Static publishing method for geographic information data

Abstract

The invention provides a geographic information data static publishing method, and belongs to the field of geographic information data publishing. By constructing a classified directory system and a non-server-side analysis architecture, a geographic information data publishing normal form of zero configuration deployment and full static publishing is realized. And a front-end localization analysis mechanism is adopted, so that data are analyzed and rendered in a browser isolation environment, and the risk of unauthorized access is effectively prevented. The method specifically comprises the steps that a hierarchical directory structure is established according to preset classification codes, and a corresponding URL access path is generated through automatic mapping; executing a geometric generalization algorithm on the original geographic information data to generate a plurality of versions containing different levels of detail; specifying a unified coordinate system and converting the coordinate system into GeoJSON format data, distinguishing precision versions through a standardized naming rule, and deploying the precision versions in corresponding classification directories according to the rule; and through independent thread analysis, security isolation rendering and coordinate boundary verification are implemented, and version tracing-supported geographic information data static Web release is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of new generation information technology industry, and in particular to a geographic information data static publishing method. BACKGROUND

[0002] The publishing technology of geographic information data has evolved from traditional GIS software, open data platform to WebGIS application program, cloud platform service and mobile application. The technical system has become mature, and users can select different publishing methods according to data characteristics and application scenarios. Although domestic and foreign researches widely cover the field of vector data publishing [1][2][3] , there are still common bottlenecks: traditional WebGIS relies on middleware such as GeoServer and Tomcat server [4] , and the operation and maintenance cost is high and the response delay is significant.

[0003] Although the cloud platform scheme improves the elastic scaling capability, it cannot avoid the middleware dependence and data sovereignty risk. For example, the cloud storage model proposed by the team of China University of Geosciences still needs GeoTools to support spatial index [5] , and although the optimization transmission technology such as CoGebuf improves the efficiency, it still needs the server to generate spatial index and maintain API, and there is the risk of unauthorized access [6] ; the static publishing scheme is limited by data size and dynamic interaction capability. For example, the mass data engine of Tian Peng et al. supports large-scale data, but relies on PostgreSQL cluster, and the deployment complexity is too high [7] .

[0004] In the lightweight solution, the static website generator (SSG) and the pre-rendering technology try to improve the performance [8] , but due to the lack of native support for spatial topology, they still need GIS servers to assist in coordinate system conversion and topology relationship processing, resulting in redundant architecture. It is worth noting that Liu Bo et al. proposed a fast publishing method of geographic information data based on browser, which represents a local optimization attempt - this scheme renders GeoJSON vector slices in real time through Canvas on the browser side, dynamically calculates the label position, avoids the pre-processing of the server side slices, and reduces the server load by using the browser computing power [9] . However, its core defect is that it still needs the server to provide the original GeoJSON data, and it does not realize full static resource hosting, and it does not design a data security isolation mechanism, and the original data may be exposed through the server interface. Other technical paths also highlight the server dependence: for example, the scheme of optimizing browser concurrency disperses the request through multiple subdomains, but needs the server to generate 3DTiles index and respond to HTTP Range request

[10] .

[0005] Compared with the above-mentioned technologies, the application realizes breakthrough through the innovative architecture of radically curing server dependence: first, an automatic directory-URL mapping mechanism is established, a hierarchical directory is constructed according to a preset classification code, and cloud platform API routing configuration is replaced; then, spatial operations such as coordinate system conversion and geometric generalization are moved to the browser isolation environment, and full-link analysis is performed to prevent unauthorized access; at the same time, static management is realized through pre-generated multi-precision GeoJSON files and standardized naming rules; finally, components such as PostgreSQL / GeoServer are removed, and pure static resource hosting is achieved, thus breaking through the server dependence bottleneck from the root.

[0006] Users only need to organize data directories according to rules to achieve efficient publishing, while supporting front-end dynamic interaction functions such as setting styles and markers, zooming and positioning, filtering and searching, and data precision switching. This method not only maintains the flexibility and ease of use of data publishing, but also simplifies the publishing process, reduces the technical threshold and cost, and enables users to more efficiently publish and display geographic information data.

