Method and device for processing remote sensing data for circulation

Abstract

The application provides a kind of remote sensing data trustful processing method and device for circulation, belong to data processing technical field, method includes: according to the operation event information generated in the execution process of the operation behavior of remote sensing data, the first unified data identifier of first moment and the second unified data identifier of first moment, determine the operation event identifier of the operation behavior for remote sensing data;Based on operation event identifier, build the operation event chain of remote sensing data;Wherein, first moment is the moment before the execution of the operation behavior for remote sensing data;Second moment is the moment after the execution of the operation behavior for remote sensing data;First unified data identifier and second unified data identifier are determined based on the multi-level meta information of remote sensing data.The application constructs the strong identification for remote sensing data, which integrates time characteristics and content characteristics, full life cycle strong binding and trusted identity, and solves the traceability problem of remote sensing data full life cycle.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a reliable method and apparatus for processing remote sensing data for circulation. Background Technology

[0002] With the emergence of massive amounts of remote sensing data from multiple platforms, sensors, and resolutions, reliable processing of remote sensing data is a crucial step in the data circulation process.

[0003] Currently, the main methods for trustworthy processing of remote sensing data include: identifying remote sensing data using filenames or database IDs, performing hashing on the original remote sensing image content, and embedding digital watermarks in the original remote sensing image content.

[0004] However, the aforementioned methods for trustworthy processing of remote sensing data lack a unified, tamper-proof, and unique identifier, making them unable to resist tampering. Furthermore, after multiple processing and distributions, the original ownership and processing history of remote sensing data are often lost, failing to address the issue of traceability throughout the entire lifecycle, resulting in a break in ownership and traceability during data circulation. Summary of the Invention

[0005] This invention provides a reliable processing method and apparatus for remote sensing data in circulation, which solves the defects of existing technologies such as inability to resist tampering and the existence of broken ownership and traceability during data circulation.

[0006] This invention provides a reliable processing method for circulating remote sensing data, comprising: Based on the remote sensing data at the first moment, determine the first unified data identifier; Obtain operation event information of the remote sensing data; the operation event information is generated during the execution of operation actions on the remote sensing data; Based on the remote sensing data at the second time point, determine the second unified data identifier; Based on the operation event information, the first unified data identifier, and the second unified data identifier, determine the operation event identifier of the operation behavior targeting the remote sensing data; Based on the operation event identifier, construct the operation event chain of the remote sensing data; Wherein, the first time point is the time before the operation on the remote sensing data is executed; the second time point is the time after the operation on the remote sensing data is executed; both the first unified data identifier and the second unified data identifier are determined based on the multi-level metadata of the remote sensing data.

[0007] According to the present invention, a trusted processing method for remote sensing data for circulation is provided. The multi-level meta-information includes spatiotemporal meta-information, source meta-information, content meta-information, quality meta-information, and ownership meta-information. The content meta-information is determined based on the image content of the remote sensing data. The first unified data identifier and the second unified data identifier are both determined based on the following unified data identifier determination method: determining the spatiotemporal identifier of the remote sensing data based on the spatiotemporal meta-information; determining the content fingerprint of the remote sensing data based on the content fingerprint and the multi-level serialization representation of the remote sensing data; signing the comprehensive identity digest using the private key of the operating device of the operation behavior to obtain the source ownership signature of the remote sensing data; and combining and encoding the spatiotemporal identifier, the comprehensive identity digest, and the source ownership signature to obtain the unified data identifier.

[0008] According to a trusted remote sensing data processing method for circulation provided by the present invention, the multi-level serialization representation is obtained by encoding the multi-level metadata according to a preset metadata hierarchy order; the step of determining the comprehensive identity digest of the remote sensing data based on the content fingerprint and the multi-level serialization representation of the remote sensing data includes: performing a whole-packet hash calculation on the multi-level serialization representation to obtain a total metadata digest of the remote sensing data; combining the content fingerprint and the total metadata digest to obtain an initial digest information of the remote sensing data; and performing a hash calculation on the initial digest information to obtain the comprehensive identity digest.

[0009] According to a reliable remote sensing data processing method for circulation provided by the present invention, the spatiotemporal layer information includes the timestamp and spatial coverage of the remote sensing data; the step of determining the spatiotemporal identifier of the remote sensing data based on the spatiotemporal layer information includes: dividing the spatial coverage into several geospatial grids according to a preset precision; performing dimensionality reduction spatial encoding on each geospatial grid to generate geospatial strings corresponding to each geospatial grid; and determining the spatiotemporal identifier based on each geospatial string and the timestamp of the remote sensing data.

[0010] According to the present invention, a reliable processing method for remote sensing data for circulation is provided, wherein the quality layer information includes a quality inspection summary of the remote sensing data.

[0011] According to the present invention, a trusted processing method for remote sensing data oriented to circulation is provided, wherein the source layer information includes the node identifier of the access node of the remote sensing data accessing the trusted aerospace data space system oriented to remote sensing data circulation, the device identifier and device platform identifier of the operating device of the operation; and / or, the ownership layer information includes the public key or digital certificate of the operating device of the operation.

[0012] According to a reliable remote sensing data processing method for circulation provided by the present invention, the step of determining the operation event identifier of the operation behavior on the remote sensing data based on the operation event information, the first unified data identifier, and the second unified data identifier includes: determining an initial event identifier based on the operation event information, the first unified data identifier, and the second unified data identifier; and combining the initial event identifier and the spatiotemporal layer information of the remote sensing data to obtain the operation event identifier.

[0013] According to a reliable remote sensing data processing method for circulation provided by the present invention, when there are multiple operation event identifiers, the step of constructing an operation event chain for the remote sensing data based on the operation event identifiers includes: determining the order of events based on the execution time of the operation behaviors corresponding to the multiple operation event identifiers; performing chain-structure processing on the multiple operation event identifiers according to the order of events to construct the operation event chain including multiple event nodes; wherein, the initial event node of the operation event chain is associated with a root unified data identifier; other time nodes in the operation event chain besides the initial event node are associated with sub-unified data identifiers; the root unified data identifier is a second unified data identifier determined when the operation behavior belongs to the original acquisition behavior of remote sensing data; the sub-unified data identifier is a second unified data identifier determined when the operation behavior does not belong to the original acquisition behavior of remote sensing data.

[0014] According to the trusted processing method for circulating remote sensing data provided by the present invention, after constructing the operation event chain of the remote sensing data based on the operation event identifier, the method further includes: performing aggregation calculation on the operation event chain to obtain event chain summary information of the operation event chain; and providing differentiated traceability query and audit support capabilities for different users based on the second unified data identifier, the operation event chain, and the event chain summary information.

[0015] The present invention also provides a reliable remote sensing data processing device for circulation, comprising: The first identifier determination module is used to determine the first unified data identifier based on the remote sensing data at the first moment; An event acquisition module is used to acquire operation event information of the remote sensing data; the operation event information is generated during the execution of operation actions on the remote sensing data; The second identifier determination module is used to determine the second unified data identifier based on the remote sensing data at the second time. The event identifier determination module is used to determine the operation event identifier of the operation behavior targeting the remote sensing data based on the operation event information, the first unified data identifier, and the second unified data identifier. An event chain construction module is used to construct an operation event chain for the remote sensing data based on the operation event identifier. Wherein, the first time point is the time before the operation on the remote sensing data is executed; the second time point is the time after the operation on the remote sensing data is executed; both the first unified data identifier and the second unified data identifier are determined based on the multi-level metadata of the remote sensing data.

