A data retrieval management system and method based on remote sensing data

Abstract

The invention discloses a data retrieval management system and method based on remote sensing data, belonging to the field of data remote sensing technology. The invention comprises the following steps: Step 1: select area, time range, cloud cover, and resolution data parameters as retrieval condition parameters, select the priority level of the condition for automatically screening data, and initiate a retrieval request; Step 2: the server receives the retrieval request, and screens according to the selected area, time range, cloud cover, and resolution parameters to obtain data set 1; Step 3: after the server performs preliminary screening, the data set 1 is automatically and preferentially searched for data that meets the requirements according to the priority level parameters set in step 1 to obtain data set 2; Step 4: optimize data set 2 and feed back the final result data set to the user; Step 5: the user performs a full coverage preview of the result data set, and performs multi-temporal screening and replacement of individual tiles to obtain data set 3.

Description

Technical Field

[0001] The present invention relates to the field of data remote sensing technology, and in particular to a data retrieval management system and method based on remote sensing data. Background Art

[0002] A tile refers to a map within a certain range that is cut into a number of rows and columns of square grid images according to a certain size and format, by zoom level or scale. The sliced ​​square grid images are figuratively called tiles.

[0003] With the development of remote sensing technology, more and more satellites are launched into space, and remote sensing image data is also increasing step by step. Faced with massive image data, how to quickly and accurately find and obtain images that meet the requirements has become one of the issues of concern in the field of spatial information science. Traditional image retrieval is based on scenes, and the parameters, attributes and time phases of the images require multiple retrievals and manual screening, which is cumbersome and inefficient. In the retrieval process, when the tile data is screened and processed, the screening accuracy is low due to different screening methods, which reduces the system retrieval efficiency. When multiple tiles are replaced, it is impossible to achieve efficient multi-temporal replacement of tile data, resulting in the replaced tile data not meeting the actual needs of users, reducing the use effect of the system. Summary of the invention

[0004] The purpose of the present invention is to provide a data retrieval management system and method based on remote sensing data to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a data retrieval management method based on remote sensing data, the method comprising the following steps:

[0006] Step 1: Select the area, time range, cloud cover, and resolution data parameters as the search condition parameters, select the priority level of the automatic data screening condition, and initiate a search request. When selecting an area, it supports manual drawing, inputting coordinates, selecting administrative districts, or users uploading kml and km files themselves. It also supports uploading compressed zip files with shp and prj. The system uses the vue+openLayers+geoserve+axios technology framework to present map tiles, vector data, and wms services to users.

[0007] Step 2: The server receives the search request and filters it according to the selected area, time range, cloud cover, and resolution parameters to obtain data set 1;

[0008] Step 3: After the server performs preliminary screening, it automatically searches for data that meets the requirements for data set 1 according to the priority parameters set in step 1 to obtain data set 2;

[0009] Step 4: Optimize data set 2 and provide the final result data set to the user;

[0010] Step 5: The user previews the full coverage of the result dataset and performs multi-temporal screening and replacement on individual tiles to obtain dataset 3;

[0011] Step 6: The user submits tile data set 3. When submitting the order, the user can choose to perform fine color grading, tile splicing, and automatic color grading services on the tiles. The background then automatically processes and confirms the submitted order.

[0012] Step 7: User downloads order data.

[0013] Furthermore, the specific method for optimizing the data set 2 in step 4 is:

[0014] 1) The comprehensive quality of each tile is calculated based on the resolution, side swing, full frame rate and cloud cover parameters in data set 2. The specific calculation method is as follows:

[0015] The coefficient of variation corresponding to the resolution, side swing, full amplitude and cloud amount parameters in data set 2 is calculated. The specific calculation formula is v j for:

[0016]

[0017] The comprehensive quality calculation formula of each tile is G i for:

[0018]

[0019] Among them, j = 1, 2, 3, 4, j = 1 means the selected parameter is resolution, j = 2 means the selected parameter is sway, j = 3 means the selected parameter is full amplitude, j = 4 means the selected parameter is cloud cover, v j represents the coefficient of variation of each parameter in the filtered data set, i=1,2,…,n represents the i-th tile selected in data set 2, r ij represents the j parameter of the i-th tile in dataset 2, It represents the average value of each tile j parameter in the filtered data set. It means to calculate the difference between the maximum and minimum values ​​of the j parameter in each tile in data set 2. By calculating the difference, we can observe the numerical change of the jth parameter. The coefficient of variation corresponding to the j parameter is calculated to determine the importance of the j parameter to the overall quality of the tile. The larger the value, the greater the degree to which the j parameter determines the overall quality of the tile. It is to solve the degree of variation of the parameters, so use (1-v j ) represents the weight coefficient of parameter j in the overall quality of the tile. Indicates the comprehensive quality value corresponding to the i-th tile;

[0020] 2) Sort the tile data of dataset 2 according to the tile comprehensive quality calculation results in 1), eliminate tile data with comprehensive quality lower than 20%, and sort according to the priority level of data comprehensive quality to ensure that the dataset returned to the user will place the best image at the front of the result list, saving the user's time in selecting tile data that meets the requirements and reducing the user's workload.

