obtained from a land observation satellite data service website. For example, image data from the Gaofen-5 02 satellite on December 13, 2022, over the Longde Mine in Dabaodang Town, Yushen Mining Area, Shenmu County, can be selected as high-resolution hyperspectral satellite data. This satellite data contains hyperspectral information from visible light to near-infrared, and the satellite's resolution is 30 meters; this resolution can be used as the target resolution. Low-resolution satellite data can be downloaded from the Google Earth Engine website to obtain low-resolution methane concentration data. For example, methane concentration product data from the Sentinel-5P satellite's Tropomi in December 2022 can be used as low-resolution satellite data.

[0078] Step 102: Upscale the high-resolution satellite data and combine it with the low-resolution satellite data to calculate the weighted spectral curve;

[0079] like Figure 2 As shown, the implementation process of step 102 can be as follows:

[0080] Step 1021: Reduce the resolution of the high-resolution satellite data so that the methane concentration data of the high-resolution satellite data is consistent with the methane concentration data of the low-resolution satellite data;

[0081] Specifically, the high-resolution satellite data from the Gaofen-5 02 satellite can be upscaled, and the resolution can be reduced to match the low-resolution satellite data obtained from the Sentinel-5P satellite's TROPOMI using a resampling method on the ArcGIS platform.

[0082] Step 1022: Obtain the spectral curves of each pixel in the high-resolution satellite data after resolution reduction, and define them as the reference spectral curves;

[0083] Specifically, each pixel of the satellite data corresponds to a spectral curve at different wavelengths. The set of these spectral curves can be named the reference spectral curve, and the elements of the set are the spectral curves of each pixel.

[0084] Step 1023: Based on the low-resolution satellite data and the corresponding atmospheric profile data, obtain the spectral curve of methane, which is defined as the simulated spectral curve;

[0085] Specifically, the spectral curve of methane can be obtained using the MODTRAN model.

[0086] Step 1024: Perform a weighted calculation on the simulated spectral curve and the reference spectral curve of any pixel to obtain the weighted spectral curve of each pixel.

[0087] Specifically, the baseline and simulated spectral curves can be calculated using the MATLAB platform, and a weighted spectral curve can be obtained by weighting them according to a certain ratio. The weighting method can be expressed by the following formula:

[0088]

[0089] In the formula, For the weighted spectral curves, A is the reference spectral curve, B is the simulated spectral curve, m is the weight of the reference spectral curve, and n is the weight of the simulated spectral curve.

[0090] In this embodiment, both m and n are 50%.

[0091] Step 103: Based on the weighted spectral curve and the spectral curve of pixels in high-resolution satellite data, determine the pixel feature weights and obtain the reweighted spectral curve;

[0092] like Figure 3 As shown, the implementation process of step 103 can be as follows:

[0093] Step 1031: Obtain the spectral curves of each pixel in the high-resolution satellite data;

[0094] Specifically, the weighted spectral curve can be used as a reference, and the spectral curves of each pixel of the high-resolution satellite data of Gaofen-5 02 satellite in the region corresponding to the weighted spectral curve can be extracted pixel by pixel based on the MATLAB platform.

[0095] Step 1032: At a specific wavelength, calculate the ratio of the peak value of the spectral curve of any pixel in the high-resolution satellite data to the peak value of the weighted spectral curve of the corresponding pixel. This ratio is the pixel feature weight.

[0096] Specifically, when selecting a specific wavelength, the absorption of the spectrum by methane should be relatively strong at that selected wavelength. Generally, a specific wavelength of 1.6 μm is chosen. After selecting the wavelength, the quotient of the two peak values ​​is taken as the pixel feature weight. For example, if the peak value of the spectral curve of a pixel in the Longde Mine Gaofen-5 image at 1.6 μm is 1.01, and the peak value of the weighted spectral curve of the corresponding wavelength combination obtained through simulation of the Sentinel-5P image is 1.13, then the pixel feature weight is 0.89. It should be noted that this invention characterizes the weight of a pixel at different wavelengths by the ratio of the peak value of any pixel at a specific wavelength to the peak value of the weighted spectral curve.

[0097] Step 1033: Multiply the obtained pixel feature weights by the weighted spectral curves of each pixel to obtain the reweighted spectral curves of each pixel.

[0098] Specifically, step 1032 obtains the pixel feature weights of each pixel. By multiplying the pixel feature weights of each pixel by the weighted spectral curve of the corresponding pixel, the spectral curve of each pixel after reweighting can be obtained.