[0016] The present invention provides a reliable remote sensing data processing method and apparatus for circulation. By utilizing different multi-level metadata of remote sensing data at different times before and after the execution of an operation, a first unified data identifier and a second unified data identifier are determined respectively. The operation time identifier of the operation is determined by using the two different unified data identifiers and the operation event information of the operation. This constructs a strong identifier that integrates time and content features, establishing a strong binding and reliable ownership identity for remote sensing data throughout its entire lifecycle. This allows the original ownership and processing history of remote sensing data to be preserved rather than lost after multiple processing and distributions, realizing the verifiability and immutability of the source of remote sensing data, thereby solving the problem of traceability of remote sensing data throughout its entire lifecycle. Attached Figure Description

[0017] 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.

[0018] Figure 1 This is a flowchart illustrating the reliable remote sensing data processing method for circulation provided by the present invention.

[0019] Figure 2 This is a schematic diagram of the structure of the space-air reliable data space system for remote sensing data circulation provided by the present invention.

[0020] Figure 3 This is a schematic diagram of the structure of the reliable remote sensing data processing device for circulation provided by the present invention.

[0021] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0022] 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.

[0023] The following is combined with Figures 1 to 4 This invention describes a reliable remote sensing data processing method and apparatus for circulation.

[0024] Remote sensing imagery, as crucial strategic data, is widely used in scenarios such as natural resources, environmental monitoring, land surveys, urban management, and aerospace telemetry and control. With the emergence of massive amounts of remote sensing data across multiple platforms, sensors, and resolutions, the following common industry challenges have been exposed during data circulation: (1) Unverifiable source: Existing remote sensing data lacks a globally unified identity identifier, making it difficult to determine its origin and easy to be counterfeited or submitted repeatedly; (2) Unclear data ownership: There is a lack of ownership record mechanism covering the data collector, provider and processor, making it difficult to form credible evidence; (3) Difficult to manage multi-source heterogeneous data: Remote sensing data from different platforms vary significantly in terms of band, resolution, imaging geometry, and coordinate system, making it difficult to manage and retrieve them in a unified manner; (4) Lack of auditability in data processing: The data flow path is not transparent, and it is difficult to trace the data processing, desensitization, and trimming processes; (5) Lack of a controllable data usage system: Once data is sent out, it is impossible to control its propagation path, reprocessing behavior, or whether it complies with security regulations.

[0025] In view of this, the present invention provides a method and apparatus for trusted processing of remote sensing data for circulation, which can provide each piece of remote sensing data with a unified identifier, unique ownership, trusted evidence storage, and auditable traceability architecture, ensuring that remote sensing data can be safely, controllably, and reliably circulated and used among multiple institutions.

[0026] Figure 1 This is a flowchart illustrating the reliable remote sensing data processing method for circulation provided by the present invention, as shown below. Figure 1 As shown, the reliable processing method for remote sensing data for circulation includes, but is not limited to, steps 101 to 105.

[0027] It should be noted that the execution subject of the trusted remote sensing data processing method for circulation provided by the present invention is a trusted aerospace data space system for remote sensing data circulation. Specifically, it can be a server, computer equipment, such as mobile phones, tablets, laptops, handheld computers, vehicle-mounted electronic devices, wearable devices, ultra-mobile personal computers (UMPCs), netbooks, or personal digital assistants (PDAs).

[0028] Step 101: Determine the first unified data identifier based on the remote sensing data at the first moment.

[0029] Step 102: Obtain the operation event information of the remote sensing data.

[0030] Operation event information is generated during the execution of operations on remote sensing data.

[0031] Step 103: Determine the second unified data identifier based on the remote sensing data at the second time point.

[0032] The first moment is the moment before the operation on the remote sensing data is executed; the second moment is the moment after the operation on the remote sensing data is executed; both the first unified data identifier and the second unified data identifier are determined based on the multi-level metadata of the remote sensing data.

[0033] The specific types of remote sensing data can be any of the various remote sensing data sources, such as optical remote sensing data, radar remote sensing data, and hyperspectral remote sensing data.

[0034] Operational behaviors include behaviors that do not change the data content of remote sensing data and behaviors that do change the data content of remote sensing data. Behaviors that do not change the data content of remote sensing data include, but are not limited to, any of the behaviors such as acquisition, circulation, forwarding, and retrieval. Behaviors that change the data content of remote sensing data include, but are not limited to, any of the behaviors such as processing and desensitization.

[0035] Operation event information includes, but is not limited to, several types of information such as the operation type, operation time, and device identifier of the operating device.

[0036] Multi-level metadata is metadata obtained by hierarchically processing key metadata extracted from remote sensing data according to a preset hierarchical information filtering and processing mechanism. The types of multi-level metadata include, but are not limited to, at least two of the following: spatiotemporal layer metadata, source layer metadata, content layer metadata, quality layer metadata, and ownership layer metadata. Specifically, multi-level metadata includes, but is not limited to: timestamps and spatial coverage of remote sensing data; hash values ​​determined based on the image content of the remote sensing data itself (such as SHA-256 or SM3 hashes); quality inspection summaries for quality checks on remote sensing data resolution, cloud cover, geometric accuracy, etc.; public keys, digital certificates, device identifiers, device platform identifiers of operating devices that perform operations on remote sensing data; and node identifiers of access nodes for remote sensing data access to the trusted aerospace data spatial system for remote sensing data circulation.

[0037] Specifically, at the first moment before the operation of remote sensing data is executed, multi-level metadata of the first moment is obtained from the remote sensing data at the first moment according to the preset hierarchical information filtering and processing mechanism. The multi-level metadata of the remote sensing data at the first moment is processed according to the predetermined unified data identifier determination method to obtain the first unified data identifier.

[0038] Perform operations on remote sensing data and acquire operation event information such as operation type, operation time, and device identifier of the operating device during the execution of the operation.

[0039] At the second moment after the operation of the remote sensing data is completed, multi-level metadata of the second moment is obtained from the remote sensing data at the second moment according to the preset hierarchical information filtering and processing mechanism. The multi-level metadata of the remote sensing data at the second moment is processed according to the predetermined unified data identifier determination method to obtain the second unified data identifier.

[0040] It should be noted that when the operation of remote sensing data is a collection or access behavior of the original acquisition behavior, the space-air trusted data space system for remote sensing data circulation is in a state of not having acquired remote sensing data (the remote sensing data is empty) before the operation of remote sensing data is executed. Therefore, the first unified data identifier determined at the first moment is empty.

[0041] In one embodiment, when remote sensing data undergoes acquisition and desensitization processes sequentially, the second moment after the acquisition process is completed is the same as the first moment before the desensitization process. The second unified data identifier determined after the acquisition process is completed is also the same as the first unified data identifier determined before the desensitization process. That is, in cases involving multiple operations, the second moment after the completion of the previous operation and the first moment before the execution of the next operation are the same moment.

[0042] Understandably, if the operation on remote sensing data involves altering the data content, the remote sensing data before and after the operation will differ in image content, resulting in different first and second unified data identifiers. Even if the operation does not alter the data content, the first and second unified data identifiers will still differ based on the difference between the first and second time points. In other words, the first and second unified data identifiers are determined based on the identifier determination time (first and second time points) and the operation.

