Geographic information data derivation method and device, computer device, readable storage medium and program product

Abstract

The application relates to a geographic information data derivation method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: reading target geographic entity data, a preconfigured geographic entity fusion library and derivation configuration; the derivation configuration comprises a derivation mapping relationship between a symbolization style and a target format graphic expression rule; according to a classification structure in the geographic entity fusion library, the category symbol attribute of each element in the target geographic entity data is filtered, and a symbolization template corresponding to the target geographic entity data is determined according to the category symbol attribute; the symbolization template comprises a symbolization style of an element; based on the symbolization template and the derivation mapping relationship between the symbolization style and the target format graphic expression rule, derivation processing is performed on each element of the target geographic entity data, and target format data is obtained. The method can improve the efficiency of generating target format data.

Description

Technical Field

[0001] This application relates to the fields of surveying and mapping, geographic information data processing technology, and in particular to a geographic information data derivation method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Technology

[0002] With the development of geographic information surveying and mapping technology, new basic surveying and mapping is based on geographic entities. After the geographic entity data is collected, the geographic entities need to be converted into DLG (Digital Line Graphic) format (DWG, the native file format of AutoCAD software) for storage.

[0003] In traditional techniques, after acquiring geographic entity data, DLG data is extracted based on the geographic entity data. The DLG data is then manually processed for symbolization and supplemented with map representations to obtain complete DLG data. Finally, the complete DLG data is converted into DWG format DLG data.

[0004] However, in current traditional technologies, the symbolization and graphic representation of DLG data require manual processing, resulting in low efficiency in converting to DWG format DLG data. Summary of the Invention

[0005] Therefore, it is necessary to provide a geographic information data derivation method, apparatus, computer equipment, computer-readable storage medium, and computer program product to address the aforementioned technical problems.

[0006] Firstly, this application provides a method for deriving geographic information data, including:

[0007] Read target geographic entity data, a pre-configured geographic entity fusion library, and derived configurations; the derived configurations include the derived mapping relationship between symbolic styles and target format graphic expression rules;

[0008] The category symbol attributes of each element in the target geographic entity data are filtered according to the classification structure in the geographic entity fusion library, and the symbolization template corresponding to the target geographic entity data is determined based on the category symbol attributes; the symbolization template includes the symbolization style of the element;

[0009] Based on the derivation mapping relationship between the symbolic template and the symbolic style and the target format graphic expression rules, the elements of the target geographic entity data are derivationally processed to obtain the target format data.

[0010] In one embodiment, prior to reading the target geographic entity data, the pre-configured geographic entity fusion library, and the derived configuration, the method further includes:

[0011] Based on the original classification structure of geographic entity data and the target mapping standards, the target classification structure corresponding to the mapping elements is selected.

[0012] Based on the preset symbol standard, configure the symbol template corresponding to the cartographic elements, and construct a geographic entity fusion library according to the target classification structure and the symbol template;

[0013] Derivative configurations are constructed based on preset mapping relationships; the preset mapping relationships include derived symbolic relationships for converting symbolic styles in the geographic entity fusion library into target format styles, and multidimensional classification mapping relationships between geographic entity categories and symbolic style categories.

[0014] In one embodiment, the step of constructing the derived configuration based on a preset mapping relationship includes:

[0015] Obtain the target format graphics environment base file; the graphics environment base file defines the target format layer categories, layer attributes, and symbol description units;

[0016] Based on the graphical environment base file, configure the symbolic style to the derived symbolic relationship of the target format graphical expression rules;

[0017] Based on the derived symbolic relationship, configure a multidimensional classification mapping relationship between geographic entity categories and symbolic style categories; the multidimensional classification mapping relationship includes one-to-one direct mapping, one-to-many conditional branch mapping, and many-to-one merge mapping.

[0018] In one embodiment, the geographic entity fusion library includes a classification structure and symbolic templates for geographic entities; reading the target geographic entity data includes:

[0019] Obtain initial geographic entity data;

[0020] Mapping is performed based on the preset mapping strategy corresponding to the category symbol attribute to obtain target geographic entity data.

[0021] In one embodiment, the category symbol attributes of each element in the initial geographic entity data include ordinary road elements and elevated road elements; the mapping processing based on the preset mapping strategy corresponding to the category symbol attributes to obtain the target geographic entity data includes:

[0022] For the common road features, the intersection position between road surface features is determined by the vector intersection relationship. At the intersection position, the road surface features are broken and deleted, and the remaining surface geometry is converted into line geometry. If the edge lines of two road segments are not adjacent, the edge line between the two road segments is generated to obtain the target geographic entity data.

[0023] For the elevated road features, the intersection position between road surface features is determined by vector intersection relationship. The hierarchical relationship of the intersection position is determined based on the preset elevation value information. The road surface features with low elevation are broken and deleted within the road surface features with high elevation. The remaining surface geometry is converted into line geometry to obtain the target geographic entity data.

[0024] In one embodiment, the derivation processing of each element of the target geographic entity data based on the derivation mapping relationship between the symbolic template and the symbolic style and the target format graphic expression rules to obtain target format data includes:

[0025] Based on the multidimensional classification mapping relationship in the derived mapping relationship, the symbolic style category corresponding to the category symbol attribute of the target geographic entity data is determined.

[0026] Based on the target template rule corresponding to the symbolization style category in the symbolization template, the target geographic entity data is rendered using map symbolization to obtain intermediate rendering data.

[0027] Based on the derived symbol relationship in the derived mapping relationship, the symbolic style in the intermediate rendering data is converted into graphic expression elements in the target format to generate target format data.

[0028] Secondly, this application also provides a geographic information data derivation device, comprising:

[0029] The acquisition module is used to read target geographic entity data, a pre-configured geographic entity fusion library, and derived configurations; the derived configurations include the derived mapping relationship between symbolic styles and target format graphic expression rules;

[0030] The identification module is used to filter the category symbol attributes of each element in the target geographic entity data according to the classification structure in the geographic entity fusion library, and determine the symbolization template corresponding to the target geographic entity data based on the category symbol attributes; the symbolization template includes the symbolization style of the element;

[0031] The derivation module is used to perform derivation processing on each element of the target geographic entity data based on the derivation mapping relationship between the symbolic template and the symbolic style and the target format graphic expression rules, so as to obtain the target format data.

[0032] In one embodiment, the device further includes:

[0033] The filtering module is used to filter the target classification structure corresponding to the mapping elements based on the original classification structure of the geographic entity data and the target mapping standard.

