Land observation satellite data distribution service efficiency evaluation method

Abstract

The invention discloses a land observation satellite data distribution service efficiency evaluation method. The method comprises the following steps: carrying out statistics to obtain a land observation satellite data distribution condition; performing data distribution service efficiency calculation factor analysis; and establishing a land observation satellite data distribution service efficiency evaluation model to obtain a land observation satellite data service efficiency value. According to the method, a land observation satellite operation service mode is combined, a data distribution service efficiency evaluation scheme based on land observation satellite data sharing characteristics is provided, and the accuracy of land observation satellite comprehensive service efficiency evaluation is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of land observation satellites, and in particular relates to a method for evaluating the performance of land observation satellite data distribution services. Background Art

[0002] Land observation satellites are widely used in many fields such as agriculture, forestry, water conservancy, land resources, urban planning, environmental protection, disaster monitoring and national defense construction, creating huge economic and social benefits.

[0003] The data obtained by land observation satellites during operation are used to complete data services through data distribution. The efficiency of data distribution services of land observation satellites is mainly reflected in the quantity, scope, and value of data distribution during the distribution process. With the continuous development of land observation satellite technology, the traditional data distribution service efficiency evaluation only focuses on the quantity and value of data distribution, without fully considering factors such as the payload type and distribution scope of different land observation satellites, resulting in the lack of targeted evaluation results of data distribution service efficiency.

[0004] How to correctly evaluate the distribution service efficiency of public welfare land observation satellite data has become an important part of the evaluation of satellite comprehensive application efficiency. Summary of the invention

[0005] The technology of the present invention solves the problem: overcomes the shortcomings of the prior art, provides a land observation satellite data distribution service efficiency evaluation method, combines the land observation satellite operation service mode, proposes a data distribution service efficiency evaluation scheme based on the land observation satellite data sharing characteristics, and improves the accuracy of the comprehensive service efficiency evaluation of the land observation satellite.

[0006] In order to solve the above technical problems, the present invention discloses a method for evaluating the effectiveness of land observation satellite data distribution services, comprising:

[0007] Statistics were obtained on the distribution of land observation satellite data;

[0008] Conduct factor analysis on data distribution service effectiveness calculation;

[0009] A land observation satellite data distribution service efficiency evaluation model is established to obtain the land observation satellite data service efficiency value.

[0010] In the above-mentioned land observation satellite data distribution service performance evaluation method, the land observation satellite data distribution situation is statistically obtained, including: the payload type, spatial resolution, distribution method, distribution object, distribution quantity, longitude and latitude information and cloud cover information of the land observation satellite during its on-orbit operation.

[0011] In the above-mentioned land observation satellite data distribution service performance evaluation method, the data distribution service performance calculation factors include: payload type, spatial resolution, distribution method, data availability, number of distribution objects, data distribution volume, single-view image area and data price.

[0012] In the above land observation satellite data distribution service performance evaluation method, data distribution service performance calculation factor analysis is performed, including:

[0013] Payload type analysis: Land observation satellite payload types are divided into six categories: visible light sensors, infrared sensors, microwave sensors, lidar sensors, hyperspectral sensors and other sensors;

[0014] Spatial resolution analysis: Spatial resolution refers to the size of the ground object represented by one pixel in land observation satellite data;

[0015] Distribution method analysis: Distribution method refers to the way in which land observation satellite data is provided to users, including: on-demand distribution method and full push method;

[0016] Data availability analysis: Data availability refers to the validity of land observation satellite data delivered to users; for data distributed on demand, the availability is 100%; for data pushed in full, data with cloud cover below 20% is available, and data with cloud cover above 80% is unavailable. The availability of data with cloud cover between 20% and 80% is calculated by weighted average according to the classification and quantity of cloud cover for a single scene;

[0017] Analysis of the number of distribution objects: The number of distribution objects refers to the number of users provided with land observation satellite data;

[0018] Data distribution volume analysis: Data distribution volume refers to the total amount of land observation satellite data provided to users. In the process of evaluating the performance of land observation satellite data distribution services, the amount of data actually used by users for business work is determined based on the distribution method and data distribution volume.

[0019] Single-view image area analysis: Single-view image area refers to the coverage area of ​​a single payload type of land observation satellite data provided to users;

[0020] Data price analysis: Data price refers to the unit price of land observation satellite data provided to users, which is differentiated according to different spatial resolutions and payload types.

