Remote sensing data management methods, devices, equipment, storage media and products

Abstract

This invention provides a remote sensing data management method, apparatus, device, storage medium, and product. The method includes: upon receiving a retrieval request from a user terminal for retrieving remote sensing data, acquiring the requested data present in the retrieval request; calculating the target image boundaries of the requested remote sensing image based on the request data; determining a storage index based on the target image boundaries and the data level of the request data; the storage index indicating the storage location of the data corresponding to the retrieval request in the target storage level of a preset remote sensing image management system; retrieving the remote sensing image from the remote sensing image management system according to the storage index; and outputting it to the user terminal. In other words, this invention improves the efficiency of remote sensing data management, thereby enhancing the near real-time application of remote sensing images.

Description

Technical Field

[0001] This invention relates to the field of remote sensing technology applications, and in particular to a remote sensing data management method, apparatus, equipment, storage medium, and product. Background Technology

[0002] With the development of my country's Earth observation technology, especially the advancement of the high-resolution Earth observation system major project, my country has basically acquired space-based Earth observation capabilities with high spatial resolution, high temporal resolution, and high spectral resolution. As remote sensing image data accumulates in massive quantities, the application needs of different fields are placing increasingly higher demands on the storage and efficient retrieval of remote sensing image data.

[0003] Remote sensing image files are typically very large, making direct retrieval of the data itself unsuitable for the remote sensing field. Currently, methods using polygon spatial overlay and database traversal to search for large amounts of remote sensing data result in low retrieval efficiency and slow response times, thus hindering near-real-time applications of large-scale remote sensing data. Summary of the Invention

[0004] This invention provides a remote sensing data management method, apparatus, device, storage medium, and product to solve the problem of low efficiency in remote sensing data management in the prior art, which prevents its near real-time application.

[0005] This invention provides a remote sensing data management method, the method comprising:

[0006] When a retrieval request for remote sensing data is received from a user terminal, the request data in the retrieval request is obtained. The request data includes the data level, row and column numbers of the remote sensing data, and the tile organization rules corresponding to the user terminal.

[0007] The target image boundaries of the requested remote sensing image are calculated based on the requested data. A storage index is determined based on the target image boundaries and the data level of the requested data. The storage index is used to indicate the storage location of the data corresponding to the retrieval request in the target storage level of the preset remote sensing image management system.

[0008] Remote sensing images are retrieved from the remote sensing image management system according to the storage index and output to the user terminal.

[0009] According to a remote sensing data management method provided by the present invention, the steps of calculating the target image boundaries of the requested remote sensing image based on the requested data, and determining the storage index based on the target image boundaries and the data hierarchy of the requested data, include:

[0010] Calculate the target image boundaries of the requested remote sensing image based on the requested data;

[0011] Based on the data hierarchy of the target image's boundaries, the corresponding target hierarchy in the preset remote sensing image management system is determined. The target hierarchy includes a storage hierarchy and a virtual hierarchy.

[0012] Determine the target grid ID corresponding to the four boundaries of the target image in the target level;

[0013] A storage index is formed based on the target grid ID. The storage index is used to indicate the storage location of the data corresponding to the retrieval request in the target storage level of the preset remote sensing image management system.

[0014] According to a remote sensing data management method provided by the present invention, the step of forming a storage index based on the target grid ID includes:

[0015] If the target level is a storage level, then a storage index is formed based on the target grid ID;

[0016] If the target level is a virtual level, the storage grid ID of the remote sensing image in the target storage level is determined based on the target grid ID and the preset grid mapping relationship, and the storage grid ID forms a storage index.

[0017] According to a remote sensing data management method provided by the present invention, the remote sensing image management system is determined based on preset grid level requirements and grid levels.

[0018] Before the steps of calculating the target image boundaries of the requested remote sensing image based on the requested data, and determining the storage index based on the target image boundaries and the data hierarchy of the requested data, the method further includes:

[0019] According to the preset tile organization rules and preset grid level requirements, the grid corresponding to each grid level is divided into multiple spatial grids. Each spatial grid contains a grid ID and an AVL tree. The grid IDs between different grid levels have a grid mapping relationship. The AVL tree stores the metadata of the remote sensing image.

[0020] An initial management system is constructed based on multiple grid levels and the spatial grids corresponding to the grid levels. The grid levels include one of the storage level and the virtual level.

[0021] Acquire remote sensing images to be added to the database, and store the images to be added to the grid level corresponding to the initial management system based on the relevant data information of the images to be added to the database, thereby obtaining the remote sensing image management system.

[0022] According to a remote sensing data management method provided by the present invention, the grid ID is an M-bit binary number, wherein M is determined based on the grid level and the number of binary bits in the user terminal register.

[0023] According to a remote sensing data management method provided by the present invention, the method further includes:

[0024] The grid level whose grid accuracy corresponds to global latitude and longitude accuracy is determined from multiple storage levels as the basic level for storing data, and the first grid ID and first AVL tree of the spatial grid in the basic level are recorded;

[0025] Based on the base level and the preset volume of remote sensing images, multiple storage data entry levels are extended with the base level as the reference. The second grid ID and second AVL tree of the spatial grid in the entry level are recorded. The tile density of the entry level is less than the tile density of the base level.

[0026] Record the ID of the third grid in the spatial grid of the virtual hierarchy;

[0027] Based on the tile organization rules preset in the remote sensing image management system, the grid mapping relationship between the second grid ID and the first grid ID and the third grid ID is determined.

[0028] According to a remote sensing data management method provided by the present invention, the steps of acquiring remote sensing images to be stored in the database and storing the remote sensing images to be stored in the database into the grid level corresponding to the initial management system based on the relevant data information of the remote sensing images to be stored in the database, thereby obtaining a remote sensing image management system, include:

[0029] Obtain metadata of the remote sensing images to be added to the database;

[0030] The boundaries of the remote sensing image to be added to the database are calculated based on the metadata.

