CN114003755B - Multi-source satellite scene-separating image data organization storage and retrieval method, system and equipment - Google Patents
Multi-source satellite scene-separating image data organization storage and retrieval method, system and equipment Download PDFInfo
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Abstract
The invention relates to a method, a system and equipment for organizing, storing and retrieving multi-source satellite panoramic image data, and relates to the technical field of satellite remote sensing image data processing. During data organization and storage, when a satellite corresponding to the satellite scene division image data is put in storage for the first time, recording satellite information and partition information in a satellite image partition registry, and creating an image metadata database table of each partition of the satellite based on a spatial database; determining the partition corresponding to the satellite scenery image, and updating the corresponding image metadata database table; after the entity file of the satellite scene division image data is stored, updating the storage path information into a corresponding image metadata database table; during data retrieval, performing primary retrieval on the satellite image partition registry according to retrieval constraint conditions, and further performing secondary retrieval on all image metadata database tables determined by the primary retrieval; the data processing mode can effectively reduce the processing of irrelevant data in the data storage and retrieval process and improve the calculation efficiency of the data storage and retrieval process.
Description
Technical Field
The invention relates to the technical field of satellite remote sensing image information systems, in particular to a method, a system and equipment for organizing, storing and retrieving multi-source satellite scenery separating image data.
Background
In the prior art, when organizing and storing satellite image data, all metadata information of one satellite is usually stored in one image metadata table, and the organization and management of the satellite image data are realized through the above way. However, with the increasing of the number of transmitted satellites, satellite images covering most of the world are rapidly accumulated, the data volume of massive satellite image data with multiple sources, multiple time phases, multiple scales and multiple versions is developed from GB to TB, and then to the current PB order of magnitude, the number of image data records acquired by one satellite is several million, which also results in a huge amount of metadata in an image metadata table. When image data organization and storage are performed and retrieval is performed in the image metadata table according to the retrieval constraint conditions, the calculation amount is very large, and the data organization and storage and retrieval efficiency is low.
Disclosure of Invention
The invention aims to solve the technical problem in the prior art and provides a method, a system and equipment for organizing, storing and retrieving multi-source satellite scenic image data.
In order to solve the above technical problem, an embodiment of the present invention provides a method for organizing and storing multi-source satellite panoramic image data, including: acquiring satellite scene division image data to be put in storage; when a satellite corresponding to the satellite scenic image data is put in storage for the first time, dividing a global geographic information base map into a plurality of partitions by using a global satellite image data partition model, recording satellite information and partition information in a satellite image partition registry, creating an image metadata database table of each partition of the satellite taking the partition as a unit based on a spatial database, and storing metadata of the satellite scenic image data in the partition corresponding to the satellite in the image database table; analyzing the satellite scenery image data, determining a subarea corresponding to the satellite scenery image data according to an analysis result, and updating a corresponding image metadata database table; and storing the entity file of the satellite panoramic image data, and updating the storage path information into a corresponding image metadata database table.
In order to solve the above technical problem, an embodiment of the present invention further provides a multi-source satellite scenic image data organization and storage system, including: the data acquisition module is used for acquiring the satellite panoramic image data to be put in storage; the database table management module is used for dividing a global geographic information base map into a plurality of partitions by using a global satellite image data partition model when a satellite corresponding to the satellite scenic image data is put in storage for the first time, recording satellite information and partition information in a satellite image partition registry, and creating an image metadata database table of each partition of the satellite with the partition as a unit based on a spatial database, wherein the image database table stores metadata of the satellite scenic image data in the partition corresponding to the satellite; the metadata storage module is used for analyzing the satellite scenery image data, determining a subarea corresponding to the satellite scenery image data according to an analysis result, and updating a corresponding image metadata database table; and the image data storage module is used for storing the entity file of the satellite scene division image data and updating the storage path information into a corresponding image metadata database table.