[0043] Optionally, Figure 2 This is a schematic diagram of the structure of the space-air reliable data space system for remote sensing data circulation provided by the present invention, combined with... Figure 2 As shown, the aerospace trusted data space system for remote sensing data circulation, which is the main body of execution, includes a multi-source remote sensing data access and quality inspection module. Before determining the first unified data identifier based on the remote sensing data at the first moment, it performs format standardization and coordinate system transformation operations on the original multi-source remote sensing data to obtain remote sensing data. The multi-source remote sensing data access and quality inspection module includes a data access unit and a format parsing and standardization unit. The data access unit supports real-time or batch access of multi-source remote sensing data in various standard remote sensing formats such as GeoTIFF, SAFE, HDF5, and NetCDF, and performs preliminary verification of the data integrity of the multi-source remote sensing data; the multi-source remote sensing data supports transmission using protocols such as FTP, API, or MQTT. The format parsing and normalization unit is used to identify the original format of multi-source remote sensing data and convert the original format of multi-source remote sensing data into standard raster remote sensing data (e.g., using the GDAL library to convert GeoTIFF format multi-source remote sensing data into standard raster remote sensing data) to ensure metadata consistency. It is also used to perform coordinate system transformation on standard raster remote sensing data to obtain remote sensing data. Furthermore, it is used to parse and extract key metadata for determining multi-level metadata and generating unified data identifiers. Key metadata includes, but is not limited to, imaging time, orbit / attitude parameters, solar geometry, projection coordinate system, resolution, band structure, and geographic extent (Bounding Box).

[0044] Optionally, the multi-source remote sensing data access and quality inspection module also includes a node authentication unit, a quality inspection unit, an evidence storage unit, and an anomaly handling unit; The node authentication unit is used for registering nodes based on digital certificates (such as X.509) and blockchain, and for authenticating access nodes that access multi-source remote sensing data to prevent forged sources; it is also used to support certificate revocation list (CRL) checks. The quality inspection unit is used to perform noise detection, ground control point (GCP) geometric accuracy verification, cloud cover and defect detection using threshold methods on remote sensing data using quality inspection algorithms, and generate a quality inspection summary (also known as a quality inspection report) of the remote sensing data. The detection thresholds are automatically adjusted based on historical data. The quality inspection algorithm can be a structural similarity index (SSIM) algorithm, etc. The evidence storage unit is used to store the quality inspection summary of remote sensing data on the blockchain using SHA-256 hashing, supporting subsequent module calls and providing an API interface for querying reports. The anomaly handling unit is used to process remote sensing data that fails quality inspection, and to initiate a retransmission mechanism or log recording in the event of a quality inspection failure; it is also used to integrate machine learning models to predict potential quality problems.

[0045] By setting up a multi-source remote sensing data access and quality inspection module in a space-air trusted data spatial system for remote sensing data circulation, the system can realize the input, parsing, quality verification, and standardization of remote sensing data. Specifically, this includes accessing multiple remote sensing data sources such as optical, radar, and hyperspectral data; supporting automatic parsing and standardization conversion of various image formats (GeoTIFF, HDF, NetCDF, etc.), using GDAL or similar libraries for coordinate system unification and metadata extraction; performing node authentication, data signing, and integrity verification to prevent unauthorized node access, using X.509 certificates and ECDSA signatures to verify the identity of source nodes; performing automated quality inspection of image data, including resolution detection, geometric accuracy verification, defect and noise detection, and cloud coverage assessment; storing the quality inspection results in summary form for subsequent rights confirmation and traceability modules to call, supporting JSON format report generation and hash on-chain, realizing standardized access and unified management of multi-source heterogeneous remote sensing data in various formats such as optical, radar, and hyperspectral data, independent of specific sensors or data formats, uniformly adapting the identity expression method of multi-source heterogeneous remote sensing data, and achieving consistent identity expression and rights confirmation across platforms and systems.

[0046] Step 104: Determine the operation event identifier for the operation behavior targeting the remote sensing data based on the operation event information, the first unified data identifier, and the second unified data identifier.

[0047] Specifically, according to the preset operation event identifier determination method, the operation event information, the first unified data identifier, and the second unified data identifier are combined and hashed to obtain the operation event identifier for the operation behavior of remote sensing data.

[0048] Step 105: Construct the operation event chain of the remote sensing data based on the operation event identifier.

[0049] Specifically, an operation event chain for remote sensing data is constructed using at least one operation event identifier corresponding to an operation action on remote sensing data.

[0050] For example, when remote sensing data undergoes acquisition and desensitization processes in sequence, the operation event chain of the remote sensing data includes the event node of the operation event identifier corresponding to the acquisition behavior and the event node of the operation event identifier corresponding to the desensitization behavior. Here, the acquisition behavior is the behavior of originally acquiring remote sensing data, and the event node of the operation event identifier corresponding to the acquisition behavior is the initial event node.

[0051] The trusted processing method for remote sensing data in circulation provided by this invention determines a first unified data identifier and a second unified data identifier by utilizing different multi-level metadata of remote sensing data at different times before and after the execution of an operation. It then uses the two different unified data identifiers and the operation event information of the operation to determine the operation time identifier of the operation, thereby constructing a strong identifier that integrates time and content features. This establishes a strong binding and trusted ownership identity for remote sensing data throughout its entire lifecycle, ensuring that the original ownership and processing history of remote sensing data are preserved rather than lost after multiple processing and distributions. This achieves verifiability and immutability of the source of remote sensing data, thus solving the problem of traceability throughout the entire lifecycle of remote sensing data.

[0052] Based on the above embodiments, as an optional embodiment, the multi-level metadata includes spatiotemporal metadata, source metadata, content metadata, quality metadata, and ownership metadata; the content metadata is determined based on the image content of the remote sensing data; both the first unified data identifier and the second unified data identifier are determined based on the following unified data identifier determination method: Based on the spatiotemporal layer information, the spatiotemporal identifier of the remote sensing data is determined; Based on the content layer information, the content fingerprint of the remote sensing data is determined; Based on the content fingerprint and the multi-level serialization representation of the remote sensing data, a comprehensive identity digest of the remote sensing data is determined; The integrated identity digest is signed using the private key of the operating device used in the operation to obtain the source ownership signature of the remote sensing data. The unified data identifier is obtained by combining and encoding the spatiotemporal identifier, the comprehensive identity digest, and the source ownership signature.

[0053] Among them, the content layer information determined based on the image content of remote sensing data can be either the image content of the remote sensing data itself, or the hash value after performing hash calculations such as SHA-256 or SM3 hash on the image content of the remote sensing data.

[0054] The multi-level serialization representation of remote sensing data is determined based on all the multi-level metadata of the remote sensing data.

[0055] Specifically, when determining the first unified data identifier at the first moment or the second unified data identifier at the second moment, the current identifier determination time (first moment or second moment) is determined. On the one hand, the spatiotemporal identifier of the remote sensing data is determined based on the spatiotemporal layer information of the remote sensing data at the current identifier determination time.

[0056] On the other hand, the content fingerprint of the remote sensing data is determined based on the image content itself or the calculated hash value and other content layer information of the remote sensing data at the current time.

