A method, system and application for interpolating reflected radiance data

Abstract

The application discloses a kind of reflected radiation data interpolation method, system and application, it is related to meteorological field, a kind of reflected radiation data interpolation method, comprising the following steps: obtaining observed radiation data and meteorological data;To incident shortwave radiation data is carried out instrument difference correction;Calculate clear sky index;To reflected shortwave radiation data, instrument difference correction after incident shortwave radiation data and meteorological data outlier rejection;To missing incident shortwave radiation data interpolation;To missing reflected shortwave radiation data interpolation;To reflected shortwave radiation data interpolation result system evaluation.The application provides a kind of reflected radiation data processing method with outlier rejection mechanism, adaptive interpolation capacity and system evaluation function, can systematically solve the problem of exception and missing in observation data, improve the accuracy of interpolation result, data integrity and reliability, provide solid data foundation for subsequent carbon flux calculation, ecological model simulation and remote sensing inversion etc.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of meteorology, in particular to a reflected radiation data interpolation method, system and application. BACKGROUND

[0002] In the study of ecosystem energy and material exchange, radiation data (including incident radiation and reflected radiation) as an important basis for estimating the surface energy budget and the photosynthetic utilization efficiency of vegetation, has wide application value in the fields of ecological monitoring, weather forecasting and carbon flux model. With the popularization of flux observation system (such as eddy correlation technology), it is possible to obtain high time resolution radiation and meteorological data, but due to instrument failure, weather interference, human operation or data transmission problems, there are often a large number of missing values and outliers in the observation data.

[0003] In the prior art, linear interpolation, average value replacement, regression model or machine learning algorithm are usually used to fill in the missing radiation data. However, when these methods face the strong seasonal variation and nonlinear dynamic characteristics of radiation data, it is often difficult to ensure the physical reasonableness and continuity of the interpolation results, especially in the case of short-time strong change (such as cloudy to sunny), which is more likely to cause interpolation error or result distortion.

[0004] In addition, some methods fail to fully combine the coupling relationship between meteorological factors (such as temperature, relative humidity, VPD, etc.) and radiation characteristics, thereby limiting the adaptability of the interpolation model to environmental changes. At the same time, for the processing of reflected radiation data, most studies rely on static empirical ratio or fixed regression coefficient, lack of adaptive adjustment mechanism based on sliding window, and it is difficult to ensure the interpolation accuracy while evaluating the data uncertainty.

[0005] Therefore, there is an urgent need for a reflected radiation data processing method with an outlier rejection mechanism, adaptive interpolation capability and system evaluation function, which can systematically solve the problems of outliers and missing values in observation data, improve data integrity and reliability, and provide a solid data foundation for subsequent carbon and water flux calculation, ecological model simulation and remote sensing inversion applications. SUMMARY

[0006] In order to solve the above problems, the present application provides a reflected radiation data interpolation method, system and application, which aims to systematically solve the problems of outliers and missing values in observation data and improve data integrity and reliability.

[0007] To achieve the above purpose, the technical scheme adopted by the present application is as follows:

[0008] A reflected radiation data interpolation method, comprising the following steps:

[0009] S1, obtain observed incident shortwave radiation data SRin and reflected shortwave radiation data SRout, meteorological data and local latitude and longitude information within a specified time period; wherein the observed incident shortwave radiation data SRin and reflected shortwave radiation data SRout within a specified time period include a plurality of radiation data arranged in time stamp order, each radiation data corresponding to a collection time stamp; the meteorological data includes air temperature Tair or soil temperature Tsoil, saturated water vapor pressure difference VPD or relative humidity RH every half hour;

[0010] S2, correct the incident shortwave radiation data SRin for instrument error to obtain the instrument error corrected incident shortwave radiation data SRin_cal;

[0011] S3, calculate the clear sky index Kt based on the instrument error corrected incident shortwave radiation data SRin_cal, latitude and longitude information and day number;

[0012] S4, perform outlier rejection processing on the reflected shortwave radiation data SRout, the instrument error corrected incident shortwave radiation data SRin_cal and the meteorological data to obtain the outlier rejected radiation data and meteorological data;

[0013] S5, based on the outlier rejected incident shortwave radiation data SRin_cal and meteorological data, interpolate the missing incident shortwave radiation data to obtain the incident shortwave radiation data interpolation result SRin_fill;

[0014] S6, based on the outlier rejected reflected shortwave radiation data SRout, the incident shortwave radiation data interpolation result SRin_fill and the clear sky index Kt, interpolate the missing reflected shortwave radiation data to obtain the reflected shortwave radiation data interpolation result SRout_fill;

[0015] S7, perform system evaluation on the reflected shortwave radiation data interpolation result SRout_fill.

