Satellite data optimization method, system and processing system based on two-stage decision
By adopting a satellite data optimization method based on two-stage decision-making, the problem of low efficiency in screening optical remote sensing satellite data is solved, achieving fast and accurate data screening, reducing labor costs and redundancy, and improving the economic benefits of data delivery.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHANGGUANG SATELLITE TECH CO LTD
- Filing Date
- 2025-07-08
- Publication Date
- 2026-07-21
AI Technical Summary
In existing technologies, the screening process for optical remote sensing satellite data relies on manual operation, which is inefficient and cannot select the optimal data. This results in high errors in manual map selection and serious data delivery redundancy, which directly harms the economic benefits of suppliers, especially when selecting maps for large areas.
A satellite data optimization method based on two-stage decision-making is adopted. By obtaining the intersection of the vector union of the map range and the standard scene of the satellite to be selected, the contribution area of a single scene is calculated, priority attributes are set, and global coverage and local optimality decisions are made to select the best satellite data.
While ensuring the coverage area remains unchanged, the system quickly filters out the data that best meets the criteria, reducing the area of data to be delivered, which greatly improves the efficiency of map selection and reduces the cost of manual screening.
Smart Images
Figure CN120808021B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of remote sensing satellite data processing technology, specifically to a satellite data optimization method, system, and processing system based on two-stage decision-making. Background Technology
[0002] With the surge in the number of optical remote sensing satellites and the exponential growth in satellite data volume, a vast amount of satellite data has accumulated for the same geographical area at different times due to the overlapping of collaborative observations by multiple satellite types and diverse imaging tasks. This data exhibits significant differences in key parameters such as resolution, imaging time, cloud cover, and quality level. Especially for large-area mapping scenarios, the data scale grows exponentially, leading to a sharp increase in manual screening costs. Satellite data optimization technology is therefore doubly necessary. Firstly, from the user's perspective, it must ensure that delivered data strictly meets quality requirements (e.g., imaging time within the last 3 months, cloud cover ≤10%) to avoid after-sales disputes caused by quality issues. Secondly, from the supplier's perspective, it must significantly reduce data production and delivery costs by removing redundant data (e.g., overlapping coverage areas).
[0003] Current methods for optimizing optical remote sensing satellite data require a comprehensive consideration of multiple parameters, including resolution, timeliness of capture, cloud cover, quality level, and side-swing angle, while also taking into account the final data coverage and delivery area. However, existing technologies suffer from the following core shortcomings: 1. Inefficient operation process: The screening process relies on manual execution of multi-condition combined queries. For large areas, parameters need to be adjusted repeatedly, which takes up to several hours. 2. Severe redundancy in delivery: Due to the lack of a spatial overlap optimization mechanism, data is often selected repeatedly, resulting in the actual delivered area often far exceeding the demand. This is especially true for large-area map selection, where manual map selection has high errors, directly damaging the economic benefits of satellite data providers.
[0004] In summary, existing technologies suffer from the technical problems of low efficiency in manual image selection and inability to select optimal data. Summary of the Invention
[0005] This invention solves the technical problems of low efficiency and inability to select optimal data by manually selecting images in existing technologies.
[0006] The satellite data optimization method based on two-stage decision-making described in this invention includes the following steps: Step 1: Obtain the union U1 of the vectors of the selected area on the map, calculate the intersection of the union U1 and all the standard scenes of the satellites to be selected, and obtain the coverage area; Step 2: Based on the coverage area, obtain the single-scene contribution area of each satellite standard scene to be selected; Step 3: Construct pre-computed vectors and store the patch shapes where the coverage area intersects with the standard scene of each satellite to be selected; Step 4: Set the priority of satellite standard scene attributes, and based on the priority, concatenate the satellite standard scene attributes into the sort value field of the pre-calculated vector. Then, attach the single scene contribution area and the sort value field of the pre-calculated vector of each satellite standard scene to be selected to the attribute table of the corresponding satellite standard scene. Step 5: Sort the satellite standard scenes to be selected in the pre-calculated vector using the sorting value field of the pre-calculated vector, and use the first-stage global coverage decision to obtain the minimum global coverage standard scene set. Step 6: Based on the single-scene contribution area of each candidate satellite standard scene, sort the candidate satellite standard scenes in the minimum global coverage standard scene set in descending order, and use the second-stage local optimal decision to obtain the optimal satellite data.
