Methane gas concentration prediction method and device

Abstract

The invention provides a methane gas concentration prediction method and device, and is applied to the technical field of environmental monitoring. The method comprises the following steps: collecting methane gas concentration data of a target area, wherein the methane gas concentration data comprises methane gas concentrations at different altitudes and different air pressures; constructing a spatio-temporal data set based on the methane gas concentration data, and matching the altitude, the air pressure and the methane gas concentration at the same time point to generate a spatio-temporal matrix; based on the space-time matrix, a Newton interpolation method is adopted to generate a target polynomial function, and the methane gas concentration of an unknown data point is predicted based on the target polynomial function; wherein the target polynomial function is used for describing a nonlinear relation between the methane gas concentration and space-time parameters, and the space-time parameters comprise the altitude and the air pressure.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular to a method and device for predicting methane gas concentration. Background Art

[0002] As the core area of ​​the Qinghai-Tibet Plateau ecological barrier, the unique alpine and hypoxic environment and complex climate conditions of the Hoh Xil region have an important impact on the regional ecological balance and global carbon cycle. Methane, as a key greenhouse gas, is closely related to permafrost thawing, wetland evolution, and microbial activities, and is an important indicator for assessing regional carbon source / sink effects and climate feedback mechanisms.

[0003] However, the extreme environment in the Hoh Xil region (such as low temperature, strong radiation, and wind and sand erosion) makes it difficult for traditional atmospheric monitoring equipment to operate stably in the long term, and existing research mostly focuses on conventional meteorological parameters (such as temperature, wind speed, and precipitation). There is a serious lack of high-precision, continuous spatiotemporal monitoring data on methane gas concentrations, which restricts the in-depth analysis of regional methane emission patterns and their driving mechanisms. Summary of the invention

[0004] The present invention provides a methane gas concentration prediction method and device to solve the problem that the prior art lacks in-situ, multi-point, high-frequency measured data support for methane concentration and is difficult to capture its temporal and spatial heterogeneity characteristics.

[0005] The present invention provides a methane gas concentration prediction method, comprising: collecting methane gas concentration data of a target area, wherein the methane gas concentration data includes methane gas concentrations at different altitudes and different air pressures; constructing a spatiotemporal data set based on the methane gas concentration data, and matching the altitude, air pressure and methane gas concentration at the same time point to generate a spatiotemporal matrix; based on the spatiotemporal matrix, using Newton interpolation to generate a target polynomial function, and predicting the methane gas concentration of an unknown data point based on the target polynomial function; wherein the target polynomial function is used to describe the nonlinear relationship between the methane gas concentration and spatiotemporal parameters, wherein the spatiotemporal parameters include altitude and air pressure.

[0006] According to a methane gas concentration prediction method provided by the present invention, the sampling method of methane gas concentration data includes an adaptive sampling method based on environmental variables, a sampling method under distance restrictions, and an altitude stratified sampling method.

[0007] According to a methane gas concentration prediction method provided by the present invention, after collecting the methane gas concentration data of the target area, the method further includes: visualizing the methane gas concentration data.

[0008] According to a methane gas concentration prediction method provided by the present invention, after collecting the methane gas concentration data of the target area, the method also includes: identifying outliers by calculating the statistics of the methane gas concentration data, deleting the outliers, and filling in the missing data; and normalizing the altitude and air pressure in the methane gas concentration data.

[0009] The present invention also provides a methane gas concentration prediction device, comprising the following modules: an acquisition module and a processing module; the acquisition module is used to collect methane gas concentration data of a target area, the methane gas concentration data including methane gas concentrations at different altitudes and different air pressures; the processing module is used to construct a spatiotemporal data set based on the methane gas concentration data, and match the altitude, air pressure and methane gas concentration at the same time point to generate a spatiotemporal matrix; based on the spatiotemporal matrix, a target polynomial function is generated using the Newton interpolation method, and the methane gas concentration of an unknown data point is predicted based on the target polynomial function; wherein the target polynomial function is used to describe the nonlinear relationship between the methane gas concentration and spatiotemporal parameters, and the spatiotemporal parameters include altitude and air pressure.

[0010] According to a methane gas concentration prediction device provided by the present invention, the sampling method of methane gas concentration data includes an adaptive sampling method based on environmental variables, a sampling method under distance restrictions, and an altitude stratified sampling method.