[0021] Furthermore, in step 5, when the user performs a full coverage preview of the result dataset, the map can be zoomed in and out. Through different zoom levels, the hierarchical effects corresponding to the archived tiles on the map can be viewed. The hierarchical effects include three resolution types: 20*20: fast loading and blurry, 200*200: smooth loading and clear, and 1000*1000: slow loading and ultra-clear. The specific algorithm for resolution is as follows:

[0022]

[0023] When the height ratio is greater than 50, the resolution is 1000*1000, when 9<height ratio<50, the resolution is 200*200, and when the height ratio is less than 9, the resolution is 20*20.

[0024] Furthermore, the specific method of performing multi-phase screening and replacement on individual tiles in step 5 is:

[0025] (1) Users can quickly sort the result datasets by time, cloud cover, measured swing, and full frame rate through the sorting button above the result dataset list, which is convenient for users to view and select. After the sorting is completed, the user selects a tile in the search result set, and the system returns the multi-temporal data list of the tile to the user. The list is displayed separately by year and month;

[0026] (2) The user checks the preview image, time, full frame rate, and cloud cover parameters of each tile in the multi-temporal list to decide whether to replace the tile selected in (1). The specific replacement method is:

[0027] The quality of each tile is calculated based on the time, full amplitude and cloud cover of each tile in the multi-temporal list. The specific calculation formula is M e for:

[0028]

[0029] Among them, e = 1, 2, 3, ..., represents the number corresponding to each tile in the multi-phase list, ae 、b e denote the full amplitude and cloud cover corresponding to the e-th tile in the multi-temporal list, t denotes the time corresponding to the tile selected in the result dataset, and t e Indicates the time corresponding to the e-th tile in the multi-phase list, Indicates that the inverse of the time difference is used as the coefficient for calculating the tile quality in the multi-temporal list, which is used to reduce the difference between the replaced tiles and the tile data in the result dataset due to the long time interval;

[0030] Compare the quality value of each tile with the comprehensive quality value of the tiles selected in the result dataset. If M e >G i , then the tiles selected in the result data set are replaced with tiles in the corresponding multi-phase list. When there are multiple tiles in the multi-phase list with higher quality values ​​than the comprehensive quality of the tiles selected in the result data, then the tiles selected in the result data set are replaced with tiles in the corresponding multiple multi-phase lists;

[0031] (3) After selection based on the method in (2), the selected tile is replaced with a tile in the multi-phase list that meets the requirements in (2) in the sorted result data set, or multiple phase images of a tile are selected for replacement at the same time. The multi-phase replacement or multiple selection provided by the system can provide users with a flexible image acquisition method. Users can freely select one or more phase tile data of any time period and put them into the data set according to their needs.

[0032] Furthermore, the fine color uniformity, tile splicing, and automatic color uniformity processing of tiles in step 6 are all manual operations.

[0033] A data retrieval management system based on remote sensing data, the system includes a tile data screening module, an optimization processing module, a tile multi-phase replacement module and a user order submission processing module;

[0034] The tile data screening module is used to initiate a search request according to the selected data parameters and the selected condition priority level, obtain a data set 2 based on the initiated search request, and transmit the obtained data set 2 to the optimization processing module;

[0035] The optimization processing module receives the data set 2 transmitted by the tile data screening module, calculates the comprehensive quality of each tile based on the resolution, side swing, full frame rate and cloud cover parameters, sorts the tile parameters based on the calculation results, removes tile data that does not meet the requirements, and after optimization processing, transmits the resulting data set to the tile multi-phase replacement module;

[0036] The tile multi-temporal replacement module receives the result data set transmitted by the optimization processing module, and the user performs a full coverage preview of the result data set. The user decides whether to perform multi-temporal screening and replacement on individual tiles based on the preview image, time, full frame rate, and cloud cover parameters of each tile in the multi-temporal list to obtain data set 3, and transmits the obtained data set 3 to the user order submission processing module;

[0037] The user order submission processing module receives the data set 3 transmitted by the tile multi-phase replacement module, and the user submits the tile data set 3. When submitting the order, the user can choose to perform fine color matching, tile splicing, and automatic color matching services on the tiles. The background then automatically processes and confirms the submitted order, and the user downloads the order data after background processing.

[0038] Further, the tile data screening module includes a retrieval request unit, a tile data preliminary screening unit and a priority ranking unit;

[0039] The retrieval request unit selects a priority level of a condition for filtering data based on the selected area, time range, cloud cover, and resolution data parameters as retrieval condition parameters, initiates a retrieval request, transmits the selected retrieval condition parameters to the tile data preliminary screening unit, and transmits the selected priority level of the condition to the priority ranking unit;

[0040] The tile data preliminary screening unit receives the selected search condition parameters transmitted by the search request unit, performs preliminary screening on the tile data according to the selected area, time range, cloud cover, and resolution parameters to obtain a data set 1, and transmits the obtained data set 1 to the priority sorting unit;

[0041] The priority sorting unit receives the selected condition priority transmitted by the retrieval request unit and the data set 1 transmitted by the tile data preliminary screening unit, automatically and preferentially searches for data that meets the requirements for the data set 1 according to the selected condition priority parameters, obtains the data set 2, and transmits the obtained data set 2 to the optimization processing module.