[0016] Further, the step S4 specifically comprises:

[0017] S41, eliminate data in the instrument error corrected incident shortwave radiation data SRin_cal that does not meet the preset threshold to obtain the initial incident shortwave radiation data; the preset threshold includes: incident shortwave radiation value ≥ 1200 W / m² or ≤ 0 W / m²;

[0018] S42, eliminate data in the reflected shortwave radiation data SRout that does not meet the preset threshold to obtain the initial reflected shortwave radiation data; the preset threshold includes: reflected shortwave radiation value ≤ 0 W / m², or reflected shortwave radiation value ≥ instrument error corrected incident shortwave radiation value SRin_cal corresponding to the time stamp;

[0019] S43, remove data in the meteorological data that does not meet the preset threshold value to obtain initial meteorological data; the preset threshold value includes: air temperature ≤-70℃, soil temperature ≥30℃ or ≤-15℃, relative humidity ≥100% or ≤0%, saturated water vapor pressure difference ≤0 hPa;

[0020] S44, using a sliding window to perform secondary outlier removal on the initial incident shortwave radiation data, the initial reflected shortwave radiation data and the initial meteorological data, the window size is 7 days, the moving step is 1 day, the n times standard deviation method is used in the window, to obtain flux data after outlier removal processing, the n value is dynamically adjusted according to the data type and the season.

[0021] Further, in the n times standard deviation method:

[0022] When processing the initial incident shortwave radiation data and the meteorological data, n=3;

[0023] When processing the initial reflected shortwave radiation data in the growth season, n=3;

[0024] When processing the initial reflected shortwave radiation data in the non-growth season, n=4.

[0025] Further, the step S5 specifically includes:

[0026] S51, align the incident shortwave radiation data SRin_cal and the meteorological data after outlier removal according to the time stamp, to generate an incident shortwave radiation data interpolation input file;

[0027] S52, using the sMDSGapFill method provided by the "REddyProc" program package in the programming software R, with the help of the meteorological data of the incident data interpolation input file, the missing incident radiation data is interpolated to generate an incident shortwave radiation data interpolation output file;

[0028] S53, arranging the incident shortwave radiation data interpolation output file, and extracting the incident shortwave radiation data interpolation result SRin_fill.

[0029] Further, the step S6 specifically includes:

[0030] S61, align the incident shortwave radiation data SRin_cal and the reflected shortwave radiation data SRout after outlier removal according to the time stamp, to generate a reflected shortwave radiation data interpolation input file;

[0031] S62, using an adaptive window estimation method to interpolate the reflected shortwave radiation data, including:

[0032] S621, calculating the albedo α of each time stampi =SRout / SRin_cal;

[0033] S622. Using a 3-day initial window size, filter data within the window whose difference between the clear sky index Kt and missing data is less than 0.1, and calculate α within the window that meets the filtering requirements. i The mean α s Standard deviation sd;

[0034] S623, using α s α s ±sd is multiplied by the corresponding SRin_cal of the missing value to generate the imputation result SRout_fill and confidence interval. The confidence interval includes SRout_Usd and SRout_Dsd, where SRout_Usd and SRout_Dsd are the upper and lower limits of the confidence interval with the standard deviation sd as the reference index, respectively.

[0035] S624. If there is no data in the window that meets the filtering requirements, expand the difference range in the filtering requirements by ±0.1 until valid data is found.

[0036] S625. If there is no valid data in the window, the window size will be increased by 1 day before or after the interpolation is successful. The maximum window size is 61 days.

[0037] S626. Mark the window size SRout_gap for the imputation data. For existing data, the value of SRout_gap is 0. For missing values, the value of SRout_gap is the window size corresponding to the imputation.

[0038] S627. Organize the above calculation results to obtain the reflection data interpolation results.

