Technical and economic integrated greenhouse gas satellite product index design method

Abstract

The invention provides a technical and economic integrated greenhouse gas satellite product index design method, and belongs to the technical field of satellite remote sensing. The method comprises the following steps: taking a series of revisit periods and detection precision, and constructing a to-be-selected satellite product index combination; and for each pair of index combination, calculating the monthly precision of the satellite under the index. And for each pair of index combination, calculating the manufacturing cost of the satellite under the index. And drawing a three-dimensional diagram of the monthly precision and two indexes of the revisit period and the detection precision. On the basis of the drawing, the relationship among the revisit period, the detection precision and the satellite cost is drawn. On the basis of the drawing, a target monthly precision range and a target satellite cost range are drawn; according to an optimization method, an optimal index combination is searched in a double-target range, the lowest satellite cost and the highest monthly precision are realized, and a technical and economic integrated greenhouse gas satellite product index design scheme is obtained.

Description

Technical Field

[0001] The present invention belongs to the technical field of satellite remote sensing, and relates to a method for designing greenhouse gas satellite product indicators integrating technology and economy. Background Art

[0002] The application of greenhouse gas satellites uses monthly average concentration to evaluate the change of greenhouse gas concentration, which puts forward higher requirements for the monthly average concentration accuracy of satellites. This accuracy is determined by three factors, two satellite indicators (single detection accuracy indicator and satellite revisit period indicator) and the objective condition of weather. At the same time, these two satellite indicators also affect the manufacturing cost of satellites.

[0003] Therefore, in order to balance the application requirements and manufacturing cost of satellites, it is necessary to comprehensively consider the greenhouse gas satellite application indicators (monthly average accuracy) and product indicators (revisit period indicator, detection accuracy indicator). However, in the prior art, there is still a lack of a set of optimization methods for greenhouse gas satellite product indicators aiming at balancing the application requirements and manufacturing cost of satellites. Summary of the Invention

[0004] To solve the above technical problems, the present application provides a method for designing greenhouse gas satellite indicators integrating technology and economy, which can optimize the greenhouse gas satellite product indicators and effectively balance the greenhouse gas satellite application indicators (monthly average accuracy) and product indicators (revisit period indicator, detection accuracy indicator).

[0005] The present application provides a method for designing greenhouse gas satellite product indicators, including:

[0006] S1: Select a series of revisit period indicators and detection accuracy indicators, and construct multiple product indicator combinations, each of which is composed of a revisit period indicator and a detection accuracy indicator;

[0007] S2: For each product indicator combination, calculate the monthly average accuracy corresponding to the greenhouse gas satellite to obtain the corresponding relationship among the revisit period indicator, the detection accuracy indicator and the monthly average accuracy;

[0008] S3: For each product indicator combination, calculate the manufacturing cost corresponding to the greenhouse gas satellite to obtain the corresponding relationship among the revisit period indicator, the detection accuracy indicator and the manufacturing cost;

[0009] S4: Draw a three-dimensional graph of the two indicators of the revisit period indicator and the detection accuracy indicator and the monthly average accuracy;

[0010] S5: On the basis of the three-dimensional graph obtained in step S4, according to the corresponding relationship among the revisit period indicator, the detection accuracy indicator and the manufacturing cost obtained in step S3, add the manufacturing cost dimension and draw a four-dimensional graph;

[0011] S6: Based on the four-dimensional map obtained in step S5, define the target monthly average accuracy range and the target manufacturing cost range;

[0012] S7: Within the target monthly average accuracy range and the target manufacturing cost range, search for the product index combination.

[0013] According to the method provided by an embodiment of the present application, wherein step S2 includes:

[0014] S2.1: Based on the ground-based monitoring data of the ground-based observation points, obtain the satellite monitoring data under specific revisit periods and specific detection accuracy conditions through simulation;

[0015] S2.2: Calculate the monthly average value of the satellite monitoring data of the ground-based observation points;

[0016] S2.3: Calculate the monthly average value of the ground-based monitoring data of the ground-based observation points;

[0017] S2.4: Using the monthly average value of the ground-based monitoring data as the true value, calculate the accuracy of the monthly average value of the satellite monitoring data according to the mean absolute deviation.