[0099] Step 104: Perform matched filtering on the weighted spectral curves to obtain high-resolution methane concentration data. This step aims to calculate the methane concentration using the reweighted spectral curve corresponding to each pixel. Methane exhibits strong rotational vibrational transitions, and its absorption in the short-wave infrared band can be detected by satellite sensors. Therefore, the spectral absorption characteristics of methane can be used to calculate data that characterizes the variation of methane gas within the same region.

[0100] like Figure 4 As shown, the implementation process of step 104 can be as follows:

[0101] Step 1041: Based on satellite observation of shortwave infrared band data, obtain the spectral radiance value of each pixel;

[0102] Specifically, the spectral radiance value can be obtained by calculation based on shortwave infrared reflectance data, or it can be obtained directly from sensors on the satellite.

[0103] Step 1042: Calculate the average spectral radiance and use it to calculate the background covariance matrix;

[0104] Specifically, the background covariance matrix is ​​calculated using the following formula:

[0105]

[0106] Where N is the number of pixels, and L is the spectral radiance value of each pixel. This represents the average spectral radiance.

[0107] Step 1043: Use matched filtering to obtain high-resolution methane concentration data.

[0108] Furthermore, such as Figure 5 As shown, the implementation process of step 1043 can be as follows:

[0109] Step 10431: The spectral radiance value is decomposed into the background radiance value of the pixel without methane enhancement and the radiative perturbation caused by the increased methane concentration. According to the Beer-Lambert absorption law and using a first-order Taylor series expansion, the methane enhancement effect is obtained and approximated by the following formula:

[0110]

[0111] Where α is the methane concentration, s is the methane absorption spectral characteristic, L0 is the background radiance value without methane enhancement, and t is the target characteristic spectrum based on the methane absorption spectral characteristic s. The average spectral radiance value approximately replaces L0.

[0112] Step 10432: Assuming the absorption characteristics of methane remain unchanged and that only methane as a single gas is of interest, the Gaussian log-likelihood of the above formula is performed and the minimum value is taken. The high-resolution methane column concentration is expressed by the following formula:

[0113]

[0114] In the formula, L i Let be the spectral radiance value of the i-th pixel, μ be the average spectral radiance, and C be the background covariance matrix. It is the target spectral radiation perturbation. This represents the perturbation value relative to background radiation caused by the increase in methane concentration.

[0115] Furthermore, in high-resolution satellite data, the proportion of pixels affected by methane concentration changes in the entire image is relatively small, and the spectrum of each pixel is also affected by different ground reflectances or other substances in the atmosphere, leading to inaccurate spectral curve results. Using the L2,1 norm for feature selection and sparsity analysis can not only effectively suppress the interference of complex terrain conditions on the inversion, but also remove irrelevant noise and filter out features that are more important to the problem. Therefore, the method of the present invention also includes step 105, which is a step of optimizing the obtained high-resolution methane column concentration data;

[0116] like Figure 6 As shown, the implementation process of step 105 can be as follows:

[0117] Step 1051: Calculate the two-dimensional reflection characteristics of the Earth's surface, expressed using the following formula:

[0118]

[0119] in, These are the observed radiance values ​​after terrain correction. This represents the original observed radiance value at the Earth's surface. It is the cosine of the angle of incidence at the zenith. Let be the cosine of the solar incident zenith angle relative to the slope, represent the cosine of the solar incident zenith angle relative to the slope, and k be the Minnaert coefficient;

[0120] Since the real ground is not a Lambertian surface and has biaxial reflectance characteristics, the empirical Minnaert coefficient k is introduced to describe the biaxial reflectance characteristics of the ground surface. When k=1, it means that the ground surface is a Lambertian surface. A decrease in the value of k means that the ground surface reflectance characteristics no longer conform to the Lambertian surface and the biaxial reflectance characteristics increase.

[0121] Step 1052: Calculate the scalar albedo factor and construct the scalar albedo matrix. The scalar albedo factor is expressed by the following formula:

[0122]

[0123] in, Here, μ is the scalar albedo factor, and μ is the average spectral radiance. The radiance value of the i-th pixel observed below a flat surface;

[0124] Step 1053: Based on the scalar albedo factor, calculate the objective function and construct the objective function matrix. The objective function is expressed by the following formula:

[0125]

[0126] in,

[0127] Through ℓ2,1 ( Solve the above optimization problems.

[0128] In the formula, Let C be the objective function, and C be the background covariance matrix. For the number of iterations, Scalar albedo factor To apply regularization weights to each row vector for the p-th iteration, Let be the radiance value of the i-th pixel observed below a flat surface; where,

[0129]

[0130] Step 1054: Optimize the objective function matrix to obtain the optimized high-resolution methane column concentration, using the following calculations:

[0131]

[0132] In the formula, and Recalculation is performed in each reweighting iteration.

