CN112396673A - Automatic processing method for space element geometric topology - Google Patents

Automatic processing method for space element geometric topology Download PDF

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CN112396673A
CN112396673A CN202011377053.7A CN202011377053A CN112396673A CN 112396673 A CN112396673 A CN 112396673A CN 202011377053 A CN202011377053 A CN 202011377053A CN 112396673 A CN112396673 A CN 112396673A
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CN112396673B (en
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陈良超
周智勇
刘昌振
胡开全
马红
张燕
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Chongqing Institute Of Surveying And Mapping Science And Technology Chongqing Map Compilation Center
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Abstract

The invention discloses a method for automatically processing space element geometric topology, which comprises the following steps: firstly, acquiring mapping data, wherein the mapping data comprises geometric data corresponding to ground features; then, classifying according to the attribute characteristics of the geometric data, determining processing parameters corresponding to the geometry of each object, and constructing different types of data sets, wherein the processing parameters comprise priority and search distance; and finally, sequentially processing the geometric data in the data set according to the priority by adopting a set processing method, wherein the processing method comprises the following steps: firstly traversing geometric data in a data set, determining a reference geometry corresponding to the geometry to be processed according to a search distance, constructing a reference data set according to the geometric data corresponding to the reference geometry, then traversing the reference data set, determining a target geometry corresponding to the geometry to be processed, and editing the geometry to be processed according to the geometric data corresponding to the target geometry.