[0057] On the other hand, all multi-level metadata of the remote sensing data at the current identified time is encoded to obtain a multi-level serialized representation of the remote sensing data. Then, using the content fingerprint and the multi-level serialized representation of the remote sensing data, a comprehensive identity digest of the remote sensing data is determined. Finally, the comprehensive identity digest is signed using the private key of the operating device (such as a remote sensing data acquisition device) to obtain a source ownership signature for the remote sensing data.

[0058] Finally, the spatiotemporal identifier, comprehensive identity digest, and source ownership signature are combined and encoded to obtain a unified data identifier.

[0059] Optionally, the content fingerprint and multi-level serialization representation are combined and hashed to obtain a comprehensive identity digest of the remote sensing data.

[0060] Optionally, the second unified data identifier is determined by the operating device of the operation behavior according to the unified data identifier determination method.

[0061] Optionally, the second unified data identifier is determined by the operating device of the operation behavior according to the unified data identifier determination method. That is, the operating device of the operation behavior uses its own private key to sign the comprehensive identity digest to obtain the source ownership signature of the remote sensing data. Correspondingly, the aerospace trusted data space system for remote sensing data circulation uses the public key or digital certificate of the operating device of the operation behavior to authenticate the signature of the comprehensive identity digest, thereby proving the source subject and ownership relationship of the remote sensing data.

[0062] In one embodiment, the expression for the content fingerprint is as follows: ; in, For content fingerprinting; This refers to the impact of remote sensing data.

[0063] In one embodiment, the expression for the source ownership signature is as follows: ; in, Signature indicating ownership of the source; For comprehensive identity summary; The private key of the operating device for the operation.

[0064] In one embodiment, the expression for the unified data identifier is as follows: ; in, To standardize data identification; As a spatiotemporal identifier; For comprehensive identity summary; Signature indicating ownership of the source.

[0065] Among them, as a unified data identifier Spatiotemporal identifiers of prefixes Spatiotemporal identity information used to characterize remote sensing data, serving as a unified data identifier. The subject's comprehensive identity summary Based on the metadata summary and content fingerprint generation of remote sensing imagery, a unified data identifier is used. The suffix indicates the source of the signature. Used for comprehensive identity summary Verify the source and ownership to achieve unified data identification. It becomes a hierarchical identity identifier that can be repeatedly computed, independently verified, and reproduced across systems.

[0066] For example, unified data identifier An example is "GeoID=GHSx3p9e8f...Jt92kaf4...SgnH82dD".

[0067] It is understandable that the unified data identifier determination method is applicable to both the generation of unified data identifiers for raw remote sensing data and the generation of new data objects after processing. Specifically, the GeoID generated from the raw data is used as the root unified data identifier (root GeoID), and the GeoID corresponding to the data object generated after processing is used as the sub-unified data identifier (sub-GeoID).

[0068] Optionally, combined Figure 2 As shown, the aerospace trusted data space system for remote sensing data circulation also includes a module for determining remote sensing data identifiers and confirming rights. The remote sensing data identifier and confirming rights module is used to determine a unified data identifier, including a first unified data identifier and a second unified data identifier, and is also used to perform data confirmation, complete digital signature verification, and on-chain evidence storage.

[0069] The trusted processing method for remote sensing data in circulation provided by this invention establishes a mechanism for defining a unified identity for the remote sensing data itself. It uses spatiotemporal layer information to determine the spatiotemporal identifier of the remote sensing data, uses the image content of the remote sensing data to determine the content fingerprint of the remote sensing data, uses the content fingerprint and multi-level serialization representation to determine the source ownership signature of the remote sensing data, and finally designs a unified data identifier that integrates spatiotemporal features, image content and owner signature, and has global uniqueness and strong anti-counterfeiting properties, using a strong identifier generation method of "spatiotemporal information + content fingerprint + node digital signature". This makes the unified data identifier a hierarchical identity identifier that can be repeatedly calculated, independently verified and reproduced across systems.

[0070] Furthermore, based on the determinism, reproducibility, and independent verification of the unified data identifier GeoID, combined with the on-chain evidence storage mechanism, it can be directly used as the basis for verifying the source, ownership, and processing history of data, meeting the verifiability requirements of judicial evidence collection and regulatory auditing, thereby supporting verifiable evidence chains in judicial and regulatory scenarios.

[0071] Based on the above embodiments, as an optional embodiment, the multi-level serialization representation is obtained by encoding the multi-level metadata according to a preset metadata hierarchy order; the step of determining the comprehensive identity digest of the remote sensing data based on the content fingerprint and the multi-level serialization representation of the remote sensing data includes: Perform a whole-packet hash calculation on the multi-level serialized representation to obtain the total metadata summary of the remote sensing data; The content fingerprint and the total metadata summary are combined and calculated to obtain the initial summary information of the remote sensing data. The initial digest information is hashed to obtain the comprehensive identity digest.

[0072] Among them, the order of metadata hierarchy is the order in which the metadata of each level in the multi-level metadata is arranged.

[0073] Specifically, in determining the comprehensive identity summary of remote sensing data, multi-level metadata is first encoded according to a preset metadata hierarchy, resulting in a multi-level serialized representation. The encoding process of the multi-level serialized representation based on the preset metadata hierarchy is a fixed and reproducible computational pipeline. At any time and at any node, as long as the input information at each level remains consistent, the calculated total metadata summary result will necessarily be consistent, thereby ensuring the reproducibility and verifiability of the unified data identifier.

[0074] An example of a multi-level serialized representation in JSON format is shown below: { "timestamp":"2025-10-18T12:41:02Z", "bbox":"[115.23,39.27,115.35,39.35]", "device_id":"GF6-PMS1", "source_signature":"SIG_xxx", "content_hash":"SHA256_xxx", "quality_root":"QHASH_xxx", "owner_pubkey":"PUB_xxx" }; Among them, timestamp is the timestamp in the spatiotemporal layer metadata, bbox is the spatial coverage area in the spatiotemporal layer metadata, device_id is the device identifier of the operating device in the source layer metadata, source_signature is the source ownership signature; content_hash is the hash value of the impact content of remote sensing data in the content layer metadata; quality_root is the quality inspection digest in the quality layer metadata; and owner_pubkey is the public key of the operating device in the ownership layer metadata.

[0075] Further, a whole-packet hash calculation is performed on the multi-level serialized representation to obtain the total metadata digest of the remote sensing data. The content fingerprint and the total metadata digest are combined to obtain the initial digest information of the remote sensing data. The initial digest information is then hashed to obtain the comprehensive identity digest of the remote sensing data.

[0076] In one embodiment, the expression for the total metadata summary is as follows: ; in, This is a summary of the metadata. It represents a multi-level serialization.

[0077] In one embodiment, the expression for the comprehensive identity digest is as follows: ; in, For comprehensive identity summary; This is a summary of the metadata. For content fingerprinting.

[0078] The reliable processing method for remote sensing data in circulation provided by this invention proposes a unified data identification system based on a hierarchical identity model. It constructs a hierarchical identity model based on spatiotemporal layer, source layer, content layer, quality layer, and ownership layer. Instead of treating the unified data identifier as a randomly generated identifier, it encodes the identity elements of each level layer by layer according to a fixed and deterministic calculation pipeline to generate the unified data identifier. As long as the input hierarchical information remains consistent, the unified data identifier can be repeatedly calculated and verified, ensuring the reproducibility and verifiability of the identity.