[0133] The result is the methane concentration data after resolution improvement and optimization.

[0134] In addition, if the obtained methane spectral curve data shows that methane concentration data cannot be obtained at the southern boundary of the Longde mine, it is speculated that this is because the wind direction in December is southerly, resulting in a lower methane gas concentration in the southern part of the mining area. The pixel feature weights obtained in step 1032 for some pixels in the southern part of the mining area are multiplied with each pixel of the low-resolution satellite methane concentration data obtained by Sentinel-5P satellite TROPOMI to obtain the methane concentration of the corresponding pixel, thereby obtaining comprehensive methane concentration data covering the Longde mine.

[0135] like Figure 7 As shown, the present invention also provides a resolution enhancement system for methane emission concentration retrieval, comprising:

[0136] The acquisition module 201 is used to acquire high-resolution satellite data and low-resolution satellite data, wherein the high-resolution satellite data includes image data and the low-resolution satellite data includes methane concentration data corresponding to the image data.

[0137] Weighting module 202 is used to upscale the high-resolution satellite data and calculate the weighted spectral curve by combining it with the low-resolution satellite data.

[0138] The reweighting module 203 is used to determine the pixel feature weights and obtain the reweighted spectral curve based on the weighted spectral curve and the spectral curve of pixels in high-resolution satellite data.

[0139] The matched filtering module 204 is used to perform matched filtering on the weighted distribution spectral curve to obtain high-resolution methane concentration data.

[0140] This invention also provides a terminal device, see [link to relevant documentation]. Figure 8 The terminal device 300 may include: at least one processor 310, a memory 320, and a computer program stored in the memory 320 and executable on the at least one processor 310, wherein the processor 310 executes the computer program to implement the steps in any of the above method embodiments.

[0141] For example, a computer program can be divided into one or more modules / units, one or more of which are stored in memory 320 and executed by processor 310 to complete the present invention. The one or more modules / units can be a series of computer program segments capable of performing specific functions, which describe the execution process of the computer program in terminal device 300.

[0142] Those skilled in the art will understand that Figure 8 This is merely an example of a terminal device and does not constitute a limitation on the terminal device. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0143] The processor 310 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0144] The memory 320 can be an internal storage unit of the terminal device or an external storage device, such as a plug-in hard drive, a smart media card (SMC), a secure digital (SD) card, or a flash card. The memory 320 is used to store the computer program and other programs and data required by the terminal device. The memory 320 can also be used to temporarily store data that has been output or will be output.

[0145] Buses can be Industry Standard Architecture (ISA) buses, Peripheral Component Interconnect (PCI) buses, or Extended Industry Standard Architecture (EISA) buses, etc. Buses can be categorized into address buses, data buses, control buses, etc.

[0146] The method for improving the inversion resolution of methane emission concentration provided in this embodiment of the invention can be applied to terminal devices such as computers, tablets, laptops, netbooks, and personal digital assistants (PDAs). This embodiment of the invention does not impose any restrictions on the specific type of terminal device.

[0147] Taking a computer as an example, the terminal device is described above. Figure 9The diagram shown is a block diagram of a portion of the structure of a computer provided in an embodiment of the present invention. (Reference) Figure 9 The computer includes components such as a communication circuit 410, a memory 420, an input unit 430, a display unit 440, an audio circuit 450, a wireless fidelity (WiFi) module 460, a processor 470, and a power supply 480. Those skilled in the art will understand that... Figure 9 The computer architecture shown does not constitute a limitation on the computer and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0148] The following is combined with Figure 9 A detailed introduction to the various components of a computer:

[0149] The communication circuit 410 can be used for receiving and sending signals during information transmission or calls. Specifically, it receives image samples sent by the image acquisition device and processes them with the processor 470. Additionally, it sends image acquisition commands to the image acquisition device. Typically, the communication circuit includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low-noise amplifier (LNA), a duplexer, etc. Furthermore, the communication circuit 410 can also communicate wirelessly with networks and other devices. The aforementioned wireless communication can use any communication standard or protocol, including but not limited to Global System for Mobile Communication (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), email, Short Messaging Service (SMS), etc.