Description

Automatic processing method for space element geometric topology
Technical Field
The invention relates to the field of data mapping data production, in particular to a space element geometric topology automatic processing method.
Background
The mapping data includes geometric data such as a plurality of points and lines, which need to meet practical situations and strict topological requirements, such as that nodes of electric wires should coincide with electric poles, the lines cannot have false nodes and suspension points, and the like. Comparing the results acquired by the model stereo acquisition or the results actually measured or drawn by field work, these requirements are not necessarily satisfied, and after data acquisition is needed, geometric data such as acquired points, lines and the like are edited according to actual conditions, so that the final results satisfy the requirements.
Mapping data includes many different kinds of geometric data, such as basic scale topographical mapping involving 8 large categories, approaching 500 categories; basic geographic national condition monitoring contents are divided into 10 primary classes, 59 secondary classes and 143 tertiary classes; the third homeland survey work is classified into 12 primary classes and 53 secondary classes, and the editing processes of different types of geometric data also have differences. In the prior art, surveying and mapping data are edited mainly by professional surveying and mapping personnel, so that the investment of human resources is large and errors are easy to occur.
Disclosure of Invention
In order to solve the technical problems, the invention provides an automatic processing method of spatial element geometric topology, which can automatically edit and process the mapping data, reduce the workload of manual intervention and improve the processing efficiency of the geometric data of the midpoint and the line of the mapping data.
The technical scheme is as follows:
in a first aspect, there is provided an automatic processing method for spatial element geometric topology, which is used for computer processing mapping data, and comprises:
acquiring mapping data, wherein the mapping data comprises geometric data corresponding to the ground object;
classifying according to the attribute characteristics of the geometric data, constructing different types of data sets, and determining processing parameters corresponding to various geometric data in the data sets, wherein the processing parameters comprise priority and search distance;
adopting a set processing method to sequentially process the geometric data in the data set according to the priority, wherein the processing method comprises the following steps:
traversing geometric data in the data set, determining a reference geometry corresponding to the geometry to be processed according to the search distance, and constructing a reference data set according to the geometric data corresponding to the reference geometry;
and traversing the reference data set, determining the target geometry corresponding to the geometry to be processed, and editing the geometry to be processed according to the geometric data corresponding to the target geometry.
With reference to the first aspect, in a first implementable manner of the first aspect, the reference data set is constructed by:
determining a search range corresponding to the geometry to be processed according to the search distance corresponding to the geometry to be processed;
traversing geometric data in the data set, and searching the object geometry in the search range as reference geometry;
a reference data set is constructed from the geometric data corresponding to the reference geometry.
With reference to the first aspect or the first implementable manner of the first aspect, in a second implementable manner of the first aspect, the determining a target geometry corresponding to the geometry to be processed includes: and traversing the reference data set, and searching a reference geometry with the distance between the reference geometry and the geometry to be processed meeting a threshold value condition as a target geometry.
With reference to the first aspect or the first or second implementable manner of the first aspect, in a third implementable manner of the first aspect, the editing the geometry to be processed according to the geometry data corresponding to the target geometry includes:
determining element points needing to be processed in the geometry to be processed and the target geometry corresponding to the element points according to the corresponding geometric data of the target geometry and the geometry to be processed;
determining a processing mode of the element points according to the element points and the distribution positions of the target geometry corresponding to the element points;
and editing the geometric data of the geometry to be processed according to the processing mode.
With reference to the third implementable manner of the first aspect, in a fourth implementable manner of the first aspect, when the same element point corresponds to multiple target points, a target geometry closest to the element point is used as an optimal target geometry for editing the geometry to be processed.
With reference to the third implementable manner of the first aspect, in a fifth implementable manner of the first aspect, when the same element point corresponds to multiple target points, the target geometry with the highest priority is used as the optimal target geometry for editing the geometry to be processed.
With reference to the third implementable manner of the first aspect, in a sixth implementable manner of the first aspect, when the same element point corresponds to multiple target points, a target geometry with the highest priority is used, and a target geometry closest to the element point is used as an optimal target geometry for editing the geometry to be processed.
In a second aspect, a storage medium is provided, storing a computer program that performs the steps of the data processing method described above to process mapping data.
Has the advantages that: by adopting the automatic processing method for the geometric topology of the space elements, the mapping data can be automatically edited, the workload of manual intervention is reduced, and the processing efficiency of the geometric data such as points and lines is improved.
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FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a flow chart of the present invention for constructing a reference data set;
FIG. 3 is a flow chart of the present invention for processing a geometry to be processed;
FIG. 4 is a flow chart of editing a geometry to be processed according to a target geometry in accordance with the present invention.
Detailed Description
The invention is further illustrated by the following examples and figures.
A flow chart of a method for automated processing of spatial element geometric topology as shown in fig. 1, the processing method for computer processing mapping data, comprising:
step 1, a computer acquires mapping data, wherein the mapping data comprises corresponding geometric data about a ground feature, and the geometric data can be point, line or plane data comprising attribute features and geometric features. The geometric features include geometric location distributions, such as geometric distribution location coordinates. The attribute features include geometrical classifications such as water systems, residential areas and facilities, traffic, pipelines, boundaries, geomorphology, vegetation, and the like.
And 2, classifying according to the attribute characteristics of the geometric data, determining processing parameters corresponding to the geometry of each object, and constructing different types of data sets, wherein the processing parameters comprise priorities and search distances.