[0007] REFERENCES

[0008] [1] Li J, Wu J P. Three-dimensional spatial data network publishing based on Skyline[J]. Surveying and Mapping Science, 2010, 35(02): 183-185. DOI:10.16251 / j.cnki.1009-2307.2010.02.048.

[0009] [2] Liang J J, Zhang Z Q, Cheng Y X. Research on data updating system of geographic information public service platform framework[J]. Bulletin of Surveying and Mapping, 2012, (12): 79-83.

[0010] [3] Li H Y, Lu X P, Wang Z J, et al. Real-time publishing and implementation of dynamic vector data and online maps[J]. Bulletin of Surveying and Mapping, 2017, (04): 104-107. DOI:10.13474 / j.cnki.11-2246.2017.0131.

[0011] [4] Wu G C, Wang B, Ge Z T. Research and implementation of automatic publishing of vector data and online map matching scheme based on GeoServer[J]. Electronic Components and Information Technology, 2022, 6(10): 9-12. DOI:10.19772 / j.cnki.2096-4455.2022.10.003.

[0012] [5] Zheng K, Fu Y L. Research on vector spatial data storage model based on HBase and GeoTools[J]. Computer Application and Software, 2015, 32(03): 23-26.

[0013] [6] Zhongke Xingtu Digital Earth Hefei Co., Ltd. Cloud-optimized static geographic information vector data online service method: 202211045374.6[P]. 2023-11-10.

[0014] [7] Tian Peng, Li Jun, Chen Guihong. Engine development and application practice of network publishing of massive vector map data[J]. Geographic Information World, 2010, 8(02): 68-73.

[0015] [8] Guangdong Chaoyang Qixuntong Technology Co., Ltd. A multi-functional dynamic website development method and system: 202411852381.6[P]. 2025-03-21.

[0016] [9] Karamay Tianditu Co., Ltd. A method for quickly publishing geographic information data based on a browser: 202310892618.2[P]. 2024-06-28.

[0017]

[10] China Four-Dimensional Surveying and Mapping Technology Co., Ltd. A method and system for optimizing concurrent request geographic information data of a browser: 202311864919.0[P]. 2024-04-09. SUMMARY

[0018] The present application provides a geographic information data static publishing method, under the architecture without server-side parsing, by constructing a classified directory system, establishing an automatic bidirectional mapping mechanism of the directory and the URL path, performing data geometric generalization processing, generating multiple precision version data, through independent thread parsing, safe isolation rendering, realizing the static publishing of geographic information data;

[0019] The steps include:

[0020] S1 Classification directory construction (1): create a multi-level directory structure conforming to the naming specification of [classification code] [serial number]_[semantic label], wherein [classification code] uses English letter to identify data classification attribute, [serial number] uses Arabic numerals to establish directory sorting, and [semantic label] is a semantic short label of general text;

[0021] S2 Path generation (2): automatically generate the corresponding URL access path according to the physical directory hierarchical structure created in step S1, and establish the bidirectional mapping relationship between the directory and the network address;

[0022] S3 Data conversion (3): attribute whitelist filtering is performed on the original geographic information data, geometric generalization algorithm is executed to process the data, multiple data versions containing different detail levels are generated, precision levels are marked, and standardized GeoJSON format data is output;

[0023] S4 Web page publishing (4): Adopting independent thread to parse GeoJSON data file, implementing coordinate boundary check, longitude range is-180 to 180, latitude range is-90 to 90.

[0024] As preferred, the serverless parsing architecture refers to not relying on server-side dynamic logic and database system, and users realize autonomous publishing of vector data through static file hosting.

[0025] As preferred, step S1 category construction naming specification follows [category code][serial number]_[semantic label] three-element rule:

[0026] [category code] adopts English letters, used for identifying data classification attribute;

[0027] [serial number] adopts two-digit number, virtual bit is filled with 0, and the fixed length is constrained from 01 to 99;

[0028] [semantic label] adopts semanticized label of general text, and the length is constrained to be less than or equal to 20 characters.

