A method for managing remote sensing data based on a grid collection object

Abstract

The application discloses a kind of remote sensing data management methods based on grid collection object, comprising: the original remote sensing data obtained in platform front-end data source is stored in the mode of data block, and the attribute information corresponding to each data block is obtained from platform general control computer;Wherein, the attribute information includes spatial latitude and longitude information;Each data block is split according to corresponding attribute information to obtain spatial coding set;The index table corresponding to the spatial coding set and the data block is established;Wherein, the spatial coding set includes several spatial codes, and each spatial code satisfies the preset mapping relationship between data block. The application guarantees the real-time of satellite remote sensing data application, and improves the utilization of satellite resources.

Description

Technical Field

[0001] This invention belongs to the field of remote sensing data processing technology, specifically relating to a remote sensing data management method based on grid set objects. Background Technology

[0002] With the advancement of technology, people can obtain extremely rich remote sensing data, and this abundance is accompanied by the rapid development of data services. In spatial information management systems, the classification, storage, organization, and mapping of remote sensing data are crucial.

[0003] Currently, the most common classification, storage, organization, and mapping of remote sensing data is based on the ground, such as... Figure 1 As shown, the process of classifying, storing, and organizing remote sensing data includes: (1) the satellite acquires the original remote sensing image corresponding to the ground information; (2) the satellite sends the acquired original remote sensing image to the ground receiving station through the data transmission system; (3) the ground receiving station receives the original remote sensing data and sends the original remote sensing image to the ground processing station, which performs data gridding processing and classifies, stores, and organizes the data. In the storage process, standard storage equipment is used, such as disk arrays and storage servers. When reading remote sensing data, the original data can only be read after obtaining the storage node information and then receiving services from the intermediate layer of the standard storage configuration. The data reading path is significantly longer and the efficiency is lower. Therefore, researchers are now shifting their focus to satellite-based processing.

[0004] However, the current on-board remote sensing data storage and management strategy is an unstructured processing method with extremely simple processing methods. It cannot directly establish a structured relationship between the current remote sensing data and multiple scales such as geographical location, space, and time, resulting in the lack of real-time application of on-board remote sensing data and insufficient utilization of satellite resources. Summary of the Invention

[0005] To address the aforementioned problems in the existing technology, this invention provides a remote sensing data management method based on grid assemblies.

[0006] In a first aspect, embodiments of the present invention provide a remote sensing data management method based on a grid set object, comprising:

[0007] The raw remote sensing data obtained from the platform's front-end data source is stored in data blocks, and the attribute information corresponding to each data block is obtained from the platform's central control computer; wherein, the attribute information includes spatial latitude and longitude information;

[0008] Each data block is partitioned according to its corresponding attribute information to obtain a spatial encoding set;

[0009] Establish an index table corresponding to the spatial encoding set and the data block; wherein the spatial encoding set includes several spatial codes, and each spatial code satisfies a preset mapping relationship with the data block.

[0010] In one embodiment of the present invention, the step of partitioning each data block according to corresponding attribute information to obtain a spatial coding set includes:

[0011] The Earth's space is divided into several first spatial grids using a preset spatial grid partitioning method; wherein, the spatial grid partitioning method includes GeoSOT, GeoHash and GJB8896-2017;

[0012] The corresponding second space grid is obtained from several first space grids based on the attribute information corresponding to each data block;

[0013] The spatial coding set is obtained by encoding all second spatial grids using a multi-scale spatial grid coding method.

[0014] In one embodiment of the present invention, establishing the index table corresponding to the spatial coding set and the data block includes:

[0015] Establish first index information between data blocks and file codes; wherein the file codes are used to determine the storage file of the data blocks;

[0016] Establish a second index information between the file encoding and the spatial encoding set;

[0017] The index table is established based on the first index information and the second index information.

[0018] In one embodiment of the present invention, the mapping relationship between each spatial code and data block includes at least one of the following: a one-to-one mapping between spatial codes and data blocks, a many-to-one mapping between spatial codes and data blocks, and a one-to-many mapping between spatial codes and data blocks.