The computer can store various processing parameters corresponding to the geometry in advance, and after the computer acquires the mapping data, the corresponding processing parameters can be determined according to the attribute characteristics in the geometry data. The processing parameters can be set manually according to natural rules.
The computer can be set according to the relevance between geometric data, such as water systems, residential areas and facilities, traffic, vegetation and the like which are located on the ground surface, and the mutual influence can exist, so that the geometric data can be classified into one category. The self-formed connection system of the pipeline, such as the connection of an electric wire or a communication line through an electric pole, has no influence on water systems, residential areas, facilities, traffic and vegetation on the earth surface, and belongs to another type.
The priority can be set according to the editable degree of the geometric data, if the frame belongs to the positioning basis and cannot be modified, the priority is highest. The geometric data corresponding to the water system and the residential area are planar ground objects, the acquisition precision is high, and the geometric data cannot be randomly modified, so that the priority is high. The traffic connection residents form a road network, and can be edited, wherein the priority is inferior to the residents ' land and the water system, the vegetation is attached to the residents ' land and the traffic road network, and the priority is inferior to the water system, the residents ' land and the traffic.
And 3, adopting a set processing method to sequentially process the geometric data in the data set according to the priority, wherein the geometric data in the data set only participates in the processing of other geometric data in the same data set and does not participate in the processing of other data sets, so that errors caused by irrelevant geometric participation in data processing can be avoided, and meanwhile, the data processing capacity of the computer is reduced.
In addition, since the feature with high positioning accuracy such as a water system and a residential area is used, the corresponding geometric data itself is not processed, and only the other geometric data is processed. Therefore, before traversing the geometric data, whether the geometry to be processed belongs to a water system, a residential area and the like or geometric data such as a surface and the like can be judged according to the attribute characteristics of the geometric data, if so, the next geometric data can be directly processed without processing the data, so that unnecessary data processing can be reduced, and computer resources can be saved.
As shown in fig. 3, the processing method includes:
and 3-1, traversing other geometric data in the data set except the geometric data corresponding to the geometry to be processed, determining the reference geometric data corresponding to the geometry to be processed according to the search distance, and constructing the reference data set according to the geometric data corresponding to the reference geometric data.
As shown in fig. 2, the specific steps include:
and 3-1-1, determining a search range corresponding to the geometry to be processed according to the search distance corresponding to the geometry to be processed.
3-1-2, traversing geometric data in the data set, and searching the object geometry in the search range as reference geometry;
and 3-1-3, constructing a reference data set according to the geometric data corresponding to the reference geometry.
Specifically, the geometric data includes distribution position coordinates, and according to the distribution position coordinates in the geometry to be processed and the corresponding search distance thereof, range coordinates of a search range corresponding to the geometry to be processed can be determined, and by traversing the distribution position coordinates of other geometric data in the same data set, if the distribution position coordinates fall within the range coordinates, the geometry corresponding to the geometric data can be determined as the reference geometry.
And 3-2, traversing the reference data set, and searching a reference geometry with the distance between the reference geometry and the geometry to be processed meeting a threshold value condition as a target geometry. The threshold condition corresponding to the geometry to be processed is artificially set according to a natural law, for example, the threshold condition of a road is less than or equal to 0.5 m, and the threshold condition of a vegetation field boundary is less than or equal to 1 m. If the distance between the other reference geometry and the road is less than or equal to 0.5 meters, the reference geometry may be the target geometry of the road.
And 3-3, editing the geometry to be processed according to the geometry data corresponding to the target geometry.
As shown in fig. 4, the method for editing the geometry to be processed includes:
and 3-2-1, determining the element points needing to be processed in the geometry to be processed and the target geometry corresponding to the element points according to the corresponding geometric data of the target geometry and the geometry to be processed. And calculating the distance between each element point in the geometry to be processed and the target geometry through the geometric data corresponding to the geometry to be processed. And if the distance between the element point and the target geometry meets the threshold condition, the data corresponding to the element point needs to be edited. When the same element point needing to be processed corresponds to a plurality of targets, the target geometry closest to the element point is used as the optimal target geometry for editing the geometry to be processed.
Step 3-2-2, determining a processing mode of the element points according to the element points and the distribution positions of the object geometry corresponding to the element points, wherein the processing mode comprises cutting, extending, moving intermediate nodes and the like, and the processing mode comprises the following steps:
cutting, wherein correspondingly, the distribution position coordinates of the geometry to be processed and the target geometry are overlapped, namely, the distance between the element point and the target geometry is less than 0 and does not meet the topological requirement, and the processing mode is to delete the element point data falling into the geometric range of the target in the geometry to be processed;
and extending, wherein the corresponding position of the geometry to be processed and the target geometry has a certain distance, namely the distance between the element point and the target geometry is greater than 0, and the processing mode is that the element point is moved to the target geometry, so that the distance between the element point and the target geometry meets the topological requirement.
And moving the intermediate node, wherein the intermediate node corresponding to the geometry to be processed has a certain distance with the target geometry, the distance is within the threshold condition, and the processing mode is to move the intermediate node to the target geometry.
And 3-2-3, editing geometric data of the geometry to be processed according to a processing mode.
And 3-3, updating the data set according to the processed geometric data, using the updated data set for the geometric processing to be processed of the next priority, repeating the steps until all the geometric data in the data set are processed, generating a new data set, and reconstructing the surveying and mapping data according to the new data set by the computer.
A storage medium stores a computer program that executes the steps of the data processing method described above to process mapping data.
Finally, it should be noted that the above-mentioned description is only a preferred embodiment of the present invention, and those skilled in the art can make various similar representations without departing from the spirit and scope of the present invention.