[0011] According to a methane gas concentration prediction device provided by the present invention, the processing module is also used to perform visualization processing on the methane gas concentration data.

[0012] According to a methane gas concentration prediction device provided by the present invention, the processing module is also used to identify outliers by calculating the statistics of the methane gas concentration data, delete the outliers, and fill in missing data; and normalize the altitude and air pressure in the methane gas concentration data.

[0013] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a methane gas concentration prediction method as described above is implemented.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the methane gas concentration prediction method as described in any one of the above is implemented.

[0015] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned methane gas concentration prediction methods.

[0016] The methane gas concentration prediction method and device provided by the present invention realize dynamic monitoring and prediction of methane gas concentration in the target area through systematic collection, structured modeling and high-precision interpolation methods, solve the core problems of scarce methane monitoring data and low model accuracy in harsh environmental areas, provide scientific tools for ecological protection and climate change response, and have significant environmental benefits and application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a schematic diagram of the flow of the methane gas concentration prediction method provided by the present invention; Figure 2 It is a structural schematic diagram of a methane gas concentration prediction device provided by the present invention; Figure 3 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0020] It should be noted that, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0021] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0022] In order to facilitate a clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, words such as "first" and "second" are used to distinguish between identical or similar items with substantially the same functions and effects. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and order of execution.

[0023] The embodiments of the present application describe some exemplary embodiments for the purpose of explanation. It should be understood that the present application can be implemented in other ways that are not specifically shown in the drawings.

[0024] like Figure 1 As shown, the embodiment of the present application provides a methane gas concentration prediction method, which can be applied to a methane gas concentration prediction device. The methane gas concentration prediction method may include S101-S103: S101. A methane gas concentration prediction device collects methane gas concentration data of a target area.

[0025] The above methane gas concentration data include methane gas concentrations at different altitudes and different air pressures.

[0026] Alternatively, users can use independently developed portable methane gas measurement equipment to carry out systematic in-situ monitoring of the spatiotemporal distribution characteristics of methane concentration in the target area. Through the four-dimensional coordinated planning of seasonal changes, altitude gradients, time series and spatial heterogeneity, a high-precision and continuous methane concentration dataset is obtained to analyze the methane release mechanism of alpine ecosystems and its coupling relationship with climate factors.

[0027] Specifically, take the target area of ​​Hoh Xil No Man's Land as an example.

[0028] The plan for seasonal changes is: the Hoh Xil uninhabited area is a high-altitude area with a harsh climate, and the annual average temperature is below 0°C. What users need to study is whether there is a greenhouse effect change in the uninhabited area, so they can choose to collect multiple sets of methane gas concentration data under high temperatures. The third quarter of each year is the time when the temperature in the uninhabited area is the highest, so users can plan to collect multiple sets of data in the uninhabited area in August to support subsequent analysis and research.

[0029] The altitude gradient is planned as follows: most of the uninhabited areas are between 4200-5000m above sea level, with an average altitude of more than 4500m. Users want to measure the methane gas concentration in different areas at the same altitude and at different altitudes, so data can be collected at different altitudes between 2800-4600m.

[0030] The planning for time series is as follows: the temperature difference between day and night in the uninhabited area is extremely large, and the weather changes instantly. Under normal conditions, the highest temperature of a single day generally occurs at 16:00-18:00 in the afternoon, the highest surface temperature, and the lowest temperature generally occurs around 7:00 in the morning. Therefore, users can choose to measure the methane atmospheric concentration data briefly and continuously at different time points from day to night. The time distribution is 7:00-22:00 to cover all time periods.

[0031] The planning for spatial heterogeneity is: the entire uninhabited area is extremely large, and it is impossible to obtain data in the entire area, especially in some places that cannot be reached by cars and people. Therefore, it is possible to consider arranging key location points to obtain data to characterize the methane concentration value in this area.

[0032] It should be noted that the selection of key location points should take into account the spatial distribution of geographical locations such as temperature, humidity, lakes, and permafrost areas.

[0033] Optionally, the sampling method of the methane gas concentration data includes an adaptive sampling method based on environmental variables, a sampling method under distance restrictions, and an altitude stratified sampling method.

[0034] (1) Adaptive sampling method based on environmental variables The adaptive sampling method dynamically selects sampling points based on environmental variables. Some environmental variables (such as humidity, precipitation, temperature, and soil type) have a significant impact on methane gas concentration, and the location of the sampling points can be selected based on these variables.