[0079] Based on the above embodiments, as an optional embodiment, the spatiotemporal layer information includes the timestamp and spatial coverage of the remote sensing data; determining the spatiotemporal identifier of the remote sensing data based on the spatiotemporal layer information includes: The spatial coverage area is divided into several geospatial grids according to a preset precision; Dimensionality reduction spatial encoding is performed on each of the geospatial grids to generate geospatial strings corresponding to each geospatial grid; The spatiotemporal identifier is determined based on each of the geospatial strings and the timestamp of the remote sensing data.

[0080] Each geospatial string is used to collectively represent the spatial coverage of the image content in the remote sensing data.

[0081] Spatiotemporal identifiers are used to represent the spatiotemporal identity characteristics of remote sensing data.

[0082] Specifically, in determining the spatiotemporal identifier of remote sensing data using spatiotemporal layer information, the spatial coverage area of ​​the WGS84 standard in the spatiotemporal layer information is divided into several geospatial grids (GeoHash grids) according to a preset precision. For each GeoHash grid, dimensionality reduction spatial encoding such as GeoHash encoding is performed on the GeoHash grid to obtain the corresponding geospatial string (GeoHash string). All GeoHash grids are traversed to obtain the GeoHash strings corresponding to each GeoHash grid.

[0083] The geohash strings of the geohash encoding result are combined with the timestamp of the ISO8601 standard to obtain the spatiotemporal identifier of the remote sensing data.

[0084] One example of the spatial coverage area (bbox) of remote sensing data is: bbox→["wx4g0d","wx4g0e",...].

[0085] In the relevant methods of trustworthy processing of remote sensing data, the main approaches are to identify the remote sensing data by file name or database ID, perform hashing on the original remote sensing image content, and embed digital watermarks in the original remote sensing image content. However, these methods fail to reflect the spatiotemporal characteristics of remote sensing data.

[0086] The trusted processing method for remote sensing data in circulation provided by this invention first divides the spatial coverage area in the spatiotemporal layer information into a geospatial grid and generates a geospatial string. Then, it determines the spatiotemporal identifier based on the geospatial string and the timestamp. The spatiotemporal identifier is used to determine a unified data identifier, thereby generating a strong identifier that considers the spatiotemporal characteristics of remote sensing data. This supports spatiotemporal dimension queries of remote sensing data. Furthermore, by using a strong identifier generation method of "spatial-temporal information GeoHash + content fingerprint hash + node digital signature", a unified data identifier is designed that integrates spatiotemporal features, image content and owner signature, and has global uniqueness and strong anti-counterfeiting properties.

[0087] Based on the above embodiments, as an optional embodiment, the quality stratum information includes a quality inspection summary of the remote sensing data.

[0088] The quality inspection summary is a report summary obtained after performing quality inspections on the original acquired, accessed, and collected remote sensing data, including resolution, cloud cover, and geometric accuracy. The quality inspection summary will change as the content of the remote sensing data changes during the entire lifecycle management of the remote sensing data.

[0089] The trustworthy processing method for remote sensing data in circulation provided by this invention incorporates the quality inspection summary as an independent quality layer into the GeoID calculation process, making the quality status of remote sensing data an inseparable part of its identity. Once the data deteriorates in quality or is tampered with during circulation, its corresponding GeoID will fail the consistency verification, thus ensuring the trustworthiness of the circulating data from a mechanism perspective and realizing a deep binding between the ownership and quality of remote sensing data.

[0090] Based on the above embodiments, as an optional embodiment, the source layer information includes the node identifier of the access node of the remote sensing data access to the aerospace trusted data space system for remote sensing data circulation, the device identifier of the operating device of the operation behavior, and the device platform identifier. And / or, the ownership layer information includes the public key or digital certificate of the operating device for the operation.

[0091] Among them, the equipment platform identifier is the identifier of the equipment platform to which the operating equipment belongs.

[0092] Specifically, in the case where the source layer metadata in the multi-level metadata includes node identifier, device identifier, and device platform identifier, the quality layer metadata includes the quality inspection summary of remote sensing data, and the ownership layer metadata includes the public key or digital certificate of the operating device for the operation behavior, the multi-level metadata is encoded according to the preset metadata hierarchy order to obtain a multi-level serialized representation.

[0093] The trustworthy processing method for remote sensing data in circulation provided by this invention organizes the relevant metadata of remote sensing data according to a hierarchical identity model. Different levels describe the identity characteristics of remote sensing data in dimensions such as time and space, source, content, quality and ownership, which together constitute the input basis for a unified data identifier, realizing the standardized modeling and serialization of multi-level metadata.

[0094] As can be seen, the unified data identifier for remote sensing data designed by the trusted processing method for circulating remote sensing data provided by this invention possesses the design principles of uniqueness, unforgeability, immutability, cross-platform consistency, and quality binding. Uniqueness ensures that different unified data identifiers are generated for different times, spatial coverage areas, and image content. Unforgeability is achieved by using digital signatures to bind operational behavior to device nodes. Immutability is ensured by the unified data identifier's structure supporting on-chain anchoring and notarization via hashing. Cross-platform consistency applies to multi-source heterogeneous remote sensing data. Quality binding incorporates quality inspection summaries into GeoID calculations, making quality part of the data identity. Once the quality is tampered with or damaged, the corresponding GeoID verification will fail, thus ensuring the credibility of circulating data. This constructs a strong identifier that integrates time and content characteristics, establishing a strong binding and trusted ownership identity for remote sensing data throughout its entire lifecycle. This allows the original ownership and processing history of remote sensing data to be preserved rather than lost after multiple processing and distributions, achieving verifiable and immutable remote sensing data sources, thereby solving the traceability problem of remote sensing data throughout its entire lifecycle.

[0095] Based on the above embodiments, as an optional embodiment, determining the operation event identifier for the operation behavior targeting the remote sensing data according to the operation event information, the first unified data identifier, and the second unified data identifier includes: Based on the operation event information, the first unified data identifier, and the second unified data identifier, an initial event identifier is determined; The operation event identifier is obtained by combining the initial event identifier and the spatiotemporal layer information of the remote sensing data.

[0096] Specifically, in combination Figure 2 As shown, the aerospace-based trusted data spatial system for remote sensing data circulation also includes a remote sensing data storage and full lifecycle traceability module. This module is responsible for the distributed storage, version management, transaction records, and full lifecycle traceability of remote sensing data, ensuring the integrity and traceability of remote sensing data during use, sharing, and reprocessing. The remote sensing data storage and full lifecycle traceability module supports high availability and fault tolerance, and provides spatiotemporal query optimization.

[0097] When any operation occurs on remote sensing data, the system acquires operation event information corresponding to that operation, including the operation type, operation time, and operation subject identifier (equipment identifier of the operating device). When determining the operation event identifier for the operation of remote sensing data, the remote sensing data storage and full lifecycle traceability module combines and encodes the operation event information, the first unified data identifier before and after the operation, and the second unified data identifier to obtain the initial event identifier. Then, it combines and encodes the initial event identifier and the spatiotemporal layer information of the remote sensing data to generate an operation event identifier with spatiotemporal constraints.