[0029] As preferred, step S3 data conversion further includes:

[0030] establishing attribute whitelist filtering rule containing field name regular expression, and performing attribute whitelist filtering;

[0031] performing geometric generalization algorithm processing data, automatically adjusting simplification threshold according to spatial span of feature, and implementing multi-level precision control of geographic feature simplification processing;

[0032] generating data precision version number corresponding to the geometric generalization processing level, and marking the precision version number in the generated GeoJSON data file name.

[0033] As preferred, for the directory level with subfolders, step S3 data conversion further includes:

[0034] In order to reduce the amount of data transmission, the hierarchical data with subfolders is generated by spatial fusion operation of geographic information data in the subfolders;

[0035] performing spatial fusion operation on the data with highest precision level in the subfolders;

[0036] The spatial fusion operation includes: performing clustering fusion on point features; performing segmented connection and smoothing processing on line features; performing geometric set operation and reconstructing topology on surface features;

[0037] performing self-intersection detection and repair on the fused geometric features, and performing gap filling and overlap elimination operation on adjacent polygons, so as to maintain the consistency of spatial topology relationship;

[0038] The geometric generalization algorithm is executed to process data, the simplification threshold is automatically adjusted according to the element space span, the geographic feature simplification processing of multi-level precision control is implemented, and a fused data precision version number is generated;

[0039] The standardized GeoJSON format data is output, named as a hierarchical folder existing subfolder [semantic label], the precision version number is marked in the generated GeoJSON data file name, and stored in the hierarchical folder existing subfolder.

[0040] As preferred, the step S4 web page publishing further comprises:

[0041] According to user interactive operation, the corresponding precision version of the GeoJSON data file is dynamically loaded and switched.

[0042] The present application has the following beneficial effects:

[0043] The present application provides a simple and effective geographic information data static publishing method, has very fast publishing capacity, and greatly simplifies the GIS data publishing process through a directory-URL intelligent mapping mechanism and an automatic processing pipeline.

[0044] The server dependence is completely eliminated, and the operation and maintenance cost is low. Traditional server functions such as data publishing and rendering are transplanted to the browser end, and complete GIS function chains are realized relying on the computing capacity of modern browsers.

[0045] The deployment is convenient, and the file is a service. The present application has a "directory as configuration" deployment mode, so that non-technical personnel can also complete professional data publishing. The physical directory structure and the web page URL are presented in a 1:1 intuitive correspondence, and the data service level is directly managed through folder operation. DETAILED DESCRIPTION

[0046] The accompanying drawings are used to provide a further understanding of the present application, and constitute a part of the specification, and are used to explain the present application together with embodiments of the present application, and do not constitute a limitation on the present application.

[0047] Figure 1 The present application is a flowchart.

[0048] In the figure: classified directory construction (1), URL path generation (2), data conversion (3), and web page publishing (4). DETAILED DESCRIPTION

[0049] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments of the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0050] Please refer to Figure 1 The present application provides a geographic information data static publishing method. In the embodiment, under the architecture without server-side parsing, by constructing a three-level directory system of province, city and county, establishing an automatic bidirectional mapping relationship between physical directory and URL path, performing vector data geometric generalization processing, generating multi-precision version data, parsing through independent threads, and safe isolation rendering, static publishing of a website of China's three-level administrative division map is realized.

[0051] The following are specific implementation steps:

[0052] S1: constructing a classified directory (1): creating a multi-level directory structure conforming to the naming specification of [classification code] [serial number] _ [semantic label], wherein the [classification code] adopts English letter to identify data classification attribute, the [serial number] adopts Arabic numeral to establish directory sorting, and the [semantic label] is a semantic short label of general text;

[0053] The directory naming follows the three-element rule of [classification code] [serial number] _ [semantic label];

[0054] The [classification code] adopts English letter to identify data classification attribute;

[0055] The [serial number] adopts two-digit number, and the virtual bit is filled with 0, with a fixed length from 01 to 99;

[0056] The [semantic label] adopts a semantic label of general text, with a length less than or equal to 20 characters.