[0034] The configuration module is used to configure the symbolic templates corresponding to the cartographic elements based on preset symbol standards, and to construct a geographic entity fusion library according to the target classification structure and the symbolic templates;

[0035] A construction module is used to construct derived configurations based on preset mapping relationships; the preset mapping relationships include derived symbolic relationships for converting symbolic styles in the geographic entity fusion library into target format styles, and multidimensional classification mapping relationships between geographic entity categories and symbolic style categories.

[0036] In one embodiment, the construction module is specifically used to obtain a graphics environment base file of the target format; the graphics environment base file defines layer categories, layer attributes, and symbol description units of the target format;

[0037] Based on the graphical environment base file, configure the symbolic style to the derived symbolic relationship of the target format graphical expression rules;

[0038] Based on the derived symbolic relationship, configure a multidimensional classification mapping relationship between geographic entity categories and symbolic style categories; the multidimensional classification mapping relationship includes one-to-one direct mapping, one-to-many conditional branch mapping, and many-to-one merge mapping.

[0039] In one embodiment, the geographic entity fusion library includes a classification structure and symbolic templates for geographic entities; the acquisition module is specifically used to acquire initial geographic entity data.

[0040] Mapping is performed based on the preset mapping strategy corresponding to the category symbol attribute to obtain target geographic entity data.

[0041] In one embodiment, the category symbol attributes of each element in the initial geographic entity data include ordinary road elements and elevated road elements; the acquisition module is specifically used to determine the intersection position between road surface elements through vector intersection relationship for the ordinary road elements, break and delete the road surface elements at the intersection position, and convert the remaining surface geometry into line geometry. If the edge lines of two road segments are not adjacent, the edge line between the two road segments is generated to obtain the target geographic entity data.

[0042] For the elevated road features, the intersection position between road surface features is determined by vector intersection relationship. The hierarchical relationship of the intersection position is determined based on the preset elevation value information. The road surface features with low elevation are broken and deleted within the road surface features with high elevation. The remaining surface geometry is converted into line geometry to obtain the target geographic entity data.

[0043] In one embodiment, the derived module is specifically used to determine the symbolic style category corresponding to the category symbol attribute of the target geographic entity data based on the multidimensional classification mapping relationship in the derived mapping relationship;

[0044] Based on the target template rule corresponding to the symbolization style category in the symbolization template, the target geographic entity data is rendered using map symbolization to obtain intermediate rendering data.

[0045] Based on the derived symbol relationship in the derived mapping relationship, the symbolic style in the intermediate rendering data is converted into graphic expression elements in the target format to generate target format data.

[0046] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0047] Read target geographic entity data, a pre-configured geographic entity fusion library, and derived configurations; the derived configurations include the derived mapping relationship between symbolic styles and target format graphic expression rules;

[0048] The category symbol attributes of each element in the target geographic entity data are filtered according to the classification structure in the geographic entity fusion library, and the symbolization template corresponding to the target geographic entity data is determined based on the category symbol attributes; the symbolization template includes the symbolization style of the element;

[0049] Based on the derivation mapping relationship between the symbolic template and the symbolic style and the target format graphic expression rules, the elements of the target geographic entity data are derivationally processed to obtain the target format data.

[0050] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0051] Read target geographic entity data, a pre-configured geographic entity fusion library, and derived configurations; the derived configurations include the derived mapping relationship between symbolic styles and target format graphic expression rules;

[0052] The category symbol attributes of each element in the target geographic entity data are filtered according to the classification structure in the geographic entity fusion library, and the symbolization template corresponding to the target geographic entity data is determined based on the category symbol attributes; the symbolization template includes the symbolization style of the element;

[0053] Based on the derivation mapping relationship between the symbolic template and the symbolic style and the target format graphic expression rules, the elements of the target geographic entity data are derivationally processed to obtain the target format data.

[0054] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0055] Read target geographic entity data, a pre-configured geographic entity fusion library, and derived configurations; the derived configurations include the derived mapping relationship between symbolic styles and target format graphic expression rules;

[0056] The category symbol attributes of each element in the target geographic entity data are filtered according to the classification structure in the geographic entity fusion library, and the symbolization template corresponding to the target geographic entity data is determined based on the category symbol attributes; the symbolization template includes the symbolization style of the element;

[0057] Based on the derivation mapping relationship between the symbolic template and the symbolic style and the target format graphic expression rules, the elements of the target geographic entity data are derivationally processed to obtain the target format data.

[0058] The aforementioned geographic information data derivation method, apparatus, computer equipment, computer-readable storage medium, and computer program product read target geographic entity data, a pre-configured geographic entity fusion library, and a derivation configuration. The derivation configuration includes derivation mapping relationships for converting symbolic styles into target format graphic representation rules. Based on the classification structure in the geographic entity fusion library, the method filters the category symbol attributes of each element in the target geographic entity data and determines the corresponding symbolic template for the target geographic entity data based on these category symbol attributes. Based on the symbolic template and the derivation mapping relationships, the method performs derivation processing on the target geographic entity data to obtain the target format data. Using this method, by pre-configuring the geographic entity fusion library and derivation configuration, the method automatically identifies element categories and calls the corresponding symbolic templates for derivation conversion, eliminating the need for manual symbolic processing and cartographic representation supplementation of intermediate data, thereby improving the efficiency of generating target format data. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0060] Figure 1 This is a flowchart illustrating a geographic information data derivation method in one embodiment;

[0061] Figure 2 This is a schematic diagram illustrating the process of building a geographic entity fusion library and building derived configurations in one embodiment;

[0062] Figure 3A This is a schematic diagram of a classification structure table in one embodiment;

[0063] Figure 3B This is a schematic diagram of a symbolic template table in one embodiment;

[0064] Figure 4 This is a flowchart illustrating the process of configuring a multidimensional classification mapping relationship between geographic entity categories and symbolic style categories in one embodiment;

[0065] Figure 5 This is a schematic diagram of the process of cartographic processing of initial geographic entity data in one embodiment;

[0066] Figure 6 This is a schematic diagram illustrating the mapping process for ordinary road features and elevated road features in one embodiment;

[0067] Figure 7 This is a schematic diagram illustrating the mapping process for ordinary road features and elevated road features in one embodiment;

[0068] Figure 8 This is a schematic diagram of the process of deriving target geographic entity data in one embodiment;

[0069] Figure 9 This is a flowchart illustrating an example of a geographic information data derivation method in one embodiment.

[0070] Figure 10 This is a structural block diagram of a geographic information data derivation device in one embodiment;

[0071] Figure 11 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0072] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0073] In one embodiment, such as Figure 1 As shown, a method for deriving geographic information data is provided. This embodiment illustrates the application of this method to a terminal. It is understood that this method can also be applied to a server, and further to a system including both a terminal and a server, and is implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0074] Step 102: Read the target geographic entity data, the pre-configured geographic entity fusion library, and the derived configuration.