[0031] The boundaries of the image to be stored are locked at the basic level. If the boundaries of the image to be stored meet the preset storage conditions when stored at the basic level, the remote sensing image to be stored is stored in the first AVL tree of the spatial grid in the basic level, and the corresponding first grid ID is recorded to complete the data storage and obtain the remote sensing image management system.

[0032] Otherwise, the remote sensing image to be added to the database is stored in an entry level outside the basic level. Based on the first grid ID and the grid mapping relationship, the second grid ID of the remote sensing image to be added to the database is determined when it is stored in the entry level, and the data entry is completed to obtain the remote sensing image management system.

[0033] The present invention also provides a remote sensing data management device, the device comprising:

[0034] The request receiving module is used to obtain the request data in the retrieval request when it receives a retrieval request for retrieving remote sensing data sent by the user terminal. The request data includes the data level, row and column numbers of the remote sensing data, and the tile organization rules corresponding to the user terminal.

[0035] The index determination module is used to calculate the target image boundaries of the requested remote sensing image based on the request data, and determine the storage index based on the target image boundaries and the data level of the request data. The storage index is used to indicate the storage location of the data corresponding to the retrieval request in the target storage level of the preset remote sensing image management system.

[0036] The data extraction module is used to retrieve remote sensing images from the remote sensing image management system according to the storage index and output them to the user terminal.

[0037] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the remote sensing data management method as described above.

[0038] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the remote sensing data management method as described above.

[0039] The remote sensing data management method, apparatus, device, storage medium, and product provided by this invention, upon receiving a retrieval request from a user terminal for retrieving remote sensing data, acquires the request data present in the retrieval request. The request data includes the data level, row and column numbers of the remote sensing data, and the tile organization rules corresponding to the user terminal. Based on the request data, the target image boundaries of the requested remote sensing image are calculated. A storage index is determined based on the target image boundaries and the data level of the request data. The storage index indicates the storage location of the data corresponding to the retrieval request within the target storage level of a preset remote sensing image management system. The remote sensing image is retrieved from the remote sensing image management system according to the storage index and output to the user terminal. In other words, by establishing a remote sensing image management system and storing massive amounts of remote sensing images at different levels within the system, it provides engine support for the efficient utilization of various types of multi-source remote sensing spatial data in the database. The required remote sensing image is quickly retrieved through the storage index, avoiding the problems of slow retrieval response in sliced ​​image storage, improving the efficiency of remote sensing data management, and thus enhancing the near real-time application of remote sensing images. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0041] Figure 1 This is one of the flowcharts illustrating the remote sensing data management method provided by the present invention;

[0042] Figure 2 This is a schematic diagram of the spatial grid division of the storage hierarchy in the remote sensing data management method provided by the present invention;

[0043] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0045] The following is combined Figures 1-3 The remote sensing data management method of the present invention is described with reference to Figure 1 The remote sensing data management method includes:

[0046] Step S100: When a retrieval request for retrieving remote sensing data is received from the user terminal, the request data in the retrieval request is obtained. The request data includes the data level, row and column numbers of the remote sensing data, and the tile organization rules corresponding to the user terminal.

[0047] Step S200: Calculate the target image boundaries of the requested remote sensing image based on the requested data, and determine a storage index based on the target image boundaries and the data level of the requested data. The storage index is used to indicate the storage location of the data corresponding to the retrieval request in the target storage level of the preset remote sensing image management system.

[0048] Step S300: Retrieve remote sensing images from the remote sensing image management system according to the storage index and output them to the user terminal.

[0049] This embodiment aims to: establish a remote sensing image management system, store massive amounts of remote sensing images at different levels within the system, provide engine support for the efficient utilization of various types of multi-source remote sensing spatial data in the database, and quickly retrieve the required remote sensing images through storage indexes, avoiding the problems of slow retrieval response in sliced ​​image storage, improving the efficiency of remote sensing data management, and thus enhancing the near real-time application of remote sensing images.

[0050] In this embodiment, the specific application scenario is:

[0051] With the development of my country's Earth observation technology, especially the advancement of the high-resolution Earth observation system major project, my country has basically acquired space-based Earth observation capabilities with high spatial resolution, high temporal resolution, and high spectral resolution. As remote sensing image data accumulates in massive quantities, the application needs of different fields are placing increasingly higher demands on the storage and efficient retrieval of remote sensing image data.

[0052] Remote sensing image files are typically very large, making direct retrieval of the data itself unsuitable for the remote sensing field. Currently, methods using polygon spatial overlay and database traversal to search for large amounts of remote sensing data result in low retrieval efficiency and slow response times, thus hindering near-real-time applications of large-scale remote sensing data.

[0053] As an example, the remote sensing data management method can be applied to a remote sensing data management system, which is applied to a remote sensing data management device.

[0054] As an example, the sources of remote sensing images used for management can be the same or different, such as those from Google Earth, China Satellite Remote Sensing Space Station, etc., and are not limited here.

[0055] As an example, remote sensing data management methods are applied to servers to demonstrate data processing, analysis, and visualization platforms. In the remote sensing image management system, users can set search content (such as search area, remote sensing image resolution, search conditions, etc.) on the front end. Considering that the metadata structure of remote sensing images with different search content is not the same, this method is difficult to directly adapt to the storage and management of remote sensing images from multiple sources. Therefore, the back end converts the input search content into the metadata format in the remote sensing image management system. Based on the converted metadata format, the remote sensing data, that is, the required remote sensing images, are retrieved from the set remote sensing image management system.

[0056] It should be noted that users can set their search content on the front end by entering data, dragging and dropping relevant areas with the mouse, or other methods of entering search requests and requesting data on the front end. No specific restrictions are imposed here.