[0019] Secondly, embodiments of the present invention provide a remote sensing data management method based on grid set objects, including:

[0020] The raw remote sensing data obtained from the platform's front-end data source is stored in data blocks, and the attribute information corresponding to each data block is obtained from the platform's central control computer; wherein, the attribute information includes time information and spatial latitude and longitude information;

[0021] Each data block is encoded according to its corresponding time information to obtain a time code;

[0022] Each data block is divided according to its corresponding spatial latitude and longitude information to obtain a spatial coding set;

[0023] An index table is established corresponding to the time code, the spatial code set, and the data block; wherein, there is a one-to-one mapping relationship between the time code and the data block; the spatial code set includes several spatial codes, and each spatial code satisfies a preset mapping relationship with the data block.

[0024] In one embodiment of the present invention, the step of encoding each data block according to corresponding time information to obtain time encoding includes:

[0025] The time code is obtained by encoding each data block according to the corresponding time information using a single-scale time grid coding method.

[0026] In one embodiment of the present invention, the step of encoding each data block according to corresponding time information to obtain time encoding includes:

[0027] The time code is obtained by encoding each data block according to the corresponding time information using a multi-scale time grid coding method.

[0028] In one embodiment of the present invention, the step of subdividing each data block according to the corresponding spatial latitude and longitude information to obtain a spatial coding set includes:

[0029] The Earth's space is divided into several first spatial grids using a preset spatial grid partitioning method; wherein, the spatial grid partitioning method includes GeoSOT, GeoHash and GJB8896-2017;

[0030] Based on the spatial latitude and longitude information corresponding to each data block, the corresponding second spatial grid is obtained from several first spatial grids;

[0031] The spatial coding set is obtained by encoding all second spatial grids using a multi-scale spatial grid coding method.

[0032] In one embodiment of the present invention, establishing the index table corresponding to the time code, the spatial code set, and the data block includes:

[0033] Establish first index information between data blocks and file codes; wherein the file codes are used to determine the storage file of the data blocks;

[0034] Establish a second index information between the file encoding and the spatial encoding set;

[0035] Establish a third index information between the spatial encoding set and the temporal encoding;

[0036] The index table is established based on the first index information, the second index information, and the third index information.

[0037] In one embodiment of the present invention, the mapping relationship between each spatial code and data block includes at least one of the following: a one-to-one mapping between spatial codes and data blocks, a many-to-one mapping between spatial codes and data blocks, and a one-to-many mapping between spatial codes and data blocks.

[0038] The beneficial effects of this invention are:

[0039] The remote sensing data management method based on grid-based objects proposed in this invention establishes a structured relationship between current remote sensing data and geographical location, space, etc., during the on-board storage mapping process, ensuring the real-time application of satellite remote sensing data and improving the utilization rate of satellite resources. This grid-based storage method breaks away from the traditional ground storage method that requires standard storage equipment, and can directly realize the storage mapping of on-board storage media through index tables. At the same time, in the subsequent data reading process, data is directly read on-board through index tables. Grid-based data storage mapping management is closer to the underlying storage medium, resulting in shorter data reading paths and higher efficiency.

[0040] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of the traditional ground data storage process;

[0042] Figure 2 This is a flowchart illustrating a remote sensing data management method based on a grid collection object provided in an embodiment of the present invention;

[0043] Figure 3 This is a schematic diagram of spatial coding corresponding to an example remote sensing data provided in an embodiment of the present invention;

[0044] Figure 4 a~ Figure 4 b is a schematic diagram illustrating the mapping relationship between spatial coding and data blocks in the remote sensing data management method based on grid set objects provided in this embodiment of the invention;

[0045] Figure 5 a to 5c are schematic diagrams illustrating the mapping relationship between spatial codes and data blocks corresponding to example remote sensing data provided in the embodiments of the present invention;

[0046] Figure 6 This is a flowchart illustrating another remote sensing data management method based on a grid collection object provided in an embodiment of the present invention;

[0047] Figure 7a to 7b are schematic diagrams illustrating the mapping relationship between spatial coding and data blocks in another remote sensing data management method based on grid set objects provided in this embodiment of the invention.

[0048] Figure 8 a to 8b are time-encoding diagrams corresponding to two example remote sensing data provided in the embodiments of the present invention;

[0049] Figure 9 This is a flowchart illustrating another remote sensing data management method based on a grid collection object provided in an embodiment of the present invention. Detailed Implementation

[0050] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0051] Example 1

[0052] Because current on-board remote sensing data storage and management strategies suffer from unstructured nature, satellite remote sensing data applications lack real-time capability and satellite resources are not fully utilized. Therefore, this invention proposes a remote sensing data management method based on grid set objects.