In order to solve the technical problem, an embodiment of the present invention further provides a multi-source satellite scenery image data retrieval method, where the satellite scenery image data is obtained by processing the organization storage method according to the above scheme, and the retrieval method includes: analyzing the data query request to obtain a retrieval constraint condition; performing primary retrieval in the satellite image partition registry according to the retrieval constraint condition, and determining all related image metadata database tables; performing secondary retrieval in all related image metadatabase tables according to the retrieval constraint conditions to acquire metadata meeting the retrieval constraint conditions in all related image metadatabase tables; and performing first-level grouping on the retrieval result according to the satellite sensor, sequencing the retrieval result in each first-level grouping according to Path-Row, and returning the metadata subjected to grouping sequencing processing to the client.
In order to solve the above technical problem, an embodiment of the present invention further provides a multi-source satellite panoramic image data retrieval system, including: the query request analysis module is used for analyzing the data query request to obtain a retrieval constraint condition; the first retrieval module is used for performing primary retrieval in the satellite image partition registry according to the retrieval constraint condition and determining all related image metadata database tables; the second retrieval module is used for performing secondary retrieval in all related image metadata database tables according to the retrieval constraint conditions to acquire metadata which accords with the retrieval constraint conditions in all related image metadata database tables; and the result sorting module is used for performing primary grouping on the retrieval result according to the satellite sensor, sorting the retrieval result in each primary grouping according to Path-Row, and returning the metadata subjected to grouping sorting processing to the client.
In order to solve the foregoing technical problem, an embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor implements the program to implement the multi-source satellite panoramic image data organization and storage method according to the above technical solution or the multi-source satellite panoramic image data retrieval method according to the above technical solution.
According to the multi-source satellite scenic image data organization and storage method, system and equipment, when a satellite is put in storage for the first time, a plurality of image metadata database tables with partitions as units are established, and satellite information and partition information are recorded in a satellite image partition registry; when the satellite scenery image data is put in storage, only the image metadata database table of the subareas corresponding to the satellite scenery image data is updated, the data calculation amount is small, and the data organization and storage efficiency is high.
According to the multi-source satellite panoramic image data retrieval method, system and equipment, when data retrieval is carried out, all related image metadata database tables can be determined by carrying out primary retrieval in the satellite image partition registry, and the retrieval range of metadata of satellite panoramic image data which accords with retrieval constraint conditions is greatly reduced; performing secondary retrieval in all related image metadata database tables according to retrieval constraint conditions, namely efficiently and quickly acquiring metadata of satellite panoramic image data meeting the retrieval constraint conditions, and having small data calculation amount and high query retrieval efficiency; and the metadata grouped and sequenced according to the Path-Row is returned to the client, so that a user can intuitively acquire the metadata of the multi-scene satellite image data at the same place, and the user can select the required satellite scene-separating image data as required.
Additional aspects of the invention and its advantages will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
Fig. 1 is a flowchart of a multi-source satellite panoramic image data organization and storage method according to an embodiment of the present invention;
FIG. 2 is a schematic view of a global geographical information base map partition according to an embodiment of the present invention;
FIG. 3 is a flowchart of a multi-source satellite panoramic image data organization and storage method according to a second embodiment of the present invention
Fig. 4 is a block diagram of a multi-source satellite scenic image data organization and storage system according to a third embodiment of the present invention;
fig. 5 is a flowchart of a multi-source satellite panoramic image data retrieval method according to the fourth embodiment of the present invention;
fig. 6 is a flowchart of a multi-source satellite panoramic image data retrieval method according to a fifth embodiment of the present invention;
fig. 7 is a block diagram of a multi-source satellite panoramic image data retrieval system according to a sixth embodiment of the present invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
Example one
Fig. 1 is a flowchart of a multi-source satellite panoramic image data organization and storage method according to an embodiment of the present invention. As shown in fig. 1, the method includes:
and S110, acquiring the satellite panoramic image data to be put in storage.
A scene image entity file of the satellite scene division image data is usually combined with a corresponding image auxiliary file, the image auxiliary file may include spatial information (i.e., an image coverage space figure) and attribute information of the satellite scene division image data, and the image entity file corresponds to the spatial information and the attribute information one to one.
S120, judging whether the satellite corresponding to the satellite panoramic image data is put into a warehouse for the first time, if so, executing S130, otherwise, executing S140;
specifically, the determination may be performed according to attribute information in an image auxiliary file of the satellite panoramic image data, for example, the satellite information in the attribute information may include a satellite type, a sensor type, and a sensor resolution; and judging whether the satellite corresponding to the satellite scene division image data is put in storage for the first time or not according to the satellite information.