[0057] Understandably, remote sensing data management methods provide the engine support for the efficient utilization of various types of multi-source remote sensing spatial data in databases. Data is centrally stored on a high-performance cloud platform, providing comprehensive and integrated remote sensing data management and distribution services. All data processing, analysis, and visualization are completed online. One set of data supports multiple applications, and users can obtain the results they need online, realizing a fully online remote sensing spatial information service model encompassing the storage, management, integration, and computation of remote sensing image data.

[0058] The specific steps are as follows:

[0059] Step S100: When a retrieval request for retrieving remote sensing data is received from the user terminal, the request data in the retrieval request is obtained. The request data includes the data level, row and column numbers of the remote sensing data, and the tile organization rules corresponding to the user terminal.

[0060] As an example, a retrieval request refers to a user-input instruction to obtain a desired remote sensing image, which includes requested data. The requested data includes the data level, row and column numbers of the remote sensing data, and the tile organization rules corresponding to the user's data. The data level refers to the accuracy requirements of the remote sensing data, such as resolution level. Different management systems have different tile organization rules, resulting in different data levels. The row and column numbers refer to the position of the requested data within its original tile organization rule system; this can be understood as each level of the management system being divided into a grid of a certain number of rows and columns. Therefore, the boundaries of the requested remote sensing image can be calculated using the data level, row and column numbers, and the tile organization rules corresponding to the user's data. These boundaries are consistent with the storage rules of the remote sensing image management system of this invention, both expressed in latitude and longitude.

[0061] As an example, common tile organization rules (TMS types) include standard WMTS, Google, Mercator, and Tianditu types. For instance, if the user requests a Google tile organization rule, where level 0 of the data layer corresponds to two tiles, then the horizontal axis x is 0 or 1, and the vertical axis y is 0. The resulting tile combinations are represented as (0, 0) and (1, 0). Level 1 of the data layer corresponds to four tiles, and level 2 corresponds to eight tiles. Their row and column representations are essentially the same and will not be elaborated further here. Therefore, the user's search request includes metadata related to the remote sensing image, such as row and column numbers, data layer, tile organization rule, and image acquisition start time. By extracting this metadata, the corresponding metadata of the remote sensing image in the remote sensing image management system is obtained, thus acquiring the remote sensing image.

[0062] Step S200: Calculate the target image boundaries of the requested remote sensing image based on the requested data, and determine a storage index based on the target image boundaries and the data level of the requested data. The storage index is used to indicate the storage location of the data corresponding to the retrieval request in the target storage level of the preset remote sensing image management system.

[0063] As an example, the boundaries of the remote sensing image, i.e. the boundaries of the target image, are calculated based on the data level, row and column numbers in the requested data, and the tile organization rules corresponding to the user terminal.

[0064] The storage index of the target image in the remote sensing image management system of this invention is determined by calculating the boundaries of the target image. It should be noted that the storage index indicates the storage location of the data corresponding to the retrieval request within the preset target storage level of the remote sensing image management system. Each spatial grid storing remote sensing images contains an AVL tree, which stores and manages multiple remote sensing images. The same remote sensing image may be stored in multiple spatial grids; that is, image data is stored in grids that are fully or partially covered by the image.

[0065] It should be noted that the data corresponding to the storage index is the metadata of the remote sensing image, and the corresponding remote sensing image is obtained through the metadata. It can be understood that by retrieving and managing the metadata, direct manipulation of large amounts of raw remote sensing imagery can be avoided, facilitating data storage and improving the efficiency of shared query processing.

[0066] As an example, the step of calculating the target image boundaries of the requested remote sensing image based on the requested data, and determining a storage index based on the target image boundaries and the data hierarchy of the requested data, wherein the storage index is used to indicate the storage location of the data corresponding to the retrieval request in the target storage hierarchy of the preset remote sensing image management system, includes:

[0067] Step S210: Calculate the target image boundaries of the requested remote sensing image based on the requested data;

[0068] Step S220: Based on the data hierarchy of the four boundaries of the target image, determine the corresponding target hierarchy in the preset remote sensing image management system. The target hierarchy includes a storage hierarchy and a virtual hierarchy.

[0069] Step S230: Determine the target grid ID corresponding to the four boundaries of the target image in the target level;

[0070] Step S240: A storage index is formed based on the target grid ID. The storage index is used to indicate the storage location of the data corresponding to the retrieval request in the target storage level of the preset remote sensing image management system.

[0071] As an example, request data from different sources or in different formats may vary. In order to improve the efficiency of data retrieval, the boundaries of the target image that conform to the remote sensing image management system are calculated based on the request data. The boundaries of the target image are expressed in latitude and longitude, which is consistent with the format in the remote sensing image management system and facilitates management.

[0072] Specifically, the pixel coordinates of the tiles in the requested data are converted into latitude and longitude coordinates using the following formula, and the boundaries of the target image in the remote sensing image are calculated.

[0073] (1) Convert latitude and longitude coordinates (Ing, lat) to tile coordinates (tilex, tileY):

[0074] tileX = (Ing + 180) / 360 * 2 level

[0075] tileY=[(1 / 2-ln(tan(lat*π / 180)+sec(lat*π / 180)))*2 level ]

[0076] (2) Convert latitude and longitude coordinates (lng, lat) to pixel coordinates (pixelX, pixelY):

[0077] pizelX = [(lng + 180) / 360 * 2 level *256%256]

[0078] pizeY=[(1-In(tan(lat*π / 180)+sec(lat*π / 180)) / 2π)*2 level *256%256]

[0079] (3) Convert the pixel coordinates (pixelX, pixelY) of tile (tileX, tileY) to latitude and longitude coordinates (Ing, lat):

[0080] Lng = (tileX + (pixelX / 256)) / 2 level *360-180

[0081] lat=arctan(sinh(x-2π*(tileY+pixelY / 256) / 2 level ))*180 / π

[0082] To determine the required remote sensing image's location within the remote sensing image management system, the calculated boundaries of the target image and the data layer are used. This system includes storage layers and virtual layers. Storage layers are the physical layers used to store remote sensing images, while virtual layers are not. However, like storage layers, virtual layers are divided into a certain number of grids, each with a unique ID, used to store metadata for the remote sensing image. In essence, all layers in the remote sensing image management system except for storage layers are virtual layers.