[0098] Optionally, the remote sensing data storage and full lifecycle traceability module includes an identity referencing and data management unit, an operation event acquisition unit, and a spatiotemporal correlation coding unit; The identity reference and data management unit is used to use the unified data identifier GeoID as the unique identity reference of remote sensing data in the system, to uniformly manage the remote sensing data ontology and its associated information, and to support data positioning, status query and version differentiation based on the unified data identifier GeoID. The operation event acquisition unit is used to automatically collect operation event information corresponding to any operation such as acquisition, processing, circulation, retrieval, or desensitization of remote sensing data. The operation event information includes, but is not limited to, operation type, operation time, operation subject identifier, and GeoID referenced before and after the operation. The spatiotemporal correlation coding unit is used to combine and encode operation event information with the corresponding GeoID and its associated spatiotemporal information to generate an operation event identifier or its hash value with spatiotemporal constraints to characterize the operation behavior of remote sensing data under specific spatiotemporal conditions.

[0099] The trusted processing method for remote sensing data in circulation provided by this invention generates a unified data identifier for remote sensing data as a unique identity reference throughout the entire life cycle of the remote sensing data. In the process of generating operation event identifiers using the unified data identifier and operation event information, spatiotemporal layer information is added for combined encoding. This can prevent operation records from being copied or reused across data, and the same operation will not generate the same event hash on different data. It supports spatiotemporal dimension query and prevents operation records from being forged or transferred. In addition, it can be combined with the traceability method of Merkle tree on-chain storage to realize spatiotemporal dimension query and auditing of remote sensing data.

[0100] Based on the above embodiments, as an optional embodiment, when the operation event identifier includes multiple identifiers, the step of constructing the operation event chain of the remote sensing data based on the operation event identifiers includes: The order of events is determined based on the execution time of the operation behaviors corresponding to the multiple operation event identifiers. The operation event identifiers are processed in a chain structure according to the order of occurrence of the events to construct the operation event chain including multiple event nodes; The initial event node of the operation event chain is associated with the root unified data identifier; other time nodes in the operation event chain, excluding the initial event node, are associated with the sub-unified data identifiers; the root unified data identifier is a second unified data identifier determined when the operation behavior belongs to the original acquisition behavior of remote sensing data; the sub-unified data identifier is a second unified data identifier determined when the operation behavior does not belong to the original acquisition behavior of remote sensing data.

[0101] Specifically, after several operating devices perform multiple operations on remote sensing data, multiple operation event identifiers are generated. The order of occurrence of these operation event identifiers is determined based on the execution time of the corresponding operations. Following this order, the multiple operation event identifiers are associated and chained using hash pointers or similar methods to construct an operation event chain containing an initial event node and other event nodes. Furthermore, the initial event node is associated with a second unified data identifier determined when the operation is a raw acquisition of remote sensing data (such as data collection), i.e., the initial event node is associated with the root unified data identifier; other event nodes are associated with a second unified data identifier determined when the operation is not a raw acquisition of remote sensing data (such as processing or desensitization), i.e., other event nodes are associated with sub-unified data identifiers.

[0102] By associating each event node with a root GeoID or a sub-GeoID in the operational event chain, the relationship between the root GeoID and each sub-GeoID generated during the remote sensing data collection, circulation, forwarding, and processing is also established, enabling each sub-GeoID to be uniformly associated with the root GeoID as the node.

[0103] Optionally, the remote sensing data storage and full lifecycle tracing module includes an event chain construction unit; The event chain construction unit is used to organize multiple operation event identifiers or hash values ​​through associated pointers according to the time sequence of the operation behavior, and construct an operation event chain structure with the root GeoID as the identity thread. It is also used to associate multiple sub-GeoIDs in the chain structure to describe the entire life cycle evolution process of remote sensing data.

[0104] The trusted processing method for remote sensing data in circulation provided by this invention establishes a root GeoID and sub-GeoID identification mechanism by associating a unified data identifier with each event node in the operation event chain of remote sensing data. For original remote sensing data that has not been modified, the GeoID calculated based on its metadata is used as the root GeoID of the data. When the remote sensing data undergoes content changes and forms new data objects during subsequent processing, a new GeoID is recalculated based on the updated metadata and denoted as a sub-GeoID. All sub-GeoIDs are organized with the corresponding root GeoID as the associated node. This method clearly represents the evolutionary relationship of the same source data at different processing stages, realizes the binding of the operation data chain and the unified data identifier, and ensures that each operation event chain has a traceable link.

[0105] Based on the above embodiments, as an optional embodiment, after constructing the operation event chain of the remote sensing data based on the operation event identifier, the method further includes: The operation event chain is aggregated and calculated to obtain the event chain summary information of the operation event chain; Based on the second unified data identifier, the operation event chain, and the event chain summary information, differentiated traceability query and audit support capabilities are provided for different users.

[0106] Among them, the event chain summary information serves as a traceability credential for subsequent verification and auditing.

[0107] Specifically, after constructing the operational event chain of remote sensing data, the operational event chain is aggregated and calculated to obtain event chain summary information (such as a Merkle tree summary) that can be used to quickly verify the integrity and consistency of the operational event chain. Based on the second unified data identifier, operational event chain, and event chain summary information, differentiated traceability query and audit support capabilities are provided for different users.

[0108] Optionally, the remote sensing data storage and full lifecycle traceability module includes a traceability summary generation unit and a query and audit support unit; The traceability summary generation unit is used to perform aggregation calculations on the operation event chain and generate corresponding event chain summary information that can be used to quickly verify the integrity and consistency of the operation event chain; The query and audit support unit is used to provide traceability query and audit support capabilities for different user entities based on GeoID, operation event chain and event chain summary information, so as to meet the needs of data users for verification, regulatory authorities for audit and other scenarios.

[0109] The trusted processing method for remote sensing data in circulation provided by this invention obtains event chain summary information by aggregating and calculating the operation event chain. Based on the second unified data identifier, operation event chain, and event chain summary information, it provides differentiated traceability query and audit support capabilities for different users. It can realize the controllability and auditability of remote sensing data desensitization and access in scenarios such as data user verification and regulatory department audit.

[0110] Overall, the trusted processing method for remote sensing data in circulation provided by this invention aims to solve key problems such as unclear ownership, inconsistent identification, unverifiable data sources, untraceable processing, and uncontrollable data use that arise during the circulation, management, and sharing of remote sensing data. Based on a constructed aerospace trusted data space covering the entire lifecycle of remote sensing data, it proposes a unified data identifier based on spatiotemporal identification, content fingerprint, and trusted source ownership signature. This establishes a strong, lifecycle-bound identity for remote sensing data, achieving verifiable and tamper-proof sources. The quality inspection results of remote sensing data participate in the calculation of GeoID in the form of independent quality metadata digests. This ensures that data with different quality inspection results automatically correspond to different GeoIDs under the same spatiotemporal range and source conditions. Any processing operations that cause changes in quality metadata (including but not limited to...) are handled accordingly. Changes in resolution, noise levels, cloud cover, and geometric accuracy are all reflected during GeoID verification, making the "quality status" of remote sensing data an auditable part of its identity rather than just an accessory attribute. This enables the detection and traceability of changes in data quality status. Through a technical system involving the access, parsing, quality inspection, identifier generation, ownership verification, desensitization, and full lifecycle tracking of multi-source remote sensing data, and especially a space-air data spatial system based on unified data identifiers to ensure the trustworthy use of remote sensing data, the system ultimately achieves standardized access and quality inspection of multi-source remote sensing data, unified identifiers (GeoID) and unique ownership verification of remote sensing data, end-to-end traceability of data processing, and controllable and auditable data desensitization and access. This provides fundamental support for the secure use, trading, and trustworthy supervision of remote sensing data.

