CN115878826A - Multi-source remote sensing image metadata traceability information organization method and management system - Google Patents
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Abstract
本发明公开了一种多源遥感影像元数据溯源信息组织方法及管理系统，所述方法包括：将多源遥感影像溯源信息抽象为事件、实体、关系和属性四类要素，以图谱化的方式建立多源遥感影像溯源信息的概念模型；建立所述概念模型与PROV模型的映射框架，使用PROV‑O将遥感影像溯源信息表达成RDF数据；对遥感影像元数据模型UMM的元数据信息进行维度归纳，将溯源信息嵌入遥感影像元数据模型UMM，得到溯源表达增强的元数据组织模型；提出遥感影像溯源信息获取方法，并搭建了遥感影像溯源信息组织管理系统。本发明将溯源模型嵌入到元数据模型中，设计了溯源表达增强的元数据组织模型，丰富了元数据内容，可方便地进行溯源追踪及元数据查找与检索，满足复杂的溯源需求。
The invention discloses a multi-source remote sensing image meta data traceability information organization method and a management system. The method includes: abstracting the multi-source remote sensing image traceability information into four types of elements: event, entity, relationship and attribute, in a map-based manner Establish a conceptual model of multi-source remote sensing image traceability information; establish a mapping framework between the conceptual model and the PROV model, use PROV-O to express remote sensing image traceability information into RDF data; dimension the metadata information of the remote sensing image metadata model UMM In summary, the traceability information is embedded in the remote sensing image metadata model UMM, and a metadata organization model with enhanced traceability expression is obtained; a method for obtaining remote sensing image traceability information is proposed, and a remote sensing image traceability information organization management system is built. The invention embeds the traceability model into the metadata model, designs a metadata organization model with enhanced traceability expression, enriches the metadata content, can conveniently perform traceability and metadata search and retrieval, and satisfies complex traceability requirements.
Description
Technical Field
The invention belongs to the field of remote sensing image data organization management, and particularly relates to a method and a system for organizing metadata source tracing information of a multi-source remote sensing image.
Background
With the continuous development of earth observation technology, a plurality of remote sensing satellites are emitted internationally and successively, multi-level, multi-angle, omnibearing and all-weather earth observation is realized, remote sensing image data are extremely rich, the remote sensing satellite earth observation system is widely applied to the fields of natural resource monitoring and the like, and rich high-grade data products such as earth surface coverage, water resource distribution and the like are formed. However, remote sensing image data has different space-time resolution and quality, and the processing method from original remote sensing data to data products is various, so that the quality of the remote sensing products is different. The tracing information records the data production process and is an important basis for evaluating the data quality such as availability, reliability and the like of remote sensing data products.
According to the processing level (radiation correction, geometric correction and the like), the remote sensing data can be divided into different levels, and the processing steps of the data of the same level are the same. For example, level L0 represents raw data received by the ground station; the L1-level data is data radiation-corrected from the L0-level data. At present, official remote sensing data platforms such as Landsat, sentinel, MODIS and high-score provide data downloading according to the scene (Granule), and multi-scene images of the same level are classified into a set (Collection). The remote sensing data is used as a reusable resource, and is distributed very frequently in a network environment. After a user downloads an image according to a scene, analysis processing such as atmospheric correction, image fusion, surface feature extraction and the like is carried out on the data according to different service requirements, and the method has the characteristics of long processing chain, various algorithms of the same type and the like, and in the analysis processing process, the spatial range, the spatial resolution, the spectral data and the like of the remote sensing image are likely to change. Therefore, the tracing of the remote sensing data is very complex, and modeling and expression of the tracing information are important technical challenges.
The patent CN 111147384A discloses a remote sensing image data transmission path encoding method facing to tracing, which acquires path node information in the remote sensing image data transmission process, encodes and updates the path node information, and realizes tracing of the path node information. At present, the tracing information recorded in the remote sensing image metadata is few, the complex tracing requirement cannot be met, and how to embed the tracing information into the metadata is also an important problem to be solved.