[0042] Furthermore, the optimization processing module includes a tile comprehensive quality calculation unit and a tile data elimination unit;

[0043] The tile comprehensive quality calculation unit receives the data set 2 transmitted by the priority sorting unit, calculates the coefficient of variation corresponding to the resolution, sway, full amplitude and cloud amount parameters in the data set 2, calculates the weight coefficient corresponding to the resolution, sway, full amplitude and cloud amount parameters in the data set 2 based on the coefficient of variation, calculates the comprehensive quality of each tile based on the weight coefficient corresponding to each parameter and the parameter corresponding to each tile in the data set 2, and transmits the comprehensive quality value corresponding to each tile to the tile data elimination unit, sorts the data according to the priority level of the comprehensive quality, ensures that the data set returned to the user arranges the best image at the front of the result list, saves the user's time in selecting tile data that meets the requirements, and reduces the user's workload;

[0044] The tile data elimination unit receives the comprehensive quality value corresponding to each tile transmitted by the tile comprehensive quality calculation unit, sorts the tile data of data set 2 according to the tile comprehensive quality calculation result, eliminates the tile data with a comprehensive quality lower than 20%, obtains a result data set, and transmits the obtained result data set to the tile multi-phase replacement module.

[0045] Further, the tile multi-temporal phase replacement module includes a tile data coverage preview unit, a screening and judgment unit, and a multi-temporal phase screening unit;

[0046] The tile data coverage preview unit quickly sorts the result data set according to time, cloud cover, measured swing, and full frame rate through the sorting button above the result data set list. After the sorting is completed, the user selects a tile in the search result set, and then the system returns the multi-temporal data list of the tile to the user. The list is displayed separately by year and month, and the tile data selected by the user and the multi-temporal data list of the tile fed back by the system are transmitted to the screening and judgment unit;

[0047] The screening and judging unit receives the tile data transmitted by the tile data coverage preview unit and the multi-temporal data list of the tile fed back by the system, checks the preview image, time, full amplitude rate, and cloud amount parameters of each tile in the multi-temporal list to determine whether to replace the tile transmitted by the tile data coverage preview unit, uses the inverse of the time difference between the tile transmitted by the tile data coverage preview unit and the tile selected in the multi-temporal list as a coefficient, combines the full amplitude and the sum of the cloud amount corresponding to the tile selected in the multi-temporal list to calculate the quality of the tile selected in the multi-temporal list, and transmits the calculation result to the multi-temporal screening unit;

[0048] The multi-phase screening unit receives the calculation result transmitted by the screening judgment unit. If the quality value of the tile selected in the multi-phase list is greater than the comprehensive quality value of the tile selected in the result data set, the selected tile is replaced with one or more tiles that meet the requirements in the multi-phase list in the result data set after sorting, and data set 3 is obtained. The obtained data set 3 is transmitted to the user order submission processing module. The multi-phase replacement or multiple selection provided by the system can provide users with a flexible image acquisition method. Users can freely select one or more phase tile data of any time period into the data set according to their needs.

[0049] Furthermore, the user order submission processing module receives the data set 3 transmitted by the multi-phase screening unit, and the user submits the tile data set 3. When submitting the order, the user can choose to perform fine color matching, tile stitching, and automatic color matching services on the tiles. The background then automatically processes and confirms the submitted order, and the user downloads the order data after background processing. All operations involved in this process are manual operations.

[0050] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0051] 1. The present invention uses the selected area, time range, cloud cover, and resolution data parameters as search condition parameters to perform a preliminary screening of tile data to obtain data set 1, performs a secondary search on the tile data after the preliminary screening with the selected automatic screening data condition priority level to obtain data set 2, screens the tile data after the secondary screening again based on the comprehensive quality value of each tile to obtain a result data set, compares and screens the quality value of each tile in the multi-phase list corresponding to the tile selected in the result data set with the comprehensive quality value corresponding to the tile selected in the result data set to obtain data set 3. This process screens the tile data four times, which reduces the number of screening times compared to traditional operations, and the data set obtained after four screenings is the optimal data set required by the user, further improving the system's processing effect on tile data.

[0052] 2. The present invention calculates the coefficient of variation corresponding to the resolution, sway, full amplitude and cloud amount parameters in data set 2, calculates the weight coefficient corresponding to the resolution, sway, full amplitude and cloud amount parameters in data set 2 based on the coefficient of variation, and calculates the comprehensive quality of each tile based on the weight coefficient corresponding to each parameter and the parameters corresponding to each tile in data set 2. This process calculates the weight coefficient corresponding to various parameters through the coefficient of variation corresponding to various parameters, which is convenient for intuitively judging the importance of various parameters to the comprehensive quality of tiles, thereby ensuring that the solved comprehensive quality value is most in line with the actual situation, further improving the system retrieval efficiency, and sorting according to the priority level of the comprehensive quality of tile data, ensuring that the data set returned to the user will arrange the best image at the front of the result list, saving the user's time in selecting tile data that meets the requirements and reducing the user's workload.