[0007] Furthermore, in this embodiment of the invention, step 2, which involves obtaining the single-scene contribution area of each selected satellite standard scene based on coverage, specifically involves: The shape of the patch intersecting the coverage area with each candidate satellite standard scene is calculated. Based on the shape of the patch intersecting the coverage area with each candidate satellite standard scene, the single scene contribution area of each candidate satellite standard scene is obtained.
[0008] Furthermore, in this embodiment of the invention, the satellite standard scene attributes in step 4 include resolution, shooting time, cloud cover, quality level, single scene contribution area, and side tilt angle.
[0009] Furthermore, in this embodiment of the invention, the first-stage global coverage decision in step 5 specifically includes: Construct the shape of the merged patch and the shape of the patch before merging. Based on the shape of the merged patch and the shape of the patch before merging, perform calculations to determine whether to retain the satellite standard scene to be selected. The retained satellite standard scene to be selected is used as the minimum global coverage standard scene set.
[0010] Furthermore, in this embodiment of the invention, the determination of whether to retain the standard view of the satellite to be selected specifically involves: For each satellite standard scene to be selected in the pre-calculated vector, determine whether the area difference between the merged patch shape and the patch shape before merging is greater than 0 after merging. If yes, retain the corresponding satellite standard scene to be selected; otherwise, discard the corresponding satellite standard scene to be selected. The judgment ends when the termination condition is met.
[0011] Furthermore, in this embodiment of the invention, the termination of the judgment after the termination condition is met specifically means: The decision ends when the area of the merged patch shape is the same as the area of the coverage area, or after traversing all the satellite standard scenes to be selected in the pre-calculated vector.
[0012] Furthermore, in this embodiment of the invention, the second-stage local optimal decision in step 6 specifically includes: Traverse the candidate satellite standard scenes in the minimum global coverage standard scene set, perform calculations based on the candidate satellite standard scenes in the minimum global coverage standard scene set, determine whether the candidate satellite standard scene is a mandatory scene, and take the candidate satellite standard scene corresponding to the mandatory scene as the optimal satellite data.
[0013] Furthermore, in this embodiment of the invention, the determination of whether the satellite standard view to be selected is a mandatory view specifically involves: Obtain the union U2 of other candidate satellite standard scenes that intersect with the candidate satellite standard scene in the minimum global coverage standard scene set. Calculate the union U2 and the union U3 of the corresponding candidate satellite standard scene in the minimum global coverage standard scene set. Obtain the area difference between the union U3 and the union U2. Set a single scene contribution area threshold. Determine whether the area difference between the union U3 and the union U2 is greater than the single scene contribution area threshold. If it is, the corresponding candidate satellite standard scene is a mandatory scene. If not, the corresponding candidate satellite standard scene is a redundant scene. The judgment ends when all candidate satellite standard scenes in the minimum global coverage standard scene set have been traversed.
[0014] The present invention discloses a satellite data optimization system based on two-stage decision-making. The system is implemented using the aforementioned satellite data optimization method based on two-stage decision-making and includes the following modules: The preparation module obtains the union U1 of the vectors of the selected map range, calculates the intersection of the union U1 and all the satellite standard scenes to be selected to obtain the coverage range, and based on the coverage range, obtains the single scene contribution area of each satellite standard scene to be selected, constructs a pre-calculated vector, stores the shape of the patch that intersects the coverage range with each satellite standard scene to be selected, sets the priority of the satellite standard scene attributes, concatenates the satellite standard scene attributes into the sort value field of the pre-calculated vector based on the priority, and attaches the single scene contribution area of each satellite standard scene to be selected and the sort value field of the pre-calculated vector to the attribute table of the corresponding satellite standard scene to be selected. The first-stage decision module uses the sorting value field of the pre-calculated vector to sort the satellite standard scenes to be selected in the pre-calculated vector, and adopts the first-stage global coverage decision to obtain the minimum global coverage standard scene set; The second-stage decision module sorts the candidate satellite standard scenes in the minimum global coverage standard scene set in descending order based on the single scene contribution area of each candidate satellite standard scene, and uses the second-stage local optimal decision to obtain the optimal satellite data.
[0015] The interactive processing system described in this invention specifically includes: After starting the system and loading and setting the system parameters, execute any of the satellite data optimization methods based on two-stage decision-making described above to achieve satellite data optimization.