And S130, dividing the global geographic information base map into a plurality of partitions by using a global satellite image data partition model, recording satellite information and partition information in a satellite image partition registry, and creating an image metadata database table of each partition of the satellite with the partition as a unit based on a spatial database.
In the embodiment of the invention, the global geographic information base map is divided into a plurality of partitions by using the global satellite image data partition model. As shown in fig. 2, when the global geographic information base map is divided, N-1 partition points may be selected at equal intervals based on the 0 ° latitude line with (-180 °,0 °) as the starting point and (180 °,0 °) as the ending point in the WGS84 coordinate system, and the longitude line passing through the partition points is used as the dividing line to divide the global geographic information base map into N partitions, where N is a positive integer greater than or equal to 2 and less than or equal to the number of satellite repetition cycle days determined according to the satellite information, and may be determined according to the number of images expected to be received. Metadata of all the satellite scenic images acquired in the same satellite partition are stored in the same image metadata database table, and metadata of the satellite scenic images acquired in different satellite partitions are stored in different image metadata database tables.
Specifically, according to the unified image metadata database table naming rule and the metadata template, the related image metadata database table is automatically created based on the spatial database. The naming rule of the image metadata database table may be: satellite + partition encoding. The image metadata information of different partitions acquired by different satellites is stored in different image metadata database tables.
If the satellite A is put in storage for the first time, the number of images expected to be received is determined to be small according to the relevant information of the satellite A, the global geographic information base map can be divided into six partitions, six image metadata base tables of each partition corresponding to the satellite A are established, for example, the satellite A + partition 1, the satellite A + partition 2 … …, the satellite A + partition 6, and each image metadata base table only records metadata of satellite scenic image data acquired by the satellite A in the corresponding partition. For another example, if it is determined that the number of images expected to be received is large according to the related information of the satellite B, the global geographic information base map may be divided into twelve partitions, and twelve image metadata database tables corresponding to the partitions of the satellite B are established, such as the satellite B + partition 1, the satellite B + partition 2 … …, and the satellite B + partition 12.
It should be understood that the satellite information may include satellite type, sensor type, and sensor resolution. The partition information may include the number of partitions and the name of the image metadata library table. The metadata may include base metadata and custom metadata. The base metadata may include: satellite type, sensor resolution, cloud cover, product level, shooting time, path-Row, spatial information of satellite scenic image data, image storage Path and the like. The custom metadata may include: the track number, the track inclination angle data size, the data format and the like, and can be expanded according to actual needs. Each record of the image metadata database table corresponds to an image entity file.
By dividing the global geographic information base map into partitions, establishing an image metadata database table of each partition and recording satellite information and partition information in the satellite image partition registry, the processing of irrelevant data in the data storage and retrieval process can be effectively reduced, and the calculation efficiency of the data storage and retrieval process is improved.
S140, analyzing the satellite scene division image data, determining a partition corresponding to the satellite scene division image data according to an analysis result, and updating an image metadata database table corresponding to the partition;
specifically, an image auxiliary file of satellite panoramic image data is analyzed, and coordinates of an image center point are obtained; coordinates (x, y) of the image center point in the WGS84 coordinate system, wherein x is a longitude value and y is a latitude value; and determining the partition where the image center point is located according to the image center point coordinates and the global satellite image data partition model. When-180 ≦ x <180 °, partition coding M = [ (180 + x)/(360/N) ] +1; when x =180 °, partition coding M = N.
The method comprises the steps of acquiring coordinates of an image central point by analyzing an image auxiliary file of satellite panoramic image data, determining a partition where the image center is located according to the coordinates of the image central point, and further determining an image metadata table name corresponding to the partition, wherein the metadata table name can be as follows: and (4) encoding the satellite and the partition, further updating a corresponding metadata database table, and storing the image coverage space graph and attribute information of the satellite scene image data based on a space database. The image coverage area space graph of the satellite scene division image data is stored by adopting a space geometric type of a space database, and each image entity file corresponds to one image coverage area space graph and one attribute information record in the space database.
S150, storing the entity file of the satellite scene division image data, and updating the storage path information to a corresponding image metadata database table.
