A method for surveying and mapping geographic multi-element data fusion processing

Abstract

The application discloses a kind of surveying and mapping geographic multi-element data fusion processing method, including design GIS+Data mode platform;Complete database fast drawing and image fast processing;Content extraction;Two kinds of logical symbols are carried out mapping form parallel distribution processing by ART network model;Obtain logical symbol combination data;Fusion data is loaded to different corresponding data resource warehouse according to different field processing and is constantly expanded and optimized using inference mechanism in symbol logic model to data.This application has the advantages that: data format conversion, content extraction, scale matching, regional splicing and other fusion processing are adopted, environmental data support is provided to users and information systems based on surveying and mapping geographic information application, and the application needs of users in different scenes are met;Different sources of data are fused according to unified standards, certain fusion rules and models, to provide support for data fusion analysis services, realize effective use of data, and improve the value of data utilization.

Description

Technical Field

[0001] This invention relates to the field of surveying and mapping geographic data processing technology, specifically a method for fusion processing of multi-source surveying and mapping geographic data. Background Technology

[0002] Surveying and mapping geographic information serves as a crucial engine for environmental protection capabilities, covering a wide area and requiring high data accuracy. However, due to the dispersed nature of surveying and mapping geographic data resources, the lack of effective connections between data resource construction, management, and application, and significant differences in data structure, a multi-source data fusion processing mechanism is urgently needed. Therefore, to address the data resource fusion problem in surveying and mapping geographic fields, this paper proposes a multi-source data fusion processing method for surveying and mapping geographic fields. Summary of the Invention

[0003] The purpose of this invention is to provide a method for fusion processing of multi-source surveying and mapping geographic data in order to solve the above-mentioned problems.

[0004] This invention achieves the above objectives through the following technical solution: a method for fusion processing of multi-source surveying and mapping geographic data, comprising the following specific steps:

[0005] Step 1: Design a GIS+ data model platform using data catalogs, thematic data, and framework data;

[0006] Step 2: The GIS+ data model platform completes rapid database mapping and rapid image processing based on the task request form.

[0007] Step 3: Extract content from the data requested by the GIS+ data model platform to obtain map data and image data;

[0008] Step 4: Label the output data and image data with two different logical symbols, and use the ART network model to perform parallel distributed processing of the two logical symbols in a mapping form;

[0009] Step 5: Obtain logical symbol combination data through parallel distributed processing using size matching and region splicing;

[0010] Step Six: The logical symbol combination data group uses ETL technology to process and load the integrated data into different corresponding data resource warehouses according to different domains;

[0011] Step 7: The data resource warehouse is connected to the symbolic logic model via a network terminal, and the data is continuously expanded and optimized using the reasoning mechanism in the symbolic logic model;

[0012] Step 8: Integrate the fused data to construct a multi-domain geographic mapping database;

[0013] Step 9: Integrate multi-domain geographic mapping databases into the service platform for users to access and reference.

[0014] Preferably, the thematic data and framework data are derived from basic surveying and mapping geographic information data, and are integrated with UAV aerial imagery and satellite imagery application results, providing high-resolution, dynamic imagery services through a cloud platform.

[0015] Preferably, the GIS+ data model platform integrates large-scale vector data, high-resolution image data, place names and addresses, oblique photogrammetry data, planning data, and other thematic data to build a spatiotemporal foundation and thematic database.

[0016] Preferably, the GIS+ data model platform transforms traditional data combination into data fusion, static data into dynamic data, and real-time data into temporal data, while transforming data publishing into capability services.

[0017] Preferably, the logical symbol of the output data is A, and the logical symbols of different output data are A1, A2...An. Each logical symbol has a vector data and a place name address.

[0018] Preferably, the logical symbol of the image data is B, and the logical symbols of different image data are B1, B2...Bn. Each logical symbol has a high-resolution image data, a place name address, and an oblique photogrammetry data.

[0019] Preferably, the logical symbols An of the map data with the same place name and address and the logical symbols Bn of the image data are mapped together through parallel distributed processing using an ART network model to obtain logical symbol combination data AnBn. The logical symbol combination data AnBn is then subjected to cleaning, transformation, and integration in ETL technology until it is processed and loaded into different corresponding data resource warehouses.