Disclosure of Invention
In view of this, the invention provides a method for organizing source tracing information of multi-source remote sensing image metadata and a management system, which are used for solving the problem that information recorded in the remote sensing image metadata cannot meet complex source tracing requirements.
The invention discloses a multi-source remote sensing image pixel data traceability information organization method in a first aspect, which comprises the following steps:
obtaining multi-source remote sensing image tracing information under different scenes; abstracting multi-source remote sensing image traceability information into four types of elements of events, entities, relations and attributes, and establishing a conceptual model of the multi-source remote sensing image traceability information in a mapping mode;
and carrying out dimension induction on the remote sensing image metadata model UMM, and embedding the traceability information into the remote sensing image metadata model UMM based on the image source, the processing process and the relationship among the images of the traceability information in the conceptual model to obtain a metadata organization model with enhanced traceability expression.
On the basis of the above technical solution, preferably, the method for obtaining the multi-source remote sensing image traceability information based on the original remote sensing image data includes:
modeling from top to bottom according to the interlayer level relation of the remote sensing images, and creating traceability information in batches;
automatically capturing algorithm, input/output and execution time information used by a remote sensing data processing tool, and recording a traceability information fragment by using PROV-O;
manually inputting the tracing information of the remote sensing data by a user through an interactive interface;
and (4) according to the semantic relation of the tracing map, performing tracing relation mining and automatically completing tracing information.
On the basis of the above technical solution, preferably, abstracting the multi-source remote sensing image traceability information into four types of elements of events, entities, relationships, and attributes specifically includes:
abstracting the processing process of the remote sensing image into event elements, wherein the event elements have attribute information within the starting time and the ending time;
abstracting an image data set, a single remote sensing image, a processing algorithm and related individuals/mechanisms involved in the processing process of the remote sensing image into entity elements;
the relationship elements comprise relationships between entities and events;
the attribute element is semantic information included in the event element, the entity element, or the relationship element.
On the basis of the above technical solution, preferably, the relationship between the entity and the entity includes an inclusion relationship between the image data set and a single remote sensing image, a derivation or substitution relationship between the image data set and the image data set, a derivation or substitution relationship between a single remote sensing image and a single remote sensing image, and an attribution relationship between the image data set or the single remote sensing image and the individual/organization;
the variable dimension information in the derivative relationship is expressed by a coding scheme, and the coding order represents the spatial range, the band information, the resolution and the data type from left to right.
On the basis of the above technical solution, preferably, the performing dimensionality induction on the remote sensing image metadata model UMM, based on the image source, the processing process and the inter-image relationship of the traceability information in the conceptual model, embedding the traceability information into the remote sensing image metadata model UMM, and obtaining the metadata organization model with enhanced traceability expression specifically includes:
the remote sensing image metadata model UMM is summarized into eight-dimensional information: identification dimension, time dimension, space dimension, traceability dimension, platform dimension, data dimension, quality dimension and authority dimension;
analyzing the image source, the processing process and the relationship information between the images of the traceability information in the conceptual model, embedding the traceability information into the traceability dimension of the remote sensing image metadata model UMM, and obtaining the metadata organization model with enhanced traceability expression.
On the basis of the above technical solution, preferably, the method further includes:
and establishing a mapping frame of the conceptual model and the PROV model, expressing the traceability information of the conceptual model into RDF data by using PROV-O, and sharing the traceability information of the remote sensing image in the Web environment based on the RDF data.
On the basis of the above technical solution, preferably, the establishing a mapping framework of the conceptual model and the PROV model specifically includes:
mapping event elements in the conceptual model to activities of the PROV model;
mapping entity elements in the conceptual model into entities or agents of the PROV model; wherein the image data set and the single remote sensing image are mapped into an entity of the PROV model, and the individuals/institutions and the software are mapped into an agent of the PROV model;
and mapping the relation elements in the conceptual model into seven relations in the PROV model.