[0021] In the above land observation satellite data distribution service performance evaluation method, the land observation satellite data distribution service performance evaluation model is expressed as follows:

[0022]

[0023] Where Q represents the land observation satellite data service efficiency value, M represents the distribution method, U represents the total number of distribution objects, N represents the total data distribution volume, i represents the payload type, j represents the spatial resolution type, and N represents the total data distribution volume. ij represents the distribution volume of the jth spatial resolution data of the ith load, K ij represents the availability of data of the jth spatial resolution for the ith load, U ij represents the number of distribution objects of the jth spatial resolution data of the i-th load, C ij represents the single image area of ​​the jth spatial resolution data of the ith load, P ij It represents the market price of the jth spatial resolution data of the ith load during the same period.

[0024] The present invention has the following advantages:

[0025] The present invention discloses a method for evaluating the performance of land observation satellite data distribution services. The method can realize accurate calculation of the performance of land observation satellite data distribution services based on different distribution modes and different payload types, and provide a basis for comprehensive performance evaluation of land observation satellites. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 The present invention is a flowchart of a method for evaluating the performance of a land observation satellite data distribution service in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments disclosed in the present invention will be further described in detail below with reference to the accompanying drawings.

[0028] As described in the background technology, land observation satellites can cover a large area in a short period of time to conduct earth observation and obtain valuable remote sensing data; they can conduct periodic observations of the same area regularly, which is conducive to monitoring changes in targets, which is particularly important for application scenarios that require rapid response (such as disaster monitoring); they are less restricted by ground conditions; the data obtained is comprehensive, and a large amount of agricultural, forestry, marine, land, environmental protection, meteorological and other data can be collected, which has broad application prospects in land resources, forest resources, geological and mineral resources, water resources, crop yield estimation, disaster prevention and mitigation, etc.

[0029] In recent years, with the rapid development of commercial aerospace, a large number of commercial and public welfare land observation satellites have been launched. The operation and management mode of public welfare land observation satellites is mainly based on public welfare services for primary users. A large amount of data is pushed to primary users through dedicated lines, and the primary users use the relevant data according to business needs. Therefore, the data distribution service efficiency of land observation satellites is difficult to calculate through the income from the sale of satellite data. It is urgent to establish a data distribution service efficiency evaluation method based on the characteristics of land observation satellites and data service conditions.

[0030] Reference Figure 1 In this embodiment, the land observation satellite data distribution service performance evaluation method includes:

[0031] Step 1: Statistically obtain the distribution of land observation satellite data.

[0032] In this embodiment, statistics on the distribution of land observation satellite data are obtained, mainly including: statistics on basic information such as payload type, spatial resolution, distribution method, distribution object, distribution quantity, longitude and latitude information, and cloud cover information during the land observation satellite's on-orbit operation.

[0033] Step 2: Conduct factor analysis on data distribution service efficiency calculation.

[0034] In this embodiment, the data distribution service efficiency calculation is closely related to the data distribution volume, and different distribution methods are used to complete the distribution in the data distribution service process. The distribution objects, coverage areas, market prices, etc. of satellites with different payloads and different resolutions all affect the overall satellite distribution service efficiency. The data distribution service efficiency calculation factors mainly include: payload type, spatial resolution, distribution method, data availability, number of distribution objects, data distribution volume, single-view image area, and data price.

[0035] (21) Load type analysis

[0036] Sensors can be classified in different ways according to different classification standards. For example, according to the working wavelength, they can be divided into visible light sensors, infrared sensors, microwave sensors, etc.; according to the working mode, they can be divided into active sensors and passive sensors; according to the data recording method, they can be divided into imaging sensors and non-imaging sensors; according to the band width and spectral continuity, they can be divided into hyperspectral sensors and conventional sensors.

[0037] Combined with the commonly used sensors carried by mainstream land observation satellites at home and abroad, the land observation satellite payload types are divided into 6 categories: visible light sensors, infrared sensors, microwave sensors, lidar sensors, hyperspectral sensors and other sensors, as shown in Table 1 below:

[0038]

[0039]

[0040] Table 1, Sensor classification example table

[0041] (22) Spatial resolution analysis

[0042] Spatial resolution refers to the size of the ground object represented by a pixel in land observation satellite data. The spatial resolution of current land observation satellites is quite diverse, ranging from better than 1 meter to several kilometers. The data distribution volume and data market price are related to the spatial resolution. In actual calculations, the resolution in the data distribution statistics is used for actual calculations.