[0083] It should be noted that the hierarchical division of the remote sensing image management system follows conventional partitioning logic. For example, a computer has 32 bits; the coded latitude and longitude location information is converted into 32 bits of binary data in a register, thus allowing for a maximum of 32 layers, each representing a resolution. The user-side management system may have the same or different layers as the remote sensing image management system of this invention, but the thinning logic for each layer is the same. Therefore, the corresponding layer in the remote sensing image management system is obtained based on the data layer in the requested data.

[0084] For example, if the data level in the requested data is 17, then its corresponding level in the remote sensing image management system is also 17. Therefore, by comparing the boundaries of the target image calculated based on the requested data with level 17 in the remote sensing image management system, the spatial grid it occupies can be determined. Since each spatial grid in the remote sensing image management system has a corresponding grid ID, a unique target grid ID can be determined through the spatial grid occupied by the boundaries of the target image. This target grid ID is the storage index, which indicates the storage location of the data corresponding to the retrieval request in the preset target storage level of the remote sensing image management system.

[0085] In this embodiment, the target image boundaries of the requested remote sensing image are calculated from the request data at the front end of the remote sensing image management system. These target image boundaries have been converted into a standardized format within the remote sensing image management system. Therefore, the remote sensing image can be extracted based on the storage index determined by these target image boundaries. This process avoids the existing tiling process and improves the efficiency of remote sensing data retrieval by retrieving data through the storage index.

[0086] Because the remote sensing image management system has storage levels and virtual levels, and the actual metadata of the remote sensing image exists in the spatial grid of the storage level, when retrieving the remote sensing image by determining the target grid ID, if the target level is a virtual level, it is necessary to first convert it to the storage level to determine the storage index.

[0087] As an example, the step of forming a storage index based on the target grid ID includes:

[0088] Step S241: If the target level is a storage level, then a storage index is formed based on the target grid ID;

[0089] Step S242: If the target level is a virtual level, the storage grid ID of the remote sensing image in the target storage level is determined based on the target grid ID and the preset grid mapping relationship, and the storage grid ID forms a storage index.

[0090] As an example, in a remote sensing image management system with 32 levels, if levels 6-8 are set as storage levels and other levels are virtual levels, and if the target level determined by the boundaries of the target image is a storage level, then the ID of the grid occupied by the boundaries of the target image in that storage level is obtained, which is the target grid ID, and a storage index is further formed.

[0091] If the target layer determined by the boundaries of the target image is a virtual layer, then the ID of the grid occupied by the boundaries of the target image in the virtual layer is obtained. This ID is then used to determine the grid ID in the storage layer through a preset grid mapping relationship; this is the storage grid ID. It should be noted that the preset grid mapping relationship refers to the spatial grid mapping relationship between different layers in the remote sensing image management system. Through the spatial grid mapping, the corresponding ID mapping relationship of the spatial grid can be obtained. It can be understood that the mapping rule between upper and lower layers in the remote sensing image management system is that four grids or tiles of the lower layer are mapped to one grid or tile of the upper layer to conform to the general tile organization rules. Therefore, after determining the grid of a certain layer, the corresponding grids of other layers can be determined. The grid ID mapping relationship is basically the same and will not be elaborated here.

[0092] It should be noted that different storage levels or virtual levels correspond to different resolutions. Therefore, the acquisition of remote sensing images is determined by the level of the remote sensing image management system based on the actual stored data, but the output of the remote sensing image is based on the data level of the requested data, thus meeting the user's resolution requirements.

[0093] In this embodiment, by dividing the remote sensing image management system into different storage levels and virtual levels, and distributing massive amounts of remote sensing images, the problem of low data retrieval efficiency caused by storing massive amounts of remote sensing images in a single file and requiring traversal for retrieval is avoided. In other words, the present invention improves the retrieval response speed by establishing a spatial storage index and hierarchical storage, thereby enabling near real-time application of remote sensing data.

[0094] Step S300: Retrieve remote sensing images from the remote sensing image management system according to the storage index and output them to the user terminal.

[0095] Based on the storage index, the metadata stored in the AVL tree of the corresponding spatial grid in the remote sensing image management system is retrieved. Based on this metadata, the remote sensing image corresponding to the retrieval request is obtained, and the remote sensing image is output.

[0096] As an example, based on data retrieval requirements, the retrieved data is filtered, deduplicated, and displayed and output in chronological order. It allows for rapid retrieval based on multiple conditions such as time, space, and data type, returning data objects filtered according to the specified criteria. For example, a spatial reference query returns the result dataset of remote sensing data queried based on spatial reference; a coordinate range query returns the result dataset of remote sensing data within a specified spatial coordinate range; a spatial resolution query returns the remote sensing dataset with a resolution better than a specified spatial resolution; a band query returns the remote sensing dataset containing a specified band; and a custom query returns the remote sensing dataset matching a custom SQL query.

[0097] This invention provides a remote sensing data management method, apparatus, device, storage medium, and product. Compared with the current low efficiency of remote sensing data management, which prevents near real-time applications, this invention, when receiving a retrieval request from a user terminal for retrieving remote sensing data, acquires the request data present in the retrieval request. The request data includes the data level, row and column numbers of the remote sensing data, and the tile organization rules corresponding to the user terminal. Based on the request data, the target image boundaries of the requested remote sensing image are calculated. Based on the target image boundaries and the data level of the request data, a storage index is determined. The storage index indicates the storage location of the data corresponding to the retrieval request in the target storage level of a preset remote sensing image management system. The remote sensing image is retrieved from the remote sensing image management system according to the storage index and output to the user terminal. In other words, by establishing a remote sensing image management system, and storing massive amounts of remote sensing images at different levels within the system, an engine is provided to support the efficient utilization of various types of multi-source remote sensing spatial data in the database. The required remote sensing images can be quickly retrieved through storage indexes, avoiding the problems of slow retrieval response in sliced ​​image storage, improving the efficiency of remote sensing data management, and thus enhancing the near real-time application of remote sensing images.

