Geographic entity construction method based on framing topographic map
By implementing unified quality inspection and data entry, classification and conversion rules, and vector data fusion for topographic maps, the problem of automating the construction of geographic entities in topographic maps has been solved. This has enabled the efficient generation of complete geographic entities, improved production efficiency, and reduced labor costs.
Patent Information
- Application Number
- CN202512055509.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-31
- Publication Date
- 2026-02-17
AI Technical Summary
Existing technologies lack automated processing steps based on attribute consistency and spatial proximity when constructing geographic entities from topographic maps, resulting in breaks, overlaps, or self-intersections during vector data fusion, which damages the integrity and connectivity of entities.
The method involves unified quality inspection and warehousing of topographic map data, establishment of transformation rules through data classification, extraction of geographic entity data, and fusion of vector data to construct geographic entities. This includes quality inspection of spatial and attribute data, unified coordinate system transformation, attribute similarity matching, and line and surface feature fusion algorithms under tolerance parameters. It also employs buffer zones and the left-hand principle to process adjacent areas.
It enables efficient fusion of topographic maps to generate complete geographic entities, improving production efficiency, reducing labor costs, and ensuring the integrity and connectivity of geographic entities.
Smart Images
Figure CN121542364A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to geographic information, surveying and mapping technology, and in particular to a geographic entity construction method based on a divided topographic map. BACKGROUND
[0002] Compared with traditional surveying and mapping, new basic surveying and mapping takes geographic entities as objects, carries out surveying and mapping according to entity granularity and spatial accuracy, and constructs a basic geographic entity database based on geographic entities. The production and construction of geographic entities are the focus of new basic surveying and mapping work. There are two types of methods for producing geographic entities at present: one is to extract and convert various existing test results to construct geographic entities; the other is to collect geographic entities through modern measurement means, such as tilt models, panoramic images, and point clouds. Since each region has stock data that meets the requirements of accuracy and timeliness, the method of extracting, converting, and reconstructing geographic entities from stock data is highly operable and low in cost. In actual production, a complete geographic entity (such as a complete river, a continuous residential area, or a complete forest) is often divided into different sheets due to differences in surveying and mapping range, mapping time, or mapping comprehensive standards, which is manifested as multiple independent, spatially close but separated vector elements, resulting in breaks, overlaps, or self-intersections, which destroys the integrity and connectivity of the entity.
[0003] At present, there are related studies on the conversion method from stock electronic map data to geographic entities. The methods are basically divided into four aspects: collecting original data, preprocessing the original data, converting the graphic data according to rules and conditions, and constructing geographic entities. Zou Lei et al. proposed a method for automatically producing geographic entities from existing DWG maps and topographic map databases, and provided detailed information on the automation efficiency of the entire process. Zhang Yiran et al. analyzed the multi-state characteristics of geographic entities in space and time, designed a geographic entity fusion method based on multi-source vector data, and introduced the specific application of the fusion results taking a house building entity as an example. However, the above studies have the following shortcomings: when fusing vector data to generate geographic entities, they mostly rely on manual operation or simple logical-based graphic merging tools, and lack an automatic comprehensive processing flow based on attribute consistency and spatial proximity. For example, simple merging operations may incorrectly merge elements with different attributes but close positions, or fail to intelligently handle small gaps and overlaps between elements. SUMMARY
[0004] The present application relates to geographic information, surveying and mapping technology, and in particular to a geographic entity construction method based on a divided topographic map.
[0005] The technical solution for achieving the object of the present application is as follows: a geographic entity construction method based on a divided topographic map, comprising the following steps:
[0006] Step 1: Unified quality inspection and warehousing of topographic map product data: The original topographic map data is inspected for quality, data with unqualified quality is removed, the data spatial coordinate system and elevation datum are unified, and the processed qualified data is stored in the database, thereby integrating the topographic map data stored in multiple standard sheets into a single SQLite database.
[0007] Step 2: Data Classification and Conversion Rules: In accordance with the database design content and requirements of GB / T 37118-2018 "Specification for Spatial Data of Geographic Entities", design all data layers and attribute fields of geographic entities, establish a conversion rule comparison table from the original topographic map elements to the target geographic entities, and perform data category conversion.
[0008] Step 3: Geographic entity data classification and extraction: For the transformed data, analyze the attribute information of geographic entity categories, extract data from the SQLite database according to the principle of similar entity attributes, and obtain a data set of line features and polygon features with the same basic attributes.