[0020] Preferably, the service support system of the data resource warehouse consists of data control, resource management, and collaboration support. Data control is used to store, manage, and back up the raw data, production process data, and result data required for production. Collaboration support is responsible for providing the operating environment and storage and computing resources required for business processing in conjunction with the GIS+ data model platform according to the business tool requirements corresponding to specific tasks.

[0021] Preferably, the inference mechanism symbols of the symbolic logic model include An, Bn, and AnBn, which determine a certain type of data to be supplemented and optimized, thereby playing the role of comprehensively updating the data.

[0022] Preferably, the multi-domain geographic mapping database adopts a hybrid polymorphic data storage method to uniformly store and manage remote sensing images and vector map multi-domain heterogeneous data, providing data storage support for various applications.

[0023] The beneficial effects of this invention are: by adopting data format conversion, content extraction, scale matching, and regional stitching, it provides environmental data support to users and information systems based on surveying and mapping geographic information applications, meeting the application needs of users in different scenarios; by fusing data from different sources according to unified standards, certain fusion rules and models, it provides support for data fusion analysis services, ultimately realizing the effective utilization of data and improving the utilization value of data. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present 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 only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart of the surveying and mapping geographic multi-source data fusion processing method of the present invention. Detailed Implementation

[0026] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0027] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0028] In the description of this invention, it should be understood that the terms "upper", "lower", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0029] Please see Figure 1 As shown, a method for fusion processing of multi-source surveying and mapping geographic data includes the following steps:

[0030] Step 1: Design a GIS+ data model platform using data catalogs, thematic data, and framework data;

[0031] Step 2: The GIS+ data model platform completes rapid database mapping and rapid image processing based on the task request form.

[0032] Step 3: Extract content from the data requested by the GIS+ data model platform to obtain map data and image data;

[0033] Step 4: Label the output data and image data with two different logical symbols, and use the ART network model to perform parallel distributed processing of the two logical symbols in a mapping form;

[0034] Step 5: Obtain logical symbol combination data through parallel distributed processing using size matching and region splicing;

[0035] Step Six: The logical symbol combination data group uses ETL technology to process and load the integrated data into different corresponding data resource warehouses according to different domains;

[0036] Step 7: The data resource warehouse is connected to the symbolic logic model via a network terminal, and the data is continuously expanded and optimized using the reasoning mechanism in the symbolic logic model;

[0037] Step 8: Integrate the fused data to construct a multi-domain geographic mapping database;

[0038] Step 9: Integrate multi-domain geographic mapping databases into the service platform for users to access and reference.

[0039] Furthermore, the thematic data and framework data are derived from basic surveying and mapping geographic information data, and are integrated with UAV aerial imagery and satellite imagery application results, providing high-resolution, dynamic imagery services through a cloud platform.

[0040] Furthermore, the GIS+ data model platform integrates large-scale vector data, high-resolution image data, place names and addresses, oblique photogrammetry data, planning data, and other thematic data to build a spatiotemporal foundation and thematic database.

[0041] Furthermore, the GIS+ data model platform transforms traditional data combination into data fusion, static data into dynamic data, and real-time data into temporal data, while also transforming data publishing into capability services.

[0042] Furthermore, the logical symbol of the output data is A, and the logical symbols of different output data are A1, A2...An. Each logical symbol has a vector data and a place name address.

[0043] Furthermore, the logical symbol for the image data is B, and the logical symbols for different image data are B1, B2...Bn. Each logical symbol contains a high-resolution image data, a place name address, and an oblique photogrammetry data.

[0044] Furthermore, the logical symbols An of the map data with the same place name and address and the logical symbols Bn of the image data are mapped together through parallel distributed processing using the ART network model to obtain logical symbol combination data AnBn. The logical symbol combination data AnBn is then subjected to cleaning, transformation, and integration in ETL technology until it is processed and loaded into different corresponding data resource warehouses.

[0045] Furthermore, the service support system of the data resource warehouse consists of data control, resource management, and collaboration support. Data control is used to store, manage, and back up the raw data, production process data, and result data required for production. Collaboration support is responsible for providing the operating environment and storage and computing resources required for business processing in conjunction with the GIS+ data model platform according to the business tool requirements corresponding to specific tasks.

[0046] Furthermore, the reasoning mechanism of the symbolic logic model includes symbols An, Bn, and AnBn, which determine a certain type of data to be supplemented and optimized, thereby playing a role in comprehensively updating the data.