[0075] Among them, the derived configuration includes the derived mapping relationship between symbolic styles and target format graphic expression rules.

[0076] The target format graphic representation rule can be the DWG format image representation rule.

[0077] In this embodiment, the target geographic entity data is the geographic entity data after cartographic processing. Geographic entity data is product data for the construction of a new basic surveying and mapping system. It provides basic base map data support for the national real-world 3D construction. The new basic surveying and mapping is a fundamental and public-interest surveying activity that takes "geographic entities" as its perspective and object, conducts surveying and mapping according to "spatial accuracy and entity granularity," and aims to build a "basic geographic entity database." The original geographic entity data is a direct digital mapping of real-world objects. For example, a road is stored in the entity database as a polygon feature, fully recording its actual boundary range; an overpass and the ground road beneath it are represented as overlapping polygon features. However, DLG product data has specific cartographic expression requirements. For example, roads need to be presented as double lines rather than filled polygons; when an overpass and a ground road are superimposed, the overpass must be displayed on top, and the obscured portion of the ground road must be hidden; annotations cannot overlap or cover important features; contour lines must break at the point of overlap when passing through houses, roads, or waterways to ensure map clarity and readability. Because the original geographic entity data's map symbolization cannot meet the requirements of DLG product data, direct derivation and conversion will result in DWG format maps with issues such as roads appearing as solid blocks, overlapping of elevated and ground-level roads, misplaced annotations, and contour lines penetrating buildings, leading to product defects. Therefore, before derivation and conversion, the terminal performs cartographic processing on the original geographic entity data to ensure that the map symbolization of the geographic entity data meets the requirements of DLG products.

[0078] The terminal reads target geographic entity data, a pre-configured geographic entity fusion library, and derived configurations from a preset storage location. The target geographic entity data can include features such as roads, buildings, water systems, and contour lines; each feature has a classification code and attribute fields. The pre-configured geographic entity fusion library is a pre-designed database template. The library defines the classification structure of geographic entities and the symbolic template corresponding to each category. The classification structure can include categories such as roads, buildings, and water systems; the symbolic template can be a building category using a red border and an annotation layer of numerical segments, etc. Derivative configurations can contain derivation mappings that define the correspondence between symbolic styles in a symbolic template and DWG format graphic representation rules. For example, a derivation mapping could be that the symbolic style "House border uses red (RGB 255, 0, 0), solid line type, line width 0.3 mm, house interior uses light red (RGB 255, 200, 200) solid fill" in a symbolic template is derivationally mapped to the DWG format image representation rule "Red border mapped to layer 'RES_BUILDING_BORDER', color index 1 (red), line type 'Continuous', line width 0.30 mm; light red solid fill mapped to AutoCAD solid fill, color index 200 (light red)".

[0079] Step 104: Filter the category symbol attributes of each element in the target geographic entity data according to the classification structure in the geographic entity fusion library, and determine the symbolization template corresponding to the target geographic entity data based on the category symbol attributes.

[0080] The symbolic template includes the symbolic styles of the elements.

[0081] In this embodiment, the terminal reads each feature in the target geographic entity data. For each feature, it extracts the category symbol attribute, which can be a classification code or a category identifier. Then, based on the feature's category symbol attribute, the terminal calls the symbolization template associated with that attribute. This symbolization template defines the symbolization style of that type of feature on the final map, including but not limited to line type (e.g., solid line, dashed line), line width, color, fill pattern, annotation content source field, annotation font and size, layer affiliation, etc.

[0082] Step 106: Based on the derivation mapping relationship between symbolic templates and symbolic styles and target format graphic expression rules, perform derivation processing on each element of the target geographic entity data to obtain target format data.

[0083] In this embodiment, the terminal stores the target geographic entity data, processed by cartographic techniques, into a geographic entity fusion library based on a symbolic template. Specifically, during storage, the terminal writes the target geographic entity data into the corresponding classification data table of the geographic entity fusion library according to the symbolic style corresponding to each element in the symbolic template, and binds a pre-configured symbolic template identifier to each element. At this point, each element of the target geographic entity data is associated with a corresponding symbolic template. Then, during derivation processing, the terminal can directly read the target geographic entity data and call the bound symbolic template for style rendering and format conversion to obtain the target format data, which is DWG format DLG product data.

[0084] In the above-mentioned geographic information data derivation method, by pre-configuring the geographic entity fusion library and derivation configuration, the feature category is automatically identified and the corresponding symbolic template is called for derivation conversion. There is no need for manual symbolic processing and cartographic expression supplementation of intermediate data, thereby improving the efficiency of generating target format data.

[0085] In one exemplary embodiment, such as Figure 2 As shown, before step 102, the method further includes steps 202 to 206. Wherein:

[0086] Step 202: Select the target classification structure corresponding to the mapping elements based on the original classification structure of the geographic entity data and the target mapping standard.

[0087] In this embodiment, the terminal first obtains the original classification structure of the geographic entity data. This original classification structure is based on the new basic surveying and mapping geographic entity classification standard (i.e., geographic entity fusion library classification). The new basic surveying and mapping geographic entity classification standard includes the classification codes, names, and hierarchical relationships of various geographic entities. Simultaneously, the terminal reads the target mapping standard, i.e., the DLG classification and mapping standard (symbolization standard), such as the national basic scale map symbol. Guided by the DLG classification and mapping standard, the terminal filters out categories related to DLG mapping from the original geographic entity classification structure, filtering out categories with poor coordinate consistency between geographic entities and DLG data. For example, categories with poor coordinate consistency may be those expressed as abstract points in the entity library but as polygons in the DLG, and whose coordinates cannot strictly correspond. Categories with consistent coordinates are then retained. Based on this, the terminal further filters out the essential element data layers for mapping, including contour lines, elevation points, road edges, land boundary lines, and other proprietary categories required for DLG mapping, forming the target classification structure of the fusion library. For situations where some cartographic elements (e.g., road boundaries, land use boundaries) may be missing from the original geographic entity classification structure, the terminal adds these categories to the target classification structure and marks them as types that "need to be automatically updated and generated through cartographic processing technology." For categories such as contour lines and elevation points that can be automatically generated by mature production software with updates, they are marked as "automatically generated." Ultimately, the terminal outputs a complete target classification structure for geographic entities oriented towards cartographic fusion.

[0088] Step 204: Based on the preset symbol standards, configure the symbol templates corresponding to the cartographic elements, and construct a geographic entity fusion library according to the target classification structure and the symbol templates.