[0098] Based on the first embodiment described above, a second embodiment of the remote sensing data management method is proposed.

[0099] As an example, before the steps of calculating the target image boundaries of the requested remote sensing image based on the requested data, and determining the storage index based on the target image boundaries and the data hierarchy of the requested data, the method further includes:

[0100] Step A1: Divide the grid corresponding to each grid level according to the preset tile organization rules and preset grid level requirements to obtain multiple spatial grids. Each spatial grid contains a grid ID and an AVL tree. The grid IDs of different grid levels have a grid mapping relationship. The AVL tree stores the metadata of the remote sensing image.

[0101] Step A2: Based on multiple grid levels and the spatial grids corresponding to the grid levels, an initial management system is constructed, wherein the grid level includes one of the storage level and the virtual level;

[0102] Step A3: Obtain the remote sensing images to be added to the database, and store the remote sensing images to be added to the database in the grid level corresponding to the initial management system based on the relevant data information of the remote sensing images to be added to the database, thereby obtaining the remote sensing image management system.

[0103] As an example, the remote sensing image management system is determined based on preset grid level requirements and grid levels. The preset grid level requirements refer to the spatial quantity or resolution information of each level. The grid level refers to the total number of levels divided within the remote sensing image management system.

[0104] For example, given that computers use 32-bit latitude and longitude coordinates, this information is converted into 32-bit binary data in registers. Therefore, a remote sensing image management system capable of accommodating 32 levels can be constructed. Each level's spatial grid covers the entire globe, but the grid density varies between levels, increasing from 0 to 31, meaning that the resolution of the remote sensing images stored at each level is higher. Following a pre-defined tile organization rule, the lowest map level is 0, at which point the world map consists of only one tile. Higher tile levels require more tiles to form the world map, resulting in a more detailed map. A map at a specific level is composed of four tiles cut from tiles at the next lower level, forming a tile pyramid.

[0105] Each spatial grid in all grid levels contains a grid ID, which is used to form a storage index for storing and retrieving remote sensing images. Each spatial grid also contains an AVL tree (balanced binary tree), which is used to store metadata of the remote sensing images and plays a role in balancing data storage.

[0106] Therefore, an initial management system was constructed using 32 levels, as well as each spatial grid, grid ID, and AVL tree within each level.

[0107] It should be noted that while hierarchical storage improves retrieval efficiency, the balance of storage space must also be considered. That is, based on the quantity of remote sensing images, the necessary levels should be selected from the 32 levels to store the remote sensing data. These levels that actually store the data are called storage levels. Other levels serve as storage indexes, establishing associations with the user end, and are not used for actual data storage. However, these virtual levels are not fixed; depending on changes in the amount of remote sensing data, more virtual levels can be reduced or expanded to become storage levels.

[0108] Remote sensing images to be stored in the database are obtained from other platforms or servers and placed into an initial management system, thus forming a remote sensing image management system. During the storage process, the required storage level is determined based on information such as the boundaries, bands, invalid data, and paths of the remote sensing image metadata. The remote sensing image management system offers high retrieval efficiency, simplifies the implementation of remote sensing data applications, and provides balanced computing power.

[0109] As an example, the grid ID is an M-bit binary number, where M is determined based on the grid level and the number of bits in the user-end register. For instance, if the remote sensing image management system is divided into 32 levels, the grid ID is at most a 32-bit binary number; that is, at level 31, the corresponding grid ID is a 32-bit binary number.

[0110] As an example, when there are multiple storage levels, it is necessary to rationally select the levels for storing remote sensing images to avoid storing images intensively in the same level, which would lead to insufficient computing power in that level and idle resources in other levels, resulting in unbalanced storage and further impacting the efficiency of remote sensing image retrieval. Therefore, it is necessary to divide the storage into multiple levels, selecting a default level for primary storage of remote sensing images, and only selecting other levels to store data under certain conditions. The specific steps are as follows:

[0111] Step B1: Determine the grid level whose grid accuracy corresponds to global latitude and longitude accuracy from multiple storage levels as the basic level for storing data, and record the first grid ID and the first AVL tree of the spatial grid in the basic level;

[0112] Step B2: Based on the base level and the preset volume of the remote sensing image, expand multiple storage data entry levels based on the base level, record the second grid ID and second AVL tree of the spatial grid in the entry level, and the tile density of the entry level is less than the tile density of the base level.

[0113] Step B3: Record the third grid ID of the spatial grid in the virtual hierarchy;

[0114] Step B4: Based on the tile organization rules preset by the remote sensing image management system, determine the grid mapping relationship between the second grid ID and the first grid ID and the third grid ID.

[0115] The grid level whose grid accuracy matches that of global latitude and longitude is determined from multiple storage levels is the base level, which is the default primary level for data storage. For example, from the 32 levels of the remote sensing image management system, three levels are selected as storage levels. If one of these three storage levels has a spatial grid that corresponds to one degree of global latitude and longitude, then that storage level is the base level, and it is divided into 180 rows and 360 columns of spatial grids corresponding to global latitude and longitude, with each row / column corresponding to latitude and longitude.

[0116] For example, when the storage level is 8, it corresponds to the basic level. The ID of the spatial grid in the basic level is recorded as the first grid ID, and the AVL tree in the spatial grid is the first AVL tree.

