CN120031713A - Multi-layer map merging method and device based on spatial and attribute multi-condition judgment - Google Patents
Multi-layer map merging method and device based on spatial and attribute multi-condition judgment Download PDFInfo
- Publication number
- CN120031713A CN120031713A CN202510030040.9A CN202510030040A CN120031713A CN 120031713 A CN120031713 A CN 120031713A CN 202510030040 A CN202510030040 A CN 202510030040A CN 120031713 A CN120031713 A CN 120031713A
- Authority
- CN
- China
- Prior art keywords
- entity
- elements
- matching
- edge
- attribute
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
- G06T3/4038—Image mosaicing, e.g. composing plane images from plane sub-images
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20212—Image combination
- G06T2207/20221—Image fusion; Image merging
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Processing Or Creating Images (AREA)
Abstract
本发明提供了一种基于空间和属性多条件判断的多图层图幅合并方法及装置，所述方法包括数据读取，最大空间范围计算；图层合并；生成分幅边界线要素图层；并行执行遍历合并后的各要素分层；空间搜索图幅边界实体要素，生成要素集；对所述要素集中的实体要素进行接边实体匹配；对实体匹配匹配成功的实体要素执行实体接边处理。本发明在20个分幅数据库合并下较传统方法提效70％。分幅数据越多地理要素复杂程度越高，该方法效率较传统方法效率成倍数增长，能有效解决该项工作的人力、资金大且时间成本高的问题。
The present invention provides a multi-layer map merging method and device based on spatial and attribute multi-condition judgment, the method includes data reading, maximum spatial range calculation; layer merging; generating a layer of sub-frame boundary line elements; parallel execution of traversal of each element layer after merging; spatial search of map boundary entity elements to generate an element set; edge entity matching of the entity elements in the element set; and entity edge processing of the entity elements that successfully match the entity. The present invention improves the efficiency by 70% compared with the traditional method when merging 20 sub-frame databases. The more sub-frame data, the higher the complexity of the geographical elements. The efficiency of this method is multiplied compared with the efficiency of the traditional method, which can effectively solve the problems of large manpower, large funds and high time costs of this work.
Description
Technical Field
The invention relates to a multi-layer chart merging method based on space and attribute multi-condition judgment.
Background
The production of geographic entity data is mostly based on basic mapping topographic map data for the extraction of entity data. The basic mapping result data are stored in a national standard framing form, so that the merging work of the image data is usually needed in the process of producing the geographic entity data.
The merging of the map data comprises the merging of the map layer data and the attribute edge of map boundary area elements, namely merging and unifying the geographic entities with the same classification attribute of adjacent map. The attribute edge of the topographic map element is processed in a manual edge-connecting mode, so that the workload is large, the time cost is high, and meanwhile, due to the fact that precision errors exist in different framing data of the topographic map, position deviation exists in the process of splicing the map of the same geographic entity, the edge-connecting workload is increased, and the time cost is increased dramatically.
Disclosure of Invention
In order to solve the problems, the invention aims to provide an automatic map splicing and geographic element entity attribute edge splicing automatic flow processing method which solves the problem that a great deal of manpower and time cost are consumed in actual work.
The invention provides a multi-layer chart merging method based on space and attribute multi-condition judgment, which comprises the following steps:
merging the layered elements in parallel, and merging the layered data of the same element in a plurality of databases into one layer in parallel;
Generating a framing boundary line element layer, and calculating framing line elements of the generated data area according to the working area and the data standard scale and the national standard scale division rule;
performing parallel execution, traversing and layering the elements after combination, and carrying out edge splicing on the boundary elements of the picture, so as to realize unification of entity logic;
space searching of the map boundary entity elements generates element sets;
Edge entity matching is carried out on the entity elements in the element set;
And executing entity edge processing on the entity elements successfully matched by the entity matching.
Optionally, the spatial search map boundary entity element includes:
traversing the framing boundary line, taking the boundary line as the center, buffering two sides, setting distances, generating a boundary buffer area, and performing space searching and extraction on geographic element entities overlapped with the buffer area in the combined element layers to obtain an element set.
Optionally, the edge entity matching includes attribute matching and space matching;
Edge entity matching is carried out on the entity elements in the element set, wherein the edge entity matching comprises the steps of carrying out attribute matching on the entity elements in the element set, and finding out entities with the same attribute;
And judging whether the found entities with the same attribute belong to the same geographic entity in space through space matching, and if so, matching the entities into the same entity element.