[0035] The adaptive sampling formula is: ; (1) in, The longitude of the direction, Indicates the latitude of the location, Indicates the humidity at this location. Indicates the amount of precipitation at this location. represents the temperature at that location, Indicates the soil type at this location. Represents the sampling probability under this orientation.

[0036] (2) Sampling method under distance restriction Due to the rugged terrain of some locations in the no-man's land, it is difficult for people and vehicles to reach, resulting in certain distance restrictions during sampling. At the same time, dense sampling should be avoided between one sampling point and another. Therefore, the distance restriction formula is: ; (2) in, , , For the The position value of the position, For the The position value of the position, for The Euclidean distance between two sample points, is the minimum distance between two sampling points.

[0037] (3) Altitude stratified sampling method The difference in altitude in the Hoh Xil No Man's Land results in different methane gas concentration data collected, and each altitude level has representative data representation. For different altitude levels, it is assumed that the range is , which is divided into The stratified sampling is determined according to the distribution of methane gas concentration at different altitude levels.

[0038] 1. Altitude stratification range The data area is divided into Levels: ; (3) in, , For the The altitude of the layer, is the highest altitude, is the lowest altitude.

[0039] 2. Stratified sampling range The spatial distribution sampling of methane gas concentration within each altitude layer is: ; (4) in, is the total number of sampling points, For the The area range of the layer, is the total area range, For the The number of layer samples.

[0040] Based on the above four spatiotemporal parameter analyses and through the above three sampling methods, users can collect methane gas concentration data in an orderly manner at different altitudes in the Hoh Xil No Man's Land and in different areas at the same altitude.

[0041] Optionally, after collecting the methane gas concentration data of the target area, the methane gas concentration prediction device may also perform visualization processing on the methane gas concentration data.

[0042] Specifically, the visualization processing mainly includes: displaying the frequency distribution of methane gas concentration through a line graph. For example, a line graph can be used to show the frequency distribution of short-term measurements of methane gas concentration at different locations and different time periods at the same altitude. Alternatively, a three-dimensional situation map can be used to show the spatiotemporal distribution of methane gas concentration with altitude, time, and air pressure.

[0043] Through the visualization of methane gas concentration data, it can be seen that the methane gas concentration is not constant over time. In the line graph, it can be shown in the form of a sine curve. In the three-dimensional situation diagram, the methane gas concentration can present a regular change curve as it changes in time and space.

[0044] Optionally, after collecting the methane gas concentration data of the target area, the methane gas concentration prediction device can also identify outliers by calculating the statistics of the methane gas concentration data, delete the outliers, and fill in missing data; and normalize the altitude and air pressure in the methane gas concentration data.

[0045] Specifically, the statistics of methane gas concentration data include calculating the mean, standard deviation, median, maximum value, and minimum value, etc. Normalization processing refers to scaling the altitude and pressure data to a similar range to avoid large numerical differences that affect model convergence.

[0046] S102. The methane gas concentration prediction device constructs a spatiotemporal data set based on the methane gas concentration data, and matches the altitude and air pressure at the same time point with the methane gas concentration to generate a spatiotemporal matrix.

[0047] S103. The methane gas concentration prediction device generates a target polynomial function based on the space-time matrix using Newton interpolation method, and predicts the methane gas concentration of unknown data points based on the target polynomial function.

[0048] The target polynomial function is used to describe the nonlinear relationship between methane gas concentration and spatiotemporal parameters, and the spatiotemporal parameters include altitude and air pressure.

[0049] It should be noted that the core of Newton interpolation method is to use the altitude, air pressure and methane concentration of known points to construct a polynomial function so that the function can perfectly pass through all known data points and predict the concentration value of unknown points.

[0050] Specifically, given the altitude and air pressure of a location, set a set of altitude and air pressure data points , , …, ,in, Different from each other, is corresponding to The function value of .

[0051] Then, construct an interpolation approximation function, given a set of discrete data points ,in , the goal of interpolation is to find a function , so that For all At the same time, the function can also reflect the changing trend between data points to a certain extent.

[0052] According to the data characteristics of altitude, air pressure and methane gas concentration, a Newton interpolation method in the interpolation approximation function is established. A polynomial function is constructed through known data points to predict the values ​​of each unknown data point.

[0053] Newton interpolation polynomial constructs a polynomial through a given set of points so that the polynomial forms all given points. Its principle can be expressed as: ; (5) in, is the value of the data point, for Order difference quotient. is the calculated polynomial value.