[0018] According to the method provided by an embodiment of the present application, wherein step S2.1 includes:

[0019] S2.1.1: Obtain the column concentration data of a ground-based observation point for one year through the ground-based equipment of the ground-based observation point as the ground-based monitoring data;

[0020] S2.1.2: Eliminate the data affected by weather in the ground-based monitoring data;

[0021] S2.1.3: According to the revisit period index and the orbital information of the greenhouse gas satellite to be designed, simulate the satellite movement to obtain the moments when the satellite passes over the ground-based observation points within one year;

[0022] S2.1.4: Use the ground-based monitoring data to simulate the satellite monitoring data;

[0023] S2.1.5: According to the additional error rule, add the error caused by the detection accuracy index to the simulated satellite monitoring data;

[0024] S2.1.6: Obtain the satellite monitoring data under specific revisit periods and detection accuracy conditions simulated based on the ground-based monitoring data.

[0025] According to the method provided by an embodiment of the present application, wherein in step S2.1.1,

[0026] the monitoring frequency of the ground-based equipment is higher than the selected revisit period index in step S1;

[0027] The measurement object of the ground-based equipment is the concentration of greenhouse gas columns, which is consistent with that of the greenhouse gas satellite;

[0028] The ground-based equipment and the greenhouse gas satellite have the same measurement method, and passive optical imaging equipment is used.

[0029] According to the method provided by an embodiment of the present application, in step S2.1.2, the data affected by weather includes the corresponding data when the observation scene is covered by clouds or other opaque objects, or is polluted by aerosols or haze;

[0030] The rejection rule is: reject single spectra with an interferogram fluctuation amplitude greater than 5% during spectral acquisition.

[0031] According to the method provided by an embodiment of the present application, in step S2.1.5, the error addition rule is: according to the detection accuracy index of the satellite product, regard the ground-based monitoring data as the true value, and add the error caused by the satellite detection accuracy index to the ground-based monitoring data.

[0032] According to the method provided by an embodiment of the present application, step S3 includes:

[0033] S3.1: Calculate the number of satellites required to meet the revisit period index under the fixed orbital altitude and viewing angle conditions of the greenhouse gas satellite to be designed;

[0034] S3.2: Calculate the price of a single greenhouse gas satellite based on the detection accuracy index;

[0035] S3.3: Calculate the satellite manufacturing cost based on the number of satellites calculated in step S3.1 and the price of a single greenhouse gas satellite calculated in step 3.2.

[0036] According to the method provided by an embodiment of the present application, in step S4, the revisit period index is used as the x-axis, the detection accuracy index is used as the y-axis, and the monthly average accuracy is used as the z-axis.

[0037] The present application provides a computer-readable storage medium storing software instructions, and the software instructions, when executed, implement the above method.

[0038] The present application provides a system for executing the above method.

[0039] The beneficial effects of the present invention compared with the prior art are:

[0040] (1) The present invention discloses a method for designing the product indicators of a greenhouse gas satellite integrating technology and economy. This method comprehensively designs satellite indicators from two perspectives: business application requirements and manufacturing costs, and has greater application benefits and economic benefits;

[0041] (2) The present invention discloses a method for designing greenhouse gas satellite product indicators integrating technology and economy. Based on satellite simulation toolkit software and monitoring ground concentrations, a method for obtaining the quantitative relationship between greenhouse gas satellite application indicators (monthly average accuracy) and product indicators (revisit period indicator, detection accuracy indicator) is proposed;

[0042] (3) The present invention discloses a method for designing greenhouse gas satellite product indicators integrating technology and economy, and a method for obtaining the quantitative relationship between the manufacturing cost of greenhouse gas satellites and product indicators (revisit period indicator, detection accuracy indicator) is proposed. Description of the Drawings

[0043] The above characteristics, technical features, advantages and their implementation manners of the present application will be further described below in a clear and understandable manner through the description of preferred embodiments and in combination with the drawings. The following drawings are only intended to illustrate and explain the present application schematically and do not limit the scope of the present application. Among them:

[0044] Figure 1 is the general flow chart of the present invention;

[0045] Figure 2 is the flow chart of the method for calculating the monthly average value of the satellite product of the present invention;

[0046] Figure 3 is the flow chart of the method for simulating satellite monitoring data through ground-based data of the present invention;

[0047] Figure 4 is the flow chart of the method for calculating the manufacturing cost of the satellite of the present invention;

[0048] Figure 5 is the schematic diagram of the satellite data volume under different revisit periods of the present invention. Detailed Embodiments

[0049] For a clearer understanding of the technical features, objectives and effects of the present application, the specific embodiments of the present application are now described with reference to the drawings.