[0117] When a single basic layer is insufficient to store massive amounts of remote sensing imagery, multiple layers are expanded based on the preset imagery volume to form storage layers. The ID of the spatial grid within each storage layer is recorded as the second grid ID, and the corresponding AVL tree for each spatial grid is recorded as the second AVL tree. Assuming there are two storage layers, then with level 8 as the basic layer, the other two storage layers are levels 6 and 7. According to preset tile organization rules, a tile in a map of a certain tile level is composed of four tiles cut from the tiles of the next lower level. Associating these tiles with spatial grids, a level 7 layer bitmap contains 90 rows and 180 columns, and a level 6 layer bitmap contains 45 rows and 90 columns, as shown below. Figure 2 , Figure 2 This is a schematic diagram of the spatial grid partitioning for the storage hierarchy.

[0118] To establish the mapping relationship between spatial grids at all levels in the remote sensing image management system, it is necessary to simultaneously record the third grid ID of the spatial grid in the virtual level. Similarly, according to the preset tile organization rules, a tile in a map of a certain tile level is composed of four tiles cut from tiles of the next lower level. Mapping these tiles to spatial grids determines the mapping relationship between spatial grids at different levels. Since each spatial grid has its unique grid ID, grid IDs at different levels in the remote sensing image management system form a grid mapping relationship. It can be understood that a grid ID in the 8th level can be used to determine the corresponding grid ID in the 7th level based on the grid mapping relationship, thus identifying the spatial grid in the 7th level.

[0119] The above-mentioned logic constructs the initial management system of the remote sensing image management system. By storing a large number of remote sensing images in the initial management system, a mature remote sensing image management system that can be used for data retrieval can be obtained.

[0120] As an example, the steps of acquiring the remote sensing image to be added to the database, and storing the remote sensing image to be added to the database in the grid level corresponding to the initial management system based on the relevant data information of the remote sensing image to be added to the database, to obtain the remote sensing image management system, include:

[0121] Step C1: Obtain the metadata of the remote sensing image to be added to the database;

[0122] Step C2: Calculate the four boundaries of the remote sensing image to be added to the database based on the metadata;

[0123] Step C3: Lock the boundaries of the image to be stored in the database to the basic level. If the boundaries of the image to be stored in the database meet the preset storage conditions when stored in the basic level, then store the remote sensing image to be stored in the first AVL tree of the spatial grid in the basic level and record the corresponding first grid ID to complete the data storage and obtain the remote sensing image management system.

[0124] Step C4: Otherwise, store the remote sensing image to be added to the database in an entry level outside the basic level. Based on the first grid ID and the grid mapping relationship, determine the second grid ID of the remote sensing image to be added to the database when it is stored in the entry level, and complete the data entry to obtain the remote sensing image management system.

[0125] The metadata of the remote sensing image to be added to the database is obtained. This metadata includes information such as the image's hierarchy, row and column numbers, and bands within its own management system. The boundaries of the image to be added to the database are calculated using this metadata. During storage, the base level is initially locked for storing the image. To improve the computational power of each level and balance storage efficiency, preset entry conditions are set. When these preset conditions are met, the metadata of the image is stored at the base level. If the preset conditions are not met, the metadata is stored at another entry level. For example, if the preset entry condition is that the number of spatial grids for storing the image's metadata is greater than 9, the image is moved up one level for storage.

[0126] As an example, assuming storage levels are 6, 7, and 8, with level 8 being the base level and levels 6 and 7 being the entry levels, the entry storage process is as follows: Based on the boundaries of the entry image, it is directly locked into the spatial grid of the level 8 bitmap, and the corresponding grid ID is determined. If the boundaries of the entry image occupy more than 9 spatial grids in level 8, then it is moved up one bitmap level, becoming level 7. Level 7 continues to check if the boundaries of the entry image occupy more than 9 spatial grids in level 7. If so, it is moved up one level, up to a maximum of level 6, which is the highest level of storage for storing remote sensing data.

[0127] The metadata of the remote sensing image to be added to the database is managed by the AVL tree of the spatial grid it occupies. That is, when the image is directly locked into the spatial grid of the 8th level bitmap based on its boundaries, the corresponding first grid ID has been determined. After determining the final storage level of the metadata of the remote sensing image to be added to the database, the second grid ID of the remote sensing image to be added to the database is determined based on the first grid ID, the final storage level, and the grid mapping relationship. This completes the data entry of the remote sensing image to be added to the database and obtains the remote sensing image management system. Remote sensing images can be retrieved efficiently and quickly from this remote sensing image management system.

[0128] As an example, before storing the metadata of the remote sensing image to be imported into the database, the legitimacy of the image is verified. Legitimacy refers to whether the image can be mapped to a specific location, i.e., whether it is mapped to a specific location. This can be determined through TIFF data parsing using the GDL library. If legitimate, the boundaries of the image to be imported are calculated using the coordinate information (usually the latitude and longitude of the top-left origin), resolution, row and column numbers, etc., contained in the image's metadata.

[0129] In this embodiment, a unified grid index is used to divide the data into grids according to global latitude and longitude. Each data entry is assigned a grid code, and a spatial grid index is built based on the code. This avoids polygonal spatial overlay and database traversal. Even with a huge amount of data, it can still ensure high search efficiency and support the application problem of online fast retrieval of massive amounts of data.

[0130] The remote sensing data management device provided by the present invention is described below. The remote sensing data management device described below can be referred to in correspondence with the remote sensing data management method described above.

[0131] The present invention also provides a remote sensing data management device, the device comprising:

[0132] The request receiving module is used to obtain the request data in the retrieval request when it receives a retrieval request for retrieving remote sensing data sent by the user terminal. The request data includes the data level, row and column numbers of the remote sensing data, and the tile organization rules corresponding to the user terminal.

[0133] The index determination module is used to calculate the target image boundaries of the requested remote sensing image based on the request data, and determine the storage index based on the target image boundaries and the data level of the request data. The storage index is used to indicate the storage location of the data corresponding to the retrieval request in the target storage level of the preset remote sensing image management system.