[0089] In this embodiment, the terminal, based on the target classification structure, further configures a corresponding symbolization template for each cartographic element category according to the symbol standard of the "National Basic Scale Map Symbol". Specifically, for the cartographic element data layer, such as contour lines, road edges, and land boundaries, the terminal uses its original DLG symbolization style, that is, directly adopts the line type, color, layer, and other symbol definitions of this type of element in the current DLG product. For categories where geographic entities have a coordinate consistency relationship with DLG data, such as building surfaces and lake surfaces, the terminal uses the symbolization style of the corresponding category in DLG according to this coordinate consistency relationship. For proprietary categories of geographic entities, that is, categories that only exist in the geographic entity library and are not within the scope of DLG mapping, the terminal, according to the preset symbol standard, only ensures the integrity of its symbol, for example, assigning a general point or line symbol and marking it as not to be derived or processed, that is, ignoring this type of element when subsequently deriving DWG. The terminal associates the aforementioned symbolic template configuration with the target classification structure to construct a geographic entity fusion library. This library is stored in database form and includes a classification structure table and a symbolic template table. For example, Figure 3A and Figure 3B As shown, Figure 3A This is a schematic diagram of a classification structure table, which is used to record the code, name, and tag type of each element category; Figure 3B This is a schematic diagram of the symbolic template table. The symbolic template table records the symbolic style parameters associated with each category, such as line type, color, line width, fill, and annotation fields. Furthermore, the category structure table and the symbolic template table are linked through category codes. The configuration of the geographic entity fusion library is completed once and can be reused long-term. Subsequent updates to geographic entity data simply require incorporating the data instance into this geographic entity fusion library framework.

[0090] Step 206: Construct derived configurations based on preset mapping relationships.

[0091] The preset mapping relationships include derived symbolic relationships used to convert symbolic styles in the geographic entity fusion library into target format styles, as well as multidimensional classification mapping relationships between geographic entity categories and symbolic style categories.

[0092] In this embodiment, the terminal constructs a derived configuration (derived technology configuration) based on a preset mapping relationship. Specifically, the terminal first obtains and configures a basic graphic environment file for the target format. This basic file defines layer categories, layer attributes, and symbolic description units under the target format. Then, based on this basic graphic environment file, the terminal configures a derived symbolic relationship between symbolic styles and graphic expression rules of the target format, mapping various symbolic styles defined by the symbolic templates in the geographic entity fusion library to graphic expression rules such as layers, colors, line types, and description units of the target format. Finally, based on the derived symbolic relationship, the terminal configures a multi-dimensional classification mapping relationship between geographic entity categories and symbolic style categories. This multi-dimensional classification mapping relationship includes one-to-one direct mapping, one-to-many conditional branch mapping, and many-to-one merging mapping, used to handle various correspondences between different geographic entity categories and symbolic style categories during derivation conversion.

[0093] In this embodiment, a reusable geographic entity fusion library is constructed by pre-screening target classification structures according to mapping standards and configuring symbolic templates. A derived configuration containing derived symbolic relationships and multidimensional classification mapping relationships is also constructed, providing a reusable foundation for subsequent automated derivation processing. This eliminates the need for manual symbolic processing and map representation supplementation of intermediate data, thereby improving the efficiency of generating target format data.

[0094] In one exemplary embodiment, such as Figure 4 As shown, step 206 includes steps 402 to 406. Wherein:

[0095] Step 402: Obtain the target format graphics environment base file.

[0096] The basic graphics environment file defines the target format of layer categories, layer attributes, and symbol description units. Layer attributes can be color attributes, and symbol description units can be the smallest unit configuration of symbol description.

[0097] In this embodiment, the terminal obtains a target-format graphical environment base file, which is stored in DWG format and serves as the seed file for the AutoCAD software, i.e., a DWG seed file configuration. This seed file pre-configures the basic environmental resources required for drawing, including layer classifications, color attributes for each layer, and the minimum unit configuration for symbol descriptions, specifically including basic line types, thicknesses, font styles, widths, and block styles. This graphical environment base file serves as a graphical template for subsequent derived conversions, ensuring a unified graphical foundation for the output results.

[0098] Step 404: Configure the symbolic style to the derived symbolic relationship of the target format graphic expression rules based on the basic graphic environment file.

[0099] In this embodiment, the terminal configures the derived symbolic relationships between symbolic styles and target format graphic expression rules based on the graphical environment base file. Specifically, the terminal reads the symbolic styles defined by each symbolic template in the geographic entity fusion library, including line type, color, line width, fill pattern, annotation font, and font size. Then, the terminal analyzes each symbolic style and maps it to the corresponding graphic expression rules in the graphical environment base file to obtain the derived symbolic relationships. Furthermore, the terminal writes all mapping relationships into a configuration file of derived symbolic relationships stored in TXT format. This configuration file records the conversion correspondence between each symbolic style and DWG graphic elements.

[0100] Step 406: Configure the multidimensional classification mapping relationship between geographic entity categories and symbolic style categories based on derived symbolic relationships.

[0101] Among them, multidimensional classification mapping relationships include one-to-one direct mapping, one-to-many conditional branch mapping, and many-to-one merge mapping.

[0102] In this embodiment, the terminal further configures a multi-dimensional classification mapping relationship between geographic entity categories and symbolic style categories based on pre-configured derived symbol relationships. This multi-dimensional classification mapping relationship is also written into the configuration file corresponding to the derived symbol relationship (or into a separate configuration file) to handle different mapping scenarios. Specifically, for the case of a one-to-one direct mapping between geographic entity categories and symbolic style categories, for example, the geographic entity "lake" directly corresponds to a blue-filled symbolic style, the terminal configures this category to directly point to the corresponding derived symbol relationship. For the case of a many-to-one merged mapping, for example, the geographic entities "railway bridge," "highway bridge," and "pedestrian bridge" all need to be mapped to the same bridge symbol, the terminal configures these three categories to point to the same derived symbol relationship. For one-to-many conditional branching mapping scenarios, such as the "House" class in a geographic entity needing to produce different symbolic effects based on different values ​​of the "Type" attribute field—that is, a red border fill style when the value is "Constructed House," and a black dashed line with no fill when the value is "Elevation House"—the terminal adds conditional judgment logic in its configuration to call different derived symbol relationships based on the value of this attribute field. Ultimately, the terminal completes the construction of the entire multi-dimensional classification mapping relationship, ensuring that it can correctly handle various complex category-symbol correspondences during derivation transformations.

[0103] In this embodiment, by pre-configuring the basic graphic environment file, the derived symbol relationship, and the multi-dimensional classification mapping relationship between geographic entity categories and symbolic style categories, the derivation conversion of DWG format DLG product data is performed based on the multi-dimensional classification mapping relationship. This eliminates the need for manual symbolization processing and map representation supplementation of intermediate data during the derivation conversion process, thereby improving the efficiency of generating target format data.