[0050] As Figure 1 shown, the present invention provides a method for designing greenhouse gas satellite product indicators integrating technology and economy, including:

[0051] S1: Select a series of revisit period indicators and detection accuracy indicators to construct multiple product indicator combinations, and each product indicator combination consists of a revisit period indicator and a detection accuracy indicator.

[0052] First, a series of revisit period indicators and detection accuracy indicators are selected, for example, a series of revisit period indicators are [1 hour, 2 hours, 3 hours...168 hours], and a series of detection accuracy indicators are [1ppm, 2ppm, 3ppm...10ppm]. Then, the selected series of revisit period indicators and detection accuracy indicators are matched one by one to construct a series of product indicator combinations for selection.

[0053] S2: For each product indicator combination, calculate the monthly average accuracy of the greenhouse gas satellite corresponding to the product indicator combination, and obtain the corresponding relationship between the revisit period indicator, detection accuracy indicator and monthly average accuracy. Figure 2 As shown, step S2 specifically includes the following steps:

[0054] S2.1: Based on the ground-based monitoring data of ground-based observation points, the satellite monitoring data under specific revisit period and detection accuracy conditions are obtained through simulation, such as Figure 3 As shown, step S2.1 specifically includes:

[0055] S2.1.1: Obtain the column concentration data of the ground-based observation point for one year through the ground-based equipment at the ground-based observation point as the ground-based monitoring data. There are three requirements for the ground-based equipment: (1) The monitoring frequency is higher than the optional revisit period indicator selected in step S1; (2) The measurement object is the greenhouse gas column concentration, not the surface concentration, to be consistent with the measurement object of the greenhouse gas satellite. (3) Consistent with the measurement method of the greenhouse gas satellite, passive optical imaging equipment is used to ensure that the quality of the monitoring data is consistent with the impact of weather;

[0056] S2.1.2: Eliminate bad data from ground-based monitoring data, such as low-quality data affected by weather, including when the observation scene is covered by clouds or other opaque objects, or is severely polluted by aerosols or haze. Specific elimination rules include: eliminate single spectra with an interference pattern fluctuation amplitude greater than 5% during spectrum acquisition;

[0057] S2.1.3: Based on the revisit period index and the orbit information of the greenhouse gas satellite to be designed, the satellite motion is simulated by the Satellite Simulation Toolkit (STK) to obtain the time when the satellite passes the ground-based observation point within one year;

[0058] S2.1.4: Use ground-based monitoring data to simulate satellite monitoring data: Perform temporal and spatial matching of satellite monitoring data and ground-based monitoring data, extract satellite transit data from ground-based monitoring data as column concentration data detected when the satellite transits;

[0059] S2.1.5: According to the error addition rule, add the error caused by the detection accuracy index to the simulated satellite monitoring data;

[0060] The rules for adding errors are as follows: According to the detection accuracy index of satellite products, the ground-based monitoring data is regarded as the true value, and the error caused by the satellite detection accuracy index is added to the ground-based monitoring data. By adding random errors between [-detection accuracy index, +detection accuracy index] to the ground-based monitoring data, satellite monitoring data with different detection accuracy indexes is simulated.

[0061] S2.1.6: After the above 5 steps, satellite monitoring data under specific revisit periods and detection accuracy conditions simulated based on ground-based monitoring data is obtained. Figure 5 The data volume of satellites with different revisit periods is exemplified.