[0009] Step 4: Vector data fusion to construct geographic entities: For line feature sets and polygon feature sets, spatial data fusion is performed by setting tolerance parameters to merge lines or polygons with similar attributes and spatially adjacent into a complete geographic entity;
[0010] Step 5: Geographic entity data inspection: Perform feature integrity, logical consistency, topological error inspection, spatial accuracy, and attribute inspection on the constructed geographic entity data.
[0011] Furthermore, in step one:
[0012] Data quality checks include spatial data quality checks, attribute data quality checks, and metadata checks.
[0013] In the unified data spatial coordinate system and elevation datum, the spatial coordinate system adopts the 2000 National Geodetic Coordinate System, and the elevation datum adopts the 1985 National Elevation Datum.
[0014] The data storage method is as follows: Geographic data that has undergone quality checks and coordinate transformation is stored separately according to layer categories. Each layer category of the topographic map is stored as a separate database table. Finally, multiple database tables are merged and stored into a single SQLite database.
[0015] Furthermore, in step three, data is extracted according to the principle of entity attribute similarity, including:
[0016] Based on the category of geographical entities, set the key attributes required for similarity matching of various entities;
[0017] Based on the defined key attributes, execute queries from the SQLite database to extract data;
[0018] For road entities, the key attributes include name and / or number; for contour line entities, the key attribute is elevation value.
[0019] Furthermore, step four, the fusion of the line feature data set, includes the following sub-steps:
[0020] (1) Extract the start and end coordinates of all line segments in the line feature set;
[0021] (2) Identify connectable line segment endpoints based on preset tolerance parameters;
[0022] (3) A bidirectional extension algorithm is used to connect line segments. All line segments are traversed. For line segments that have not yet been connected, forward extension and backward extension operations are performed to find and connect connectable line segments within the tolerance parameter range. Forward extension means starting from the end of the current line segment and finding connectable endpoints for connection and merging. Backward extension means starting from the beginning of the current line segment and finding connectable endpoints for connection and merging.
[0023] (4) Based on the connection result of step (3), determine whether the generated line segment is a single continuous line segment or a polyline composed of multiple sub-segments.
[0024] (5) Perform topology checks on the line features generated in step (4) to identify self-intersecting and dangling nodes.
[0025] Furthermore, the condition for determining whether an endpoint is connectable is:
[0026] Calculate the Euclidean distance r between two points. If r is less than or equal to the tolerance parameter tolerance, the points are considered connectable; otherwise, they are considered inconnectable.
[0027] Furthermore, step four, the fusion of the surface element data set, includes the following sub-steps:
[0028] (1) Perform a union operation on the vector surface data set to generate a new polygon set;
[0029] (2) If the result generated in step (1) is a single polygon, then the fusion is complete; if the result is multiple polygons, then step (3) is executed.
[0030] (3) Traverse multiple polygons, generate a buffer according to the preset tolerance parameter size, and determine whether there is an intersection with other polygons; if the buffers of two polygons intersect, then execute steps (4) to (7) for these two polygons.
[0031] (4) Calculate the positions of multiple intersection points between the intersecting region between the two polygonal buffer zones and the respective boundaries of the two polygons;
[0032] (5) For each calculated intersection point, search for the point closest to the intersection point on the boundaries of the two corresponding polygons to generate a set of fusion points of the two polygons;
[0033] (6) Starting from a fusible point of any polygon, search for the nearest fusible point along the edge of the polygon using the left-hand rule, and connect adjacent fusible points into a line; when the polygon has no fusible points, search for the nearest fusible point of another polygon and connect them; repeat the above search and connection steps until a closable loop is formed.
[0034] (7) Generate polygon data for the closed loop formed in step (6), and use the vector surface union operation to merge the loop with the two original polygons to generate a complete polygon.
[0035] Furthermore, the left-hand principle means that when traveling along the boundary of a polygon, the outer edge of the polygon should be kept on the left-hand side of the direction of travel.
[0036] Furthermore, in step five, the inspection content also includes: focusing on inspecting the line segment sets and polygon sets that could not be merged in step four; and through human-computer interaction inspection, if it is found that there are omissions, misstructures, or multiple structures in the constructed geographic entities, the geographic entities are manually edited and modified.