[0104] In one exemplary embodiment, such as Figure 5 As shown, step 102 includes steps 502 to 504. Wherein:

[0105] Step 502: Obtain initial geographic entity data.

[0106] In this embodiment, the terminal acquires initial geographic entity data, which can be a geographic entity library file after the operator completes the update operation within the production update scope. The initial geographic entity data is typically stored in .MDB or .GDB format. The terminal can directly connect to the geographic entity database and automatically input data by selecting or drawing a certain range within the database; alternatively, the terminal can directly read the geographic entity library file specified by the operator. This initial geographic entity data contains geometric information (e.g., points, lines, polygons) and attribute information (e.g., classification codes, names, types, elevation values, etc.) of various geographic entities, but has not yet undergone graphical processing required for DLG mapping.

[0107] Step 504: Perform mapping processing based on the preset mapping strategy corresponding to the category symbol attribute to obtain the target geographic entity data.

[0108] In this embodiment, the terminal performs mapping processing based on a preset mapping strategy corresponding to the category symbol attributes to obtain target geographic entity data. Specifically, the terminal first reads the classification and symbolization template configuration of the geographic entities to determine the classification structure and symbolization style of the input data. Then, the terminal processes the initial geographic entity data according to the preset mapping strategy to ensure that the processed map symbolization effect meets the requirements of DLG product data, thus obtaining the target geographic entity data. The initial geographic entity data before mapping processing retains the original geometric shapes and spatial relationships of the real world. For example, roads are represented as surfaces, elevated roads overlap with ground roads, contour lines pass through buildings, annotations are not located, and land boundaries are not generated. The target geographic entity data after mapping processing has been optimized according to DLG mapping requirements, including converting road surfaces to edges, eliminating hidden lines at elevated and ordinary road levels, intelligently generating annotation content and location, automatically generating and deduplicating land boundaries, and automatically disconnecting contour lines that cross features, ensuring that its map symbolization effect meets the requirements of DLG product data.

[0109] The preset mapping strategies include mapping processing strategies corresponding to geographic entities such as ordinary roads, elevated roads, annotations, land use boundaries, and contour lines. Specifically, for ordinary roads, the preset mapping strategy is used to automatically generate boundary features based on road surface features; for elevated roads, the preset mapping strategy is used to ensure the correct hierarchical display relationship between elevated roads and ordinary roads; for annotations, the preset mapping strategy is used to ensure the correct nature and name of annotations; for land use boundaries, the preset mapping strategy is used to automatically generate correct land use boundaries; and for contour lines, the preset mapping strategy is used to automatically hide contour lines that cross features.

[0110] For geographic entities of ordinary roads and elevated roads, the terminal automatically generates edge features from the polygon features of ordinary roads and handles the hierarchical display relationship between elevated roads and ordinary roads. The processing of geographic entities of ordinary roads and elevated roads is described in detail in the following embodiments.

[0111] For annotations, the terminal ensures the correctness of the annotation's nature and name through preset mapping strategies. Specifically, for basic property annotations (e.g., building structure and floor height), the terminal automatically generates annotations based on the property attributes corresponding to the geographic entity and using integrated map library symbolization technology, by configuring symbolization templates. For example, buildings typically have their structure and floor height annotated on the map; this can be achieved by configuring the corresponding attribute fields to the symbolization template. For road name annotations, the terminal ensures that each road in each map sheet has at least one name annotation by judging the vector topological relationship between the road and the map sheet. Secondly, within the same map sheet, the node spacing is determined using the map sheet junction as the start and end point. If the node spacing is greater than or equal to 3 / 4 of the map sheet length (greater than or equal to 1 indicates no nodes within the map sheet), road name annotations are generated at 1 / 3 and 2 / 3 positions of the two nodes, respectively. If the node spacing is greater than or equal to 1 / 4 and less than 3 / 4 of the map sheet length, road name annotations are generated at 1 / 2 position of the two nodes. If the node spacing is less than 1 / 4 of the map sheet length, no annotation is generated. Finally, to avoid the lack of annotations within the map due to excessively dense nodes, the terminal also performs supplementary judgments. When the distance between two nodes is less than 1 / 4 of the map length (for example, when the nodes of a curved road are densely distributed), the terminal performs a cumulative length judgment on the next node and generates a road name annotation at the position where the cumulative length is equal to 1 / 3 of the map length each time.

[0112] For land use boundaries, the terminal automatically generates land use boundaries from the extent or line entities of geographic entities using a preset mapping strategy. Specifically, the terminal automatically generates land use boundaries by matching the corresponding land features of the geographic entity. For issues such as duplicate land use boundaries leading to dense symbol distribution (e.g., the junction of grassland and forest ground), the terminal removes duplicate boundaries by determining the overlap relationship between the geographic entity and the corresponding land feature. When land use boundaries meet with land features such as walls, the terminal similarly uses the overlap relationship to hide the overlapping parts of the land use boundaries, retaining only the wall's representation and jointly representing the partially enclosed area.

[0113] For contour lines, the terminal uses a preset mapping strategy to automatically remove hidden features that the contour lines pass through. The terminal determines whether the contour lines overlap with the preset types of geographic entities (i.e., buildings, roads, and water systems). When a contour line overlaps with a feature of the above preset type, the overlapped portion of the contour line is removed (deleted or hidden) to ensure the clear readability of the topographic map.

[0114] In this embodiment, after cartographic processing, the geographic entity fusion database data is entered into the database. This data entry not only completes the data update and entry into the geographic entity database, but also completes the merging of geographic entity fusion data. This ensures that the entire geographic entity fusion database can be downloaded by map sheet cutting, realizing automated derivation technology processing by map sheet and the submission of DWG format DLG results, which can improve the efficiency of generating target format data.

[0115] In one exemplary embodiment, the category symbol attributes of each feature in the initial geographic entity data include ordinary road features and elevated road features; such as Figure 6 As shown, step 504 includes steps 602 to 604. Wherein:

[0116] Step 602: For ordinary road features, determine the intersection position between road surface features through vector intersection relationship, break and delete the road surface features at the intersection position, and convert the remaining surface geometry into line geometry. If the edge lines of two road segments are not adjacent, generate the edge line between the two road segments to obtain the target geographic entity data.

[0117] In this embodiment of the application, for the mapping processing of ordinary roads, the terminal performs mapping processing that automatically generates edge line features from road surface features. First, as... Figure 7 As shown, the terminal determines all road classification categories, then determines the intersection position based on the vector intersection relationship between road surface features and intersection surface features, and performs interruption, deletion or set type conversion processing at the intersection position based on the intersection situation to generate and connect connecting lines, thereby realizing the automatic generation of edge line features from road surface features.