[0053] Firstly, please see Figure 2 This invention proposes a remote sensing data management method based on grid set objects, which includes the following steps:

[0054] S201. The raw remote sensing data obtained from the platform's front-end data source is stored in the form of data blocks, and the attribute information corresponding to each data block is obtained from the platform's central control computer; wherein, the attribute information includes spatial latitude and longitude information.

[0055] Specifically, in this embodiment of the invention, raw remote sensing data is acquired through a platform front-end data source and stored in data blocks. For example, the platform front-end data source can be raw remote sensing data acquired by an onboard payload camera and stored on the satellite. However, the acquisition method is not limited to the onboard payload camera; raw remote sensing data can also be acquired through drones, aerospace equipment, etc. Correspondingly, auxiliary data is acquired through the platform's central control computer, such as auxiliary information acquired through a satellite-based computer. Auxiliary data can include the satellite's attitude, orbit, time, etc. Based on the satellite's orbit, attitude, time, etc., and combined with the optical path design of the sensors in the imaging subsystem, the positioning processing of the remote sensing data is completed, forming the attribute information of the remote sensing data. This attribute information includes time information and spatial latitude and longitude information. The auxiliary data varies depending on the scenario and is determined according to the actual situation of the scenario. There are many solutions for the onboard imaging subsystem, such as optical remote sensing imaging systems, radar remote sensing imaging systems, and infrared remote sensing imaging systems.

[0056] For storing raw remote sensing data on satellite in data blocks, the size of the data blocks when storing remote sensing data is unlimited. Each data block can obtain its corresponding attribute information through the platform's central control computer. This attribute information will be used for subsequent grid coding.

[0057] S202. Divide each data block according to its corresponding attribute information to obtain a spatial encoding set.

[0058] Specifically, current on-board remote sensing data storage and management strategies do not establish a multi-scale structured relationship between current remote sensing data and geographical location, space, and time, resulting in a lack of real-time application of on-board remote sensing data and insufficient utilization of satellite resources. To address this issue, this invention proposes an on-board remote sensing data storage mapping and management method. This method considers the spatial latitude and longitude information of the data during the storage mapping process, and establishes a multi-scale structured remote sensing data storage mapping and management method based on this spatial latitude and longitude information.

[0059] Next, we will introduce how to combine spatial latitude and longitude information to establish a multi-scale remote sensing data storage and mapping structure.

[0060] This invention embodiment divides each data block into a spatially encoded set according to its corresponding attribute information (spatial latitude and longitude information), including the following steps:

[0061] A1. The Earth's space is divided into several first spatial grids using a preset spatial grid partitioning method.

[0062] Specifically, a spatial grid is a method for calibrating spatial geographic location information. In this embodiment of the invention, the latitude and longitude space of the Earth is divided into several first spatial grids according to a preset spatial grid subdivision method. Among them, the spatial grid subdivision method includes GeoSOT, GeoHash, and GJB8896-2017, but is not limited to these three methods.

[0063] Taking GeoSOT as an example, the core idea of ​​GeoSOT grid partitioning is based on the principle of Earth partitioning. By dividing the Earth's surface according to its dimensions and considering the characteristics of Earth's space, the Earth can be partitioned into a grid as follows: First, the latitudinal space is expanded to make its spatial range consistent with that of the longitude space, resulting in an expanded latitude-longitude space. Second, this expanded latitude-longitude space is divided into hierarchical grids using the GeoSOT partitioning method, resulting in several first-level spatial grids. GeoSOT can be used to explore and construct a dedicated grid suitable for spatial information or data organization. On the one hand, this grid can have good scale aggregation and locational correlation with existing major spatial information organization grids on Earth; on the other hand, a location identification system more suitable for spatial information organization can be built on this grid, providing a reference basis for the geographic grid identification and consistent indexing of global spatial information locations, thus solving the problems of unified locational organization and regional correlation scheduling of spatial information.

[0064] The several first spatial codes obtained in the embodiments of the present invention can be understood as projections of the Earth observation area containing the original remote sensing data onto the grid coding plane in the smallest grid form. These first spatial codes represent a coarse-resolution spatial location calibration of the Earth observation area containing the original remote sensing data. For example, assuming the current Earth observation area is a single image of the entire Chinese landscape, then the first spatial grid is a large grid encompassing the longitude range of 73°33′E to 135°05′E and the latitude range of 3°51′N to 53°33′N of China.