[0111] Optionally, the aerospace trusted data space system for remote sensing data circulation also includes a remote sensing data desensitization and access auditing module, which is responsible for identifying sensitive information, performing graded desensitization processing and compliance auditing during the circulation and sharing of remote sensing data, to ensure the privacy and security of data under the premise of usability; the remote sensing data desensitization and access auditing module also integrates an AI model to support dynamic policy adjustment.

[0112] Specifically, the remote sensing data desensitization and access auditing module addresses the desensitization needs of different security levels and usage scenarios by invoking pre-trained target detection and semantic segmentation models to automatically identify sensitive features or areas in remote sensing images. Based on preset security levels and access permissions, it executes different levels of desensitization strategies, including but not limited to blurring, masking, resolution downsampling, or statistical perturbation, to achieve controlled hiding of sensitive information. The module also uniformly records and preserves desensitization processes, data access, and related operations, ensuring the traceability and auditability of remote sensing data before, during, and after desensitization, thereby meeting relevant data security and compliance requirements.

[0113] When the desensitization process causes changes in the content of remote sensing data and generates new data objects, the remote sensing data desensitization and access auditing module recalculates and generates a sub-GeoID for the remote sensing data object and establishes an association between it and the corresponding root GeoID.

[0114] Optionally, the remote sensing data desensitization and access audit module includes a sensitive information identification unit, a desensitization strategy configuration unit, a desensitization processing execution unit, an audit evidence storage unit, a compliance audit unit, and a recovery mechanism unit; The sensitive information identification unit is used to call pre-trained target detection models and semantic segmentation models to automatically identify and locate sensitive targets or regions in remote sensing images for different levels of desensitization tasks, and supports processing remote sensing data of different resolutions and scales. The data masking strategy configuration unit is used to configure multi-level data masking strategies according to data security level, usage scenario and access subject permissions, and supports dynamic adjustment based on rules or strategy templates; The desensitization processing execution unit is used to perform corresponding desensitization processing operations on the identified sensitive areas according to the configured desensitization strategy, and record the status change information before and after desensitization to support subsequent verification and auditing. The audit evidence storage unit is used to generate corresponding identification information or summary information for the de-identification process and related operational events, and to store it as audit evidence to support the integrity verification of the de-identification behavior; The compliance audit unit is used to provide regulatory or authorized entities with verification of de-identified compliance and support for behavior tracing based on de-identified records and operation logs; The recovery mechanism unit is used to support controlled recovery of specific desensitization results when authorization conditions are met, and to record and audit the recovery process.

[0115] By setting up a remote sensing data anonymization and access auditing module in a space-air trusted data space system for remote sensing data circulation, the privacy and security of remote sensing data can be ensured under the premise of availability, and the safe and controllable use of data can be ensured.

[0116] Compared to other trusted remote sensing data processing solutions that only address single aspects like transactions or copyright protection, the Aerospace Trusted Data Space System for remote sensing data circulation achieves closed-loop management across the entire chain, from remote sensing data access and parsing, GeoID generation, storage and traceability to de-identification and distribution. It tightly couples four modules using blockchain technology: a multi-source remote sensing data access and quality inspection module (input layer), a remote sensing data identification and rights confirmation module (core layer), a remote sensing data storage and full lifecycle traceability module (infrastructure layer), and a remote sensing data de-identification and access audit module (security layer). This covers the entire process of access, quality inspection, de-identification, storage, and retrieval. Every operation record is recorded on the blockchain, ensuring that every piece of outgoing data is traceable, auditable, and compliant with security standards, meeting the requirements for comprehensive, traceable, and penetrating supervision.

[0117] Figure 3 This is a schematic diagram of the structure of the reliable remote sensing data processing device for circulation provided by the present invention, as shown below. Figure 3 As shown, the remote sensing data trust processing device for circulation includes, but is not limited to, a first identifier determination module 301, an event acquisition module 302, a second identifier determination module 303, an event identifier determination module 304, and an event chain construction module 305.

[0118] The first identifier determination module 301 is used to determine the first unified data identifier based on the remote sensing data at the first moment.

[0119] The event acquisition module 302 is used to acquire operation event information of the remote sensing data; the operation event information is generated during the execution of operation behaviors on the remote sensing data.

[0120] The second identifier determination module 303 is used to determine the second unified data identifier based on the remote sensing data at the second time.

[0121] The event identifier determination module 304 is used to determine the operation event identifier of the operation behavior on the remote sensing data based on the operation event information, the first unified data identifier and the second unified data identifier.

[0122] The event chain construction module 305 is used to construct the operation event chain of the remote sensing data based on the operation event identifier.

[0123] Wherein, the first time point is the time before the operation on the remote sensing data is executed; the second time point is the time after the operation on the remote sensing data is executed; both the first unified data identifier and the second unified data identifier are determined based on the multi-level metadata of the remote sensing data.

[0124] It should be noted that the remote sensing data trust processing device for circulation provided by the present invention can execute the remote sensing data trust processing method for circulation described in any of the above embodiments during specific operation, which will not be elaborated in this embodiment.

[0125] The remote sensing data trusted processing device for circulation provided by this invention determines a first unified data identifier and a second unified data identifier by utilizing different multi-level metadata of remote sensing data at different times before and after the execution of an operation. It then uses the two different unified data identifiers and the operation event information of the operation to determine the operation time identifier of the operation, thereby constructing a strong identifier that integrates time and content features. This establishes a strong binding and trusted ownership identity for remote sensing data throughout its entire lifecycle, ensuring that the original ownership and processing history of remote sensing data are preserved rather than lost after multiple processing and distributions. This achieves verifiability and immutability of the source of remote sensing data, thus solving the problem of traceability throughout the entire lifecycle of remote sensing data.

[0126] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 4 As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430, and a communications bus 440, wherein the processor 410, the communications interface 420, and the memory 430 communicate with each other through the communications bus 440. The processor 410 can call logical instructions in the memory 430 to execute the circulation-oriented trusted remote sensing data processing method provided in any of the above embodiments. The circulation-oriented trusted remote sensing data processing method includes, but is not limited to, the following steps: determining a first unified data identifier based on remote sensing data at a first moment; obtaining operation event information of the remote sensing data; the operation event information is generated during the execution of an operation behavior on the remote sensing data; determining a second unified data identifier based on the remote sensing data at a second moment; determining an operation event identifier for the operation behavior on the remote sensing data based on the operation event information, the first unified data identifier, and the second unified data identifier; constructing an operation event chain for the remote sensing data based on the operation event identifier; wherein, the first moment is the moment before the execution of the operation behavior on the remote sensing data; the second moment is the moment after the execution of the operation behavior on the remote sensing data; and both the first unified data identifier and the second unified data identifier are determined based on the multi-level metadata of the remote sensing data.

[0127] Furthermore, the logical instructions in the aforementioned memory 430 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.