[0037] Furthermore, after step five, the method further includes: storing the modified fusion result as a new geographic entity object in the database, wherein the geographic entity object has a unique ID and a complete geometric shape.
[0038] A geographic entity construction system based on a topographic map includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements any of the methods described above.
[0039] Compared with existing technologies, the significant advantages of this invention are as follows: 1) When merging topographic maps into geographic entities, existing technologies only consider the edge fusion processing of vector data between different map sheets, and do not consider the fusion of vector elements within the same topographic map. Furthermore, the attribute information of vector elements is not reasonably utilized during fusion. This invention proposes a classified fusion process from topographic maps to geographic entities, and proposes attribute matching rules corresponding to the categories of different geographic entity types. In application, this patent can extract and fuse the "Yangtze River" from thousands of topographic maps into a complete geographic entity object. 2) Existing technologies have difficulty processing gaps in the fusion algorithm for line and polygon vector elements. This invention proposes a line and polygon element fusion method suitable for geographic entity construction. Polygon data fusion uses a buffer and the "left-hand principle" to search for neighboring areas at the boundary to construct a complete geographic entity. Attached Figure Description
[0040] Figure 1 This is a flowchart of a geographic entity construction method based on a topographic map.
[0041] Figure 2 This is a schematic diagram of fusion within the tolerance range of the line fusion algorithm.
[0042] Figure 3 This is a schematic diagram of the gap processing flow of the surface fusion algorithm. Detailed Implementation
[0043] 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.
[0044] Geographic entities are fundamental data units that use digital methods to structurally represent indivisible geographical phenomena in the real world. They include natural landforms, man-made structures, and other types. They are globally uniquely identified through spatial identity coding and stored and managed using various database formats, such as relational and object-oriented databases. Geographic entity data is widely used in fields such as land planning and environmental monitoring, and a technical specification system has been established that includes lifecycle management and topological relationship maintenance.
[0045] This invention proposes a method for constructing geographic entities based on topographic maps. It intelligently handles overlap and gap issues between vector data based on attribute consistency and spatial proximity, improving geographic entity production efficiency and reducing labor costs. The method includes unified quality inspection and warehousing of topographic map product data, data classification and transformation rule establishment, geographic entity data classification and extraction, vector data fusion to construct geographic entities, and result data inspection. A flowchart is provided below. Figure 1 The specific steps are as follows:
[0046] Step 1: Unified Quality Inspection and Database Entry of Topographic Map Product Data. The original topographic map data undergoes quality inspection, discarding data that does not meet quality standards. The spatial coordinate system and elevation datum are standardized, and the reconstructed data is then entered into the database. Finally, the topographic map data stored in multiple standard sheet formats are reconstructed into a single SQLite database.
[0047] The data quality is checked by reading the attribute and spatial information of vector data from the topographic map, which mainly includes spatial data quality check, attribute data quality check, and metadata check, and data that does not meet the quality requirements is removed.
[0048] Data from different sources undergoes unified coordinate system and elevation datum transformations to form a unified data model. The geographic data in the database uses the 2000 National Geodetic Coordinate System (CGCS2000) as the spatial coordinate system and the 1985 National Elevation Datum as the elevation datum. Data from each layer of the topographic map is stored in a separate database table, and finally, multiple topographic map data stored in standard sheet format are combined to form a single SQLite database.
[0049] Step Two: Establish conversion rules for data classification, mainly including encoding conversion and attribute comparison. Following the database design content and requirements of GB / T37118-2018 "Specification for Spatial Data of Geographic Entities," define all data layers and attribute fields for geographic entities. Compare the elements on the original topographic map with the desired geographic entity standards to determine the element categories that need conversion, and establish a conversion rule comparison table for data category conversion.
[0050] Step 3: Geographic Entity Data Classification and Extraction. The transformed data is analyzed to determine the attribute information of geographic entity categories. Data extraction is performed based on attribute similarity matching of similar features (e.g., using name and number for road categories, and elevation for contour line categories) to obtain a data set of line and polygon features with the same basic attributes.
[0051] Step 4: Vector data fusion to construct geographic entities. For line and polygon data, the main steps include deleting duplicate data, stitching adjacent lines, and stitching adjacent polygons. By setting tolerance parameters, spatial data is fused to merge lines or polygons with similar attributes and spatially adjacent areas into a complete geographic entity.