[0065] A2. Obtain the corresponding second space grid from several first space grids based on the attribute information corresponding to each data block.

[0066] Specifically, as shown in A1, the first grid code is a coarse-resolution spatial location determination. Within the first grid code, the Earth projection of the original remote sensing data area can be further precisely located and depicted. That is, any data block can be represented by several fine-resolution spatial grids using its spatial latitude and longitude information. For example, if the first grid code cannot accurately locate the spatial location of Xi'an, Shaanxi, China, the first grid code corresponding to Xi'an, Shaanxi, China can be further subdivided until the spatial location of Xi'an, Shaanxi, China can be accurately located. Figure 3 As shown, the entire Figure 3 This can be understood as the first grid encoding form. Figure 3 The gray rectangular area represents the projection of a satellite's original remote sensing image of the Earth onto a gridded map. Multiple levels of grids, as shown in the figure, are used to label the geographic location information of this original remote sensing image. The remote sensing image and the grids that label its location have two relationships: containment and intersection. Figure 3The spatial coding set corresponding to remote sensing data includes 1 to 11. This is just an illustration; 1 to 11 represent only a portion of the spatial coding for this remote sensing data. These spatial coding sets are used to describe the spatial relationship information of the remote sensing image. It can be seen that any data block can be represented using... Figure 3 The data can be described by several spatial grids, that is, the first spatial grids obtained in A1 can be further subdivided to find the second spatial grid that describes the data block more accurately.

[0067] A3. A spatial coding set is obtained by encoding all second spatial grids using a multi-scale spatial grid coding method.

[0068] Specifically, since hardware processing often uses fixed-length data, especially for remote sensing data, which commonly exhibits varying resolutions and coverage areas, different scales of spatial grids are necessary for on-board organization and storage. Therefore, it is essential to standardize the variable-length multi-scale spatial grid encoding. The encoding method that uses fixed-length integer codes to represent multi-scale information is called multi-scale integer encoding, which is the multi-scale spatial grid encoding method employed. For example, a 31-level integer grid encoding method using an inverted quadtree can be used.

[0069] Based on the characteristics of the multi-scale spatial grid integer encoding, the origin of the coordinates of each second spatial grid is determined, and multi-scale integer encoding is performed on the origin of the coordinates of each second spatial grid to obtain the second spatial grid encoding corresponding to each second spatial grid.

[0070] S103. Establish an index table corresponding to the spatial code set and the data block; wherein, the spatial code set includes several spatial codes, and each spatial code and the data block satisfy a preset mapping relationship.

[0071] Specifically, the spatial coding set of the present invention includes several spatial codes, and the mapping relationship between each spatial code and the data block includes at least one of the following: a one-to-one mapping between the spatial code and the data block, a many-to-one mapping between the spatial code and the data block, and a one-to-many mapping between the spatial code and the data block. Figure 4 a~ Figure 4 b clearly demonstrates several mapping relationships between spatial encoding and data blocks, such as Figure 4 In file a, spatial encoding 1, spatial encoding 2, spatial encoding 3, and spatial encoding 4 in files 1, 2, and 3 have a one-to-one mapping relationship with data block 1, data block 2, data block 3, and data block 4, respectively. Figure 4In file b, spatial code 1 in file 1 has a one-to-many mapping relationship with data block 1, data block 2, and data block 3, while spatial code 2, spatial code 3, and spatial code 4 have a many-to-one mapping relationship with data block 4. Within the same file, these three mapping relationships can be combined arbitrarily.

[0072] by Figure 3 Taking the spatial coding of a set of remote sensing data as an example, Figure 5 a~ Figure 5 c clearly shows the mapping relationship between the spatial code corresponding to the remote sensing data and its divided data blocks. Figure 5 'a' represents a one-to-one mapping between spatial codes and data blocks. Figure 5 b represents a one-to-many mapping relationship between spatial encoding and data blocks. Figure 5 c represents a many-to-one mapping relationship between spatial encoding and data blocks.

[0073] Under the above mapping relationship, an index table corresponding to the spatial encoding set and the data block is established, including the following steps:

[0074] B1. Establish the first index information between the data block and the file encoding; wherein, the file encoding is used to determine the storage file of the data block.