[0054] When the data point values ​​are substituted into the formula, the polynomial can be simplified to obtain: ; (6) in, , are the coefficients of each item.

[0055] Therefore, through the construction of Newton interpolation polynomials, there is a nonlinear relationship between methane gas concentration and time and space parameters. The above formula can be simplified by substituting the collected altitude, atmospheric pressure, and methane gas concentration data into: ; (7) in, is the altitude, is the atmospheric pressure, is the methane gas concentration, , , is the regression coefficient.

[0056] The coefficients of the formula can be obtained by deduction, and the following fitting formula can be obtained by symbol replacement: ; (8) in, is the altitude, is the atmospheric pressure, is the methane gas concentration.

[0057] In the embodiments of the present application, dynamic monitoring and prediction of methane gas concentration in the target area are achieved through systematic collection, structured modeling and high-precision interpolation methods, which solves the core problems of scarce methane monitoring data and low model accuracy in harsh environmental areas, provides scientific tools for ecological protection and climate change response, and has significant environmental benefits and application value.

[0058] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of the method. In order to realize the above functions, it includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment disclosed herein, the embodiment of the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0059] It should be noted that the device in the embodiment of the present application includes a virtual device and a physical device. The virtual device can be a methane gas concentration prediction device, and the physical device can include an electronic device, a computer storage medium, and a computer program product.

[0060] The methane gas concentration prediction method provided in the embodiment of the present application can be executed by a methane gas concentration prediction device or a control module for methane gas concentration prediction in the methane gas concentration prediction device. In the embodiment of the present application, the methane gas concentration prediction method is executed by a methane gas concentration prediction device as an example to illustrate the methane gas concentration prediction device provided in the embodiment of the present application.

[0061] It should be noted that the embodiment of the present application can divide the functional modules of the methane gas concentration prediction device according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules. Optionally, the division of modules in the embodiment of the present application is schematic and is only a logical functional division. There may be other division methods in actual implementation.

[0062] like Figure 2 As shown, an embodiment of the present application provides a methane gas concentration prediction device 200. The methane gas concentration prediction device 200 includes: an acquisition module 201 and a processing module 202. The acquisition module 201 is used to collect methane gas concentration data of the target area, and the methane gas concentration data includes methane gas concentrations at different altitudes and different air pressures; the processing module 202 is used to construct a spatiotemporal data set based on the methane gas concentration data, and match the altitude, air pressure and methane gas concentration at the same time point to generate a spatiotemporal matrix; based on the spatiotemporal matrix, a target polynomial function is generated using the Newton interpolation method, and the methane gas concentration of unknown data points is predicted based on the target polynomial function; wherein the target polynomial function is used to describe the nonlinear relationship between the methane gas concentration and spatiotemporal parameters, and the spatiotemporal parameters include altitude and air pressure.

[0063] Optionally, the sampling method of the methane gas concentration data includes an adaptive sampling method based on environmental variables, a sampling method under distance restrictions, and an altitude stratified sampling method.

[0064] Optionally, the processing module 202 is further used to perform visualization processing on the methane gas concentration data.

[0065] Optionally, the processing module 202 is further configured to identify outliers by calculating statistics of the methane gas concentration data, delete the outliers, and fill in missing data; and normalize the altitude and air pressure in the methane gas concentration data.

[0066] In the embodiments of the present application, dynamic monitoring and prediction of methane gas concentration in the target area are achieved through systematic collection, structured modeling and high-precision interpolation methods, which solves the core problems of scarce methane monitoring data and low model accuracy in harsh environmental areas, provides scientific tools for ecological protection and climate change response, and has significant environmental benefits and application value.

[0067] Figure 3 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 3As shown, the electronic device may include: a processor 310, a communication interface 320, a memory 330 and a communication bus 340, wherein the processor 310, the communication interface 320 and the memory 330 communicate with each other through the communication bus 340. The processor 310 may call the logic instructions in the memory 330 to execute the methane gas concentration prediction method, which includes: collecting methane gas concentration data of the target area, wherein the methane gas concentration data includes methane gas concentrations at different altitudes and different air pressures; constructing a spatiotemporal data set based on the methane gas concentration data, and matching the altitude and air pressure at the same time point with the methane gas concentration to generate a spatiotemporal matrix; based on the spatiotemporal matrix, using the Newton interpolation method to generate a target polynomial function, and predicting the methane gas concentration of an unknown data point based on the target polynomial function; wherein the target polynomial function is used to describe the nonlinear relationship between the methane gas concentration and the spatiotemporal parameters, wherein the spatiotemporal parameters include the altitude and air pressure.