[0118] In one specific embodiment, for intersections between regular intersections and road segments, the terminal determines the intersection location through vector intersection relationships, breaks the road segment at the intersection point, deletes the intersecting facets, and converts the geometry of the remaining facets into line geometry to generate road edge lines. For intersections without intersections, the terminal determines the intersection location through vector intersection relationships between the road segment faces, similarly breaks and deletes the intersecting portion, and converts the remaining facets into lines.

[0119] For irregular intersections in cities where road segments are not adjacent, the terminal first breaks down each road segment, deletes intersecting parts, and converts them into lines, just like in the case of intersections at regular intersections, to obtain the edge lines of each road segment. Then, the terminal determines the intersection status of the edge lines of each road segment. If there is no direct intersection between the edge lines of each road segment, it automatically converts the connecting line segment between the two road segment edge lines at the irregular intersection into the edge line of the higher-level road segment between them (for example, taking the higher one according to the road level), and connects it to the edge line of the adjacent road segment, thereby ensuring the continuity of the edge lines of the entire road network.

[0120] Step 604: For elevated road features, determine the intersection position between road surface features by vector intersection relationship, determine the upper and lower hierarchical relationship of the intersection position based on preset elevation value information, break and delete low elevation road surface features within high elevation road surface features, and convert the remaining surface geometry into line geometry to obtain target geographic entity data.

[0121] In this embodiment of the application, for the mapping processing of elevated roads, the terminal performs mapping processing to correctly display the hierarchical relationship between elevated roads and ordinary roads. For example... Figure 7 As shown, the terminal obtains the pre-assigned 3D model elevation values ​​for each node of the elevated road. For example, the terminal obtains the 3D model elevation values ​​by applying a layer of material to the vector data using the 3D model of the elevated bridge. Then, the terminal determines the intersection relationships between road surface features and reads the elevation value attribute information of the elevated road to determine the actual hierarchical relationship. Specifically, roads with higher elevation values ​​are considered upper-level roads, and those with lower elevation values ​​are considered lower-level roads. Finally, based on the intersection relationships and elevation values, the terminal breaks up road surface features with lower elevations within road surface features with higher elevations, deleting the intersecting surfaces and converting the remaining surface geometry to line geometry. At this point, in the final map display, the portion of the lower-level road obscured below the elevated bridge is automatically hidden, and only the complete graphic of the upper-level elevated road is displayed, thus correctly presenting the hierarchical relationship between the elevated road and ordinary roads.

[0122] In this embodiment, by automatically determining the intersection relationship and elevation information of road surface elements, the generation of road edge lines, connection of irregular intersections, and hierarchical hidden line removal of elevated roads and ordinary roads are automatically completed. There is no need for manual editing of road geometry and upper and lower layer relationships, thereby improving the efficiency of mapping processing and the accuracy of derived data.

[0123] In one exemplary embodiment, such as Figure 8 As shown, step 106 includes steps 802 to 806. Wherein:

[0124] Step 802: Based on the multidimensional classification mapping relationship in the derived mapping relationship, determine the symbolic style category corresponding to the category symbol attribute of the target geographic entity data.

[0125] In this embodiment, the terminal reads the multidimensional classification mapping relationship from the pre-configured derived mapping relationship and obtains the target geographic entity data after cartographic processing. For each feature in the target geographic entity data, the terminal matches it in the multidimensional classification mapping relationship according to the feature's category symbol attribute and attribute field value to determine the symbolic style category corresponding to the category symbol attribute of the target geographic entity data. If it is a one-to-one or one-to-many case, the terminal determines the symbolic style category corresponding to the feature according to the conditional branch of the attribute field, which is taken as the symbolic style category corresponding to the target geographic entity data; if it is a many-to-one case, the terminal maps features of different categories to the same symbolic style category to obtain the symbolic style category corresponding to the target geographic entity data. Thus, the terminal obtains a unique symbolic style category identifier for each target geographic entity.

[0126] Step 804: Based on the target template rules corresponding to the symbolization style category in the symbolization template, perform map symbolization rendering on the target geographic entity data to obtain intermediate rendering data.

[0127] In this embodiment, the terminal, based on the symbolic style category, calls the target template rule from the symbolic template corresponding to that category in the geographic entity fusion library to perform map symbolic rendering on the target geographic entity data, obtaining intermediate rendering data. During the rendering process, the terminal adds symbolic style parameters to each feature according to the template rules, such as line type, color, line width, fill, and annotations. After rendering is completed, the terminal performs a map sheet-based cropping and downloading operation. Specifically, guided by the surveying and mapping production requirement that "DLG result data is submitted by map sheet," the terminal calls fixed map sheet grid lines (for example, fixed map sheet grid lines are determined by the map sheet division rules of the national standard map sheet) to cut the intermediate rendering data covering a large area into multiple independent map sheet data files according to the map sheet boundaries. Each map sheet data file still retains the format and symbolic style information of the intermediate rendering data, but only contains features falling within the map sheet range. After cropping, the terminal obtains multiple map sheet files composed of map sheets, each containing the intermediate rendering data corresponding to the target geographic entity data.

[0128] Step 806: Based on the derived symbol relationship in the derived mapping relationship, convert the symbolic style in the intermediate rendering data into the graphic expression elements of the target format to generate the target format data.

[0129] In this embodiment, for each segmented intermediate rendering data file, the terminal sequentially converts the symbolic styles in the intermediate rendering data based on the derivation symbolic relationships in the derivation mapping relationship to obtain the graphic expression elements of the target format and generate the target format data. Specifically, the terminal reads a pre-configured derivation symbolic relationship configuration file, which records the mapping relationship between each symbolic style and the target format graphic expression rules.

[0130] For each sheet file, the terminal finds the corresponding derived symbol relationships based on the symbolization style of each feature in the current sheet file, converts the symbolization style into graphic representation elements in the target format (e.g., line objects, fill objects, text objects, etc.), and sets the correct layer, color, line type, line width, and other attributes. After the conversion is complete, the terminal outputs the target format data file corresponding to that sheet file, which is the DWG format DLG product data.

[0131] After processing all the map sheet files sequentially, the terminal obtains a complete set of DLG product data in DWG format. In addition, the terminal will automatically refine the map frame of each DWG format DLG product data according to the requirements of the national basic scale map style, using preset parameters. The refinement parameters include map frame boundary parameters, auxiliary element parameters, and label and text parameters, which can be modified in advance according to actual needs.