[0047] Furthermore, the multi-domain geographic mapping database adopts a hybrid polymorphic data storage method to uniformly store and manage remote sensing images and vector maps, providing data storage support for various applications.

[0048] The advantages of this multi-source data fusion processing method for surveying and mapping geographic information are as follows: by adopting fusion processing such as data format conversion, content extraction, scale matching, and regional stitching, it provides environmental data support to users and information systems based on surveying and mapping geographic information applications, meeting the application needs of users in different scenarios; by fusing data from different sources according to unified standards, certain fusion rules and models, it provides support for data fusion analysis services, ultimately realizing the effective utilization of data and improving the utilization value of data.

[0049] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalent elements of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0050] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. 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. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for fusion processing of multi-source surveying and mapping geographic data, characterized in that: The specific steps include: Step 1: Design a GIS+ data model platform using data catalogs, thematic data, and framework data; Step 2: The GIS+ data model platform completes rapid database mapping and rapid image processing based on the task request form. Step 3: Extract content from the data requested by the GIS+ data model platform to obtain map data and image data; Step 4: Label the output data and image data with two different logical symbols, and use the ART network model to perform parallel distributed processing of the two logical symbols in a mapping form; Step 5: Obtain logical symbol combination data through parallel distributed processing using size matching and region splicing; Step Six: The logical symbol combination data group uses ETL technology to process and load the integrated data into different corresponding data resource warehouses according to different domains; Step 7: The data resource warehouse is connected to the symbolic logic model via a network terminal, and the data is continuously expanded and optimized using the reasoning mechanism in the symbolic logic model; Step 8: Integrate the fused data to construct a multi-domain geographic mapping database; Step 9: Integrate multi-domain geographic mapping databases into the service platform for user reference.

2. The method for fusion processing of multi-source surveying and mapping geographic data according to claim 1, characterized in that: The thematic and framework data are derived from basic surveying and mapping geographic information data, and also integrate UAV aerial imagery and satellite imagery application results, providing high-resolution, dynamic imagery services through a cloud platform.

3. The method for fusion processing of multi-source surveying and mapping geographic data according to claim 1, characterized in that: The GIS+ data model platform integrates large-scale vector data, high-resolution image data, place names and addresses, oblique photogrammetry data, planning data, and other thematic data to build a spatiotemporal foundation and thematic database.

4. The method for fusion processing of multi-source surveying and mapping geographic data according to claim 1, characterized in that: The GIS+ data model platform transforms traditional data combination into data fusion, static data into dynamic data, and real-time data into temporal data, while also transforming data publishing into capability services.

5. The method for fusion processing of multi-source surveying and mapping geographic data according to claim 1, characterized in that: The logical symbol for the output data is A, and the logical symbols for different output data are A1, A2...An. Each logical symbol has a vector data and a place name address.

6. The method for fusion processing of multi-source surveying and mapping geographic data according to claim 1, characterized in that: The logical symbol for the image data is B, and the logical symbols for different image data are B1, B2...Bn. Each logical symbol contains a high-resolution image data, a place name address, and an oblique photogrammetry data.

7. The method for fusion processing of multi-source surveying and mapping geographic data according to claim 5, characterized in that: The logical symbols An of the map data with the same place name and address and the logical symbols Bn of the image data are mapped together through parallel distributed processing using the ART network model to obtain the logical symbol combination data AnBn. The logical symbol combination data AnBn is then cleaned, transformed, and integrated in ETL technology until it is processed and loaded into different corresponding data resource warehouses.

8. The method for fusion processing of multi-source surveying and mapping geographic data according to claim 1, characterized in that: The service support system of the data resource warehouse consists of data control, resource management, and collaboration support. Data control is used to store, manage, and back up the raw data, production process data, and output data required for production. Collaboration support is responsible for providing the necessary operating environment and storage / computing resources to work with the GIS+ data model platform to meet the specific business tool requirements of each task.

9. The method for fusion processing of multi-source surveying and mapping geographic data according to claim 1, characterized in that: The inference mechanism of the symbolic logic model includes symbols An, Bn, and AnBn, which determine a certain type of data to be supplemented and optimized, thus playing a role in comprehensively updating the data.

10. The method for fusion processing of multi-source surveying and mapping geographic data according to claim 1, characterized in that: The multi-domain geographic mapping database adopts a hybrid polymorphic data storage method to uniformly store and manage remote sensing images and vector maps, providing data storage support for various applications.

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