In the embodiment, when the satellite is put into storage for the first time, a plurality of image metadata database tables with partitions as units are established, and satellite information and partition information are recorded in a satellite image partition registry; when the satellite scenery image data is put in storage, only the image metadata database table of the subarea corresponding to the satellite scenery image data is updated, so that the processing of irrelevant data in the data storage process can be effectively reduced, and the calculation efficiency of data storage is improved.
Example two
Fig. 3 is a flowchart of a multi-source satellite panoramic image data organization and storage method according to a second embodiment of the present invention. As shown in fig. 3, the method includes:
s310, acquiring satellite scenery image data to be put in storage;
s320, judging whether the satellite corresponding to the satellite panoramic image data is put into a warehouse for the first time, if so, executing S330, and if not, executing S350;
s330, dividing the global geographic information base map into a plurality of partitions by using a global satellite image data partition model, and recording satellite information and partition information in a satellite image partition registry;
s340, creating an image metadata database table of each partition of the satellite with the partition as a unit based on a spatial database;
s350, analyzing an image auxiliary file of the satellite scene division image data, determining a partition where the coordinates of the image center point are located, and determining an image metadata database table corresponding to the partition;
s360, storing image coverage area space graphics and attribute information of the satellite panoramic image data based on a space database;
and S370, storing the image entity file of the satellite panoramic image data, and updating the image storage path information into a corresponding metadata database table.
The method for organizing and storing multi-source satellite panoramic image data according to the embodiment of the invention is described in detail with reference to fig. 1 to 3. The multi-source satellite panoramic image data organization and storage system provided by the embodiment of the invention is described in detail below with reference to fig. 4.
EXAMPLE III
As shown in fig. 4, the multi-source satellite scenic imagery data organization and storage system 400 includes a data acquisition module 410, a database table management module 420, a metadata storage module 430, and an imagery data storage module 440. The data acquisition module 410 is configured to acquire satellite panoramic image data to be put into a warehouse; the database table management module 420 is configured to, when a satellite corresponding to the satellite scenic image data is put in storage for the first time, divide a global geographic information base map into a plurality of partitions by using a global satellite image data partition model, record satellite information and partition information in a satellite image partition registry, create an image metadata database table of each partition of the satellite using the partition as a unit based on a spatial database, and store metadata of the satellite scenic image data in the partition corresponding to the satellite in the image database table; the metadata storage module 430 is configured to analyze the satellite scenery image data, determine a partition corresponding to the satellite scenery image data according to an analysis result, and update a corresponding image metadata database table; the image data storage module 440 is configured to store an entity file of the satellite scenic image data, and update the storage path information to a corresponding image metadata database table.
Example four
Fig. 5 is a flowchart of a multi-source satellite panoramic image data retrieval method according to the fourth embodiment of the present invention. The method can realize the retrieval and result display of the interactive sharing service system class. As shown in fig. 5, the method includes:
s510, analyzing the data query request to obtain a retrieval constraint condition;
in general, the search constraint conditions mainly include a spatial search range, a satellite type, a sensor resolution, a cloud cover, an image shooting time and the like, and the search constraint conditions can be customized and expanded.
S520, performing primary retrieval in the satellite image partition registry according to the retrieval constraint condition, and determining all related image metadata database tables;
if the satellite information can be determined in the satellite image partition registry according to the satellite type, the sensor resolution and the like, the start-stop partition coding can be determined according to the outsourcing rectangle of the space retrieval range, specifically, the partition coding where the upper left corner coordinate and the lower right corner coordinate of the outsourcing rectangle are located can be respectively calculated, and the start-stop interval of the partition coding where the retrieval range is located can be determined. Therefore, all relevant image metadata database tables can be determined according to the satellite information and/or the start-stop interval of the partition codes.
S530, performing secondary retrieval in all related image metadata database tables according to the retrieval constraint conditions, and acquiring metadata which accords with the retrieval constraint conditions in all related image metadata database tables;
specifically, according to constraint conditions such as a space retrieval range, a satellite, a sensor, resolution, cloud cover, image shooting time and the like in the query request, space-attribute integrated query retrieval is carried out in a corresponding image metadata database table, and metadata information meeting the retrieval constraint conditions in the partition is obtained.