[0150] The memory 420 can be used to store software programs and modules. The processor 470 executes various computer functions and data processing by running the software programs and modules stored in the memory 420. The memory 420 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc. The data storage area may store data created according to the use of the computer (such as audio data, telephone directory, etc.). In addition, the memory 420 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0151] The input unit 430 can be used to receive input numerical or character information, and to generate key signal inputs related to user settings and function control of the computer. Specifically, the input unit 430 may include a touch panel 431 and other input devices 432. The touch panel 431, also known as a touch screen, can collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch panel 431), and drive the corresponding connection devices according to a pre-set program. Optionally, the touch panel 431 may include two parts: a touch detection device and a touch controller. The touch detection device detects the user's touch position and the signal generated by the touch operation, and transmits the signal to the touch controller. The touch controller receives touch information from the touch detection device, converts it into touch point coordinates, sends it to the processor 470, and can receive and execute commands sent by the processor 470. In addition, the touch panel 431 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch panel 431, the input unit 430 may also include other input devices 432. Specifically, other input devices 432 may include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, joystick, etc.

[0152] Display unit 440 can be used to display information input by the user or information provided to the user, as well as various menus of the computer. Display unit 440 may include a display panel 441, optionally configured as a Liquid Crystal Display (LCD), Organic Light-Emitting Diode (OLED), or similar device. Further, touch panel 431 may cover display panel 441. When touch panel 431 detects a touch operation on or near it, it transmits the information to processor 470 to determine the type of touch event. Subsequently, processor 470 provides corresponding visual output on display panel 441 based on the type of touch event. Although in the figures, touch panel 431 and display panel 441 are shown as two separate components for implementing computer input and output functions, in some embodiments, touch panel 431 and display panel 441 can be integrated to achieve computer input and output functions.

[0153] Audio circuit 450 provides an audio interface between the user and the computer. Audio circuit 450 converts received audio data into electrical signals, which are then transmitted to a speaker for conversion into sound signals for output. Conversely, a microphone converts collected sound signals into electrical signals, which are received by audio circuit 450, converted back into audio data, and then processed by processor 470 before being transmitted via communication circuit 410 to, for example, another computer, or output to memory 420 for further processing.

[0154] WiFi is a short-range wireless transmission technology. Computers using WiFi modules can help users send and receive emails, browse web pages, and access streaming media, providing wireless broadband internet access. Although Figure 9 WiFi module 460 is shown, but it is understood that it is not an essential component of a computer and can be omitted as needed without changing the nature of the invention.

[0155] The processor 470 is the control center of the computer, connecting various parts of the computer through various interfaces and lines. It performs various computer functions and processes data by running or executing software programs and / or modules stored in the memory 420, and by calling data stored in the memory 420, thereby providing overall monitoring of the computer. Optionally, the processor 470 may include one or more processing units. Preferably, the processor 470 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 470.

[0156] The computer also includes a power supply 480 (such as a battery) that supplies power to various components. Preferably, the power supply 480 can be logically connected to the processor 470 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system.

[0157] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the various embodiments of the above-described method for improving the inversion resolution of methane emission concentration.

[0158] This invention provides a computer program product that, when run on a mobile terminal, enables the mobile terminal to execute the steps in the various embodiments of the above-described method for improving the inversion resolution of methane emission concentration.

[0159] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0160] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0161] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0162] In the embodiments provided by this invention, it should be understood that the disclosed apparatus / network devices and methods can be implemented in other ways. For example, the apparatus / network device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0163] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0164] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for improving the resolution of methane emission concentration inversion, characterized in that, include: Acquire high-resolution satellite data and low-resolution satellite data, where high-resolution satellite data includes image data and low-resolution satellite data includes methane concentration data corresponding to the image data; Upscaling of high-resolution satellite data involves reducing the resolution of the high-resolution satellite data to make the methane concentration data of the high-resolution satellite data consistent with the methane concentration data of the low-resolution satellite data, and obtaining the spectral curves of each pixel of the high-resolution satellite data after the resolution reduction, which are defined as the reference spectral curves. Based on the low-resolution satellite data and the corresponding atmospheric profile data, a simulated spectral curve of methane is obtained, and the simulated spectral curve and the reference spectral curve of any pixel are weighted to obtain a weighted spectral curve for each pixel. The spectral curves of each pixel in high-resolution satellite data are obtained. At a specific wavelength, the ratio of the peak value of the spectral curve of any pixel in the high-resolution satellite data to the peak value of the weighted spectral curve of the corresponding pixel is calculated as the pixel feature weight. This weight is then multiplied by the weighted spectral curves of each pixel to obtain the reweighted spectral curves of each pixel. Based on satellite observation of shortwave infrared band data, the spectral radiance values ​​of each pixel are obtained, the average spectral radiance is calculated, and the background covariance matrix is ​​generated accordingly. The reweighted spectral curve is processed using the matched filtering method to obtain high-resolution methane concentration data.

2. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for improving the inversion resolution of methane emission concentration as described in claim 1.

3. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for improving the inversion resolution of methane emission concentration as described in claim 1.

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