[0016] This invention solves the technical problems of low efficiency and inability to select optimal data through manual image selection in existing technologies. Specific beneficial effects include: This invention provides a satellite data optimization method based on a two-stage decision-making process. It obtains the selected map range vector and the satellite standard scenes to be selected. Based on the single-scene contribution area of each satellite standard scene and the ranking value field of the pre-calculated vector formed by concatenating the satellite standard scene attributes according to priority, the satellite standard scenes to be selected are sorted twice. A first-stage global coverage decision and a second-stage local optimal decision are employed to obtain the optimal satellite data. This invention not only ensures that the most suitable data is quickly selected from the already selected data while maintaining the same coverage area, but also ensures that the area of the delivered data is minimized while meeting the conditions, greatly improving the map selection efficiency for users and data processing personnel. Attached Figure Description
[0017] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a satellite data optimization method based on two-stage decision-making, as described in Implementation Method 1. Figure 2 This is a preferred example diagram of satellite data as described in Implementation Method 1; Figure 3 This is an example diagram of an interactive processing system as described in Implementation Method 10. Detailed Implementation
[0018] Various embodiments of the present invention will now be clearly and completely described with reference to the accompanying drawings. The embodiments described with reference to the drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.
[0019] Implementation Method 1. A satellite data optimization method based on two-stage decision-making, comprising the following steps: Step 1: Obtain the union U1 of the vectors of the selected area on the map, calculate the intersection of the union U1 and all the standard scenes of the satellites to be selected, and obtain the coverage area; Step 2: Based on the coverage area, obtain the single-scene contribution area of each satellite standard scene to be selected; Step 3: Construct pre-computed vectors and store the patch shapes where the coverage area intersects with the standard scene of each satellite to be selected; Step 4: Set the priority of satellite standard scene attributes, and based on the priority, concatenate the satellite standard scene attributes into the sort value field of the pre-calculated vector. Then, attach the single scene contribution area and the sort value field of the pre-calculated vector of each satellite standard scene to be selected to the attribute table of the corresponding satellite standard scene. Step 5: Sort the satellite standard scenes to be selected in the pre-calculated vector using the sorting value field of the pre-calculated vector, and use the first-stage global coverage decision to obtain the minimum global coverage standard scene set. Step 6: Based on the single-scene contribution area of each candidate satellite standard scene, sort the candidate satellite standard scenes in the minimum global coverage standard scene set in descending order, and use the second-stage local optimal decision to obtain the optimal satellite data.
[0020] Existing technologies suffer from the technical problems of low efficiency in manual image selection and inability to select the optimal data.
[0021] To address the aforementioned technical problems, this embodiment provides a satellite data optimization method based on a two-stage decision-making process, such as... Figure 1 As shown, the specific steps include: Step 1: Obtain the union U1 of the vectors of the selected area on the map, calculate the intersection of the union U1 and all the standard scenes of the satellites to be selected, and obtain the coverage area; Step 2: Based on the coverage area, obtain the single-scene contribution area of each satellite standard scene to be selected; Step 3: Construct pre-computed vectors and store the patch shapes where the coverage area intersects with the standard scene of each satellite to be selected; Step 4: Set the priority of satellite standard scene attributes, and based on the priority, concatenate the satellite standard scene attributes into the sort value field of the pre-calculated vector. Then, attach the single scene contribution area and the sort value field of the pre-calculated vector of each satellite standard scene to be selected to the attribute table of the corresponding satellite standard scene. Step 5: Sort the satellite standard scenes to be selected in the pre-calculated vector using the sorting value field of the pre-calculated vector, and use the first-stage global coverage decision to obtain the minimum global coverage standard scene set. Phase 1: Sort all satellite standard scene data to be selected in the pre-computed vector (pre_result) according to the sort value field (sortKey) of the pre-computed vector, and use the first phase of global coverage decision to obtain the minimum global coverage standard scene set; Step 6: Based on the single-scene contribution area of each candidate satellite standard scene, sort the candidate satellite standard scenes in the minimum global coverage standard scene set in descending order, and use the second-stage local optimal decision to obtain the optimal satellite data. The second stage: Sort all remaining scene data in descending order of interArea contribution for each candidate satellite standard scene, and use the second stage local optimum decision to obtain the optimal satellite data, such as... Figure 2 As shown; Therefore, this implementation method obtains the selected range vector of the map and the standard scenes of the satellites to be selected, attaches the single scene contribution area of each standard scene to be selected, and the sorting value field of the pre-calculated vector formed by splicing the attributes of the standard scenes based on priority to the attribute table of the corresponding standard scene to be selected, sorts the standard scenes to be selected twice, and adopts the first stage global coverage decision and the second stage local optimal decision to obtain the optimal satellite data. This solves the technical problems of low efficiency of manual map selection and inability to select the optimal data in the prior art.