[0075] Specifically, data storage typically involves simple auxiliary processing, such as using a file system to store data in corresponding files, each with a pre-defined file code. However, this file storage is merely simple data storage and does not comprehensively consider the relationship between remote sensing data and geographical location, leading to unreal-time applications of satellite remote sensing data and insufficient utilization of satellite resources. Therefore, this invention integrates file system and spatial location information for remote sensing data storage. During data storage, a first index is established between data blocks and file codes, indicating the file location where the data block is stored. The file code determines the storage file for the data block. A file system corresponding to a file code can store only one data block or multiple data blocks, depending on the specific needs.

[0076] B2. Establish a second index information between the file encoding and the spatial encoding set.

[0077] Specifically, based on B1, this embodiment of the invention establishes a second index information between the file encoding and the spatial encoding set. This second index information can indicate the file location corresponding to the spatial encoding set, and can also indicate the file location corresponding to each spatial encoding in the spatial encoding set.

[0078] B3. Create an index table based on the first index information and the second index information.

[0079] Specifically, a final index table is established using first and second index information. This index table shows the index relationship between file encoding and spatial encoding sets, thereby achieving gridded storage. This gridded storage breaks away from the traditional terrestrial storage method that requires standard storage equipment, as it can directly map the storage media on the satellite through the index table. Furthermore, during subsequent data retrieval, data is read directly from the index table within the on-board storage media. Gridded data storage mapping management is closer to the underlying storage media, resulting in shorter data retrieval paths, higher efficiency, and, when combined with a file system, is more suitable for the actual conditions of on-orbit operation.

[0080] In summary, the remote sensing data management method based on grid-based objects proposed in this invention establishes a structured relationship between current remote sensing data and geographical location, space, etc., during the on-board storage mapping process, ensuring the real-time application of satellite remote sensing data and improving the utilization rate of satellite resources. This grid-based storage method breaks away from the traditional ground-based storage method that requires standard storage equipment, directly achieving storage mapping of on-board storage media through an index table. Furthermore, during subsequent data retrieval, data is directly read on-board through the index table. Grid-based data storage mapping management is closer to the underlying storage medium, resulting in shorter data retrieval paths and higher efficiency. The combination of this invention with a file system is more suitable for the actual situation of on-orbit operation. The storage mapping method of this invention allows multiple satellites to use the same grid coding method, effectively improving the accuracy of satellite resource retrieval, reducing the pressure on the ground-to-ground data downlink channels and ground processing stations, and in the future, it can support the realization of an "on-board data storage center" and provide "virtual remote sensing satellite services."

[0081] Secondly, please see Figure 6 This invention also proposes a remote sensing data management method based on grid set objects, which includes the following steps:

[0082] S601. The raw remote sensing data obtained from the platform's front-end data source is stored in data blocks, and the attribute information corresponding to each data block is obtained from the platform's central control computer; the attribute information includes time information and spatial latitude and longitude information.

[0083] S602. Encode each data block according to the corresponding time information to obtain a time code;

[0084] S603. Divide each data block according to the corresponding spatial latitude and longitude information to obtain a spatial coding set;

[0085] S604. Establish an index table corresponding to the time code, spatial code set and data block; wherein, there is a one-to-one mapping relationship between the time code and the data block; the spatial code set includes several spatial codes, and each spatial code satisfies a preset mapping relationship with the data block.

[0086] Specifically, data storage typically employs simple auxiliary processing methods, such as timestamps, strings, and time counts, scattered across file systems, database systems, and various programming languages. However, the reality is that big data contains diverse temporal information with varying scales and precision. Some data uses instantaneous counts, some precise time periods, and some fuzzy time ranges. Currently, this temporal information is not fully utilized. Therefore, this embodiment of the invention, while considering the aforementioned spatial latitude and longitude information, also incorporates the temporal information of remote sensing data during the storage mapping process.

[0087] In S501 to S504, the spatial latitude and longitude information is processed in the same way as in S101 to S103 above, and the spatial coding also includes several spatial codes. The mapping relationship between each spatial code and the data block includes at least one of the following: a one-to-one mapping between the spatial code and the data block, a many-to-one mapping between the spatial code and the data block, and a one-to-many mapping between the spatial code and the data block. Figure 7 a~ Figure 7 b clearly demonstrates the mapping relationship between spatial encoding and data blocks.

[0088] The following section provides a detailed explanation of the time information of the added remote sensing data.