[0068] In addition, the logic instructions in the above-mentioned memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0069] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the methane gas concentration prediction method provided by the above methods, which method includes: collecting methane gas concentration data in the target area, the methane gas concentration data including methane gas concentrations at different altitudes and different air pressures; constructing a spatiotemporal data set based on the methane gas concentration data, and matching the altitude and air pressure at the same time point with the methane gas concentration to generate a spatiotemporal matrix; based on the spatiotemporal matrix, using Newton interpolation to generate a target polynomial function, and predicting the methane gas concentration of unknown data points based on the target polynomial function; wherein the target polynomial function is used to describe the nonlinear relationship between the methane gas concentration and spatiotemporal parameters, and the spatiotemporal parameters include altitude and air pressure.

[0070] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the methane gas concentration prediction method provided by the above-mentioned methods, the method comprising: collecting methane gas concentration data of a target area, the methane gas concentration data comprising methane gas concentrations at different altitudes and different air pressures; constructing a spatiotemporal data set based on the methane gas concentration data, and matching the altitude, air pressure and methane gas concentration at the same time point to generate a spatiotemporal matrix; based on the spatiotemporal matrix, generating a target polynomial function using Newton interpolation method, and predicting the methane gas concentration of unknown data points based on the target polynomial function; wherein the target polynomial function is used to describe the nonlinear relationship between the methane gas concentration and spatiotemporal parameters, the spatiotemporal parameters comprising altitude and air pressure.

[0071] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0072] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting methane gas concentration, characterized in that: include: Collecting methane gas concentration data of a target area, wherein the methane gas concentration data includes methane gas concentrations at different altitudes and different air pressures; Building a spatiotemporal data set based on the methane gas concentration data, and matching the altitude and air pressure with the methane gas concentration at the same time point to generate a spatiotemporal matrix; Based on the space-time matrix, a target polynomial function is generated using a Newton interpolation method, and the methane gas concentration of the unknown data point is predicted based on the target polynomial function; The target polynomial function is used to describe the nonlinear relationship between methane gas concentration and spatiotemporal parameters, and the spatiotemporal parameters include altitude and air pressure.

2. The methane gas concentration prediction method according to claim 1, characterized in that: The sampling methods for methane gas concentration data include an adaptive sampling method based on environmental variables, a sampling method under distance restrictions, and an altitude stratified sampling method.

3. The methane gas concentration prediction method according to claim 1, characterized in that: After collecting the methane gas concentration data of the target area, the method further includes: The methane gas concentration data is visualized.

4. The methane gas concentration prediction method according to claim 1, characterized in that: After collecting the methane gas concentration data of the target area, the method further includes: Identify outliers by calculating statistics of the methane gas concentration data, delete the outliers, and fill in missing data; The altitude and air pressure in the methane gas concentration data are normalized.

5. A methane gas concentration prediction device, characterized in that: include: Acquisition module and processing module; The acquisition module is used to collect methane gas concentration data in the target area, wherein the methane gas concentration data includes methane gas concentrations at different altitudes and different air pressures; The processing module is used to construct a spatiotemporal data set based on the methane gas concentration data, and match the altitude and air pressure with the methane gas concentration at the same time point to generate a spatiotemporal matrix; Based on the space-time matrix, a target polynomial function is generated using a Newton interpolation method, and the methane gas concentration of the unknown data point is predicted based on the target polynomial function; The target polynomial function is used to describe the nonlinear relationship between methane gas concentration and spatiotemporal parameters, and the spatiotemporal parameters include altitude and air pressure.

6. The methane gas concentration prediction device according to claim 5, characterized in that: The sampling methods for methane gas concentration data include an adaptive sampling method based on environmental variables, a sampling method under distance restrictions, and an altitude stratified sampling method.

7. The methane gas concentration prediction device according to claim 5, characterized in that: The processing module is also used to perform visualization processing on the methane gas concentration data.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the methane gas concentration prediction method according to any one of claims 1 to 4 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the methane gas concentration prediction method according to any one of claims 1 to 4 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the methane gas concentration prediction method according to any one of claims 1 to 4 is implemented.

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