[0022] Implementation Method 2. This implementation method further defines the satellite data optimization method based on two-stage decision-making described in Implementation Method 1. In step 2, based on coverage area, the single-scene contribution area of each candidate satellite standard scene is obtained, specifically as follows: The shape of the patch intersecting the coverage area with each candidate satellite standard scene is calculated. Based on the shape of the patch intersecting the coverage area with each candidate satellite standard scene, the single scene contribution area of each candidate satellite standard scene is obtained.
[0023] In this implementation, the geometry of the patch that intersects with the coverage area A of each satellite standard scene to be selected is obtained and assigned to pre_result. At the same time, the area of the patch shape is calculated, which is the single-scene contribution area of the standard scene.
[0024] Implementation Method 3. This implementation method is a further limitation of the satellite data optimization method based on two-stage decision-making described in Implementation Method 2. The satellite standard scene attributes in step 4 include resolution, shooting time, cloud cover, quality level, single scene contribution area, and side tilt angle.
[0025] Implementation Method 4. This implementation method further defines the satellite data optimization method based on two-stage decision-making described in Implementation Method 1. The first stage global coverage decision in step 5 specifically includes: Construct the shape of the merged patch and the shape of the patch before merging. Based on the shape of the merged patch and the shape of the patch before merging, perform calculations and determine whether the area difference between the shape of the merged patch and the shape of the patch before merging is greater than 0 for each satellite standard scene to be selected in the pre-calculated vector after merging. If it is, retain the corresponding satellite standard scene to be selected; otherwise, discard the corresponding satellite standard scene to be selected. The judgment ends when the termination condition is met, and the retained satellite standard scenes to be selected are taken as the minimum global coverage standard scene set.
[0026] The process of ending the judgment after the termination condition is met is specifically as follows: The decision ends when the area of the merged patch shape is the same as the area of the coverage area, or after traversing all the satellite standard scenes to be selected in the pre-calculated vector.
[0027] The first stage of global coverage decision-making involves establishing two empty geometries, unionGeom and unionGeomBefore. Each candidate satellite standard scene in pre_result is sequentially traversed, and each is first merged into unionGeom. The area difference (diffArea1) between unionGeom and unionGeomBefore is calculated. If the area increases, the candidate satellite standard scene is retained, and unionGeomBefore is updated to unionGeom. Otherwise, the candidate satellite standard scene is discarded. The decision-making process stops when the area of unionGeom is the same as the area of coverage area A, or after traversing all candidate satellite standard scenes, thus obtaining the minimum global coverage standard scene set that can completely cover area A.
[0028] Implementation Method 5. This implementation method further defines the satellite data optimization method based on two-stage decision-making described in Implementation Method 1. The second-stage local optimal decision-making in step 6 specifically refers to: Traverse the candidate satellite standard scenes in the minimum global coverage standard scene set, perform calculations based on the candidate satellite standard scenes in the minimum global coverage standard scene set, determine whether the candidate satellite standard scene is a mandatory scene, and take the candidate satellite standard scene corresponding to the mandatory scene as the optimal satellite data.
[0029] The determination of whether the satellite standard view to be selected is a mandatory view specifically involves: Obtain the union U2 of other candidate satellite standard scenes that intersect with the candidate satellite standard scene in the minimum global coverage standard scene set. Calculate the union U2 and the union U3 of the corresponding candidate satellite standard scene in the minimum global coverage standard scene set. Obtain the area difference between the union U3 and the union U2. Set a single scene contribution area threshold. Determine whether the area difference between the union U3 and the union U2 is greater than the single scene contribution area threshold. If it is, the corresponding candidate satellite standard scene is a mandatory scene. If not, the corresponding candidate satellite standard scene is a redundant scene. The judgment ends when all candidate satellite standard scenes in the minimum global coverage standard scene set have been traversed.