And S540, performing first-level grouping on the retrieval result according to the satellite sensor, sequencing the retrieval result in each first-level grouping according to Path-Row, and returning the metadata subjected to grouping and sequencing to the client.
In the embodiment of the invention, the retrieval results are grouped at a first level according to the satellite sensors. That is, the search results of the sectors of the same type of sensor of the same satellite are combined into one search result set.
Sequencing in a first-level packet according to Path-Row: and firstly sorting the search result set from small to large based on Path, and then sorting the satellite scenic images with the same Path from small to large according to Row. The method can realize the spatial pattern spot elements of the same satellite sensor image are sorted from top to bottom and from left to right, the image data corresponding to the same Path-Row are displayed in a set, and the images of the same Path are displayed in an adjacent order from top to bottom according to the Row sorting.
In addition, after the search results are grouped according to the satellite sensors and sorted according to the Path-Row, the search results can also be sorted according to other metadata information such as shooting time, cloud cover and the like. Metadata returned to the client can be organized according to a directory tree structure of satellite-sensor-partition-Path-Row-image metadata information, and image coverage space graphic information is displayed in a visual mode in a GIS space graphic mode based on a global geographic base map.
In the embodiment, all related image metadata database tables can be determined by performing primary retrieval in the satellite image partition registry, so that the retrieval range of metadata of satellite panoramic image data meeting retrieval constraint conditions is greatly reduced; and performing secondary retrieval in all related image metadata database tables according to the retrieval constraint conditions, so that metadata of the satellite panoramic image data meeting the retrieval constraint conditions can be efficiently and quickly acquired, the data calculation amount is small, and the query retrieval efficiency is high.
In the prior art, retrieval results are returned for multiple times in a form of listing and dividing into multiple pages, and multiple-period image data results at the same position are often distributed on different pages and cannot be compared and checked; however, attribute information lists of images with adjacent spatial positions are often not adjacent or in different pages, and when images are viewed according to the order of the attribute lists, spatial positions of images in the spatial range of the same page are not continuous, so that user experience is poor.
In the embodiment of the invention, the metadata after grouping and sequencing is returned to the client, so that a user can intuitively obtain the attribute information of the multi-scene satellite image data and the corresponding image coverage space graph in the same place, and further the user can select the required satellite scene-dividing image data according to the requirement.
EXAMPLE five
Fig. 6 is a flowchart of a multi-source satellite panoramic image data retrieval method according to the fifth embodiment of the present invention. The method can realize the screening of the optimal coverage image of the designated area. As shown in fig. 6, the method includes:
s610, analyzing the data query request to obtain a retrieval constraint condition;
s620, performing primary retrieval in the satellite image partition registry according to the retrieval constraint conditions, and determining all related image metadata database tables;
s630, respectively carrying out secondary retrieval in all related image metadata database tables according to the retrieval constraint conditions, and acquiring metadata which accords with the retrieval constraint conditions in all related image metadata database tables; s640, performing first-level grouping on the retrieval results according to the satellite sensors, and sequencing the retrieval results in each first-level grouping according to Path-Row;
s650, performing secondary grouping in each primary grouping according to Path-Row, grading the satellite scene-dividing image data of each secondary grouping one by one according to preset grading items (such as attribute relevant conditions of resolution, shooting time, cloud cover and the like) and grading weights, reserving the first scene satellite scene-dividing image data with the highest score, taking the corresponding score as a secondary grouping score, and determining the average score of the primary grouping according to the score of each secondary grouping in the primary grouping;
s660, sorting the average scores of the first-level groups, and taking all satellite scene-separating image data acquired by the satellite sensor with the highest average score as an initial screening result;
s670, judging whether the space retrieval range is completely covered by the space coverage range corresponding to the screening result or the satellite panoramic image data of all the satellite sensors which meet the retrieval constraint condition in the data query request are screened, if so, ending the processing flow, otherwise, executing S680;
s680, removing the space coverage range corresponding to the screening result from the space retrieval range by using a space erasure analysis function supported by a space database, and acquiring a residual space retrieval range which is not covered in the space retrieval range;
and S690, screening the image search results of the satellite sensor with the highest residual average score by using the residual space search range, merging the screening result with the initial screening result, and returning to S670.