[0052] The following fusion algorithm is used to merge the line segment sets within a certain error range after extraction of the line data set: 1) Extract the start and end points of all line segments; 2) Based on the error tolerance, identify the endpoints of connectable line segments. The Euclidean distance between two points is calculated and compared with the error tolerance to determine whether the endpoints are connectable, as shown in the following formula; 3) A bidirectional extension algorithm is used to connect line segments. It iterates through the unconnected line segments and merges connectable lines within the error range, including forward and backward extensions. Forward extension finds connectable line segments from the end of the current line segment; backward extension finds connectable line segments from the beginning of the current line segment. The fusion process can be referenced. Figure 2 ;4) Based on the connection results, determine whether the generated result is a single line segment (LineString) or a multi-line segment (MultiLineString);5) Perform topology checks to identify problems such as self-intersections and dangling nodes. If problems exist, they should be handled manually later.
[0053] ≤ tolerance
[0054] In the formula, r is the Euclidean distance between the two points, (x1, y1) are the latitude and longitude coordinates of point 1, (x2, y2) are the latitude and longitude coordinates of point 2, and tolerance is the set tolerance.
[0055] The following fusion method is used to automatically merge adjacent, intersecting, and gap-free polygon features after extraction. 1) First, the vector polygon data set is merged to generate a new vector dataset. This method can effectively merge edge-connected and intersecting polygons and eliminate common boundaries, but it cannot merge gaps between polygons. If the result generates multiple polygons (format: MultiPolygons), proceed to the next step; 2) Traverse the polygons, generate a buffer based on the tolerance size, and determine if there are intersections with other polygons. If there are intersections, proceed to the next step; 3) Calculate the positions of multiple intersections, search for the closest point to each intersection point in each of the two polygons, and generate a set of possible fusion points for the two polygons, hereinafter referred to as fusion points; 4) Using any fusion point of a polygon as the starting point, search for the nearest fusion point along the edge of the polygon according to the left-hand principle (i.e., the left-hand side along the search direction is the outer edge of the polygon). When the polygon has no fusion points, search for the nearest fusion point of the other polygon and connect them. Repeat the above steps until a closable loop is formed; 5) Reconstruct the polygon boundary, generate polygons from the closed loop, and use the vector face union operation to merge the two polygons and the gap loop, eliminating the gaps between the faces and generating a complete polygon. The fusion process can be found in [reference needed]. Figure 3 .
[0056] Step 5: The geographic entity data inspection mainly includes checking feature completeness, logical consistency, topological errors, spatial accuracy, and attributes. In addition, it is crucial to inspect line segment sets and polygon sets that could not be merged in Step 4. Through interactive inspection, if omissions, misalignments, or multiple structures are found in the constructed geographic entities, manual editing and modification are required. After modification, the merged result is stored in the database as a new geographic entity object, possessing a unique ID and complete geometric shape.
[0057] The present invention also proposes a geographic entity construction system based on a topographic map, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements any of the methods described above.
[0058] 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 specification.
[0059] 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 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 modifications and improvements 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 constructing geographic entities based on topographic maps, characterized in that, Includes the following steps: Step 1: Unified quality inspection and warehousing of topographic map product data: The original topographic map data is inspected for quality, data with unqualified quality is removed, the data spatial coordinate system and elevation datum are unified, and the processed qualified data is stored in the database, thereby integrating the topographic map data stored in multiple standard sheets into a single SQLite database. Step 2: Data Classification and Conversion Rules: In accordance with the database design content and requirements of GB / T 37118-2018 "Specification for Spatial Data of Geographic Entities", design all data layers and attribute fields of geographic entities, establish a conversion rule comparison table from the original topographic map elements to the target geographic entities, and perform data category conversion. Step 3: Geographic entity data classification and extraction: For the transformed data, analyze the attribute information of geographic entity categories, extract data from the SQLite database according to the principle of similar entity attributes, and obtain a data set of line features and polygon features with the same basic attributes. Step 4: Vector data fusion to construct geographic entities: For line feature sets and polygon feature sets, spatial data fusion is performed by setting tolerance parameters to merge lines or polygons with similar attributes and spatially adjacent into a complete geographic entity; Step 5: Geographic entity data inspection: Perform feature integrity, logical consistency, topological error inspection, spatial accuracy, and attribute inspection on the constructed geographic entity data.