[0134] The data extraction module is used to retrieve remote sensing images from the remote sensing image management system according to the storage index and output them to the user terminal.

[0135] And / or, the index determination module further includes:

[0136] The first boundary calculation submodule is used to calculate the boundary of the target image of the requested remote sensing image based on the requested data.

[0137] The hierarchical determination submodule is used to determine the corresponding target level in the preset remote sensing image management system based on the data hierarchy of the target image's boundaries. The target level includes a storage level and a virtual level.

[0138] The grid determination submodule is used to determine the target grid ID corresponding to the four boundaries of the target image in the target level;

[0139] The index determination submodule is used to form a storage index based on the target grid ID. The storage index is used to indicate the storage location of the data corresponding to the retrieval request in the target storage level of the preset remote sensing image management system.

[0140] And / or, the index determination submodule further includes:

[0141] The first index determining unit is used to form a storage index based on the target grid ID if the target level is a storage level;

[0142] The second index determination unit is used to determine the storage grid ID of the remote sensing image in the target storage level based on the target grid ID and the preset grid mapping relationship if the target level is a virtual level, and the storage grid ID forms a storage index.

[0143] And / or, the device further includes:

[0144] The hierarchical partitioning module is used to partition the grid corresponding to each grid level according to preset tile organization rules and preset grid level requirements to obtain multiple spatial grids. Each spatial grid contains a grid ID and an AVL tree. The grid IDs between different grid levels have a grid mapping relationship. The AVL tree stores the metadata of the remote sensing image. The remote sensing image management system is determined according to the preset grid level requirements and grid levels.

[0145] The first construction module is used to construct an initial management system based on multiple grid levels and the spatial grids corresponding to the grid levels, wherein the grid levels include one of the storage level and the virtual level;

[0146] The second construction module is used to acquire remote sensing images to be stored in the database, and store the remote sensing images to be stored in the database into the grid level corresponding to the initial management system based on the relevant data information of the remote sensing images to be stored in the database, thereby obtaining the remote sensing image management system.

[0147] The grid ID is an M-bit binary number, where M is determined based on the grid level and the number of bits in the user-side register.

[0148] And / or, the device further includes:

[0149] The first-level determination module is used to determine the grid level whose grid accuracy corresponds to the global latitude and longitude accuracy from multiple storage levels as the basic level for storing data, and to record the first grid ID and the first AVL tree of the spatial grid in the basic level;

[0150] The second-level determination module is used to expand multiple storage data entry levels based on the basic level and the preset volume of the remote sensing image, and to record the second grid ID and second AVL tree of the spatial grid in the entry level. The tile density of the entry level is less than the tile density of the basic level.

[0151] A grid recording module is used to record the third grid ID of the spatial grid in the virtual hierarchy;

[0152] The relationship determination module is used to determine the grid mapping relationship between the second grid ID and the first grid ID and the third grid ID based on the tile organization rules preset in the remote sensing image management system.

[0153] And / or, the second building module further includes:

[0154] The data acquisition submodule is used to acquire metadata of the remote sensing images to be added to the database;

[0155] The second boundary calculation submodule is used to calculate the boundary of the remote sensing image to be added to the database based on the metadata.

[0156] The first data storage submodule is used to lock the boundaries of the imported image to the basic level. If the boundaries of the imported image meet the preset import conditions when stored in the basic level, the remote sensing image to be imported is stored in the first AVL tree of the spatial grid in the basic level, and the corresponding first grid ID is recorded to complete the data import and obtain the remote sensing image management system.

[0157] The second data storage submodule is used to otherwise store the remote sensing image to be stored in an entry level outside the basic level, and determine the second grid ID of the remote sensing image to be stored in the entry level according to the first grid ID and the grid mapping relationship, so as to complete the data entry and obtain the remote sensing image management system.

[0158] The specific implementation of the remote sensing data management device of the present invention is basically the same as the embodiments of the remote sensing data management method described above, and will not be repeated here.

[0159] Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3 As shown, the electronic device may include a processor 810, a communications interface 820, a memory 830, and a communication bus 840. The processor 810, communications interface 820, and memory 830 communicate with each other via the communication bus 840. The processor 810 can call logical instructions in the memory 830 to execute a remote sensing data management method. This method includes: when receiving a retrieval request from a user terminal for retrieving remote sensing data, acquiring the request data present in the retrieval request, the request data including the data level, row and column numbers of the remote sensing data, and the tile organization rules corresponding to the user terminal; calculating the target image boundaries of the requested remote sensing image based on the request data; determining a storage index based on the target image boundaries and the data level of the request data, the storage index indicating the storage location of the data corresponding to the retrieval request in the target storage level of a preset remote sensing image management system; retrieving the remote sensing image from the remote sensing image management system according to the storage index and outputting it to the user terminal.

[0160] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0161] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the remote sensing data management method provided by the above methods. The method includes: when receiving a retrieval request for retrieving remote sensing data sent by a user terminal, obtaining request data existing in the retrieval request, the request data including the data level, row and column numbers of the remote sensing data, and the tile organization rules corresponding to the user terminal; calculating the target image boundaries of the requested remote sensing image based on the request data, determining a storage index based on the target image boundaries and the data level of the request data, the storage index indicating the storage location of the data corresponding to the retrieval request in the target storage level of a preset remote sensing image management system; retrieving the remote sensing image from the remote sensing image management system according to the storage index, and outputting it to the user terminal.

[0162] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the remote sensing data management method provided by the above methods. The method includes: when receiving a retrieval request for retrieving remote sensing data sent by a user terminal, acquiring request data present in the retrieval request, the request data including the data level, row and column numbers, and tile organization rules corresponding to the user terminal of the remote sensing data; calculating the target image boundaries of the requested remote sensing image based on the request data; determining a storage index based on the target image boundaries and the data level of the request data, the storage index indicating the storage location of the data corresponding to the retrieval request in the target storage level of a preset remote sensing image management system; retrieving the remote sensing image from the remote sensing image management system according to the storage index and outputting it to the user terminal.