That is, the space search range which is not covered in the search constraint condition is used for screening in the image search results of the satellite sensor with the highest average score, and the screening result is merged with the selected image data; and repeating the steps until the screening results obtained after the spatial retrieval ranges in the retrieval constraint conditions are combined completely cover or the satellite panoramic image data of all satellite sensor types conforming to the retrieval conditions in the data query request are screened, and ending the process.
In the embodiment, the satellite image attribute information is used as the constraint condition to perform optimal image data screening on the large-range specified target area covered by multiple satellites for multiple times, the method can utilize a computer to perform full-automatic parallel processing, the efficiency is high, and the comprehensive screening of satellite images of different satellite sensor types can be realized.
EXAMPLE six
Fig. 7 is a block diagram of a multi-source satellite panoramic image data retrieval system according to a sixth embodiment of the present invention. As shown in fig. 7, the multi-source satellite scenic image data retrieval system 700 includes: a query request parsing module 710, a first retrieval module 720, a second retrieval module 730, and a result sorting module 740.
The query request analysis module 710 is configured to analyze the data query request to obtain a retrieval constraint condition; the first retrieval module 720 is configured to perform a first-level retrieval in the satellite image partition registry according to the retrieval constraint condition, and determine all related image metadata database tables; the second retrieval module 730 is configured to perform secondary retrieval on all related image metadata database tables according to the retrieval constraint condition, and acquire metadata in all related image metadata database tables that meet the retrieval constraint condition; the result sorting module 740 is configured to perform first-level grouping on the search result according to the satellite sensor, sort the search result in each first-level grouping according to Path-Row, and return the metadata subjected to the grouping and sorting processing to the client.
The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein when the processor executes the program, the multi-source satellite panoramic image data organization and storage method provided by the embodiment or the multi-source satellite panoramic image data retrieval method provided by the embodiment is realized.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is only a logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A multi-source satellite scenic image data organization and storage method is characterized by comprising the following steps:
acquiring satellite scene division image data to be put in storage;
when the satellite corresponding to the satellite scenery image data is put in storage for the first time, dividing the global geographic information base map into a plurality of partitions by using a global satellite image data partition model; the number of the partitions is determined according to the number of the images expected to be received;
the dividing of the global geographic information base map into a plurality of partitions by using the global satellite image data partition model comprises the following steps:
under a WGS84 coordinate system, taking a 0-degree latitude line with (-180 degrees, 0 degrees as a starting point and (180 degrees, 0 degrees as an end point as a reference, selecting N-1 partition points at equal intervals, taking a meridian line passing through the partition points as a partition line, and dividing the global geographic information base map into N partitions at equal intervals, wherein N is a positive integer which is determined according to satellite information and is greater than or equal to 2 and less than or equal to the number of days of a satellite repetition cycle;
recording satellite information and partition information in a satellite image partition registry, and creating an image metadata database table of each partition of the satellite with partitions as units based on a spatial database, wherein the image metadata database table stores metadata of satellite scene partition image data in the partition corresponding to the satellite;
analyzing the satellite scenery image data, determining a subarea corresponding to the satellite scenery image data according to an analysis result, and updating a corresponding image metadata database table;
storing an entity file of the satellite scene division image data, and updating storage path information into a corresponding image metadata database table; each record of the image metadata database table corresponds to an image entity file.
2. The multi-source satellite scenery image data organization and storage method according to claim 1, wherein the analyzing the satellite scenery image data and determining the subareas corresponding to the satellite scenery image data according to the analysis result comprises:
analyzing an image auxiliary file of the satellite scene division image data to obtain an image center point coordinate;
and determining the partition where the image center point is located according to the image center point coordinates and the global satellite image data partition model.
3. The multi-source satellite scenic image data organization and storage method according to claim 2, wherein the determining the partition where the image center point is located according to the image center point coordinates and the global satellite image data partition model comprises:
when-180 ° ≦ x <180 °, partition coding M = [ (180 + x)/(360/N) ] +1;
when x =180 °, partition coding M = N;
wherein x is the longitude value of the image center point coordinate in the WGS84 coordinate system.