[0132] In this embodiment, by automatically determining the symbolic style category of geographic entities, performing map symbolic rendering, cropping by map sheet, and automatically converting to target format data based on derived symbol relationships, the efficiency of generating target format data is improved without the need for manual symbolic processing and cartographic supplementation of intermediate data.

[0133] In one exemplary embodiment, an example of geographic information data derivation is provided, such as... Figure 9 As shown, it includes the backend configuration phase and the program execution phase, wherein:

[0134] The backend configuration phase includes:

[0135] Step 901: Determine the classification and symbolization standards for geographic entities based on the geographic entity fusion database classification and symbol design. The geographic entity fusion database classification includes the original classification structure of geographic entity data and the target classification structure corresponding to the cartographic elements selected according to the target cartographic standards.

[0136] Step 902: Construct derived technology configurations based on the classification and symbolization standards of geographic entities. Derived technology configurations include DWG seed file configurations, derived symbol relationship configurations, classification mapping relationship configurations, and one-to-many relationship symbol configurations.

[0137] The program execution phase includes:

[0138] Step 903: Based on the preset mapping strategy corresponding to the category symbol attributes, the geographic entity data (initial geographic entity data) within the production update scope is processed using mapping techniques to obtain the target geographic entity data. The mapping processing based on the preset mapping strategy includes automatically generating boundary features based on road surface features, ensuring correct hierarchical display relationships between elevated roads and ordinary roads, correct nature and name of annotations, automatic and correct generation of land boundary, and automatic removal of contour lines crossing features.

[0139] Step 904: Input the target geographic entity data into the geographic entity fusion database.

[0140] Step 905: Download the map by map sheet to obtain the map sheet data.

[0141] Step 906: Invoke the derived technology configuration, perform derived technology processing based on the derived technology configuration, and perform outline finishing to output DWG format DLG product data.

[0142] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0143] Based on the same inventive concept, this application also provides a geographic information data derivation apparatus for implementing the geographic information data derivation method described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more geographic information data derivation apparatus embodiments provided below can be found in the limitations of the geographic information data derivation method described above, and will not be repeated here.

[0144] In one exemplary embodiment, such as Figure 10 As shown, a geographic information data derivation device 1000 is provided, including: an acquisition module 1001, an identification module 1002, and a derivation module 1003, wherein:

[0145] The acquisition module 1001 is used to read target geographic entity data, a pre-configured geographic entity fusion library, and derived configurations; the derived configurations include the derivation mapping relationship between symbolic styles and target format graphic expression rules;

[0146] The identification module 1002 is used to filter the category symbol attributes of each element in the target geographic entity data according to the classification structure in the geographic entity fusion library, and determine the symbolization template corresponding to the target geographic entity data based on the category symbol attributes; the symbolization template includes the symbolization style of the element.

[0147] Derivation module 1003 is used to perform derivation processing on each element of the target geographic entity data based on the derivation mapping relationship between symbolic templates and symbolic styles and target format graphic expression rules, so as to obtain target format data.

[0148] In one embodiment, the device 1000 further includes:

[0149] The filtering module is used to filter the target classification structure corresponding to the mapping elements based on the original classification structure of the geographic entity data and the target mapping standard.

[0150] The configuration module is used to configure symbolic templates corresponding to cartographic elements based on preset symbol standards, and to build a geographic entity fusion library based on the target classification structure and symbolic templates.

[0151] The building module is used to construct derived configurations based on preset mapping relationships. The preset mapping relationships include derived symbolic relationships for converting symbolic styles in the geographic entity fusion library into target format styles, as well as multi-dimensional classification mapping relationships between geographic entity categories and symbolic style categories.

[0152] In one embodiment, the construction module is specifically used to obtain a graphics environment base file of the target format; the graphics environment base file defines the layer classification, layer attributes and symbol description units of the target format;

[0153] Based on the graphical environment base file, configure symbolic styles to derive symbolic relationships from the target format graphical representation rules;

[0154] The multidimensional classification mapping relationship between geographic entity categories and symbolic style categories is configured based on derived symbolic relationships. The multidimensional classification mapping relationship includes one-to-one direct mapping, one-to-many conditional branching mapping, and many-to-one merge mapping.

[0155] In one embodiment, the geographic entity fusion library includes a classification structure and symbolic templates for geographic entities; the acquisition module 1001 is specifically used to acquire initial geographic entity data;

[0156] Mapping is performed based on a preset mapping strategy corresponding to the category symbol attribute to obtain target geographic entity data.

[0157] In one embodiment, the category symbol attributes of each element in the initial geographic entity data include ordinary road elements and elevated road elements; the acquisition module 1001 is specifically used to determine the intersection position between road surface elements through vector intersection relationship for ordinary road elements, break and delete the road surface elements at the intersection position, and convert the remaining surface geometry into line geometry. If the edge lines of two road segments are not adjacent, the edge line between the two road segments is generated to obtain the target geographic entity data.

[0158] For elevated road features, the intersection position between road surface features is determined by vector intersection relationship. The hierarchical relationship between the intersection position is determined based on the preset elevation value information. Road surface features with low elevation are broken and deleted within road surface features with high elevation. The remaining surface geometry is converted into line geometry to obtain the target geographic entity data.

[0159] In one embodiment, the derivation module 1003 is specifically used to determine the symbolic style category corresponding to the category symbol attribute of the target geographic entity data based on the multidimensional classification mapping relationship in the derivation mapping relationship.

[0160] Based on the target template rules corresponding to the symbolic style category in the symbolic template, the target geographic entity data is rendered using map symbolization to obtain intermediate rendering data.

[0161] Based on the derived symbol relationship in the derived mapping relationship, the symbolic style in the intermediate rendering data is converted into the graphic expression elements of the target format, and the target format data is generated.

[0162] Each module in the aforementioned geographic information data generation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0163] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 11 As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a geographic information data derivation method. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0164] Those skilled in the art will understand that Figure 11The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0165] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0166] Read target geographic entity data, pre-configured geographic entity fusion library, and derived configuration; the derived configuration includes the derivation mapping relationship between symbolic styles and target format graphic expression rules;

[0167] Based on the classification structure in the geographic entity fusion library, the category symbol attributes of each element in the target geographic entity data are filtered, and the symbolization template corresponding to the target geographic entity data is determined based on the category symbol attributes; the symbolization template includes the symbolization style of the elements;

[0168] Based on the derivation mapping relationship between symbolic templates and symbolic styles and target format graphic representation rules, the elements of the target geographic entity data are derivationally processed to obtain the target format data.

[0169] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0170] Based on the original classification structure of geographic entity data and the target mapping standards, the target classification structure corresponding to the mapping elements is selected.