2. The geographic entity construction method based on sheet topographic maps according to claim 1, characterized in that, In step one: Data quality checks include spatial data quality checks, attribute data quality checks, and metadata checks. In the unified data spatial coordinate system and elevation datum, the spatial coordinate system adopts the 2000 National Geodetic Coordinate System, and the elevation datum adopts the 1985 National Elevation Datum. The data storage method is as follows: Geographic data that has undergone quality checks and coordinate transformation is stored separately according to layer categories. Each layer category of the topographic map is stored as a separate database table. Finally, multiple database tables are merged and stored into a single SQLite database.
3. The method for constructing geographic entities based on topographic maps according to claim 1, characterized in that, In step three, data is extracted according to the principle of similar entity attributes, including: Based on the category of geographical entities, set the key attributes required for similarity matching of various entities; Based on the defined key attributes, execute queries from the SQLite database to extract data; For road entities, the key attributes include name and / or number; for contour line entities, the key attribute is elevation value.
4. The method for constructing geographic entities based on topographic maps according to claim 1, characterized in that, Step four, the fusion of the line feature data set, includes the following sub-steps: (1) Extract the start and end coordinates of all line segments in the line feature set; (2) Identify connectable line segment endpoints based on preset tolerance parameters; (3) Use a bidirectional extension algorithm to connect line segments. Traverse all line segments. For line segments that have not yet been connected, perform forward extension and backward extension operations to find and connect connectable line segments within the tolerance parameter range. The forward extension refers to starting from the end of the current line segment and finding a connectable endpoint for connection and merging; the backward extension refers to starting from the beginning of the current line segment and finding a connectable endpoint for connection and merging. (4) Based on the connection result of step (3), determine whether the generated line segment is a single continuous line segment or a polyline composed of multiple sub-segments. (5) Perform topology checks on the line features generated in step (4) to identify self-intersecting and dangling nodes.
5. The geographic entity construction method based on sheet topographic maps according to claim 4, characterized in that, The condition for determining whether an endpoint is connectable is: Calculate the Euclidean distance r between two points. If r is less than or equal to the tolerance parameter tolerance, the points are considered connectable; otherwise, they are considered inconnectable.
6. The method for constructing geographic entities based on topographic maps according to claim 1, characterized in that, Step four, the fusion of the surface feature data set, includes the following sub-steps: (1) Perform a union operation on the vector surface data set to generate a new polygon set; (2) If the result generated in step (1) is a single polygon, then the fusion is complete; if the result is multiple polygons, then step (3) is executed. (3) Traverse multiple polygons, generate a buffer according to the preset tolerance parameter size, and determine whether there is an intersection with other polygons; if the buffers of two polygons intersect, then execute steps (4) to (7) for these two polygons. (4) Calculate the positions of multiple intersection points between the intersecting region between the two polygonal buffer zones and the respective boundaries of the two polygons; (5) For each calculated intersection point, search for the point closest to the intersection point on the boundaries of the two corresponding polygons to generate a set of fusion points of the two polygons; (6) Starting from a fusible point of any polygon, search for the nearest fusible point along the edge of the polygon using the left-hand rule, and connect adjacent fusible points into a line; when the polygon has no fusible points, search for the nearest fusible point of another polygon and connect them; repeat the above search and connection steps until a closable loop is formed. (7) Generate polygon data for the closed loop formed in step (6), and use the vector surface union operation to merge the loop with the two original polygons to generate a complete polygon.
7. The geographic entity construction method based on sheet topographic maps according to claim 6, characterized in that, The left-hand rule refers to keeping the outer edge of the polygon on the left-hand side of the direction of travel when moving along the polygon boundary.
8. The method for constructing geographic entities based on topographic maps according to claim 1, characterized in that, In step five, the inspection also includes: focusing on inspecting the line segment sets and polygon sets that could not be merged in step four; and manually editing and modifying the geographic entities if omissions, errors, or multiple structures are found in the constructed geographic entities through human-computer interaction.
9. The method for constructing geographic entities based on topographic maps according to claim 8, characterized in that, Step five is followed by storing the modified fusion result as a new geographic entity object in the database, wherein the geographic entity object has a unique ID and a complete geometric shape.
10. A geographic entity construction system based on a topographic map, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 9.