[0053] 3. The present invention uses the inverse of the time difference between the tile transmitted by the tile data coverage preview unit and the tile selected in the multi-phase list as a coefficient, combines the full amplitude and cloud amount corresponding to the tile selected in the multi-phase list to calculate the quality of the tile selected in the multi-phase list, compares the quality value of the tile selected in the multi-phase list with the comprehensive quality value of the tile selected in the result data set, and replaces the tile selected in the sorted result data set with one or more tiles that meet the requirements in the multi-phase list according to the comparison result. The multi-phase replacement or multiple selection provided by the system can provide users with a flexible image acquisition method. Users can freely select one or more phase tile data of any time period into the data set according to their needs, which further improves the use effect of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0055] Figure 1 It is a workflow diagram of a data retrieval management system and method based on remote sensing data in the present invention;

[0056] Figure 2 The present invention is a schematic diagram of the working principle structure of a data retrieval management system and method based on remote sensing data. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] See also Figure 1 and Figure 2 The present invention provides a technical solution: a data retrieval management method based on remote sensing data, the method comprising the following steps:

[0059] Step 1: Select the area, time range, cloud cover, and resolution data parameters as the search condition parameters, select the priority level of the automatic data screening condition, and initiate a search request. When selecting an area, it supports manual drawing, inputting coordinates, selecting administrative districts, or users uploading kml and km files themselves. It also supports uploading compressed zip files with shp and prj. The system uses the vue+openLayers+geoserve+axios technology framework to present map tiles, vector data, and wms services to users.

[0060] Step 2: The server receives the search request and filters it according to the selected area, time range, cloud cover, and resolution parameters to obtain data set 1;

[0061] Step 3: After the server performs preliminary screening, it automatically searches for data that meets the requirements for data set 1 according to the priority parameters set in step 1 to obtain data set 2;

[0062] Step 4: Optimize data set 2 and feed back the final result data set to the user. The specific method for optimizing data set 2 is as follows:

[0063] 1) The comprehensive quality of each tile is calculated based on the resolution, side swing, full frame rate and cloud cover parameters in data set 2. The specific calculation method is as follows:

[0064] The coefficient of variation corresponding to the resolution, side swing, full amplitude and cloud amount parameters in data set 2 is calculated. The specific calculation formula is v j for:

[0065]

[0066] The comprehensive quality calculation formula of each tile is G i for:

[0067]

[0068] Among them, j = 1, 2, 3, 4, j = 1 means the selected parameter is resolution, j = 2 means the selected parameter is sway, j = 3 means the selected parameter is full amplitude, j = 4 means the selected parameter is cloud cover, v j represents the coefficient of variation of each parameter in the filtered data set, i=1,2,…,n represents the i-th tile selected in data set 2, r ijrepresents the j parameter of the i-th tile in dataset 2, It represents the average value of each tile j parameter in the filtered data set. It means to calculate the difference between the maximum and minimum values ​​of the j parameter in each tile in data set 2. By calculating the difference, we can observe the numerical change of the jth parameter. The coefficient of variation corresponding to the j parameter is calculated to determine the importance of the j parameter to the overall quality of the tile. The larger the value, the greater the degree to which the j parameter determines the overall quality of the tile. It is to solve the degree of variation of the parameters, so use (1-v j ) represents the weight coefficient of parameter j in the overall quality of the tile. Indicates the comprehensive quality value corresponding to the i-th tile;

[0069] 2) Sort the tile data of dataset 2 according to the tile comprehensive quality calculation results in 1), remove the tile data with comprehensive quality lower than 20%, and sort them according to the superior level of data comprehensive quality, so as to ensure that the dataset returned to the user places the best image at the front of the result list, saving the user time in selecting tile data that meets the requirements and reducing the user's workload;

[0070] Step 5: The user previews the result dataset in full coverage and performs multi-temporal screening and replacement on individual tiles to obtain dataset 3. When the user previews the result dataset in full coverage, the user can zoom in and out on the map. Through different zoom levels, the layer effects corresponding to the archived tiles on the map can be viewed. The layer effects include three resolution types: 20*20: fast loading and blurry, 200*200: smooth loading and clear, and 1000*1000: slow loading and ultra-clear. The specific resolution algorithm is as follows:

[0071]

[0072] When the height ratio is greater than 50, the resolution is 1000*1000, when 9<height ratio<50, the resolution is 200*200, when the height ratio is less than 9, the resolution is 20*20;

[0073] The specific method for multi-temporal screening and replacement of individual tiles is:

[0074] (1) Users can quickly sort the result datasets by time, cloud cover, measured swing, and full frame rate through the sorting button above the result dataset list, which is convenient for users to view and select. After the sorting is completed, the user selects a tile in the search result set, and the system returns the multi-temporal data list of the tile to the user. The list is displayed separately by year and month;