[0030] The second stage involves local optimal decision-making: Following the sorting results from the second stage, each scene (curFeature) is traversed sequentially. The union of all scenes intersecting with this scene (U2, excluding the standard satellite scene to be selected) is obtained. The union of U2 and curFeature (U3) is then calculated. The area difference (diffArea2) between U3 and U2 is calculated. If diffArea2 is greater than the user-set single-scene contribution area threshold, removing this scene would result in incomplete coverage, making it a mandatory scene. If diffArea2 is less than or equal to the single-scene contribution area threshold, this scene is redundant and is deleted before continuing to the next scene. After traversing all scenes, the selected scene is saved to the vector result, and the scene number of the retained scene is saved to a txt file, thus completing the decision-making process.
[0031] In summary, this embodiment provides a satellite data optimization method based on a two-stage decision-making process. The first stage, global coverage decision-making, filters out all satellite data that perfectly covers the target area and meets the most suitable conditions. The second stage, local optimal decision-making, extracts the optimal subset of data from the selected data. This embodiment can eliminate redundant errors from manual screening while ensuring full coverage of the target area. Through the two-stage collaborative decision-making mechanism, the time required for screening large-area data is reduced from hours to seconds, and the area of delivered data is minimized.
[0032] Implementation Method Six. This implementation method provides a satellite data optimization system based on a two-stage decision-making process. The system employs the satellite data optimization method based on a two-stage decision-making process described in Implementation Method One, and includes the following modules: The preparation module obtains the union U1 of the vectors of the selected map range, calculates the intersection of the union U1 and all the satellite standard scenes to be selected to obtain the coverage range, and based on the coverage range, obtains the single scene contribution area of each satellite standard scene to be selected, constructs a pre-calculated vector, stores the shape of the patch that intersects the coverage range with each satellite standard scene to be selected, sets the priority of the satellite standard scene attributes, concatenates the satellite standard scene attributes into the sort value field of the pre-calculated vector based on the priority, and attaches the single scene contribution area of each satellite standard scene to be selected and the sort value field of the pre-calculated vector to the attribute table of the corresponding satellite standard scene to be selected. The first-stage decision module uses the sorting value field of the pre-calculated vector to sort the satellite standard scenes to be selected in the pre-calculated vector, and adopts the first-stage global coverage decision to obtain the minimum global coverage standard scene set; The second-stage decision module sorts the candidate satellite standard scenes in the minimum global coverage standard scene set in descending order based on the single scene contribution area of each candidate satellite standard scene, and uses the second-stage local optimal decision to obtain the optimal satellite data.
[0033] Implementation Method Seven. The interactive processing system described in this implementation method is specifically as follows: After starting the system and loading and setting the system parameters, the satellite data optimization method based on two-stage decision-making described in any one of embodiments one to five is executed to achieve satellite data optimization.
[0034] The overall functional flow of this implementation method is as follows: Start the quick map selection system platform, load the vector of the selected single-scene product, load the vector of the selected map range, load the excluded scene txt (optional), set the priority order of resolution, shooting time, cloud cover, quality level, single-scene contribution area, and side angle, and set the single-scene contribution area threshold, such as... Figure 3 As shown, the system is used to implement a satellite data optimization method based on two-stage decision-making as described in any one of embodiments one to five, to obtain the optimal satellite data scene number, thereby achieving the goal of optimizing the data.
[0035] The above provides a detailed description of the satellite data optimization method, system, and processing system based on two-stage decision-making proposed in this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.