[0039] Furthermore, step S7 specifically includes:

[0040] S71. Determine data availability based on confidence intervals of interpolation results;

[0041] S72. Determine the quality level of the reflection data interpolation result based on the window size SRout_gap of the marked interpolation data. The smaller the window size SRout_gap of the marked interpolation data, the higher the quality, and vice versa.

[0042] A reflected radiation data interpolation system, comprising:

[0043] The data acquisition module is used to acquire incident shortwave radiation data SRin, reflected shortwave radiation data SRout, and meteorological data;

[0044] The data processing module is used to execute steps S2-S6 of any of the methods described above;

[0045] An evaluation module for performing step S7 of any of the above methods.

[0046] A computer-readable storage medium storing a computer program that, when executed by a processor, implements any of the above methods.

[0047] A computing device comprising a processor and a memory storing a computer program that, when executed by the processor, implements any of the above methods.

[0048] Compared with the prior art, the technical progress achieved by the present application is that the present application provides a reflected radiation data processing method with an outlier elimination mechanism, adaptive interpolation capability, and system evaluation function, which can systematically solve the problems of outliers and missing values in observation data, improve the accuracy of the interpolation results, and further improve the data integrity and reliability, thereby providing a solid data foundation for subsequent carbon flux calculation, ecological model simulation, remote sensing inversion, and other applications. BRIEF DESCRIPTION OF DRAWINGS

[0049] The accompanying drawings are included to provide a further understanding of the application, and constitute a part of the specification, illustrate the application, and are used to explain the application together with the embodiments of the application, and do not constitute a limitation on the application.

[0050] In the drawings:

[0051] Figure 1 A flowchart of the data processing method of the present application;

[0052] Figure 2 A framework diagram of the data processing method of the present application;

[0053] Figure 3 A comparison chart of the original data and the missing value interpolation results in the embodiment of the present application. DETAILED DESCRIPTION

[0054] The following specific embodiments can be combined with each other, and the same or similar concepts or processes can not be described again in some embodiments. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0055] Embodiment 1: A method for interpolating reflected radiation data, a data processing method flowchart as shown in Figure 1 , a data processing method framework as shown in Figure 2 , comprising the following steps:

[0056] S1, obtaining observed radiation data and meteorological data.

[0057] Obtain the radiation data, related meteorological data and latitude and longitude information observed by No. 1 flux tower in Liaoning Qingyuan Forest Ecosystem National Field Scientific Observation Station (hereinafter referred to as: Qingyuan Forest Station) in 2020; the radiation data includes: shortwave incident radiation data SRin and shortwave reflected radiation data SRout of No. 1 tower of Qingyuan Forest Station every half hour in 2020; the meteorological data includes: air temperature Tair or soil temperature Tsoil and saturated water vapor pressure difference VPD or relative humidity RH of No. 1 tower of Qingyuan Forest Station every half hour in 2020; the radiation data and meteorological data have the same time stamp corresponding to the data acquisition time.

[0058] S2, instrument difference correction is carried out on the shortwave incident radiation data SRin, and instrument difference corrected shortwave incident radiation data SRin_cal corresponding to each time stamp in 2020 is obtained.

[0059] The correction coefficient used in the instrument difference correction is:

[0060]

[0061] S3, the clear sky index Kt is calculated according to the instrument difference corrected incident shortwave radiation data SRin_cal, latitude and longitude information and day sequence number.

[0062] S4, the abnormal value elimination processing is carried out on the shortwave reflected radiation data SRout, the instrument difference corrected shortwave incident radiation data SRin_cal and the meteorological data, and the abnormal value eliminated radiation data and meteorological data corresponding to each time stamp in 2020 are obtained.

[0063] In the embodiment, the S4 specifically includes:

[0064] S41, the instrument difference corrected shortwave incident radiation data SRin_cal meeting any abnormal value condition in the radiation data in 2020 is eliminated, and the initial shortwave incident radiation data is obtained.

[0065] The abnormal value condition includes:

[0066] The instrument difference corrected shortwave incident radiation value in the radiation data is greater than 1200 W / m 2 .

[0067] The instrument difference corrected shortwave incident radiation value in the radiation data is less than 0 W / m 2 .

[0068] S42, the reflected radiation data SRout meeting any abnormal value condition in the radiation data in 2020 is eliminated, and the initial shortwave reflected radiation data is obtained.