[0057] In the embodiment:

[0058] First-level directory:

[0059] The [classification code] adopts English letter, and the full spelling [sheng] of province is determined as the specified classification code;

[0060] The province includes provinces, municipalities directly under the central government, autonomous regions and special administrative regions;

[0061] The [serial number] adopts two-digit number, and the virtual bit is filled with 0, with a fixed length from 01 to 99. Taking Hebei province as an example, the serial number

[00] is used;

[0062] In order to facilitate the visualization of the title, the [serial number] and the [semantic label] are separated by an underscore.

[0063] [Semantic Tag] Adopt semantic tag of general text, constraint length less than or equal to 20 characters, the semantic tag is the first level classification title of visualization, this title is the data navigation name of browser online viewing, take Beijing as an example, use semantic tag [Hebei Province];

[0064] Syntax structure example is: sheng00_Hebei Province;

[0065] Second level directory:

[0066] [Classification Code] Adopt English letter, determine the full spelling [shi] of city as the specified classification code;

[0067] The city includes prefecture-level city, autonomous prefecture, alliance and other municipal administrative units;

[0068] [Serial Number] Adopt two-digit number, fill 0 with virtual bit, constraint fixed length from 01 to 99, take Shijiazhuang City of Hebei Province as an example, use serial number

[00] ;

[0069] In order to facilitate the visualization of title, [serial number] is separated from [semantic tag] by underscore;

[0070] [Semantic Tag] Adopt semantic tag of general text, constraint length less than or equal to 20 characters, the semantic tag is the second level classification title of visualization, this title is the classification name in data navigation name of browser online viewing, take Beijing City Chaoyang District as an example, use semantic tag [Shijiazhuang City];

[0071] Syntax structure example is: shi00_Shijiazhuang City;

[0072] Third level directory:

[0073] [Classification Code] Adopt English letter, determine the full spelling [xian] of county as the specified classification code;

[0074] The county includes county-level city, district, self-governance county, banner and other county-level administrative units;

[0075] [Serial Number] Adopt two-digit number, fill 0 with virtual bit, constraint fixed length from 01 to 99, take Zhengding County of Shijiazhuang City of Hebei Province as an example, use serial number

[00] ;

[0076] In order to facilitate the visualization of title, [serial number] is separated from [semantic tag] by underscore;

[0077] [semantic tag] adopt semantic tag of general text, constraint length is less than or equal to 20 characters, the semantic tag is visual two-level classification title, this title is the navigation name of data division of browser online viewing, taking shengding county of shijiazhuang city of hebei province as an example, using semantic tag [shengding county];

[0078] Syntax structure example is: xian00_shengding county;

[0079] Three-level directory structure example:

[0080] sheng00_hebei province

[0081] shi00_shijiazhuang city

[0082] xian00_shengding county

[0083] S2 path generation (2): according to the physical directory hierarchy created in step S1, automatically generate the corresponding URL access path, establish the bidirectional mapping relationship between directory and network address;

[0084] Extract [classification code] in the classification directory as API root path;

[0085] Convert [serial number] segment in the classification directory into path parameters;

[0086] Map [semantic tag] in the classification directory directly to the terminal node name;

[0087] The first level directory of the classification directory folder is used as the first level path;

[0088] The second level directory of the classification directory folder is used as the second level path;

[0089] The third level directory of the classification directory folder is used as the third level path;

[0090] In this way, each subdirectory represents a path level;

[0091] Taking shengding county of shijiazhuang city of hebei province as an example, the physical path is: data / sheng00_hebei province / shi00_shijiazhuang city / xian00_shengding county;

[0092] Use automatic tool to automatically generate corresponding URL path;

[0093] Wherein the Chinese name processing is unified lowercase alphabet full spelling pinyin;

[0094] Automatic generation of bidirectional routing mapping table, record the corresponding relationship between physical path and network address, support path reverse tracing;

[0095] Take Zhengding County of Shijiazhuang City in Hebei Province as an example, the URL path is: data / sheng00-hebeisheng / shi00-shijiazhuangshi / xian00-zhengdingxian;

[0096] The generated URL path supports manual adjustment by users to meet special user needs.