[0075] (2) The user checks the preview image, time, full frame rate, and cloud cover parameters of each tile in the multi-temporal list to decide whether to replace the tile selected in (1). The specific replacement method is:

[0076] The quality of each tile is calculated based on the time, full amplitude and cloud cover of each tile in the multi-temporal list. The specific calculation formula is M e for:

[0077]

[0078] Among them, e = 1, 2, 3, ..., represents the number corresponding to each tile in the multi-phase list, a e 、b e denote the full amplitude and cloud cover corresponding to the e-th tile in the multi-temporal list, t denotes the time corresponding to the tile selected in the result dataset, and t e Indicates the time corresponding to the e-th tile in the multi-phase list, Indicates that the inverse of the time difference is used as the coefficient for calculating the tile quality in the multi-temporal list, which is used to reduce the difference between the replaced tiles and the tile data in the result dataset due to the long time interval;

[0079] Compare the quality value of each tile with the comprehensive quality value of the tiles selected in the result dataset. If M e >G i , then the tiles selected in the result data set are replaced with tiles in the corresponding multi-phase list. When there are multiple tiles in the multi-phase list with higher quality values ​​than the comprehensive quality of the tiles selected in the result data, then the tiles selected in the result data set are replaced with tiles in the corresponding multiple multi-phase lists;

[0080] (3) After the selection is made based on the method in (2), the selected tile is replaced with a tile in the multi-phase list that meets the requirements in (2) in the sorted result data set, or multiple phase images of a tile are selected for replacement at the same time. The multi-phase replacement or multiple selection provided by the system can provide users with a flexible image acquisition method. Users can freely select one or more phase tile data of any time period to be put into the data set according to their own needs;

[0081] Step 6: The user submits tile data set 3. When submitting the order, the user can choose to perform fine color grading, tile splicing, and automatic color grading services on the tiles. The background then automatically processes and confirms the submitted order. Fine color grading, tile splicing, and automatic color grading on tiles are all manual operations.

[0082] Step 7: User downloads order data.

[0083] A data retrieval management system based on remote sensing data, the system includes a tile data screening module, an optimization processing module, a tile multi-phase replacement module and a user order submission processing module;

[0084] The tile data screening module is used to initiate a search request according to the selected data parameters and the selected condition priority level, obtain a data set 2 based on the initiated search request, and transmit the obtained data set 2 to the optimization processing module; the tile data screening module includes a search request unit, a tile data preliminary screening unit and a priority level sorting unit;

[0085] The retrieval request unit selects a priority level of a condition for filtering data based on the selected area, time range, cloud cover, and resolution data parameters as retrieval condition parameters, initiates a retrieval request, transmits the selected retrieval condition parameters to the tile data preliminary screening unit, and transmits the selected priority level of the condition to the priority ranking unit;

[0086] The tile data preliminary screening unit receives the selected search condition parameters transmitted by the search request unit, performs preliminary screening on the tile data according to the selected area, time range, cloud cover, and resolution parameters to obtain a data set 1, and transmits the obtained data set 1 to the priority sorting unit;

[0087] The priority sorting unit receives the selected condition priority transmitted by the retrieval request unit and the data set 1 transmitted by the tile data preliminary screening unit, automatically and preferentially searches for data that meets the requirements for the data set 1 according to the selected condition priority parameters, obtains the data set 2, and transmits the obtained data set 2 to the optimization processing module;

[0088] The optimization processing module receives the data set 2 transmitted by the tile data screening module, calculates the comprehensive quality of each tile based on the resolution, side swing, full frame rate and cloud cover parameters, sorts the tile parameters based on the calculation results, removes the tile data that does not meet the requirements, and after optimization processing, transmits the obtained result data set to the tile multi-phase replacement module; the optimization processing module includes a tile comprehensive quality calculation unit and a tile data removal unit;

[0089] The tile comprehensive quality calculation unit receives the data set 2 transmitted by the priority sorting unit, calculates the coefficient of variation corresponding to the resolution, sway, full amplitude and cloud amount parameters in the data set 2, calculates the weight coefficient corresponding to the resolution, sway, full amplitude and cloud amount parameters in the data set 2 based on the coefficient of variation, calculates the comprehensive quality of each tile based on the weight coefficient corresponding to each parameter and the parameter corresponding to each tile in the data set 2, and transmits the comprehensive quality value corresponding to each tile to the tile data elimination unit, sorts the data according to the priority level of the comprehensive quality, and ensures that the data set returned to the user arranges the best image at the front of the result list, saving the user's time in selecting tile data that meets the requirements and reducing the user's workload;

[0090] The tile data elimination unit receives the comprehensive quality value corresponding to each tile transmitted by the tile comprehensive quality calculation unit, sorts the tile data of data set 2 according to the tile comprehensive quality calculation result, eliminates the tile data with comprehensive quality lower than 20%, obtains the result data set, and transmits the obtained result data set to the tile multi-phase replacement module;