[0069] The abnormal value condition includes:

[0070] The shortwave reflected radiation value in the radiation data is less than 0 W / m 2 ;

[0071] The shortwave reflected radiation value in the radiation data is less than the shortwave incident radiation after the difference correction when the time stamps are the same.

[0072] S43, remove the meteorological data meeting any of the abnormal value conditions from the meteorological data in 2020 to obtain initial meteorological data.

[0073] The abnormal value conditions include:

[0074] The air temperature value in the meteorological data is less than -70℃;

[0075] The soil temperature value in the meteorological data is greater than 30℃;

[0076] The soil temperature value in the meteorological data is less than -15℃;

[0077] The relative humidity value in the meteorological data is greater than 100%;

[0078] The relative humidity value in the meteorological data is less than 0%;

[0079] The difference value of the saturated water vapor pressure in the meteorological data is less than 0hPa;

[0080] S44, use a sliding window to remove abnormal values from the initial shortwave incident radiation, shortwave reflected radiation and meteorological data, use n times standard deviation method in the window, window size is 7 days, moving step is 1 day, to obtain flux data after abnormal value removal processing.

[0081] The n value is determined according to the geographical position and climate conditions of Qingyuan forest station, including:

[0082] When processing the initial incident shortwave radiation and meteorological data, n = 3;

[0083] When processing the initial reflected shortwave radiation in the growth season, n = 3;

[0084] When processing the initial reflected shortwave radiation in the non-growth season, n = 4.

[0085] S5, for the incident radiation result SRin_cal after removing abnormal values, with the meteorological data after removing abnormal values, the missing incident radiation data is interpolated to obtain the incident radiation data interpolation result.

[0086] In this embodiment, the S4 specifically includes:

[0087] S51, collate the shortwave incident data SRin_cal after removing outliers in S4 and the meteorological data according to the same principle of time stamp, to obtain an incident data interpolation input file.

[0088] S52, use the "REddyProc" program package in the programmed software R-4.4.2 to process the above-mentioned incident data interpolation input file, use the sMDSGapFill method, and interpolate the missing shortwave incident radiation data by means of the meteorological data in the shortwave incident data interpolation input file, to obtain a shortwave incident data interpolation output file.

[0089] S53, collate the shortwave incident data interpolation output file to obtain the shortwave incident data interpolation result SRin_fill.

[0090] S6, for the shortwave reflection data result after removing outliers, interpolate the missing shortwave reflection radiation data by means of the shortwave incident radiation data after removing outliers, to obtain a shortwave reflection radiation data interpolation result.

[0091] In the embodiment, the S6 specifically comprises:

[0092] S61, collate the shortwave incident data SRin_cal after removing outliers in S4 and the shortwave reflection data SRout according to the same principle of time stamp, to obtain a reflection data interpolation input file.

[0093] S62, use an adaptive window estimation method to interpolate the reflection data, and the S62 specifically comprises:

[0094] S621, calculate the ratio of SRout and SRin_cal corresponding to each time stamp in 2020, i.e. the albedo α i .

[0095] S622, the initial window size is 3 days (including the missing data, a total of 144 data), for each missing value of SRout retrieved in the window, and the data with a difference of 0.1 between the clear sky index Kt and the missing value in the window are screened, the mean value α i , the standard deviation sd of all α s satisfying the screening requirements in the window are calculated.

[0096] S623, respectively use α s , α s±sd respectively multiplied by the SRin_cal corresponding to the missing value, to generate the interpolation result SRout_fill and the confidence interval, the confidence interval includes SRout_Usd and SRout_Dsd, wherein SRout_Usd and SRout_Dsd are the upper limit and the lower limit of the confidence interval with the standard deviation sd as the reference index.

[0097] S624, if there is no data meeting the screening requirements in the initial window, the screening requirement is changed to the difference between the clear sky index Kt and the missing data being less than 0.2 (that is, the difference range is expanded by ±0.1), and if there is still no data meeting the screening requirements, the difference range continues to be expanded by ±0.1 until data meeting the screening requirements is retrieved.

[0098] S625, if SRout in the initial window is all missing values, the window size is expanded to 5 days (that is, each side is expanded by one day), and if it is still all missing values, each side continues to be expanded by one day until the interpolation is successful, and the maximum window size is 61 days.