Claims (8)

1. An automatic processing method for geometrical topology of spatial elements, which is used for computer processing mapping data, and is characterized by comprising the following steps:
acquiring mapping data, wherein the mapping data comprises geometric data corresponding to the ground object;
classifying according to the attribute characteristics of the geometric data, constructing different types of data sets, and determining processing parameters corresponding to various geometric data in the data sets, wherein the processing parameters comprise priority and search distance;
adopting a set processing method to sequentially process the geometric data in the data set according to the priority, wherein the processing method comprises the following steps:
traversing geometric data in the data set, determining a reference geometry corresponding to the geometry to be processed according to the search distance, and constructing a reference data set according to the geometric data corresponding to the reference geometry;
and traversing the reference data set, determining the target geometry corresponding to the geometry to be processed, and editing the geometry to be processed according to the geometric data corresponding to the target geometry.
2. The method for automatically processing the geometric topology of a spatial element according to claim 1, wherein: the reference data set is constructed using the following method:
determining a search range corresponding to the geometry to be processed according to the search distance corresponding to the geometry to be processed;
traversing geometric data in the data set, and searching the object geometry in the search range as reference geometry;
a reference data set is constructed from the geometric data corresponding to the reference geometry.
3. The method for automatically processing the geometric topology of the spatial elements according to claim 1 or 2, wherein: the determining the target geometry corresponding to the geometry to be processed comprises: and traversing the reference data set, and searching a reference geometry with the distance between the reference geometry and the geometry to be processed meeting a threshold value condition as a target geometry.
4. A method for automatic processing of spatial element geometric topology according to any of claims 1-3, characterized by: the editing the geometry to be processed according to the geometry data corresponding to the target geometry comprises the following steps:
determining element points needing to be processed in the geometry to be processed and the target geometry corresponding to the element points according to the corresponding geometric data of the target geometry and the geometry to be processed;
determining a processing mode of the element points according to the element points and the distribution positions of the target geometry corresponding to the element points;
and editing the geometric data of the geometry to be processed according to the processing mode.
5. The method of claim 4, wherein the spatial element geometric topology is automatically processed by: when the same element point corresponds to a plurality of targets, the target geometry closest to the element point is used as the optimal target geometry for editing the geometry to be processed.
6. The method of claim 4, wherein the spatial element geometric topology is automatically processed by: when the same element point corresponds to a plurality of targets, the target geometry with the highest priority is used as the optimal target geometry for editing the geometry to be processed.
7. The method of claim 4, wherein the spatial element geometric topology is automatically processed by: when the same element point corresponds to a plurality of targets, the target geometry with the highest priority is used, and the target geometry closest to the element point is used as the optimal target geometry for editing the geometry to be processed.
8. A storage medium storing a computer program, characterized in that: the computer program performs the steps of the data processing method according to any of claims 1-7 for processing the mapping data.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102360387A (en) * 2011-10-19 2012-02-22 浙江大学 Method for outputting geometric data of facet element of vector data transfer format of topology 1
CN106844977A (en) * 2017-01-23 2017-06-13 重庆市勘测院 A kind of town road BIM designs a model and GIS data integrated approach
US20200051278A1 (en) * 2018-08-10 2020-02-13 Canon Kabushiki Kaisha Information processing apparatus, information processing method, robot system, and non-transitory computer-readable storage medium
US20200132477A1 (en) * 2018-10-29 2020-04-30 Aptiv Technologies Limited Automatic annotation of environmental features in a map during navigation of a vehicle

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102360387A (en) * 2011-10-19 2012-02-22 浙江大学 Method for outputting geometric data of facet element of vector data transfer format of topology 1
CN106844977A (en) * 2017-01-23 2017-06-13 重庆市勘测院 A kind of town road BIM designs a model and GIS data integrated approach
US20200051278A1 (en) * 2018-08-10 2020-02-13 Canon Kabushiki Kaisha Information processing apparatus, information processing method, robot system, and non-transitory computer-readable storage medium
US20200132477A1 (en) * 2018-10-29 2020-04-30 Aptiv Technologies Limited Automatic annotation of environmental features in a map during navigation of a vehicle

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
RONGHUA YANG等: "A Global Registration Algorithm of the Single-Closed Ring Multi-Stations Point Cloud", THE INTERNATIONAL ARCHIVES OF THE PHOTOGRAMMETRY, REMOTE SENSING AND SPATIAL INFORMATION SCIENCES, pages 2093 - 2100 *
吕海洋;周卫;盛业华;李佳;张思阳;: "拓扑保形的矢量地理数据几何脱密方法", 中国矿业大学学报, no. 03, pages 203 - 209 *
菅建华;蔡志刚;: "基于省级基础地理信息数据库制图的关键技术研究", 测绘通报, no. 07, pages 53 - 56 *
陈良超;陈光;薛梅;: "新型三维测绘地理信息产品集成建库研究技术", 地理信息世界, no. 04, pages 94 - 99 *

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