[0091] The tile multi-temporal replacement module receives the result data set transmitted by the optimization processing module, and the user performs a full coverage preview of the result data set. The user decides whether to perform multi-temporal screening and replacement on individual tiles based on the preview image, time, full frame rate, and cloud cover parameters of each tile in the multi-temporal list, and obtains data set 3, and transmits the obtained data set 3 to the user order submission processing module; the tile multi-temporal replacement module includes a tile data coverage preview unit, a screening judgment unit, and a multi-temporal screening unit;

[0092] The tile data coverage preview unit uses the sort button above the result data set list to quickly sort the result data set according to time, cloud cover, measured swing, and full frame rate. After the sorting is completed, the user selects a tile in the search result set, and then the system returns the multi-temporal data list of the tile to the user. The list is displayed separately by year and month, and the tile data selected by the user and the multi-temporal data list of the tile fed back by the system are transmitted to the screening and judgment unit;

[0093] The screening and judgment unit receives the tile data transmitted by the tile data coverage preview unit and the multi-temporal data list of the tile fed back by the system, checks the preview image, time, full amplitude rate, and cloud amount parameters of each tile in the multi-temporal list to determine whether to replace the tile transmitted by the tile data coverage preview unit, uses the inverse of the time difference between the tile transmitted by the tile data coverage preview unit and the tile selected in the multi-temporal list as a coefficient, combines the sum of the full amplitude and cloud amount corresponding to the tile selected in the multi-temporal list, and calculates the quality of the tile selected in the multi-temporal list, and transmits the calculation result to the multi-temporal screening unit;

[0094] The multi-phase screening unit receives the calculation result transmitted by the screening judgment unit. If the quality value of the tile selected in the multi-phase list is greater than the comprehensive quality value of the tile selected in the result data set, the selected tile is replaced with one or more tiles that meet the requirements in the multi-phase list in the result data set after sorting, and data set 3 is obtained. The obtained data set 3 is transmitted to the user order submission processing module. The multi-phase replacement or multiple selection provided by the system can provide users with a flexible image acquisition method. Users can freely select one or more phase tile data of any time period into the data set according to their needs;

[0095] The user order submission processing module is used to receive the data set 3 transmitted by the multi-temporal screening unit. The user submits the tile data set 3. When submitting the order, you can choose to perform fine color grading, tile splicing, and automatic color grading services on the tiles. The background then automatically processes and confirms the submitted order. The user downloads the order data processed by the background. All operations involved in this process are manual operations.

[0096] Embodiment 1: The specific steps of a data retrieval management method based on remote sensing data are as follows:

[0097] Step 1: The user selects the administrative region "Beijing" in the search conditions on the system search homepage, selects 1 month for the time, selects 0% to 20% for the cloud range, selects 0 to 25m for the resolution, selects cloud cover as the default data priority, and initiates the search;

[0098] Step 2: The server performs a preliminary search according to the search conditions and obtains the search data set 1

[0099] Step 3: Search and sort the dataset 1 again according to the cloud cover priority set by the user, and obtain the dataset 2 after sorting;

[0100] Step 4: Sort the data set 2 according to the comprehensive image quality parameters, remove the data with quality lower than 20%, and obtain the data set 3 which is returned to the front end;

[0101] Step 5: The user clicks a tile in the result list of dataset 3, selects another more suitable phase in the multi-phase list of the tile to replace it, and then selects multiple tiles in the result list of dataset 3, saves them as dataset 4, and clicks Get after the selection is completed;

[0102] Step 6: Pack the tile information in Dataset 4 into an order. The user can also select additional data processing services for this order, such as stitching, color balancing, etc., and submit the order;

[0103] Step 7: The backend processes data according to the order, submits finished product data, and updates the order status;

[0104] Step 8: User downloads order data.

[0105] Embodiment 2:

[0106] The side swing refers to the inclination of the satellite when shooting images. When the satellite shoots vertically, the side swing is 0°. The smaller the side swing, the better the image effect.

[0107] The full frame rate indicates the proportion of the effective part of the satellite image to the entire image. The higher the full frame rate, the more effective display parts of the image. The higher the full frame rate, the better the image quality.

[0108] The time phase indicates the time when the satellite image is taken. Multi-temporal images are images of the same area at different times. For multi-time series analysis and comparison, such as analyzing the changes before, during and after a fire, multi-temporal images of the area where the fire occurred before, during and after the disaster are required.