[0099] S626, add SRout_gap, for existing data, the value of SRout_gap is 0, and for missing values, the value of SRout_gap is the window size corresponding to the interpolation.

[0100] S627, the above calculation results are arranged to obtain the interpolation result of the reflection data.

[0101] The original data and the interpolation result of the gap are compared as shown in the table. Figure 3

[0102] S7, system evaluation is performed on the interpolation result of the reflection data.

[0103] In the embodiment, the S7 specifically includes:

[0104] S71, SRout_Usd and SRout_Dsd are the upper limit and the lower limit of the confidence interval with the standard deviation sd as the reference index, and the usability of the interpolation result of the reflection data is judged by the confidence interval.

[0105] S72, the quality level of the interpolation result of the reflection data is judged according to SRout_gap, the smaller the SRout_gap, the higher the quality, and vice versa.

[0106] Embodiment 2: a method for interpolating reflection radiation data, comprising:

[0107] The data acquisition part is used to obtain the half-hour scale radiation data and meteorological data observed by the Qingyuan Forest Station No. 1 flux tower in 2020.

[0108] ​The data processing part performs outlier rejection and gap filling on the shortwave reflected radiation data of the No. 1 flux tower of Qingyuan Forest Station in 2020 by using the method of steps S2-S6.

[0109] The system evaluation part performs system evaluation on the shortwave reflected radiation data of the No. 1 flux tower of Qingyuan Forest Station in 2020 by using the method of step S7.

[0110] Embodiment 3: A computer-readable storage medium storing one or more programs including instructions that, when executed by a computing device, cause the computing device to perform the method of embodiment 1.

[0111] Embodiment 4: A computing device comprising:

[0112] one or more processors, memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for performing the method of embodiment 1.

[0113] Finally, it should be noted that: the above only for the preferred embodiments of the present application, and not for limiting the present application, although the present application is described in detail with reference to the foregoing embodiments, for those skilled in the art, it still can be modified to the technical solution recorded in the foregoing embodiments, or equivalent replacement of some technical features. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the scope of protection of the claims of the present application.

Claims

1. A method of interpolating reflected radiance data, the method comprising: The method comprises the following steps: S1, obtaining observed incident shortwave radiation data SRin and reflected shortwave radiation data SRout, meteorological data and local latitude and longitude information within a specified time period; wherein the observed incident shortwave radiation data SRin and reflected shortwave radiation data SRout within the specified time period include a plurality of radiation data arranged in chronological order, each radiation data corresponding to a collection timestamp; the meteorological data includes air temperature Tair or soil temperature Tsoil, saturated vapor pressure difference VPD or relative humidity RH every half hour; S2, performing instrument difference correction on the incident shortwave radiation data SRin to obtain instrument difference corrected incident shortwave radiation data SRin_cal; S3, calculating the clear sky index Kt based on the instrument difference corrected incident shortwave radiation data SRin_cal, latitude and longitude information and day sequence number; S4, performing outlier rejection processing on the reflected shortwave radiation data SRout, instrument difference corrected incident shortwave radiation data SRin_cal and meteorological data to obtain outlier rejected radiation data and meteorological data; S5, based on the outlier rejected incident shortwave radiation data SRin_cal and meteorological data, interpolating the missing incident shortwave radiation data to obtain incident shortwave radiation data interpolation result SRin_fill; S6, based on the outlier rejected reflected shortwave radiation data SRout, incident shortwave radiation data interpolation result SRin_fill and clear sky index Kt, interpolating the missing reflected shortwave radiation data to obtain reflected shortwave radiation data interpolation result SRout_fill; S7, performing system evaluation on the reflected shortwave radiation data interpolation result SRout_fill; The step S6 specifically comprises: S61, aligning the outlier rejected incident shortwave radiation data SRin_cal and reflected shortwave radiation data SRout by timestamp to generate reflected shortwave radiation data interpolation input file; S62, using an adaptive window estimation method to interpolate the reflected shortwave radiation data, comprising: S621, calculate the albedo a of each timestamp i = SRout / SRin cal; S622. Using a 3-day initial window size, filter data within the window whose difference between the clear sky index Kt and missing data is less than 0.1, and calculate α within the window that meets the filtering requirements. i The mean α s Standard deviation sd; S623、use α s , α s ±sd respectively multiplied by the missing value corresponding to SRin_cal, generate the interpolation result SRout_fill and the confidence interval, the confidence interval includes SRout_Usd and SRout_Dsd, wherein SRout_Usd and SRout_Dsd are the upper and lower limits of the confidence interval with the standard deviation sd as the reference index; S624, if there is no data in the window that meets the screening requirements, the difference range in the screening requirements is expanded by ±0.1 until valid data is found; S625, if there is no valid data in the window, expand 1 day before and after, until the interpolation is successful, and the maximum window size is 61 days; S626, mark the window size of the interpolated data SRout_gap, for the existing data, the value of SRout_gap is 0, and for the missing value, the value of SRout_gap is the window size corresponding to the interpolation; S627, collate the input data and the calculation results, specifically including the incident shortwave radiation data SRin cal and the reflected shortwave radiation data SRout after removing the abnormal values in the input file, the mean value α in S622 s , the standard deviation sd, the interpolation results SRout fill in S623 and the upper and lower limits of the confidence interval SRout_Usd, SRout_Dsd, and the interpolation mark SRout_gap in S626, to obtain the interpolation results of the reflected data.