In a second aspect of the present invention, a multi-source remote sensing image metadata traceability information management system is disclosed, the system is based on the method of the first aspect of the present invention, the system comprises:
the source tracing information importing module comprises: the tracing information is used for importing tracing information and supports the import of a tracing information fragment in a PROV-O format;
a metadata storage module: the source tracing system is used for organizing and storing the tracing information and the metadata according to a metadata organization model;
a source tracing information query module: the remote sensing image source tracing and metadata searching and retrieving system is used for tracing the remote sensing image and searching and retrieving metadata based on the metadata organization model;
the tracing information visualization module: the method is used for performing map type visual display on the tracing information.
Compared with the prior art, the invention has the following beneficial effects:
1) According to the invention, event, entity, relation and attribute information in the remote sensing image derivation process are expressed in a atlas mode, a concept model facing to the tracing information is constructed, the tracing model is embedded into a metadata model, a metadata organization model for enhancing the tracing information is designed, and metadata content is enriched;
2) The traceability information-oriented conceptual model records information such as steps, used algorithms, software environments, activity executors, changes of derivative data generated after processing and the like from a data source to the processing process, expresses the variable dimensional information in the derivative relation through a coding scheme, can perform traceability tracking in all directions, and improves the availability and reliability of remote sensing image traceability;
3) The invention provides a mapping method of a traceability concept model and a PROV traceability model, expands a W3CPROV model, improves the interoperability of remote sensing image traceability information in the Web field, and facilitates data sharing.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a multi-source remote sensing image metadata traceability information organization method of the present invention;
FIG. 2 is a conceptual model diagram of remote sensing image traceability information according to the present invention;
FIG. 3 is a diagram of the remote sensing image metadata change encoding of the present invention;
FIG. 4 is a mapping frame diagram of a remote sensing image traceability information conceptual model and a W3C PROV model according to the invention;
FIG. 5 is a diagram of the method for extending the remote sensing image metadata model of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments of the present invention, belong to the protection scope of the present invention.
Referring to fig. 1, the present invention provides a method for organizing metadata traceability information of a multi-source remote sensing image, where the method includes:
s1, obtaining multi-source remote sensing image traceability information under different scenes.
The remote sensing image traceability information refers to the complete record of all processes from the beginning to the extinction of the remote sensing image, and comprises the source of data, producer information, processing steps and processing algorithms in the data production process and the like. The invention provides four acquisition modes of remote sensing image traceability information:
1) Modeling from top to bottom: modeling from top to bottom according to the interlayer level relation of the remote sensing images, and creating traceability information in batches; for example, in fig. 2, the video data L2 in the data set Landsat Collection2 is derived from the video data L1.
2) Automatic capture by the remote sensing data processing tool: when the remote sensing image is processed by using a remote sensing data software processing tool, information such as an algorithm, input/output, execution time and the like used in the remote sensing image is automatically captured, and a tracing information fragment is recorded by using PROV-O.
3) Manual input: manually inputting the tracing information of the remote sensing data through an interactive interface by a user;
4) And (3) tracing relation mining: and (4) according to the semantic relation of the tracing atlas, performing tracing relation mining and automatically completing tracing information.
S2, abstracting the multi-source remote sensing image traceability information into four elements of events, entities, relations and attributes, and establishing a conceptual model of the multi-source remote sensing image traceability information in a mapping mode.
The method constructs a conceptual model of the tracing information in a mapping mode, and abstracts the tracing information into four types of elements of events, entities, relationships and attributes. The processing process of the remote sensing image is abstracted into event elements, and the event elements have attribute information with the starting time and the ending time; abstracting an image data set (Collection), a single remote sensing image (Granule), a processing algorithm and related individuals/mechanisms involved in the processing process of the remote sensing image into entity elements; the relationship element describes the relationship between the entity and the relationship between the entity and the event; the attribute element describes semantic information contained in the event element, the entity element, or the relationship element.