[0043] (23) Distribution method analysis

[0044] The distribution method refers to the way in which land observation satellite data is provided to users. Data distribution service methods can be divided into two categories: one is the on-demand distribution method, which provides users with the required data, including online network distribution and offline distribution; the other is the full push method, which provides users with all the data obtained by land observation satellites and pushes them online.

[0045] (24) Data availability analysis

[0046] Generally, land observation satellite data will be subject to data quality inspection before being provided to users, and only data that meets the delivery standards will be distributed to users. The data availability referred to in the present invention refers to: the validity of land observation satellite data that has been delivered to users, usually referring to whether the delivered data meets the user's application requirements. Data availability is mainly related to the distribution method and data cloud coverage. Among them, for data distributed on demand, its availability is 100%. For data in all push methods, data with cloud cover (which can be obtained in the metadata file of the image) less than 20% (including 20%) is available data, data with cloud cover greater than 80% (including 80%) is unavailable data, and the availability of data with cloud cover between 20%-80% (excluding 20% ​​and 80%) is calculated by weighted average according to the classification and quantity of single-scene cloud cover.

[0047] The cloud cover is graded in 10% steps (i.e. 30%, 40%, ..., 70%) to standardize the data availability. The calculation formula is:

[0048]

[0049] Where p represents the number of cloud cover levels, q represents the number of cloud cover levels in a certain cloud cover level, and σ q represents the qth cloud cover value, N p represents the total distribution of the pth level, N q represents the data distribution of the qth cloud cover, K prepresents the data availability of the pth classification, q=1,2,3,...,10.

[0050] The comparison of cloud cover and data validity is shown in Table 2:

[0051]

[0052] Table 2. Comparison of cloud cover and data validity

[0053] (25) Analysis of the number of distribution objects

[0054] The number of distribution objects refers to the number of users provided with land observation satellite data. In the actual distribution process, users are authorized or distributed free of charge in accordance with the satellite data policy. The wider the scope and the greater the number of distribution objects, the higher the efficiency of the data distribution service.

[0055] (26) Data distribution analysis

[0056] Data distribution volume refers to the total amount of land observation satellite data provided to users. Data distribution volume is affected by payload type, spatial resolution, data policy, etc. In the process of evaluating the performance of land observation satellite data distribution services, the amount of data actually used by users for business work is determined based on the distribution method and data distribution volume.

[0057] For data shared in the full push distribution mode, the actual usage should take into account the data distribution volume and data availability; for data shared in the on-demand acquisition distribution mode, the data availability is calculated as 100%, so the actual usage is the amount of data actually obtained by the user.

[0058] (27) Single-view image area analysis

[0059] The single-view image area refers to the coverage area of ​​a single payload type of land observation satellite data provided to users. The single-view image area is related to the payload type, spatial resolution, length and width of the single-view image. The global coverage area of ​​the distributed data can be obtained through the single-view image area and actual usage. The larger the coverage area, the higher the data distribution service efficiency.

[0060] The calculation formula for the area of ​​a single scene image is:

[0061] C=l ij *w ij

[0062] Where C represents the area of ​​a single scene image, usually measured in square kilometers; l ij represents the length of the jth spatial resolution data of the i-th load, w ij Represents the width of the jth spatial resolution data of the i-th load.

[0063] (28) Data price analysis

[0064] Data price refers to the unit price of land observation satellite data provided to users, which is differentiated according to different spatial resolutions and payload types. It is generally calculated based on the image area. Usually, the unit price of high-resolution satellite data is higher. Under the same conditions, the higher the resolution, the higher the data distribution service efficiency.

[0065] Step 3: Establish a land observation satellite data distribution service performance evaluation model to obtain the land observation satellite data service performance value.

[0066] In this embodiment, combined with the data distribution service efficiency calculation factor analysis for different distribution methods and different payload types in step 2, it is determined that the calculation factors required for the land observation satellite data distribution service efficiency evaluation are 8: payload type (i), spatial resolution (j), distribution method (M), data availability (K), data distribution volume (N), number of distribution objects (U), single-view image area (C), and data price (P). The calculation factors of the data distribution service efficiency are obtained according to the determination method, calculation method and correlation of each factor. The effective use of the satellite is obtained by weighted calculation based on the data distribution volume, number of distribution objects and data availability of different satellite payloads, different resolutions and different distribution methods. The effective use, single-view image area and data price are used to calculate the data distribution service efficiency value of the satellite.