2. The method of claim 1, wherein, The step S4 specifically comprises: S41, rejecting data in the instrument difference corrected incident shortwave radiation data SRin_cal that does not meet the preset threshold to obtain initial incident shortwave radiation data; the preset threshold includes: incident shortwave radiation value ≥1200 W / m² or ≤0 W / m²; S42, reject data in the reflected shortwave radiation data SRout that does not meet a preset threshold value, to obtain initial reflected shortwave radiation data; the preset threshold value includes: reflected shortwave radiation value ≤ 0 W / m², or reflected shortwave radiation value ≥ incident shortwave radiation value SRin_cal after instrument difference correction corresponding to the time stamp; S43, reject data in the meteorological data that does not meet a preset threshold value, to obtain initial meteorological data; the preset threshold value includes: air temperature ≤ -70℃, soil temperature ≥ 30℃ or ≤ -15℃, relative humidity ≥ 100% or ≤ 0%, saturated water vapor pressure difference ≤ 0hPa; S44, using a sliding window to perform secondary outlier rejection on the initial incident shortwave radiation data, the initial reflected shortwave radiation data and the initial meteorological data, the window size is 7 days, the moving step is 1 day, the n times standard deviation method is used in the window, to obtain flux data after outlier rejection processing, the n value is dynamically adjusted according to the data type and the season.

3. The method of claim 2, wherein, In the n times standard deviation method: When processing the initial incident shortwave radiation data and the initial meteorological data, n = 3; When processing the initial reflected shortwave radiation data in the growing season, n = 3; When processing the initial reflected shortwave radiation data in the non-growing season, n = 4.

4. The method of claim 1, wherein, The step S5 specifically includes: S51, align the incident shortwave radiation data SRin_cal and the meteorological data after outlier rejection according to the time stamp, to generate an incident shortwave radiation data interpolation input file; S52, using the sMDSGapFill method provided by the "REddyProc" program package in the programming software R, with the aid of the meteorological data of the incident data interpolation input file, to interpolate the missing incident radiation data, to generate an incident shortwave radiation data interpolation output file; S53, collate the incident shortwave radiation data interpolation output file, to extract the incident shortwave radiation data interpolation result SRin_fill.

5. The method of claim 1, wherein, The step S7 specifically includes: S71, judging data availability based on the confidence interval of the interpolation result; S72, judging the quality level of the reflected data interpolation result according to the window size SRout_gap of the marked interpolation data, the smaller the window size SRout_gap of the marked interpolation data, the higher the quality, and vice versa.

6. A system for interpolating reflected radiance data, characterized by It includes: A data acquisition module for acquiring incident shortwave radiation data SRin, reflected shortwave radiation data SRout and meteorological data; A data processing module for executing the steps S2-S6 of the method of any one of claims 1-5; An evaluation module for executing the step S7 of the method of any one of claims 1-5.

7. A computer readable storage medium characterized in that, A computer program is stored, and the program is executed by a processor to realize the method of any one of claims 1-5.

8. A computing device, comprising: It includes a processor and a memory, the memory stores a computer program, and the processor executes the program to realize the method of any one of claims 1-5.

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