Fig. 2 is a conceptual model diagram of remote sensing image traceability information, which is illustrated by Landsat data, and records change information, such as changes in spatial range, resolution, and band information, generated from steps, algorithms, software environments, and activity executors, which are performed in the data source to processing, to the processed information. In fig. 2, an image data set Collection1L1 and an image data set Collection 2L 1 obtained from a data source Landsat are in a replaceable relationship, the image data set Collection 2L 1 derives an image data set Collection 2L 2, a single image data grain 2 in the image data set Collection 2L 1 is subjected to atmospheric correction processing to obtain a single image data grain 3, the single image data grain 3 is subjected to water body extraction to obtain a single image data grain 4, various attribution relationships, incidence relationships, derivation relationships and the like are included, and a complete remote sensing image traceability information conceptual model is finally constructed and obtained.
Table 1 lists the concepts of the four types of elements of events, entities, relationships and attributes and the elements that they contain.
Table 1 traceability information conceptual model element table
As can be seen from table 1, the relationship between the entities includes an inclusion relationship between the image dataset and a single remote-sensing image, a derivation or substitution relationship between the image dataset and the image dataset, a derivation or substitution relationship between a single remote-sensing image and a single remote-sensing image, and an attribution relationship between the image dataset or a single remote-sensing image and a person/organization. The derivative relationship between the images can identify the variation dimensionality of the images through the attribute of the variation code, for example, the variation of the spatial dimensionality (cropping operation and the like), the variation of the spatial resolution dimensionality (resampling and the like), and the variation of the image wave band dimensionality (calculation of the normalized vegetation index and the like).
The invention expresses the changed dimension information in the derivative relation through an encoding scheme, encodes the changed information into '01', and encodes other dimensions which are not changed into '00'. As shown in fig. 3, a specific encoding method is illustrated, and the encoding sequence represents a spatial range, band information, resolution, data type, and the like from left to right, and the encoding method can be extended according to actual needs.
Taking the image processing process in fig. 2 as an example, the water extraction processing operation is performed between the image kernel 4 and the image kernel 3, and the operation is implemented by calculating the water index through the NDWI, and the image band information is changed, so the metadata change information is encoded to "00010000", and the encoding sequence represents the spatial range, the band information, the resolution and the data type from left to right.
And S3, establishing a mapping frame of the conceptual model and the PROV model, using PROV-O to express the traceability information of the conceptual model into RDF data, and sharing the traceability information of the remote sensing image in the Web environment based on the RDF data.
The W3C PROV model defines three cores including an Entity (Entity), an Agent (Agent), and an Activity (Activity), and seven relations defining the relationships between the inside of each of the three cores and each other, such as a derivative relationship between output and input data, a representative relationship between an individual and an organization, a usage or generation relationship between processing and data, and the like.
The method realizes the tracing information sharing under the distributed environment by establishing the mapping framework of the tracing information conceptual model and the W3C PROV tracing model. Specifically, mapping event elements in the conceptual model into activities (Activities) of the PROV model; mapping entity elements in the conceptual model into entities or agents of the PROV model; wherein, the entities such as mapping of the image data set (Collection) and the single remote sensing image (Granule) are entities (Entity) of the PROV model, and the individuals/mechanisms and the software are mapped to agents (Agent) of the PROV model; the relationship elements in the conceptual model are mapped to seven relationships in the PROV model. Two entities may be considered as alternatives to each other if they differ only slightly or not.
As shown in fig. 4, which is a mapping framework constructed by the present invention, the present invention uses elements with different shapes to respectively represent three elements, namely an Entity (Entity), an Activity (Activity), and an Agent (Agent) in a PROV model, and further maps the relationship between the elements. For example, an ellipse represents an Entity (Entity) in the PROV model, and may include an image data set (Collection), a single remote sensing image (Granule), an Algorithm (Algorithm), and the like; rectangles represent activities (Activities) in the PROV model, which may represent the processing of imagery; the hexagon represents an Agent (Agent) in the PROV model, and can be an organization or an individual to which the remote sensing image data source belongs, or an executor of the processing process, and the like.