[0163] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0164] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0165] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method of managing remote sensing data, characterized in that, The method comprises: When receiving a retrieval request for retrieving remote sensing data sent by a user terminal, obtaining request data existing in the retrieval request; According to the request data, the target image four of the requested remote sensing image is calculated, and the storage index is determined based on the target image four and the data level of the request data. The storage index is used to indicate the storage position of the data corresponding to the retrieval request in the target storage level of the preset remote sensing image management system; According to the storage index, the remote sensing image is called from the remote sensing image management system and output to the user terminal; The step of calculating the target image four of the requested remote sensing image according to the request data, and determining the storage index based on the target image four and the data level of the request data, comprises: According to the request data, the target image four of the requested remote sensing image is calculated, and the request data includes the data level, row and column number of the remote sensing data, and the tile organization rule corresponding to the user terminal; Based on the data level of the target image four, the corresponding target level in the preset remote sensing image management system is determined. The target level includes a storage level and a virtual level; Determine the target grid ID corresponding to the target image four in the target level; Based on the target grid ID, a storage index is formed, which is used to indicate the storage position of the data corresponding to the retrieval request in the target storage level of the preset remote sensing image management system.

2. The remote sensing data management method of claim 1, wherein, The step of forming a storage index based on a target grid ID comprises: If the target level is a storage level, a storage index is formed based on the target grid ID; If the target level is a virtual level, the storage grid ID of the remote sensing image in the target storage level is determined based on the target grid ID and the preset grid mapping relationship, and the storage grid ID forms a storage index.

3. The method of claim 1, wherein, The remote sensing image management system is determined according to the preset grid level requirement and grid level, Before the step of calculating the target image four of the requested remote sensing image according to the request data, and determining the storage index based on the target image four and the data level of the request data, the method further comprises: According to the preset tile organization rule and the preset grid level requirement, each grid corresponding to each grid level is divided to obtain a plurality of spatial grids. The spatial grid contains a grid ID and an AVL tree. The grid IDs between different grid levels have a grid mapping relationship. The metadata of the remote sensing image is stored on the AVL tree; Based on the plurality of grid levels and the spatial grid corresponding to the grid level, an initial management system is constructed. The grid level includes one level of the storage level and the virtual level; Obtain the to-be-stored remote sensing image, and store the to-be-stored remote sensing image in the grid level corresponding to the initial management system based on the related data information of the to-be-stored remote sensing image, to obtain a remote sensing image management system.

4. The method of claim 3, wherein, The method further comprises: From the plurality of storage levels, determine the grid level corresponding to the grid precision and the global latitude and longitude precision as the basic level for storing data, and record the first grid ID and the first AVL tree of the spatial grid in the basic level; According to the base level and the remote sensing image preset volume, a plurality of storage data warehouse levels are extended based on the base level, a second grid ID of a spatial grid in the warehouse level and a second AVL tree are recorded, and a tile density of the warehouse level is less than a tile density of the base level; A third grid ID of a spatial grid in the virtual level is recorded; Based on a tile organization rule preset by the remote sensing image management system, a grid mapping relationship of the second grid ID, the first grid ID and the third grid ID is determined.

5. The method of claim 4, wherein, The step of obtaining the to-be-warehoused remote sensing image, storing the to-be-warehoused remote sensing image into a grid level corresponding to the initial management system based on related data information of the to-be-warehoused remote sensing image, and obtaining the remote sensing image management system, includes: Obtaining metadata of the to-be-warehoused remote sensing image; According to the metadata, the warehouse image four corners of the to-be-warehoused remote sensing image are calculated; The warehouse image four corners are locked in the base level, and if the warehouse image four corners meet the preset warehouse conditions when stored in the base level, the to-be-warehoused remote sensing image is stored in the first AVL tree of the spatial grid in the base level, and the corresponding first grid ID is recorded, the data warehouse is completed, and the remote sensing image management system is obtained; Otherwise, the to-be-warehoused remote sensing image is stored in the warehouse level outside the base level, the second grid ID of the to-be-warehoused remote sensing image stored in the warehouse level is determined according to the first grid ID and the grid mapping relationship, the data warehouse is completed, and the remote sensing image management system is obtained.

6. A remote sensing data management apparatus, characterized by, The device includes: The request receiving module is configured to, when receiving a retrieval request for retrieving remote sensing data sent by a user terminal, obtain request data present in the retrieval request, the request data including a data level, row and column numbers of remote sensing data, and a tile organization rule corresponding to the user terminal; The index determining module is configured to calculate a target image four corners of the requested remote sensing image according to the request data, and determine a storage index based on the target image four corners and the data level of the request data, the storage index being used to indicate a storage position of data corresponding to the retrieval request in a target storage level of a preset remote sensing image management system; The data extraction module is configured to retrieve remote sensing images from the remote sensing image management system according to the storage index, and output the remote sensing images to the user terminal; The index determining module further includes: The first four corners calculating submodule is configured to calculate a target image four corners of the requested remote sensing image according to the request data; The level determining submodule is configured to determine a target level corresponding to the target image four corners in the preset remote sensing image management system based on the data level of the target image four corners, the target level including a storage level and a virtual level; The grid determining submodule is configured to determine a target grid ID corresponding to the target image four corners in the target level; The index determining submodule is configured to form a storage index based on the target grid ID, the storage index being used to indicate a storage position of data corresponding to the retrieval request in a target storage level of a preset remote sensing image management system.

7. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the remote sensing data management method according to any one of claims 1-5 when executing the program.

8. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program implements the remote sensing data management method according to any one of claims 1-5 when executed by the processor.

9. A computer program product comprising a computer program, characterized in that, The computer program implements the remote sensing data management method according to any one of claims 1-5 when executed by the processor.

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