Optionally, when the attributes are matched, the rules are classified according to the eight data categories of positioning foundation, water system, residential land and facilities, traffic, pipelines, boundaries and politics, landforms, vegetation and soil.
Optionally, three types of entities, namely a point entity, a line entity and a plane entity, are matched in space matching.
Optionally, the matching of the dot entities is to judge the dot distance of the two dot elements, wherein the two dot elements with the dot distance smaller than the field distance of 0.5mm on the graph are judged to be the same dot entity, and the actual distance of 0.5mm on the graph is equal to 0.5 x the frame scale denominator mm, and the two dot elements are converted into meters for use;
The matching of the line entities is to judge the endpoint distance of the two line elements near the framing joint, and the two line elements with the distance smaller than the field distance of 0.6mm on the graph are judged to be the same line entity;
The matching of the surface entities is to judge the end point distance of the two surface elements at the south and north sides of the boundary of the same picture, and the two surface elements with the distance of the two end points of the south and north sides being smaller than the field distance of 0.8mm on the picture are judged to be the same surface entity.
Optionally, executing the entity edge processing on the entity element successfully matched by the entity matching includes:
And carrying out graphic edge connection processing on the entity elements successfully matched by the entity to combine the entity elements into a new entity element, and completing edge connection of the entity at the joint of the drawing.
Optionally, the physical edge processing includes a point physical edge, a line physical edge, and a face physical edge.
The invention also provides a multi-layer chart merging device based on space and attribute multi-condition judgment, which comprises a processor and a memory storing program instructions, and is characterized in that the processor is configured to execute the multi-layer chart merging method based on space and attribute multi-condition judgment according to any one of the above when executing the program instructions.
The invention provides a computer-flow automatic processing method for merging a large number of sectional topographic map vector databases into a total library, which aims to solve the problems of large workload and low efficiency of topographic map merging and edge splicing in the production process of basic geographic entity data.
The invention provides a method and a device for automatically splicing pictures and automatically processing physical attribute edge connection of geographic elements, which automatically reads layered data of different elements under a plurality of topographic map databases to merge the data in parallel, and (3) searching geographical entities at the boundary line of the framing map in parallel, performing entity element attribute inspection and space precision error inspection, processing the edges, and combining a large number of framing databases by full-flow automatic parallel processing to form a basic geographical database with complete entity logic.
The automatic framing data merging entity edge splicing method provided by the invention has the efficiency obviously superior to that of the traditional manual framing edge splicing method, and the efficiency is improved by 70% compared with that of the traditional method under 20 framing database merging. The more the framing data is, the higher the complexity of the geographic elements is, the efficiency of the method is increased by multiple than that of the traditional method, and the problems of large manpower and fund and high time cost of the work can be effectively solved.
The above, as well as additional objectives, advantages, and features of the present invention will become apparent to those skilled in the art from the following detailed description of a specific embodiment of the present invention when read in conjunction with the accompanying drawings.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
FIG. 1 is a schematic flow diagram of an automated process for automatically splicing and bordering physical attributes of geographic elements according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of edge joining of physical elements according to an embodiment of the present invention;
FIG. 3 is a diagram of matching entity elements according to an embodiment of the present invention;
FIG. 4 is a schematic illustration of a point entity edge connection in accordance with an embodiment of the present invention;
FIG. 5 is a schematic view of a solid line junction according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a face entity edge process according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the invention, taken in conjunction with the accompanying drawings, is given by way of illustration and not limitation.
The invention provides a computer automatic processing method for splicing split topographic maps and splicing element edges, which realizes the automatic splicing of basic geographic vector databases such as multi-split residential areas, water systems, traffic road networks, vegetation, soil and the like and the automatic edge splicing of the same geographic entity element, quickly combines a plurality of topographic map databases into a topographic map vector database with consistent physical structure and unified element logic, and provides a data base for the production of geographic entities.
As shown in FIG. 1, the invention provides a multi-layer chart merging method based on space and attribute multi-condition judgment, which comprises the following steps S1-S6.
S1, merging the layering elements in parallel, reading layering data of the elements in the databases, and merging the layering data of the same element in the databases into one layer in parallel.