[0089] As seen in S101, the attribute information corresponding to each data block obtained from the platform's central control computer can also include time information. In S502, each data block is encoded according to its corresponding time information to obtain a time code, specifically:

[0090] This invention proposes an optional scheme that uses a single-scale time grid coding method to encode each data block according to its corresponding time information to obtain a time code. The specific process for generating the single-scale time code is as follows:

[0091] Convert a time period in input form into a single-scale time period integer code Tc. Encode time using an m-bit integer (m = 64 on existing 64-bit computers; adjustments can be made for other bit-level systems). Time periods of various scales are encoded using a single-scale integer code according to the smallest scale (e.g., μs), where:

[0092] (1) Convert the integer A of the year count into a (m-46) bit binary number. The positive and negative signs are designed using its two's complement. The first bit is the sign bit, which indicates the year before and after Christ, ranging from 2m-47 BC to 2m-47-1 AD.

[0093] (2) The integer B of the month count is converted into a 4-bit binary number, representing 0 to 15. Among them, 0, 13, 14 and 15 are invalid in the month and will not be reflected in the encoding.

[0094] (3) The integer C of the day count is converted into a 5-bit binary number, representing 0 to 31, where 0 is invalid in the day count and will not be reflected in the encoding;

[0095] (4) The integer D of the time count is converted into a 5-bit binary number, representing 0 to 31. Among them, 24 to 31 are invalid in the time count and will not be reflected in the encoding.

[0096] (5) The integer E of the fraction count is converted into a 6-bit binary number, representing 0 to 63. Among them, 60 to 63 are invalid in the fraction count and will not be reflected in the encoding.

[0097] (6) The integer F of the second count is converted into a 6-bit binary number, representing 0 to 63. Among them, 660 to 63 are invalid in the second count and will not be reflected in the encoding.

[0098] (7) The integer G of the millisecond count is converted into a 10-bit binary number, representing 0 to 1023. Among them, 1000 to 1023 are invalid in the millisecond count and will not be reflected in the encoding.

[0099] (8) The integer H of the microsecond count is converted into a 10-bit binary number, representing 0 to 1024. Among them, 1000 to 1023 are invalid in the microsecond count and will not be reflected in the encoding.

[0100] For example, Tc uses integers of different sizes, A ((m-46)bit), B (4bit), C (5bit), D (5bit), E (6bit), F (6bit), G (10bit), and H (10bit), to directly concatenate them in the bit field to form an m-bit integer time encoding. The range of this single-scale time period encoding is from 2m-47 BC to 2m-47-1 AD, represented by integers -2m-1 to 2m-1-1. Below, taking m=64 as an example, to adapt to existing 64-bit computers, Tc represents the integer encoding formed at a 1μs scale, using 64-bit integers from -263 to 263-1 to represent 131072 BC to 131071 AD. The specific time encoding result is shown in 8(a).

[0101] This invention proposes another alternative scheme: encoding each data block according to its corresponding time information using a multi-scale time grid coding method to obtain a time code. The specific process for generating the multi-scale time code is as follows:

[0102] The timestamp / string Time is decomposed into integer counts of common time scales: year (A), month (B), day (C), hour (D), minute (E), second (F), millisecond (G), and microsecond (H). A is converted to a 17-bit binary number, B to a 4-bit binary number, C and D to 5-bit binary numbers, E and F to 6-bit binary numbers, and G and H to 10-bit binary numbers. The high bits of each binary number are padded with 0s. The binary numbers corresponding to A to H are concatenated in the bit field to obtain the single-scale time code corresponding to Time. The single-scale time code value is shifted one bit to the left to obtain the 63rd level multi-scale time code, which is the final time code in this embodiment.

[0103] For example, the time information of remote sensing image data is: Year (A): 2018, Month (B): 10, Day (C): 1, Hour (D): 13, Minute (E): 30, Second (F): 29, Millisecond (G): 300, Microsecond (H): 0; After performing binary conversion on this time information according to the above rules, we get: Year (A): 00000011111100010, Month (B): 1010, Day (C): 0001, Hour (D): 01101, Minute (E): 011110, Second (F): 011101, Millisecond (G): 0 100101100, microseconds (H): 0000000000; After concatenating the above binary code values, the single-scale time code value corresponding to the time information of the remote sensing image data is obtained as: 71024248425328640; Then, shift the obtained single-scale time code value one bit to the left to obtain the multi-scale time code value of the 63rd level as: 142048496850657280, that is, the time code of the remote sensing data is: 142048496850657280, and the specific time code result is shown in 8(b).