The source tracing information is expressed into RDF (Resource Description Framework) data by using PROV Ontology (PROV-O) pushed by W3C, and the expression of the source tracing information knowledge can be realized. The traceability information expression based on the PROV model improves the interoperation capacity of the remote sensing image traceability information in the Web environment, and can conveniently share the traceability information.
And S4, carrying out dimensionality induction on metadata information of the remote sensing image metadata model UMM, and embedding the traceability information into the remote sensing image metadata model UMM based on the image source, the processing process and the relationship among the images of the traceability information in the conceptual model to obtain a metadata organization model with enhanced traceability expression.
The remote sensing image Metadata model UMM used by NASA is an extensible Metadata model, mainly comprises seven configuration files including UMM-C, UMM-G, UMM-S, UMM-Var, UMM-Vis, UMM-T and UMM Common, and provides a bridge for mapping between Metadata standards supported by CMR (Common Metadata Repository). The method expands a remote sensing image metadata model UMM, embeds the traceability information into the metadata model, and designs a metadata organization model with enhanced traceability expression.
Firstly, the metadata information of the remote sensing image metadata model UMM is summarized into eight-dimensional information: the identification dimension, the time dimension, the space dimension, the traceability dimension, the platform dimension, the data dimension, the quality dimension and the authority dimension, and the metadata information mainly contained in the eight dimensions is shown in table 2.
Table 2 metadata organizational model dimension table
And then, analyzing the image source, the processing process and the relationship information among the images of the tracing information in the conceptual model established in the step S2, and embedding the tracing information into the tracing dimension of a remote sensing image metadata model UMM to obtain a metadata organization model with enhanced tracing expression. Fig. 4 shows an example of the metadata organization model obtained by extension, in which a dashed box is embedded traceability information, and specifically, information such as relationships between images, relationship types, single image traceability, image processing procedures, image processing events, image processing data sources, and image set traceability is embedded.
And S5, visual traceability tracking and metadata searching and retrieving of the remote sensing image.
The metadata information of the remote sensing image metadata model UMM is subjected to multi-dimensional induction, the metadata information of each dimension is summarized, the traceability information is embedded into the metadata information, the metadata content is enriched, the capability of expressing the traceability information by the remote sensing image metadata is improved, the traceability tracking and the metadata searching and retrieving of the image can be realized through the organizational model, the image processing process is made public and transparent, and the guarantee is provided for the traceability of the quality of remote sensing image products.
On the basis of the above method for organizing the source tracing information of the metadata of the multi-source remote sensing image, the invention also provides a system for managing the source tracing information of the metadata of the multi-source remote sensing image, which comprises:
the source tracing information importing module: the tracing information is used for importing tracing information and supports the import of a tracing information fragment in a PROV-O format;
a metadata storage module: the source tracing system is used for organizing and storing the source tracing information and the metadata according to the form of a metadata organization model; the specific organization is the same as steps S1 to S4 of the method embodiment described above.
A source tracing information query module: the remote sensing image source tracing and metadata searching and retrieving system is used for tracing the remote sensing image and searching and retrieving metadata based on the metadata organization model;
the traceability information visualization module: the method is used for performing map type visual display on the tracing information.
The system adopts a B/S framework, the back end of the system is developed based on a Springboot framework by using a JAVA language, and the front end of the system is developed based on OpenLayers. The system uses open-source relational database software PostgreSQL to store remote sensing image metadata, wherein spatial dimension information is stored in a spatial extension PostGIS of the PostgreSQL. The system supports the import of the tracing information fragment in the PROV-O format, and also provides a remote sensing image tracing information query interface and a map type visualization mode.
The above system embodiments are implemented based on method embodiments, and please refer to the method embodiments for brief description of the system embodiments.
The above-described system embodiments are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, i.e. may be distributed over a plurality of network units. Without creative labor, a person skilled in the art can select some or all of the modules according to actual needs to achieve the purpose of the solution of the embodiment.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
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