[0062] S2.2: Calculate the monthly average value of the satellite monitoring data at the ground-based observation points;

[0063] S2.3: Calculate the monthly average value of the ground-based monitoring data at the ground-based observation points;

[0064] S2.4: Taking the monthly average value of the ground-based monitoring data as the true value, calculate the accuracy of the monthly average value of the satellite monitoring data according to the mean absolute deviation.

[0065]

[0066] Where:

[0067] MAE - Mean Absolute Error, ppb;

[0068] n - The data volume of the satellite monitoring data, pieces;

[0069] S i ——The i-th satellite monitoring data, ppb;

[0070] G i ——The i-th ground-based monitoring data, ppb;

[0071] S3: For each product index combination, calculate the manufacturing cost corresponding to the greenhouse gas satellite under this product index combination, and obtain the corresponding relationship among the revisit period index, detection accuracy index, and manufacturing cost; as Figure 4 shown, this step S3 specifically includes the following steps:

[0072] S3.1: Under the fixed orbital altitude and viewing angle conditions of the greenhouse gas satellite to be designed, calculate the number of satellites required to achieve this revisit period index.

[0073]

[0074] N = 40075 / W / T (3)

[0075] Where:

[0076] W — The ground width when the satellite faces directly forward, km;

[0077] R — The average radius of the Earth, usually taken as 6371.004 km.

[0078] H — The satellite orbit altitude, km;

[0079] FOV — The field of view angle, °;

[0080] N — The number of satellites, unit;

[0081] T — The revisit period index, days;

[0082] S3.2: Calculate the price of a single greenhouse gas satellite based on the detection accuracy index.

[0083] P = E·t ew ·(w p +w L )+E·t es (4)

[0084] In the formula:

[0085] P — The manufacturing price of a single satellite, yuan;

[0086] E — The satellite detection accuracy index, ppb;

[0087] t ew — The weight of the satellite per unit accuracy, kg / ppb;

[0088] w p — The manufacturing price of the satellite per unit weight, yuan / kg;

[0089] w L — The launch price of the satellite per unit weight, yuan / kg;

[0090] t es — The ground data processing system price of the satellite per unit accuracy, yuan / kg;

[0091] t ew 、w p 、w L 、t es The coefficients are determined by the companies providing each service (satellite manufacturing, launch, data processing companies). For example, a certain greenhouse gas satellite supplier quotes that for a detection accuracy index of 15 ppb, the corresponding satellite weight is 300 kg, the manufacturing unit price is 300,000 yuan / kg, the launch unit price is 200,000 yuan / kg, and the data processing price is 200,000 yuan / kg.

[0092] S3.3: Calculate the satellite manufacturing cost based on the number of satellites calculated in step S3.1 and the price of a single greenhouse gas satellite calculated in step 3.2.

[0093] S4: Plot a three-dimensional graph of the two metrics, namely the revisit period metric and the detection accuracy metric, against the monthly average accuracy;

[0094] Based on the corresponding relationships among the revisit period metric, the detection accuracy metric, and the monthly average accuracy obtained in step S2, plot a three-dimensional graph of the revisit period metric and the detection accuracy metric against the monthly average accuracy. Use the revisit period metric as the x-axis, the detection accuracy metric as the y-axis, and the monthly average accuracy as the z-axis.

[0095] S5: On the basis of the three-dimensional graph obtained in step S4, according to the corresponding relationships among the revisit period metric, the detection accuracy metric, and the manufacturing cost obtained in step S3, add the manufacturing cost dimension and plot a four-dimensional graph;

[0096] S6: On the basis of the four-dimensional graph obtained in step S5, define the target monthly average accuracy range and the target manufacturing cost range;

[0097] S7: Using an optimization method, within the target monthly average accuracy range and the target manufacturing cost range, with the goal of minimizing the manufacturing cost and maximizing the monthly average accuracy, find the optimal product metric combination.