[0104] In S504, time encoding is also considered, and an index table is established to correspond to the time encoding, spatial encoding set and the data block, including the following steps:

[0105] C1. Establish the first index information between the data block and the file encoding; whereby the file encoding is used to determine the storage file of the data block;

[0106] C2. Establish a second index information between the file encoding and the spatial encoding set;

[0107] C3. Establish a third index information between the spatial encoding set and the temporal encoding;

[0108] C4. Create an index table based on the first index information, the second index information, and the third index information.

[0109] Steps C1 and C2 are similar to steps B1 and B2, and will not be described again here. This embodiment of the invention adds a third index information to B1 and B2, establishing a relationship between the spatial encoding set and the temporal encoding. This third index information indicates the index relationship between the temporal encoding and the spatial encoding set, and also indicates the temporal encoding corresponding to each spatial encoding in the spatial encoding set. Furthermore, a final index table is established using the first, second, and third index information. This index table indicates the index relationship between file encoding, the spatial encoding set, and the temporal encoding, thereby achieving gridded storage. The storage considers both spatial latitude and longitude information and temporal information, establishing a structured relationship between current remote sensing data and geographical location, space, and time, enabling real-time application of satellite remote sensing data and full utilization of satellite resources.

[0110] It should be noted that, please refer to Figure 9 In this embodiment of the invention, the storage mapping of on-board remote sensing data can also be achieved by using file encoding and time encoding to establish an index table. In this case, the mapping relationship between time encoding and data blocks is a one-to-one mapping relationship. The specific implementation process is similar to that of spatial encoding sets, and will not be described in detail here.

[0111] In summary, the remote sensing data management method based on grid-based objects proposed in this invention establishes a structured relationship between current remote sensing data and geographical location, space, and time during the on-board storage mapping process. This ensures the real-time application of satellite remote sensing data and improves the utilization rate of satellite resources. This grid-based storage method breaks away from the traditional ground-based storage method that requires standard storage equipment. It directly achieves storage mapping of on-board storage media through an index table. Furthermore, during subsequent data retrieval, data is directly read on-board through the index table. Grid-based data storage mapping management is closer to the underlying storage medium, resulting in shorter data retrieval paths and higher efficiency. The combination of this invention with a file system is more suitable for the actual situation of on-orbit operation. The storage mapping method of this invention allows multiple satellites to use the same grid coding method, effectively improving the accuracy of satellite resource retrieval, reducing the pressure on the ground-to-ground data downlink channels and ground processing stations, and in the future, it can support the realization of an "on-board data storage center" and provide "virtual remote sensing satellite services."

[0112] In the description of this invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0113] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0114] Although this application has been described herein in conjunction with various embodiments, those skilled in the art, by reviewing the accompanying drawings, disclosure, and appended claims, will understand and implement other variations of the disclosed embodiments in carrying out the claimed application. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. A single processor or other unit can implement several functions listed in the claims. While different dependent claims may recite certain measures, this does not mean that these measures cannot be combined to produce good results.

[0115] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A remote sensing data management method based on grid set objects, characterized in that, include: The raw remote sensing data obtained from the platform's front-end data source is stored on the satellite in data blocks, and the attribute information corresponding to each data block is obtained from the platform's central control computer. The attribute information includes spatial latitude and longitude information. The platform's front-end data source includes onboard payload cameras. The platform's central control computer includes a satellite-based computer. Auxiliary data, including the satellite's attitude, orbit, and time, is acquired through the platform's central control computer. Based on the satellite's orbit, attitude, and time, and combined with the optical path design of the sensors in the imaging subsystem, the positioning processing of the raw remote sensing data is completed, forming the attribute information of the raw remote sensing data. Each data block on the satellite is partitioned according to its corresponding attribute information to obtain a spatial encoding set; An index table is established corresponding to the spatial coding set and the data block. During the on-board storage mapping process, the index table is used to establish a structured relationship between the original remote sensing data and the geographical location and space, realizing the storage mapping of the on-board storage medium, and directly reading data from the satellite through the index table. The gridded data storage mapping management is close to the underlying layer of the storage medium, with a short data reading path and high efficiency. The spatial coding set includes several spatial codes, and each spatial code satisfies a preset mapping relationship with the data block. The step of establishing an index table corresponding to the spatial encoding set and the data block includes: establishing first index information between the data block and the file encoding; wherein the file encoding is used to determine the storage file of the data block; establishing second index information between the file encoding and the spatial encoding set; and establishing the index table based on the first index information and the second index information.