4. The multi-source satellite scenic imagery data organization and storage method of any one of claims 1 to 3, wherein the satellite information comprises: at least one of a satellite type, a sensor type, and a sensor resolution; the partition information comprises at least one of the number of partitions and the name of an image metadata database table;
the metadata stored in the image metadata database table includes: the satellite scene dividing method comprises basic metadata and custom metadata, wherein the basic metadata comprise spatial information and attribute information of a satellite scene dividing image, and the custom metadata are information to be recorded according to satellite characteristics.
5. A multi-source satellite scenic image data organization and storage system is characterized by comprising:
the data acquisition module is used for acquiring the satellite panoramic image data to be put in storage;
the database table management module is used for dividing a global geographic information base map into a plurality of partitions by using a global satellite image data partition model when a satellite corresponding to the satellite scenic image data is put in a warehouse for the first time; the number of the partitions is determined according to the number of the images expected to be received;
the dividing of the global geographic information base map into a plurality of partitions by using the global satellite image data partition model comprises the following steps:
under a WGS84 coordinate system, taking a 0-degree latitude line with (-180 degrees, 0 degrees as a starting point and (180 degrees, 0 degrees as an end point as a reference, selecting N-1 partition points at equal intervals, taking a meridian line passing through the partition points as a partition line, and dividing the global geographic information base map into N partitions at equal intervals, wherein N is a positive integer which is determined according to satellite information and is greater than or equal to 2 and less than or equal to the number of days of a satellite repetition cycle;
recording satellite information and partition information in a satellite image partition registry, and creating an image metadata database table of each partition of the satellite with partitions as units based on a spatial database, wherein the image metadata database table stores metadata of satellite scene partition image data in the partition corresponding to the satellite;
the metadata storage module is used for analyzing the satellite scenery image data, determining a subarea corresponding to the satellite scenery image data according to an analysis result, and updating a corresponding image metadata database table;
the image data storage module is used for storing entity files of the satellite scenery separating image data and updating the storage path information to a corresponding image metadata database table; each record of the image metadata database table corresponds to an image entity file.
6. A multi-source satellite scenic image data retrieval method, wherein the satellite scenic image data is obtained by processing the organization storage method according to any one of claims 1 to 4, the retrieval method comprising:
analyzing the data query request to obtain a retrieval constraint condition;
performing primary retrieval in the satellite image partition registry according to the retrieval constraint condition, and determining all related image metadata database tables;
performing secondary retrieval in all related image metadatabase tables according to the retrieval constraint conditions to acquire metadata meeting the retrieval constraint conditions in all related image metadatabase tables;
and performing first-level grouping on the retrieval result according to the satellite sensor, sequencing the retrieval result in each first-level grouping according to Path-Row, and returning the metadata subjected to grouping and sequencing processing to the client.
7. The multi-source satellite scenic image data retrieval method according to claim 6, wherein the performing a first-level retrieval in the satellite image partition registry according to the retrieval constraint condition to determine all relevant image metadata database tables comprises:
when the data query request comprises constraints of a spatial retrieval range and/or satellite information;
and determining start-stop intervals of the partitions according to the space retrieval range, performing query retrieval in the satellite image partition registry according to the start-stop intervals of the partitions and/or satellite information, and determining all related image metadata database tables.
8. The multi-source satellite scenic image data retrieval method according to claim 6, wherein when the data query request includes a spatial retrieval range, the first-stage grouping of the retrieval results according to a satellite sensor and the sorting in each first-stage grouping according to Path-Row further comprises the following steps:
a, performing secondary grouping in each primary grouping according to Path-Row, grading satellite scene-dividing image data of each secondary grouping one by one according to preset grading items and grading weights, keeping the first-scene satellite scene-dividing image data with the highest score, taking the corresponding score as a secondary grouping score, and determining the average score of the primary grouping according to the score of each secondary grouping in the primary grouping;
b, sorting the average scores of the first-level groups, and taking all satellite scene-dividing image data acquired by the satellite sensor with the highest average score as an initial screening result;
c, judging whether the space retrieval range is completely covered by the space coverage range corresponding to the screening result or the satellite panoramic image data of all the satellite sensors which accord with the retrieval constraint condition in the data query request are screened, if so, ending the processing flow, otherwise, executing the step d;
d, removing the space coverage range corresponding to the screening result from the space retrieval range by using a space erasing analysis function supported by a space database, and acquiring a residual space retrieval range which is not covered in the space retrieval range;
and e, screening the image retrieval results of the satellite sensor with the highest residual average score by using the residual space retrieval range, combining the screening result with the initial screening result, and returning to the step c.