[0109] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0110] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A data retrieval management method based on remote sensing data, characterized in that: The method comprises the following steps: Step 1: Select the region, time range, cloud cover, and resolution data parameters as the search condition parameters, select the priority level of the automatic data screening condition, and initiate a search request; Step 2: The server receives the search request and filters it according to the selected area, time range, cloud cover, and resolution parameters to obtain data set 1; Step 3: After the server performs preliminary screening, it automatically searches for data that meets the requirements for data set 1 according to the priority parameters set in step 1 to obtain data set 2; Step 4: Optimize data set 2 and provide the final result data set to the user; Step 5: The user previews the full coverage of the result dataset and performs multi-temporal screening and replacement of individual tiles. The specific method is as follows: (1) Users can quickly sort the result datasets by time, cloud cover, measured swing, and full frame rate through the sorting button above the result dataset list, which is convenient for users to view and select. After the sorting is completed, the user selects a tile in the search result set, and the system returns the multi-temporal data list of the tile to the user. The list is displayed separately by year and month; (2) The user checks the preview image, time, full frame rate, and cloud cover parameters of each tile in the multi-temporal list to decide whether to replace the tile selected in (1). The specific replacement method is: The quality of each tile is calculated based on the time, full amplitude and cloud cover of each tile in the multi-temporal list. The specific calculation formula is M e for: Among them, e = 1, 2, 3, ..., represents the number corresponding to each tile in the multi-phase list, a e 、b e denote the full amplitude and cloud cover corresponding to the e-th tile in the multi-temporal list, t denotes the time corresponding to the tile selected in the result dataset, and t e Indicates the time corresponding to the e-th tile in the multi-phase list, Indicates that the inverse of the time difference is used as the coefficient for calculating the tile quality in the multi-temporal list, which is used to reduce the difference between the replaced tiles and the tile data in the result dataset due to the long time interval; Compare the quality value of each tile with the comprehensive quality value of the tiles selected in the result dataset. If M e >G i , then the tiles selected in the result data set are replaced with tiles in the corresponding multi-phase list. When there are multiple tiles in the multi-phase list with higher quality values ​​than the comprehensive quality of the tiles selected in the result data, then the tiles selected in the result data set are replaced with tiles in the corresponding multiple multi-phase lists; (3) After selection based on the method in (2), in the sorted result dataset, the selected tile is replaced with a tile in the multi-temporal list that meets the requirements in (2), or multiple temporal images of a tile are selected at the same time for replacement, thereby obtaining dataset 3; Step 6: The user submits tile data set 3. When submitting the order, the user can choose to perform fine color grading, tile splicing, and automatic color grading services on the tiles. The background then automatically processes and confirms the submitted order. Step 7: User downloads order data.

2. The data retrieval management method based on remote sensing data according to claim 1 is characterized in that: The specific method for optimizing the data set 2 in step 4 is: 1) The comprehensive quality of each tile is calculated based on the resolution, side swing, full frame rate and cloud cover parameters in data set 2. The specific calculation method is as follows: The coefficient of variation corresponding to the resolution, side swing, full amplitude and cloud amount parameters in data set 2 is calculated. The specific calculation formula is v j for: The comprehensive quality calculation formula of each tile is G i for: Among them, j = 1, 2, 3, 4, j = 1 means the selected parameter is resolution, j = 2 means the selected parameter is sway, j = 3 means the selected parameter is full amplitude, j = 4 means the selected parameter is cloud cover, v j represents the coefficient of variation of each parameter in the filtered data set, i=1,2,…,n represents the i-th tile selected in data set 2, r ij represents the j parameter of the i-th tile in dataset 2, r j It represents the average value of each tile j parameter in the filtered data set. It means to calculate the difference between the maximum and minimum values ​​of the j parameter in each tile in data set 2. By calculating the difference, we can observe the numerical change of the jth parameter. The coefficient of variation corresponding to the j parameter is calculated to determine the importance of the j parameter to the overall quality of the tile. The larger the value, the greater the degree to which the j parameter determines the overall quality of the tile. It is to solve the degree of variation of the parameters, so use (1-v j ) represents the weight coefficient of parameter j in the overall quality of the tile. Indicates the comprehensive quality value corresponding to the i-th tile; 2) Sort the tile data of data set 2 according to the calculation result of tile comprehensive quality in 1), and remove tile data with comprehensive quality lower than 20%.

3. The data retrieval management method based on remote sensing data according to claim 1 is characterized in that: When the user performs a full coverage preview of the result dataset in step 5, the map can be zoomed in and out. Through different zoom levels, the hierarchical effects corresponding to the archived tiles on the map can be viewed. The hierarchical effects include three resolution types: 20*20: fast loading and blurry, 200*200: smooth loading and clear, and 1000*1000: slow loading and ultra-clear. The specific resolution algorithm is as follows: When the height ratio is greater than 50, the resolution is 1000*1000, when 9<height ratio<50, the resolution is 200*200, and when the height ratio is less than 9, the resolution is 20*20.

4. The data retrieval management method based on remote sensing data according to claim 1 is characterized in that: In step 6, fine color uniformity, tile splicing, and automatic color uniformity processing of tiles are all manual operations.