[0128] 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 trustworthy remote sensing data processing method for circulation provided in any of the above embodiments. The trustworthy remote sensing data processing method for circulation includes, but is not limited to, the following steps: determining a first unified data identifier based on remote sensing data at a first moment; obtaining operation event information of the remote sensing data; the operation event information is generated during the execution of an operation behavior on the remote sensing data; determining a second unified data identifier based on the remote sensing data at a second moment; determining an operation event identifier for the operation behavior on the remote sensing data based on the operation event information, the first unified data identifier, and the second unified data identifier; constructing an operation event chain for the remote sensing data based on the operation event identifier; wherein, the first moment is the moment before the operation behavior on the remote sensing data is executed; the second moment is the moment after the operation behavior on the remote sensing data is executed; and both the first unified data identifier and the second unified data identifier are determined based on the multi-level metadata of the remote sensing data.

[0129] 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 circulation-oriented trusted remote sensing data processing method provided in any of the above embodiments. The circulation-oriented trusted remote sensing data processing method includes, but is not limited to, the following steps: determining a first unified data identifier based on remote sensing data at a first moment; obtaining operation event information of the remote sensing data; the operation event information is generated during the execution of an operation on the remote sensing data; determining a second unified data identifier based on the remote sensing data at a second moment; determining an operation event identifier for the operation on the remote sensing data based on the operation event information, the first unified data identifier, and the second unified data identifier; constructing an operation event chain for the remote sensing data based on the operation event identifier; wherein, the first moment is the moment before the execution of the operation on the remote sensing data; the second moment is the moment after the execution of the operation on the remote sensing data; and both the first unified data identifier and the second unified data identifier are determined based on the multi-level metadata of the remote sensing data.

[0130] 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.

[0131] 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.

[0132] 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 reliable processing method for remote sensing data for distribution, characterized in that, include: Based on the remote sensing data at the first moment, determine the first unified data identifier; Operation event information for acquiring the remote sensing data; The operation event information is generated during the execution of operation actions targeting the remote sensing data; Based on the remote sensing data at the second time point, determine the second unified data identifier; Based on the operation event information, the first unified data identifier, and the second unified data identifier, determine the operation event identifier of the operation behavior targeting the remote sensing data; Based on the operation event identifier, construct the operation event chain of the remote sensing data; Wherein, the first time point is the time before the operation on the remote sensing data is executed; the second time point is the time after the operation on the remote sensing data is executed; both the first unified data identifier and the second unified data identifier are determined based on the multi-level metadata of the remote sensing data.

2. The reliable remote sensing data processing method for circulation as described in claim 1, characterized in that, The multi-level metadata includes spatiotemporal metadata, source metadata, content metadata, quality metadata, and ownership metadata; the content metadata is determined based on the image content of the remote sensing data; both the first unified data identifier and the second unified data identifier are determined based on the following unified data identifier determination method: Based on the spatiotemporal layer information, the spatiotemporal identifier of the remote sensing data is determined; Based on the content layer information, the content fingerprint of the remote sensing data is determined; Based on the content fingerprint and the multi-level serialization representation of the remote sensing data, a comprehensive identity digest of the remote sensing data is determined; The integrated identity digest is signed using the private key of the operating device used in the operation to obtain the source ownership signature of the remote sensing data. The unified data identifier is obtained by combining and encoding the spatiotemporal identifier, the comprehensive identity digest, and the source ownership signature.

3. The reliable remote sensing data processing method for circulation as described in claim 2, characterized in that, The multi-level serialization representation is obtained by encoding the multi-level metadata according to a preset metadata hierarchy order; the step of determining the comprehensive identity digest of the remote sensing data based on the content fingerprint and the multi-level serialization representation of the remote sensing data includes: Perform a whole-packet hash calculation on the multi-level serialized representation to obtain the total metadata summary of the remote sensing data; The content fingerprint and the total metadata summary are combined and calculated to obtain the initial summary information of the remote sensing data. The initial digest information is hashed to obtain the comprehensive identity digest.

4. The reliable remote sensing data processing method for circulation as described in claim 2, characterized in that, The spatiotemporal layer information includes the timestamp and spatial coverage of the remote sensing data; determining the spatiotemporal identifier of the remote sensing data based on the spatiotemporal layer information includes: The spatial coverage area is divided into several geospatial grids according to a preset precision; Dimensionality reduction spatial encoding is performed on each of the geospatial grids to generate geospatial strings corresponding to each geospatial grid; The spatiotemporal identifier is determined based on each of the geospatial strings and the timestamp of the remote sensing data.

5. The reliable remote sensing data processing method for circulation according to any one of claims 2-4, characterized in that, The quality stratum information includes a quality inspection summary of the remote sensing data.

6. The reliable remote sensing data processing method for circulation as described in claim 5, characterized in that, The source layer information includes the node identifier of the access node of the remote sensing data access to the aerospace trusted data space system for remote sensing data circulation, the device identifier of the operating device of the operation behavior, and the device platform identifier. And / or, the ownership layer information includes the public key or digital certificate of the operating device for the operation.

7. The reliable remote sensing data processing method for circulation as described in claim 1, characterized in that, The step of determining the operation event identifier for the operation behavior targeting the remote sensing data based on the operation event information, the first unified data identifier, and the second unified data identifier includes: Based on the operation event information, the first unified data identifier, and the second unified data identifier, an initial event identifier is determined; The operation event identifier is obtained by combining the initial event identifier and the spatiotemporal layer information of the remote sensing data.

8. The reliable remote sensing data processing method for circulation as described in claim 1, characterized in that, When there are multiple operation event identifiers, constructing the operation event chain of the remote sensing data based on the operation event identifiers includes: The order of events is determined based on the execution time of the operation behaviors corresponding to the multiple operation event identifiers. The operation event identifiers are processed in a chain structure according to the order of occurrence of the events to construct the operation event chain including multiple event nodes; The initial event node of the operation event chain is associated with the root unified data identifier; other time nodes in the operation event chain, excluding the initial event node, are associated with the sub-unified data identifiers; the root unified data identifier is a second unified data identifier determined when the operation behavior belongs to the original acquisition behavior of remote sensing data; the sub-unified data identifier is a second unified data identifier determined when the operation behavior does not belong to the original acquisition behavior of remote sensing data.

9. The reliable remote sensing data processing method for circulation as described in claim 1, characterized in that, After constructing the operation event chain of the remote sensing data based on the operation event identifier, the method further includes: The operation event chain is aggregated and calculated to obtain the event chain summary information of the operation event chain; Based on the second unified data identifier, the operation event chain, and the event chain summary information, differentiated traceability query and audit support capabilities are provided for different users.

10. A reliable remote sensing data processing device for distribution, characterized in that, include: The first identifier determination module is used to determine the first unified data identifier based on the remote sensing data at the first moment; An event acquisition module is used to acquire operation event information of the remote sensing data; the operation event information is generated during the execution of operation actions on the remote sensing data; The second identifier determination module is used to determine the second unified data identifier based on the remote sensing data at the second time. The event identifier determination module is used to determine the operation event identifier of the operation behavior targeting the remote sensing data based on the operation event information, the first unified data identifier, and the second unified data identifier. An event chain construction module is used to construct an operation event chain for the remote sensing data based on the operation event identifier. Wherein, the first time point is the time before the operation on the remote sensing data is executed; the second time point is the time after the operation on the remote sensing data is executed; both the first unified data identifier and the second unified data identifier are determined based on the multi-level metadata of the remote sensing data.

Images