[0067] Preferably, the land observation satellite data distribution service performance evaluation model is expressed as follows:

[0068]

[0069] Where Q represents the land observation satellite data service efficiency value, M represents the distribution method, U represents the total number of distribution objects, N represents the total data distribution volume, i represents the payload type, j represents the spatial resolution type, and N represents the total data distribution volume. ij represents the distribution volume of the jth spatial resolution data of the ith load, K ij represents the availability of data of the jth spatial resolution for the ith load, U ij represents the number of distribution objects of the jth spatial resolution data of the i-th load, C ij represents the single image area of ​​the jth spatial resolution data of the ith load, P ij It represents the market price of the jth spatial resolution data of the ith load during the same period.

[0070] Although the present invention has been disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications to the technical solution of the present invention by using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope of the technical solution of the present invention.

[0071] The contents not described in detail in the specification of the present invention belong to the common knowledge of the professionals in this field.

Claims

1. A method for evaluating the performance of land observation satellite data distribution services, characterized in that: include: Statistics were obtained on the distribution of land observation satellite data; Conduct factor analysis on data distribution service effectiveness calculation; A land observation satellite data distribution service efficiency evaluation model is established to obtain the land observation satellite data service efficiency value.

2. The land observation satellite data distribution service performance evaluation method according to claim 1, characterized in that: The data distribution of land observation satellites is statistically obtained, including: the payload type, spatial resolution, distribution method, distribution object, distribution quantity, longitude and latitude information, and cloud cover information of land observation satellites during their on-orbit operation.

3. The land observation satellite data distribution service performance evaluation method according to claim 1, characterized in that: Data distribution service performance calculation factors include: payload type, spatial resolution, distribution method, data availability, number of distribution objects, data distribution volume, single-view image area and data price.

4. The land observation satellite data distribution service performance evaluation method according to claim 3, characterized in that: Conduct factor analysis on data distribution service performance calculation, including: Payload type analysis: Land observation satellite payload types are divided into six categories: visible light sensors, infrared sensors, microwave sensors, lidar sensors, hyperspectral sensors and other sensors; Spatial resolution analysis: Spatial resolution refers to the size of the ground object represented by one pixel in land observation satellite data; Distribution method analysis: Distribution method refers to the way in which land observation satellite data is provided to users, including: on-demand distribution method and full push method; Data availability analysis: Data availability refers to the validity of land observation satellite data delivered to users; for data distributed on demand, the availability is 100%; for data pushed in full, data with cloud cover below 20% is available, and data with cloud cover above 80% is unavailable. The availability of data with cloud cover between 20% and 80% is calculated by weighted average according to the classification and quantity of cloud cover for a single scene; Analysis of the number of distribution objects: The number of distribution objects refers to the number of users provided with land observation satellite data; Data distribution volume analysis: Data distribution volume refers to the total amount of land observation satellite data provided to users. In the process of evaluating the performance of land observation satellite data distribution services, the amount of data actually used by users for business work is determined based on the distribution method and data distribution volume. Single-view image area analysis: Single-view image area refers to the coverage area of ​​a single payload type of land observation satellite data provided to users; Data price analysis: Data price refers to the unit price of land observation satellite data provided to users, which is differentiated according to different spatial resolutions and payload types.

5. The land observation satellite data distribution service performance evaluation method according to claim 1, characterized in that: The land observation satellite data distribution service performance evaluation model is as follows: Where Q represents the land observation satellite data service efficiency value, M represents the distribution method, U represents the total number of distribution objects, N represents the total data distribution volume, i represents the payload type, j represents the spatial resolution type, and N represents the total data distribution volume. ij represents the distribution volume of the jth spatial resolution data of the ith load, K ij represents the availability of data of the jth spatial resolution for the ith load, U ij represents the number of distribution objects of the jth spatial resolution data of the i-th load, C ij represents the single image area of ​​the jth spatial resolution data of the ith load, P ij It represents the market price of the jth spatial resolution data of the ith load during the same period.

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