5. A data retrieval management system based on remote sensing data, characterized in that: The system includes a tile data screening module, an optimization processing module, a tile multi-phase replacement module and a user order submission processing module; The tile data screening module is used to initiate a search request according to the selected data parameters and the selected condition priority level, obtain a data set 2 based on the initiated search request, and transmit the obtained data set 2 to the optimization processing module; The optimization processing module receives the data set 2 transmitted by the tile data screening module, calculates the comprehensive quality of each tile based on the resolution, side swing, full frame rate and cloud cover parameters, sorts the tile parameters based on the calculation results, removes tile data that does not meet the requirements, and after optimization processing, transmits the resulting data set to the tile multi-phase replacement module; The tile multi-temporal replacement module receives the result data set transmitted by the optimization processing module, and the user performs a full coverage preview of the result data set. The user decides whether to perform multi-temporal screening and replacement on individual tiles based on the preview image, time, full frame rate, and cloud cover parameters of each tile in the multi-temporal list to obtain data set 3, and transmits the obtained data set 3 to the user order submission processing module; The tile multi-temporal phase replacement module includes a tile data coverage preview unit, a screening and judgment unit, and a multi-temporal phase screening unit; The tile data coverage preview unit quickly sorts the result data set according to time, cloud cover, measured swing, and full frame rate through the sorting button above the result data set list. After the sorting is completed, the user selects a tile in the search result set, and then the system returns the multi-temporal data list of the tile to the user. The list is displayed separately by year and month, and the tile data selected by the user and the multi-temporal data list of the tile fed back by the system are transmitted to the screening and judgment unit; The screening and judging unit receives the tile data transmitted by the tile data coverage preview unit and the multi-temporal data list of the tile fed back by the system, checks the preview image, time, full amplitude rate, and cloud amount parameters of each tile in the multi-temporal list to determine whether to replace the tile transmitted by the tile data coverage preview unit, uses the inverse of the time difference between the tile transmitted by the tile data coverage preview unit and the tile selected in the multi-temporal list as a coefficient, combines the full amplitude and the sum of the cloud amount corresponding to the tile selected in the multi-temporal list to calculate the quality of the tile selected in the multi-temporal list, and transmits the calculation result to the multi-temporal screening unit; The multi-temporal screening unit receives the calculation result transmitted by the screening judgment unit. If the quality value of the tile selected in the multi-temporal list is greater than the comprehensive quality value of the tile selected in the result data set, the selected tile is replaced with one or more tiles meeting the requirements in the multi-temporal list in the result data set after sorting, to obtain data set 3, and the obtained data set 3 is transmitted to the user order submission processing module; The user order submission processing module receives the data set 3 transmitted by the tile multi-phase replacement module, and the user submits the tile data set 3. When submitting the order, the user can choose to perform fine color matching, tile splicing, and automatic color matching services on the tiles. The background then automatically processes and confirms the submitted order, and the user downloads the order data after background processing.

6. The data retrieval management system based on remote sensing data according to claim 5 is characterized in that: The tile data screening module includes a retrieval request unit, a tile data preliminary screening unit and a priority ranking unit; The retrieval request unit selects a priority level of a condition for filtering data based on the selected area, time range, cloud cover, and resolution data parameters as retrieval condition parameters, initiates a retrieval request, transmits the selected retrieval condition parameters to the tile data preliminary screening unit, and transmits the selected priority level of the condition to the priority ranking unit; The tile data preliminary screening unit receives the selected search condition parameters transmitted by the search request unit, performs preliminary screening on the tile data according to the selected area, time range, cloud cover, and resolution parameters to obtain a data set 1, and transmits the obtained data set 1 to the priority sorting unit; The priority sorting unit receives the selected condition priority transmitted by the retrieval request unit and the data set 1 transmitted by the tile data preliminary screening unit, automatically and preferentially searches for data that meets the requirements for the data set 1 according to the selected condition priority parameters, obtains the data set 2, and transmits the obtained data set 2 to the optimization processing module.

7. The data retrieval management system based on remote sensing data according to claim 6 is characterized in that: The optimization processing module includes a tile comprehensive quality calculation unit and a tile data elimination unit; The tile comprehensive quality calculation unit receives the data set 2 transmitted by the priority sorting unit, calculates the coefficient of variation corresponding to the resolution, sway, full amplitude and cloud amount parameters in the data set 2, calculates the weight coefficient corresponding to the resolution, sway, full amplitude and cloud amount parameters in the data set 2 based on the coefficient of variation, calculates the comprehensive quality of each tile based on the weight coefficient corresponding to each parameter and the parameter corresponding to each tile in the data set 2, and transmits the comprehensive quality value corresponding to each tile to the tile data elimination unit; The tile data elimination unit receives the comprehensive quality value corresponding to each tile transmitted by the tile comprehensive quality calculation unit, sorts the tile data of data set 2 according to the tile comprehensive quality calculation result, eliminates the tile data with a comprehensive quality lower than 20%, obtains a result data set, and transmits the obtained result data set to the tile multi-phase replacement module.

8. The data retrieval management system based on remote sensing data according to claim 7 is characterized in that: The user order submission processing module receives the data set 3 transmitted by the multi-phase screening unit, and the user submits the tile data set 3. When submitting the order, the user can choose to perform fine color matching, tile splicing, and automatic color matching services on the tiles. The background then automatically processes and confirms the submitted order, and the user downloads the order data processed by the background. All operations involved in this process are manual operations.

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