For example, the two 1:1 ten thousand standard frame GDB databases, I49G034010 and I49G034011, are known as I49G034010.GDB and I49G034011.GDB, both of which contain HYDA, RESA, LRDL, LFCA, PIPA, TFCA, AANP hierarchical elements under the library as shown in table 1 below.
Table 1 database element hierarchical schematic table
And (3) carrying out parallel calculation and merging on the same element layered data of the two framing databases and even more framing databases shown in the table to obtain a layer to obtain a merged database Database Union. Gdb, wherein the steps are shown in the following table 2:
TABLE 2 hierarchical representation of elements after merger
S2, reversely calculating and generating the framing border line elements among all the pictures of the data area according to the working area and the data standard scale and the national standard scale division principle to obtain a line element set DATASETLINE. As shown in fig. 2, the panels I49G034010 and I49G034011 are connected, and it can be seen from fig. 2 that the two panels are adjacent to each other, so that the panel boundary line AB at the connection is calculated.
And S3, layering elements after traversing and merging are executed in parallel, and edge splicing of the boundary elements of the graph is carried out according to the following steps S31-S34, so that entity logic is unified. The specific process can be as follows:
s31, traversing the framing border element set DATASETLINE.
S32, space searching of the map border entity elements is carried out, and the edge element set is obtained.
And generating a boundary buffer area by taking the traversed current framing borderline element as the center and setting the buffer distance on two sides, and performing space searching to extract geographic element entities which are overlapped with the buffer area in the combined element layers to obtain a borderline element set DataSetH.
S33, performing edge entity matching on the entity elements in the searched edge element set DataSetH.
In an alternative embodiment of the invention, the bordering entity matches include attribute matches and spatial matches. When the entity elements in the element set are subjected to edge entity matching, the same geographic entity element can be obtained through attribute matching and space matching. The method specifically comprises the steps of carrying out attribute matching on entity elements in element sets to find out entities with the same attribute, judging whether the found entities with the same attribute spatially belong to the same geographic entity through space matching, and matching the entities into the same entity element if the entities belong to the same geographic entity. For example, the bordering element set DataSetH contains a plurality of elements of the jing geographic entity, belonging to two graphs of drawing frames I49G034010 and I49G034011, respectively, and matches the same entity element by an element that can be named "jing" by a river name and a road name, as shown in fig. 3.
S34, executing entity edge processing on the entity elements successfully matched by the entity matching. And (3) carrying out graphic edge splicing processing on the successfully matched entities to combine the successfully matched entities into an entity element, and finishing edge splicing of the entities at the graph and the picture joint.
In an alternative embodiment of the invention, entity attribute matching, namely judging whether elements of the same hierarchical data at the joint of the framing graphs belong to the same entity in terms of attributes, mainly classifying rules according to positioning basis, water system, residential land and facilities, traffic, pipelines, boundaries and government areas, landforms, vegetation and soil eight-big data categories, judging attributes according to rules in a table as shown in an entity attribute matching rule table, and matching element attributes meeting rule requirements through, and carrying out entity space matching.
Table 3 entity attribute matching rule table
In an alternative embodiment of the present invention, entity space matching, that is, whether two identical type elements successfully matched at the joint of the frame images belong to the same entity is determined spatially, and the three types of entity matching mainly include three types of entity matching of point entity, line entity and plane entity, where the three types of matching rules are shown in the entity space matching rule table. The matching of the point entities is to judge the point distance of two point elements, wherein the point distance is smaller than the solid distance of 0.5mm on the graph, the two point elements are judged to be the same point entity, the actual distance of 0.5mm on the graph is equal to 0.5 x the frame scale denominator mm, the two point elements are converted into meters and used, the end point distance of the two line elements near the frame joint is judged to be the same line entity, the two line elements with the distance smaller than the solid distance of 0.6mm on the graph are judged to be the same line entity, the end point distance of the two surface elements at the south and north of the edge at the dividing line of the same graph is judged, and the two surface elements with the end point distances of the south and the north of the edge smaller than the solid distance of 0.8mm on the graph are judged to be the same surface entity.
Table 4 entity space matching rule table
In an alternative embodiment of the invention, executing the entity edge processing on the entity elements successfully matched by the entity matching comprises the step of carrying out the graph edge processing on the entity elements successfully matched by the entity matching to combine the entity elements into a new entity element so as to finish the edge of the entity at the picture joint.
The solid graph edge processing is divided into three types, namely point solid edge, line solid edge and surface solid edge, which are respectively shown in fig. 4-6. The concrete edge bonding treatment method is shown in the following table 5.