[0097] S3 data conversion (3): attribute white list filtering is performed on the original geographic information data, geometric generalization processing is performed to control spatial precision, and the data precision level is marked by version number, and the standardized GeoJSON is output;

[0098] In the example, QGIS software is selected to convert the original geographic information data into GeoJson format:

[0099] Open the QGIS software and load the original geographic information data file to be converted into GeoJson format;

[0100] Use the PyQGIS script to define the regular expression whitelist rule and perform field filtering;

[0101] Use the Simplify tool in the QGIS toolbox to perform geometric generalization processing;

[0102] It is specified to use the distance-based Douglas-Pork algorithm, with high-precision tolerance 0.0001, medium-precision tolerance 0.001, and low-precision tolerance 0.01;

[0103] Open the data layer attribute field tab after generalization, create the precision field version, the field type is string, set the high-precision precision version number to 1.0, set the medium-precision precision version number to 2.0, and set the low-precision precision version number to 3.0;

[0104] Select the vector data layer after creating the precision field, right-click to select Export, select the file format of the output file as "GeoJSON", specify the unified coordinate reference system, and save to the specified location in the directory;

[0105] The coordinate reference system is EPSG: 4326 (WGS84);

[0106] The GeoJSON format data is named [semantic tag] in the target folder, and the precision version number is marked, for example: Zhengding County 1.0;

[0107] To reduce the amount of data transmitted, the hierarchical data existing in the subfolder is generated by spatial fusion operation of the geographic information data in the subfolder;

[0108] The highest precision data in the subfolder is executed by spatial fusion operation;

[0109] In an embodiment, the GeoJSON data with precision version number 1.0 in all sub-folders under the “shi00-Shijiazhuang City” folder is subjected to a spatial fusion operation;

[0110] The spatial fusion operation includes: clustering fusion for point elements; segmented connection and smoothing processing for line elements;

[0111] Geometric set operation and topology reconstruction are performed on the surface elements;

[0112] Self-intersection detection and repair are performed on the fused geometric elements, and gap filling and overlap elimination operations are performed on adjacent polygons to maintain the consistency of spatial topological relationships;

[0113] A regular expression whitelist rule is defined using a PyQGIS script, and field filtering is performed;

[0114] The vector data geometric generalization processing is performed using the Simplify tool in the QGIS toolbox;

[0115] The Douglas-Peucker algorithm based on distance is specified, with high-precision tolerance 0.0001, medium-precision tolerance 0.001, and low-precision tolerance 0.01;

[0116] Open the data layer attribute field tab after generalization, create the precision field version, and set the field type to string. Set the high-precision precision version number to 1.0, the medium-precision precision version number to 2.0, and the low-precision precision version number to 3.0;

[0117] Select the vector data layer after creating the precision field, right-click Export, select the output file format as “GeoJSON”, specify the unified coordinate reference system, and save to the specified location in the directory;

[0118] The coordinate reference system is EPSG:4326 (WGS84);

[0119] The GeoJSON format data is named with the [semantic tag] of the hierarchical folder “shi00-Shijiazhuang City” under which the storage sub-folder is located, and the precision version number is marked, for example: Shijiazhuang City 1.0;

[0120] In an embodiment, the GeoJSON data with precision version number 1.0 in all sub-folders under the “sheng00-Hebei Province” folder is subjected to a spatial fusion operation;

[0121] Repeat the above steps to perform the spatial fusion operation and geometric generalization algorithm processing to obtain multi-precision version provincial data, and save to the specified location in the directory, and name according to the specified rules, for example: Hebei Province 1.0.

[0122] S4Web page publishing (4): using independent threads to parse GeoJSON data files, performing coordinate boundary verification, longitude range-180 to 180, latitude range-90 to 90, implementing safe isolation rendering, building precision version traceability mechanism;

[0123] Using independent threads to execute GeoJSON parsing of different precision versions through URL paths, isolating data parsing process from main thread, reducing potential security risks affecting page interaction;

[0124] Traverse all coordinate points in the GeoJSON data, check whether the longitude of each point is in the range of-180 to 180, and check whether the latitude of each point is in the range of-90 to 90;

[0125] When illegal coordinates are detected, record error information and report to the main thread;

[0126] The front-end page directly references the parsed GeoJSON data file to realize the localization loading of geographic data;

[0127] By setting the front-end page traceability path, dynamically switching the loaded GeoJSON data, the traceability and switching of different precision versions are realized.