2. The remote sensing data management method based on grid set objects according to claim 1, characterized in that, The process of partitioning each data block on the satellite according to its corresponding attribute information to obtain a spatial encoding set includes: The Earth's space is divided into several first spatial grids using a preset spatial grid partitioning method; wherein, the spatial grid partitioning method includes GeoSOT, GeoHash and GJB8896-2017. The corresponding second space grid is obtained from several first space grids based on the attribute information corresponding to each data block; The spatial coding set is obtained by encoding all second spatial grids using a multi-scale spatial grid coding method.

3. The remote sensing data management method based on grid set objects according to claim 1, characterized in that, The mapping relationship between each spatial code and data block includes at least one of the following: a one-to-one mapping between spatial codes and data blocks, a many-to-one mapping between spatial codes and data blocks, and a one-to-many mapping between spatial codes and data blocks.

4. A remote sensing data management method based on grid set objects, characterized in that, include: The raw remote sensing data obtained from the platform's front-end data source is stored on the satellite in data blocks, and the attribute information corresponding to each data block is obtained from the platform's central control computer. The attribute information includes time information and spatial latitude and longitude information. The platform's front-end data source includes onboard payload cameras; the platform's central control computer includes a satellite-based computer. Auxiliary data, including the satellite's attitude, orbit, and time, is acquired through the platform's central control computer. Based on the satellite's orbit, attitude, and time, and combined with the optical path design of the sensors in the imaging subsystem, the positioning processing of the raw remote sensing data is completed, forming the attribute information of the raw remote sensing data. Each data block on the satellite is encoded according to its corresponding time information to obtain a time code; Each data block is divided according to its corresponding spatial latitude and longitude information to obtain a spatial coding set; An index table is established corresponding to the time code, the spatial code set, and the data block. During the on-board storage mapping process, the index table establishes a structured relationship between the original remote sensing data and its geographical location, space, and time. This enables storage mapping of the on-board storage medium and allows direct data reading from the satellite via the index table. The gridded data storage mapping management is close to the underlying storage medium, resulting in a short data reading path and high efficiency. Specifically, there is a one-to-one mapping relationship between the time code and the data block. The spatial code set includes several spatial codes, and each spatial code satisfies a preset mapping relationship with the data block. The step of establishing an index table corresponding to the time code, the spatial code set, and the data block includes: establishing first index information between the data block and the file code; wherein the file code is used to determine the storage file of the data block; establishing second index information between the file code and the spatial code set; establishing third index information between the spatial code set and the time code; and establishing the index table based on the first index information, the second index information, and the third index information.

5. The remote sensing data management method based on grid set objects according to claim 4, characterized in that, The process of encoding each data block on the satellite according to its corresponding time information to obtain time encoding includes: The time code is obtained by encoding each data block according to the corresponding time information using a single-scale time grid coding method.

6. The remote sensing data management method based on grid set objects according to claim 4, characterized in that, The process of encoding each data block on the satellite according to its corresponding time information to obtain time encoding includes: The time code is obtained by encoding each data block according to the corresponding time information using a multi-scale time grid coding method.

7. The remote sensing data management method based on grid set objects according to claim 4, characterized in that, The process of subdividing each data block according to its corresponding spatial latitude and longitude information to obtain a spatial coding set includes: The Earth's space is divided into several first spatial grids using a preset spatial grid partitioning method; wherein, the spatial grid partitioning method includes GeoSOT, GeoHash and GJB8896-2017. Based on the spatial latitude and longitude information corresponding to each data block, the corresponding second spatial grid is obtained from several first spatial grids; The spatial coding set is obtained by encoding all second spatial grids using a multi-scale spatial grid coding method.

8. The remote sensing data management method based on grid set objects according to claim 4, characterized in that, The mapping relationship between each spatial code and data block includes at least one of the following: a one-to-one mapping between spatial codes and data blocks, a many-to-one mapping between spatial codes and data blocks, and a one-to-many mapping between spatial codes and data blocks.

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