[0171] Based on preset symbol standards, configure symbol templates corresponding to cartographic elements, and construct a geographic entity fusion library according to the target classification structure and symbol templates;

[0172] Derivative configurations are constructed based on preset mapping relationships; the preset mapping relationships include derived symbolic relationships used to convert symbolic styles in the geographic entity fusion library into target format styles, as well as multi-dimensional classification mapping relationships between geographic entity categories and symbolic style categories.

[0173] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0174] Obtain the target format's graphics environment base file; the graphics environment base file defines the target format's layer categories, layer attributes, and symbol description units;

[0175] Based on the graphical environment base file, configure symbolic styles to derive symbolic relationships from the target format graphical representation rules;

[0176] The multidimensional classification mapping relationship between geographic entity categories and symbolic style categories is configured based on derived symbolic relationships. The multidimensional classification mapping relationship includes one-to-one direct mapping, one-to-many conditional branching mapping, and many-to-one merge mapping.

[0177] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0178] Obtain initial geographic entity data;

[0179] Mapping is performed based on a preset mapping strategy corresponding to the category symbol attribute to obtain target geographic entity data.

[0180] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0181] For ordinary road features, the intersection position between road surface features is determined by vector intersection relationship. At the intersection position, the road surface features are broken and deleted, and the remaining surface geometry is converted into line geometry. If the edge lines of two road segments are not adjacent, the edge line between the two road segments is generated to obtain the target geographic entity data.

[0182] For elevated road features, the intersection position between road surface features is determined by vector intersection relationship. The hierarchical relationship between the intersection position is determined based on the preset elevation value information. Road surface features with low elevation are broken and deleted within road surface features with high elevation. The remaining surface geometry is converted into line geometry to obtain the target geographic entity data.

[0183] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0184] Based on the multidimensional classification mapping relationship in the derived mapping relationship, determine the symbolic style category corresponding to the category symbol attribute of the target geographic entity data;

[0185] Based on the target template rules corresponding to the symbolic style category in the symbolic template, the target geographic entity data is rendered using map symbolization to obtain intermediate rendering data.

[0186] Based on the derived symbol relationship in the derived mapping relationship, the symbolic style in the intermediate rendering data is converted into the graphic expression elements of the target format, and the target format data is generated.

[0187] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0188] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0189] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0190] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0191] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0192] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for deriving geographic information data, characterized in that, The method includes: Read target geographic entity data, a pre-configured geographic entity fusion library, and derived configurations; the derived configurations include the derived mapping relationship between symbolic styles and target format graphic expression rules; The category symbol attributes of each element in the target geographic entity data are filtered according to the classification structure in the geographic entity fusion library, and the symbolization template corresponding to the target geographic entity data is determined based on the category symbol attributes; the symbolization template includes the symbolization style of the element; Based on the derivation mapping relationship between the symbolic template and the symbolic style and the target format graphic expression rules, the elements of the target geographic entity data are derivationally processed to obtain the target format data.

2. The method according to claim 1, characterized in that, Before reading the target geographic entity data, the pre-configured geographic entity fusion library, and the derived configuration, the method further includes: Based on the original classification structure of geographic entity data and the target mapping standards, the target classification structure corresponding to the mapping elements is selected. Based on the preset symbol standard, configure the symbol template corresponding to the cartographic elements, and construct a geographic entity fusion library according to the target classification structure and the symbol template; A derived configuration is constructed based on a preset mapping relationship; the preset mapping relationship includes a derived symbol relationship for deriving symbolic styles in the geographic entity fusion library into target format styles, and a multi-dimensional classification mapping relationship between geographic entity categories and symbolic style categories.

3. The method according to claim 2, characterized in that, The step of constructing derived configurations based on preset mapping relationships includes: Obtain the target format graphics environment base file; the graphics environment base file defines the target format layer categories, layer attributes, and symbol description units; Based on the graphical environment base file, configure the symbolic style to the derived symbolic relationship of the target format graphical expression rules; Based on the derived symbolic relationship, configure a multidimensional classification mapping relationship between geographic entity categories and symbolic style categories; the multidimensional classification mapping relationship includes one-to-one direct mapping, one-to-many conditional branch mapping, and many-to-one merge mapping.

4. The method according to claim 1, characterized in that, The geographic entity fusion library includes a classification structure and symbolic templates for geographic entities; The reading of target geographic entity data includes: Obtain initial geographic entity data; Mapping is performed based on the preset mapping strategy corresponding to the category symbol attribute to obtain target geographic entity data.

5. The method according to claim 4, characterized in that, The category symbol attributes of each element in the initial geographic entity data include ordinary road elements and elevated road elements; the mapping processing based on the preset mapping strategy corresponding to the category symbol attributes to obtain the target geographic entity data includes: For the common road features, the intersection position between road surface features is determined by the vector intersection relationship. At the intersection position, the road surface features are broken and deleted, and the remaining surface geometry is converted into line geometry. If the edge lines of two road segments are not adjacent, the edge line between the two road segments is generated to obtain the target geographic entity data. For the elevated road features, the intersection position between road surface features is determined by vector intersection relationship. The hierarchical relationship of the intersection position is determined based on the preset elevation value information. The road surface features with low elevation are broken and deleted within the road surface features with high elevation. The remaining surface geometry is converted into line geometry to obtain the target geographic entity data.

6. The method according to claim 1, characterized in that, The derivation processing of each element of the target geographic entity data based on the derivation mapping relationship between the symbolic template and the symbolic style and the target format graphic expression rules yields target format data, including: Based on the multidimensional classification mapping relationship in the derived mapping relationship, the symbolic style category corresponding to the category symbol attribute of the target geographic entity data is determined. Based on the target template rule corresponding to the symbolization style category in the symbolization template, the target geographic entity data is rendered using map symbolization to obtain intermediate rendering data. Based on the derived symbol relationship in the derived mapping relationship, the symbolic style in the intermediate rendering data is converted into graphic expression elements in the target format to generate target format data.

7. A geographic information data derivation device, characterized in that, The device includes: The acquisition module is used to read target geographic entity data, a pre-configured geographic entity fusion library, and derived configurations; the derived configurations include the derived mapping relationship between symbolic styles and target format graphic expression rules; The identification module is used to filter the category symbol attributes of each element in the target geographic entity data according to the classification structure in the geographic entity fusion library, and determine the symbolization template corresponding to the target geographic entity data based on the category symbol attributes; the symbolization template includes the symbolization style of the element; The derivation module is used to perform derivation processing on each element of the target geographic entity data based on the derivation mapping relationship between the symbolic template and the symbolic style and the target format graphic expression rules, so as to obtain the target format data.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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