[0098] Although the present invention has been disclosed above with preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications to the technical solution of the present invention using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes, and decorations made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention all fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for designing greenhouse gas satellite product indicators, comprising: S1: Select a series of revisit period indicators and detection accuracy indicators, and construct multiple product indicator combinations, where each product indicator combination consists of a revisit period indicator and a detection accuracy indicator; S2: For each product indicator combination, calculate the monthly average accuracy corresponding to the greenhouse gas satellite to obtain the corresponding relationship among the revisit period indicator, the detection accuracy indicator, and the monthly average accuracy; S3: For each product indicator combination, calculate the manufacturing cost corresponding to the greenhouse gas satellite to obtain the corresponding relationship among the revisit period indicator, the detection accuracy indicator, and the manufacturing cost; S4: Draw a three-dimensional graph of the two indicators of the revisit period indicator and the detection accuracy indicator against the monthly average accuracy; S5: Based on the three-dimensional graph obtained in step S4, according to the corresponding relationship among the revisit period indicator, the detection accuracy indicator, and the manufacturing cost obtained in step S3, add the manufacturing cost dimension and draw a four-dimensional graph; S6: Based on the four-dimensional graph obtained in step S5, limit the target monthly average accuracy range and the target manufacturing cost range; S7: Within the target monthly average accuracy range and the target manufacturing cost range, search for product indicator combinations.

2. The method according to claim 1, wherein Step S2 includes: S2.1: Based on the ground-based monitoring data of the ground-based observation points, simulate the satellite monitoring data under specific revisit period and specific detection accuracy conditions; S2.2: Calculate the monthly average value of the satellite monitoring data of the ground-based observation points; S2.3: Calculate the monthly average value of the ground-based monitoring data of the ground-based observation points; S2.4: Using the monthly average value of the ground-based monitoring data as the true value, calculate the accuracy of the monthly average value of the satellite monitoring data according to the mean absolute deviation.

3. The method according to claim 2, wherein, Step S2.1 includes: S2.1.1: Obtain the column concentration data of a ground-based observation point for one year through the ground-based equipment of the ground-based observation point as the ground-based monitoring data; S2.1.2: Eliminate the data affected by weather in the ground-based monitoring data; S2.1.3: According to the revisit period indicator and the orbital information of the greenhouse gas satellite to be designed, simulate the satellite movement to obtain the moments when the satellite passes over the ground-based observation points within one year; S2.1.4: Simulate the satellite monitoring data using the ground-based monitoring data; S2.1.5: According to the additional error rule, add the error caused by the detection accuracy indicator to the simulated satellite monitoring data; S2.1.6: Obtain the satellite monitoring data under specific revisit period and detection accuracy conditions simulated based on the ground-based monitoring data.

4. The method according to claim 3, wherein, In step S2.1.1, the monitoring frequency of the ground-based equipment is higher than the selectable revisit period indicators selected in step S1; the measurement object of the ground-based equipment is the greenhouse gas column concentration, which is consistent with the measurement object of the greenhouse gas satellite; the measurement method of the ground-based equipment is the same as that of the greenhouse gas satellite, using passive optical imaging equipment.

5. The method according to claim 3, wherein, In step S2.1.2, the data affected by weather includes the corresponding data when the observation scene is covered by clouds or other opaque objects, or is contaminated by aerosols or haze; The elimination rule is: Eliminate the single spectral line with an interference pattern fluctuation amplitude greater than 5% during the spectral acquisition period.

6. The method according to claim 3, wherein, In step S2.1.5, the added error rule is as follows: according to the detection accuracy index of the satellite product, the ground-based monitoring data is regarded as the true value, and the error caused by the satellite detection accuracy index is added to the ground-based monitoring data.

7. The method according to claim 1, wherein, Step S3 includes: S3.1: Calculate the number of satellites required to meet the revisit period index under the fixed orbital altitude and viewing angle conditions of the greenhouse gas satellite to be designed; S3.2: Calculate the price of a single greenhouse gas satellite based on the detection accuracy index; S3.3: Calculate the satellite manufacturing cost based on the number of satellites calculated in step S3.1 and the price of a single greenhouse gas satellite calculated in step 3.

2.

8. The method according to claim 1, wherein In step S4, the revisit period index is used as the x-axis, the detection accuracy index is used as the y-axis, and the monthly average accuracy is used as the z-axis.

9. A computer-readable storage medium storing software instructions, which when executed implement the method according to any one of claims 1-8.

10. A system for executing the method according to any one of claims 1-8.

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