[0128] The above shows and describes the basic principles and main features of the present application and the advantages of the present application, for those skilled in the art, it is obvious that the present application is not limited to the details of the above exemplary embodiments, and the present application can be realized in other specific forms without departing from the spirit or basic characteristics of the present application; therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting, the scope of the present application is defined by the appended claims rather than the above description, therefore all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present application, any reference signs in the claims should not be regarded as limiting the claims involved.

[0129] Although embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present application, the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for static publishing of geographic information data, characterized by, Under the architecture without server-side analysis, the static publication of geographic information data is realized by constructing a classified directory system, establishing an automatic bidirectional mapping mechanism of the directory and URL path, performing data geometric generalization processing, generating multiple precision version data, analyzing through independent threads, and safely isolated rendering. The method comprises the following steps: S1: constructing a classified directory (1), creating a multi-level directory structure in accordance with the naming specification of [classification code] [serial number] _ [semantic label], wherein the [classification code] adopts English letter to identify the data classification attribute, the [serial number] adopts Arabic numerals to establish the directory sorting, and the [semantic label] is a semantic short label of general text; S2: generating a path (2), automatically generating the corresponding URL access path according to the physical directory hierarchical structure created in step S1, and establishing the bidirectional mapping relationship between the directory and the network address; S3: data conversion (3), performing attribute white list filtering on the original geographic information data, executing geometric generalization algorithm to process the data, generating multiple data versions containing different levels of details, marking the precision level, and outputting standardized GeoJSON format data; S4: Web page publication (4), analyzing the GeoJSON data file through independent threads, and implementing coordinate boundary verification, wherein the longitude range is -180 to 180, and the latitude range is -90 to 90.

2. The method of claim 1, wherein, The serverless analysis architecture refers to not relying on the server-side dynamic logic and database system, and the user realizes the independent publication of geographic information data through static file hosting.

3. The method for static publishing of geographic information data according to claim 1, wherein, The naming specification of the S1 classified directory construction follows the three-element rule of [classification code] [serial number] _ [semantic label]: The [classification code] adopts English letters to identify the data classification attribute; The [serial number] adopts two-digit numbers, with 0 filling for virtual bits, and the fixed length is constrained from 01 to 99; The [semantic label] adopts a semantic label of general text, and the length is constrained to be less than or equal to 20 characters.

4. The geographic information data static publishing method according to claim 1, wherein, Step S3 data conversion further comprises: Establishing attribute white list filtering rules containing field name regular expressions, and performing attribute white list filtering; Executing geometric generalization algorithm to process the data, automatically adjusting the simplification threshold according to the spatial span of the feature, and implementing multi-level precision control of geographic feature simplification processing; Generating a data precision version number corresponding to the geometric generalization processing level, and marking the precision version number in the generated GeoJSON data file name.

5. The geographic information data static publishing method according to claim 1, wherein, For the directory hierarchy with subfolders, step S3 data conversion further comprises: In order to reduce the amount of data transmission, the hierarchical data with subfolders is generated by spatial fusion operation of the geographic information data in the subfolders; The data with the highest precision level in the subfolder is executed for spatial fusion operation; The spatial fusion operation comprises: clustering fusion for point features; segmented connection and smoothing processing for line features; Geometric set operation and topology reconstruction for surface features; Self-intersection detection and repair are performed on the fused geometric features, and gap filling and overlap elimination operations are performed on adjacent polygons to maintain the consistency of the spatial topology relationship; The geometric generalization algorithm is executed to process the data, the simplification threshold is automatically adjusted according to the spatial span of the feature, the geographic feature simplification processing with multi-level precision control is implemented, and a fused data precision version number is generated; The standardized GeoJSON format data is output, named as the [semantic tag] of the hierarchical folder in which the subfolder exists, the precision version number is marked in the name of the generated GeoJSON data file, and stored in the hierarchical folder in which the subfolder exists.

6. The geographic information data static publishing method according to claim 1, wherein, The step S4 Web page publishing further includes: According to the user interaction operation, the GeoJSON data file of the corresponding precision version is dynamically loaded and switched.

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