Table 5 physical edge processing method induction table
The embodiment of the invention also provides a multi-layer chart merging device based on the space and attribute multi-condition judgment, which comprises a processor and a memory storing program instructions, and is characterized in that the processor is configured to execute the multi-layer chart merging method based on the space and attribute multi-condition judgment in the embodiment when executing the program instructions.
The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to the present invention may occur to one skilled in the art without departing from the principles of the present invention and are intended to be within the scope of the present invention.
Claims (9)
1. A multi-layer graph merging method based on space and attribute multi-condition judgment is characterized by comprising the following steps:
batch reading the layered data of each element in a plurality of databases, and calculating the space range rectangle of all the framing vector data layers;
merging the layered elements in parallel, and merging the layered data of the same element in a plurality of databases into one layer in parallel;
Generating a framing boundary line element layer, and calculating framing line elements of the generated data area according to the working area and the data standard scale and the national standard scale division rule;
performing parallel execution, traversing and layering the elements after combination, and carrying out edge splicing on the boundary elements of the picture, so as to realize unification of entity logic;
space searching of the map boundary entity elements generates element sets;
Edge entity matching is carried out on the entity elements in the element set;
And executing entity edge processing on the entity elements successfully matched by the entity matching.
2. The method of claim 1, wherein spatially searching the map border entity elements comprises:
Traversing the framing boundary line, taking the boundary line as the center, buffering two sides, setting distances, generating a boundary buffer area, and performing space searching and extraction on geographic element entities overlapped with the buffer area in the combined element layers to obtain an element set DataSetH.
3. The method of claim 1, wherein the bordering entity matches include attribute matches and space matches;
Edge entity matching is carried out on the entity elements in the element set, wherein the edge entity matching comprises the steps of carrying out attribute matching on the entity elements in the element set, and finding out entities with the same attribute;
And judging whether the found entities with the same attribute belong to the same geographic entity in space through space matching, and if so, matching the entities into the same entity element.
4. A method according to claim 3, wherein the attribute matching is performed by regular classification according to location basis, water system, residential land and facilities, traffic, pipelines, boundaries and politics, landforms, vegetation and earth eight data categories.
5. A method according to claim 3, wherein the spatial matching is performed by three types of entity matching, namely a point entity, a line entity and a plane entity.
6. The method of claim 5, wherein the step of determining the position of the probe is performed,
The matching of the point entities is to judge the point distance of the two point elements, wherein the two point elements with the point distance smaller than the field distance of 0.5mm on the graph are judged to be the same point entity, and the actual distance of 0.5mm on the graph is equal to 0.5 x the frame scale denominator mm, and the two point elements are converted into meters for use;
The matching of the line entities is to judge the endpoint distance of the two line elements near the framing joint, and the two line elements with the distance smaller than the field distance of 0.6mm on the graph are judged to be the same line entity;
The matching of the surface entities is to judge the end point distance of the two surface elements at the south and north sides of the boundary of the same picture, and the two surface elements with the distance of the two end points of the south and north sides being smaller than the field distance of 0.8mm on the picture are judged to be the same surface entity.
7. A method according to claim 3, wherein performing entity-bordering processing on entity elements for which entity matching is successful comprises:
And carrying out graphic edge connection processing on the entity elements successfully matched by the entity to combine the entity elements into a new entity element, and completing edge connection of the entity at the joint of the drawing.
8. The method of claim 7, wherein the physical edge processing comprises a point physical edge, a line physical edge, and a face physical edge.