9. A multi-source satellite scenery image data retrieval system, wherein the satellite scenery image data is obtained by processing the organization storage method of any one of claims 1 to 4, and the system comprises:
the query request analysis module is used for analyzing the data query request to obtain a retrieval constraint condition;
the first retrieval module is used for performing primary retrieval in the satellite image partition registry according to the retrieval constraint condition and determining all related image metadata database tables;
the second retrieval module is used for performing secondary retrieval in all related image metadatabase tables according to the retrieval constraint conditions to acquire metadata meeting the retrieval constraint conditions in all related image metadatabase tables;
and the result sorting module is used for performing primary grouping on the retrieval results according to the satellite sensor, sorting the retrieval results in each primary grouping according to Path-Row, and returning the metadata subjected to grouping sorting processing to the client.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the multi-source satellite scenic image data organization and storage method according to any one of claims 1 to 4 or the multi-source satellite scenic image data retrieval method according to any one of claims 6 to 8 when executing the program.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108089850A (en) * | 2018-01-02 | 2018-05-29 | 北京建筑大学 | A kind of ground mulching product increment updating method based on image collaboration segmentation with ecogeography zoning ordinance storehouse |
| CN110855638A (en) * | 2019-10-28 | 2020-02-28 | 中国资源卫星应用中心 | Remote sensing satellite data decompression processing system and method based on cloud computing |
Family Cites Families (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102081669B (en) * | 2011-01-24 | 2012-11-21 | 哈尔滨工业大学 | Hierarchical retrieval method for multi-source remote sensing resource heterogeneous databases |
| US9977978B2 (en) * | 2011-11-14 | 2018-05-22 | San Diego State University Research Foundation | Image station matching, preprocessing, spatial registration and change detection with multi-temporal remotely-sensed imagery |
| CN102798381B (en) * | 2012-07-20 | 2014-12-24 | 中国资源卫星应用中心 | Scene division cataloging method based on geographical location of real image |
| CN103677761B (en) * | 2013-12-11 | 2016-09-21 | 中国资源卫星应用中心 | A kind of quick processing system of satellite remote sensing date |
| CN104899282B (en) * | 2015-06-02 | 2018-11-27 | 北京博阳世通信息技术有限公司 | A kind of processing method and search method of multi-source multi-temporal satellite remote sensing tile data |
| CN110019879B (en) * | 2017-07-31 | 2021-03-05 | 清华大学 | Satellite remote sensing image searching method and device |
| CN108446288B (en) * | 2017-08-01 | 2023-10-17 | 北京四维新世纪信息技术有限公司 | One-time full-coverage retrieval method for remote sensing tile data |
| CN109299060A (en) * | 2018-11-22 | 2019-02-01 | 华东计算技术研究所（中国电子科技集团公司第三十二研究所） | Distributed file method and system based on image rectangular blocks |
| CN110046270A (en) * | 2019-02-26 | 2019-07-23 | 中科遥感(深圳)卫星应用创新研究院有限公司 | Information memory managing method based on MongoDB |
| CN110781325A (en) * | 2019-10-21 | 2020-02-11 | 武汉大学 | High-resolution remote sensing data grid refined management model and construction method thereof |
| CN113297407B (en) * | 2021-05-21 | 2021-11-26 | 生态环境部卫星环境应用中心 | Remote sensing image optimization method and device |
-
2021
- 2021-10-25 CN CN202111239906.5A patent/CN114003755B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108089850A (en) * | 2018-01-02 | 2018-05-29 | 北京建筑大学 | A kind of ground mulching product increment updating method based on image collaboration segmentation with ecogeography zoning ordinance storehouse |
| CN110855638A (en) * | 2019-10-28 | 2020-02-28 | 中国资源卫星应用中心 | Remote sensing satellite data decompression processing system and method based on cloud computing |
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