Claims
1. A satellite data optimization method based on two-stage decision-making, characterized in that, Includes the following steps: Step 1: Obtain the union U1 of the vectors of the selected area on the map, calculate the intersection of the union U1 and all the standard scenes of the satellites to be selected, and obtain the coverage area; Step 2: Based on the coverage area, obtain the single-scene contribution area for each selected satellite standard scene, specifically as follows: Calculate the shape of the patch where the coverage area intersects with each candidate satellite standard scene. Based on the shape of the patch where the coverage area intersects with each candidate satellite standard scene, obtain the single scene contribution area of each candidate satellite standard scene. Step 3: Construct pre-computed vectors and store the patch shapes where the coverage area intersects with the standard scene of each satellite to be selected; Step 4: Set the priority of satellite standard scene attributes, and based on the priority, concatenate the satellite standard scene attributes into the sort value field of the pre-calculated vector. Then, attach the single scene contribution area and the sort value field of the pre-calculated vector of each satellite standard scene to be selected to the attribute table of the corresponding satellite standard scene. Step 5: Sort the satellite standard scenes to be selected in the pre-calculated vector using the sorting value field of the pre-calculated vector, and use the first-stage global coverage decision to obtain the minimum global coverage standard scene set. Step 6: Based on the single-scene contribution area of each candidate satellite standard scene, sort the candidate satellite standard scenes in the minimum global coverage standard scene set in descending order, and use the second-stage local optimal decision to obtain the optimal satellite data. The second-stage local optimal decision-making process is specifically as follows: Traverse the candidate satellite standard scenes in the minimum global coverage standard scene set, perform calculations based on the candidate satellite standard scenes in the minimum global coverage standard scene set, determine whether the candidate satellite standard scenes are mandatory scenes, and take the candidate satellite standard scenes corresponding to the mandatory scenes as the optimal satellite data. The determination of whether the satellite standard view to be selected is a mandatory view specifically involves: Obtain the union U2 of other candidate satellite standard scenes that intersect with the candidate satellite standard scene in the minimum global coverage standard scene set. Calculate the union U2 and the union U3 of the corresponding candidate satellite standard scene in the minimum global coverage standard scene set. Obtain the area difference between the union U3 and the union U2. Set a single scene contribution area threshold. Determine whether the area difference between the union U3 and the union U2 is greater than the single scene contribution area threshold. If it is, the corresponding candidate satellite standard scene is a mandatory scene. If not, the corresponding candidate satellite standard scene is a redundant scene. The judgment ends when all candidate satellite standard scenes in the minimum global coverage standard scene set have been traversed.
2. The satellite data optimization method based on two-stage decision-making according to claim 1, characterized in that, The satellite standard scene attributes in step 4 include resolution, shooting time, cloud cover, quality level, single scene contribution area, and side tilt angle.
3. The satellite data optimization method based on two-stage decision-making according to claim 1, characterized in that, The first stage of global coverage decision-making in step 5 is specifically as follows: Construct the shape of the merged patch and the shape of the patch before merging. Based on the shape of the merged patch and the shape of the patch before merging, perform calculations to determine whether to retain the satellite standard scene to be selected. The retained satellite standard scene to be selected is used as the minimum global coverage standard scene set.
4. The satellite data optimization method based on two-stage decision-making according to claim 3, characterized in that, The determination of whether to retain the standard view of the satellite to be selected is specifically as follows: For each satellite standard scene to be selected in the pre-calculated vector, determine whether the area difference between the merged patch shape and the patch shape before merging is greater than 0 after merging. If yes, retain the corresponding satellite standard scene to be selected; otherwise, discard the corresponding satellite standard scene to be selected. The judgment ends when the termination condition is met.
5. The satellite data optimization method based on two-stage decision-making according to claim 4, characterized in that, The process of ending the judgment after the termination condition is met is specifically as follows: The decision ends when the area of the merged patch shape is the same as the area of the coverage area, or after traversing all the satellite standard scenes to be selected in the pre-calculated vector.
6. A satellite data optimization system based on two-stage decision-making, wherein the system is implemented using the satellite data optimization method based on two-stage decision-making as described in claim 1, characterized in that, Includes the following modules: The preparation module obtains the union U1 of the vectors of the selected map range, calculates the intersection of the union U1 and all the satellite standard scenes to be selected to obtain the coverage range, and based on the coverage range, obtains the single scene contribution area of each satellite standard scene to be selected, constructs a pre-calculated vector, stores the shape of the patch that intersects the coverage range with each satellite standard scene to be selected, sets the priority of the satellite standard scene attributes, concatenates the satellite standard scene attributes into the sort value field of the pre-calculated vector based on the priority, and attaches the single scene contribution area of each satellite standard scene to be selected and the sort value field of the pre-calculated vector to the attribute table of the corresponding satellite standard scene to be selected. The first-stage decision module uses the sorting value field of the pre-calculated vector to sort the satellite standard scenes to be selected in the pre-calculated vector, and adopts the first-stage global coverage decision to obtain the minimum global coverage standard scene set; The second-stage decision module sorts the candidate satellite standard scenes in the minimum global coverage standard scene set in descending order based on the single scene contribution area of each candidate satellite standard scene, and uses the second-stage local optimal decision to obtain the optimal satellite data.
7. An interactive processing system, characterized in that, Specifically: After starting the system and loading and setting the system parameters, the satellite data optimization method based on two-stage decision-making as described in any one of claims 1-5 is executed to achieve satellite data optimization.