9. A multi-layer map merging device based on spatial and attribute multi-condition judgment, comprising a processor and a memory storing program instructions, wherein the processor is configured to perform the multi-layer map merging method based on spatial and attribute multi-condition judgment as claimed in any one of claims 1 to 7 when executing the program instructions.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202510030040.9A CN120031713A (en) | 2025-01-08 | 2025-01-08 | Multi-layer map merging method and device based on spatial and attribute multi-condition judgment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202510030040.9A CN120031713A (en) | 2025-01-08 | 2025-01-08 | Multi-layer map merging method and device based on spatial and attribute multi-condition judgment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN120031713A true CN120031713A (en) | 2025-05-23 |
Family
ID=95733199
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202510030040.9A Pending CN120031713A (en) | 2025-01-08 | 2025-01-08 | Multi-layer map merging method and device based on spatial and attribute multi-condition judgment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN120031713A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030227899A1 (en) * | 2002-06-11 | 2003-12-11 | Mccann Thomas Matthew | Methods and systems for automatically provisioning address translation information in a mobile services node address translation database |
| CN115187694A (en) * | 2022-06-24 | 2022-10-14 | 中汽创智科技有限公司 | Map sheet edge connecting method, device, equipment and storage medium |
| CN118747350A (en) * | 2024-06-14 | 2024-10-08 | 自然资源部第一地理信息制图院(陕西省第六测绘地理信息工程院) | A universal data fusion method and system based on massive vector data |
| CN118885447A (en) * | 2024-09-29 | 2024-11-01 | 天津市城市规划设计研究总院有限公司 | A method of converting road network CAD data to GIS data based on spatial capture |
| CN119027697A (en) * | 2024-10-28 | 2024-11-26 | 安徽省测绘档案资料馆(安徽省基础测绘信息中心) | A multi-granularity geographic entity matching method, device, equipment and medium |
-
2025
- 2025-01-08 CN CN202510030040.9A patent/CN120031713A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030227899A1 (en) * | 2002-06-11 | 2003-12-11 | Mccann Thomas Matthew | Methods and systems for automatically provisioning address translation information in a mobile services node address translation database |
| CN115187694A (en) * | 2022-06-24 | 2022-10-14 | 中汽创智科技有限公司 | Map sheet edge connecting method, device, equipment and storage medium |
| CN118747350A (en) * | 2024-06-14 | 2024-10-08 | 自然资源部第一地理信息制图院(陕西省第六测绘地理信息工程院) | A universal data fusion method and system based on massive vector data |
| CN118885447A (en) * | 2024-09-29 | 2024-11-01 | 天津市城市规划设计研究总院有限公司 | A method of converting road network CAD data to GIS data based on spatial capture |
| CN119027697A (en) * | 2024-10-28 | 2024-11-26 | 安徽省测绘档案资料馆(安徽省基础测绘信息中心) | A multi-granularity geographic entity matching method, device, equipment and medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR102510809B1 (en) | A method and a device, an apparatus and a storage medium for merging building block data | |
| CN111209915B (en) | Three-dimensional image synchronous recognition and segmentation method based on deep learning | |
| EP4116935B1 (en) | High-definition map creation method and device, and electronic device | |
| WO2024077812A1 (en) | Single building three-dimensional reconstruction method based on point cloud semantic segmentation and structure fitting | |
| Chen et al. | Automatically and accurately conflating orthoimagery and street maps | |
| US20120133639A1 (en) | Strip panorama | |
| CN107885790B (en) | A Multi-factor Automatic Update Method for Road Spatial Networks | |
| CN113010793A (en) | Method, device, equipment, storage medium and program product for map data processing | |
| CN111723798A (en) | A Multi-Instance Natural Scene Text Detection Method Based on Relevance Hierarchical Residuals | |
| CN111854758A (en) | Indoor navigation map conversion method and system based on building CAD (computer-aided design) drawing | |
| CN110914870A (en) | Annotation generation for image networks | |
| CN113724279A (en) | System, method, equipment and storage medium for automatically dividing traffic cells into road networks | |
| CN116630830A (en) | Method and system for presenting full-space information flow of power pipeline based on oblique photography | |
| CN102831169B (en) | Plane figure relation determining method and system in geographical information system | |
| US12190445B2 (en) | High-precision map construction method, apparatus and electronic device | |
| CN120031713A (en) | Multi-layer map merging method and device based on spatial and attribute multi-condition judgment | |
| Siriba et al. | Geometric quality enhancement of legacy graphical cadastral datasets through thin plate splines transformation | |
| CN116067391B (en) | Path generation method and system for multi-map information fusion | |
| CN115797415A (en) | Digital processing method and device for historical paper map | |
| CN116721226A (en) | Real estate unit dynamic modeling and ownership information association method based on real-life three-dimensional scene | |
| CN113886597B (en) | A method for extending the layout of a graph | |
| Chiang et al. | Generating named road vector data from raster maps | |
| Zhang et al. | Bidimensional regression and order relations: evaluating sketch maps with various spatial knowledge and distortions | |
| CN120707977A (en) | Cluster point cloud driven underground parking garage plane structure extraction and update method | |
| CN108986035B (en) | Digital image correction method containing two rock cores |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |