CN114169771A

CN114169771A - Region dividing method and device, electronic equipment and storage medium

Info

Publication number: CN114169771A
Application number: CN202111503542.7A
Authority: CN
Inventors: 黎明洋; 傅昆
Original assignee: Shell Housing Network Beijing Information Technology Co Ltd
Current assignee: Shell Housing Network Beijing Information Technology Co Ltd
Priority date: 2021-12-09
Filing date: 2021-12-09
Publication date: 2022-03-11

Abstract

The embodiment of the disclosure discloses a region division method and device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring regional road network data of a region to be divided; triangulating road network node data in the regional road network data to obtain a subdivision result; merging triangles in the subdivision results based on road data in the regional road network data to obtain at least one minimum connected block, wherein each minimum connected block is a closed block formed by roads; and mapping each interest point of the area to be divided into each minimum connected block to obtain a division result of the area to be divided. The block boundary disclosed by the invention is the road constraint, is attached to the road, avoids dividing a real geographic element into a plurality of blocks, realizes more effective division of urban areas, and solves the problems of poor division effectiveness and the like caused by easily dividing a real geographic element into a plurality of blocks.

Description

Region dividing method and device, electronic equipment and storage medium

Technical Field

The disclosure relates to a region dividing method and apparatus, an electronic device, and a storage medium.

Background

With the development of the internet, electronic commerce based on the network is also popularized in daily life of users, and huge user consumption groups and articles with geographic attributes bring challenges to the effectiveness of city region division. In the application of the existing urban area division, grid division is generally performed according to standard rules, for example, in a taxi taking scene, the urban area is divided by taking a regular hexagon as a minimum unit, but the existing grid division mode is easy to divide a real geographic element into a plurality of blocks, for example, a floor is divided into a plurality of blocks, so that the division effectiveness is poor.

Disclosure of Invention

The embodiment of the disclosure provides a region division method and device, electronic equipment and a storage medium, so as to solve the problems of poor region division effectiveness and the like.

In an aspect of the embodiments of the present disclosure, a method for dividing a region is provided, including: acquiring regional road network data of a region to be divided, wherein the regional road network data comprises road network node data of the region to be divided and road data among road network nodes; triangulating the road network node data in the regional road network data to obtain subdivision results, wherein the subdivision results comprise a plurality of triangles taking each road network node as a vertex; merging triangles in the subdivision results based on road data in the regional road network data to obtain at least one minimum connected block, wherein each minimum connected block is a closed block formed by roads; and mapping each interest point of the area to be divided into each minimum connected block to obtain a division result of the area to be divided.

In an embodiment of the present disclosure, the acquiring regional road network data of regions to be divided includes: acquiring a coordinate point set of each road of a region to be divided and an intersection point between the roads; constructing a regional road network graph of the region to be divided by taking intersection points among roads as road network nodes and coordinate point sets of the roads as edges; and taking the regional road network graph as the regional road network data.

In an embodiment of the present disclosure, after constructing the regional road network map of the region to be divided by using intersection points between roads as road network nodes and using coordinate point sets of each road as edges, the method further includes: traversing the regional road network graph, removing invalid road network nodes, and connecting adjacent edges of the road network nodes to obtain a preprocessed first regional road network graph; and taking the first regional network graph as the regional network data.

In an embodiment of the present disclosure, the triangulating the road network node data in the regional road network data to obtain a subdivision result includes: and triangulating the road network node data in the regional road network data based on a Delaunay triangulation algorithm to obtain a subdivision result.

In an embodiment of the present disclosure, the merging triangles in the subdivision result based on the road data in the regional road network data to obtain at least one minimum connected block includes: traversing the triangles in the subdivision result in a depth-first traversal mode, judging whether the sides of the first triangles have corresponding roads or not according to the first triangles and the road data in the regional road network data, and judging whether the second sides of the adjacent triangles of the first sides have corresponding roads or not if the first sides of the first triangles do not have corresponding roads; if the first edge has a corresponding road, continuously judging the next edge of the first edge in the first triangle, and so on until returning to the initial edge of the initial triangle to obtain a first triangle group needing to be merged; then, the steps are carried out on the second triangles except the obtained triangle group needing to be merged, and the second triangle group needing to be merged is obtained; by analogy, at least one triangle group needing to be merged is obtained; and removing the edges of the roads which do not exist in the triangle groups to be merged, so as to realize the merging of the triangle groups and obtain the corresponding minimum connected blocks.

In an embodiment of the present disclosure, the mapping each interest point of the region to be divided into each minimum connected block to obtain a division result of the region to be divided includes: acquiring the center point coordinates of each minimum connected block; for a first interest point in the region to be divided, determining the distance between the first interest point and the center point of each minimum connected block based on the coordinate of the first interest point and the coordinate of the center point of each minimum connected block; determining the minimum connected block to which the first interest point belongs according to the distance between the first interest point and the center point of each minimum connected block; and obtaining the division result of the area to be divided based on the minimum connected block to which each interest point belongs.

In an embodiment of the present disclosure, after mapping each interest point of a region to be divided into each minimum connected block and obtaining a division result of the region to be divided, the method further includes: classifying the minimum connected blocks in the division result based on a preset classification rule to obtain a classification result; and determining the region attribute corresponding to each minimum connected block based on the classification result.

In an embodiment of the present disclosure, the classifying the minimum connected block in the division result based on a preset classification rule to obtain a classification result includes: acquiring feature data of each minimum connected block based on the interest points included in each minimum connected block; clustering the characteristic data of each minimum connected block by adopting a preset clustering algorithm to obtain a clustering result; and taking the clustering result as the classification result.

In another aspect of the embodiments of the present disclosure, there is provided an area dividing apparatus including: the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring regional road network data of a region to be divided, and the regional road network data comprises road network node data of the region to be divided and road data among road network nodes; the first processing module is used for triangulating the road network node data in the regional road network data to obtain subdivision results, and the subdivision results comprise a plurality of triangles taking each road network node as a vertex; the second processing module is used for merging the triangles in the subdivision result based on the road data in the regional road network data to obtain at least one minimum connected block, and each minimum connected block is a closed block formed by roads; and the third processing module is used for mapping each interest point of the area to be divided into each minimum connected block to obtain the division result of the area to be divided.

In an embodiment of the present disclosure, the first obtaining module includes: the system comprises a first acquisition unit, a second acquisition unit and a control unit, wherein the first acquisition unit is used for acquiring a coordinate point set of each road of an area to be divided and an intersection point between the roads; the first processing unit is used for constructing a regional road network map of the region to be divided by taking intersection points among roads as road network nodes and coordinate point sets of all the roads as edges; a second processing unit for using said regional network graph as said regional network data.

In an embodiment of the present disclosure, the first processing unit is further configured to traverse the regional road network graph, remove an invalid road network node, and connect adjacent edges of the road network node to obtain a preprocessed first regional road network graph; the second processing unit is further configured to use the first regional network graph as the regional network data.

In an embodiment of the present disclosure, the first processing module is specifically configured to: and triangulating the road network node data in the regional road network data based on a Delaunay triangulation algorithm to obtain a subdivision result.

In an embodiment of the present disclosure, the second processing module is specifically configured to: traversing the triangles in the subdivision result in a depth-first traversal mode, judging whether the sides of the first triangles have corresponding roads or not according to the first triangles and the road data in the regional road network data, and judging whether the second sides of the adjacent triangles of the first sides have corresponding roads or not if the first sides of the first triangles do not have corresponding roads; if the first edge has a corresponding road, continuously judging the next edge of the first edge in the first triangle, and so on until returning to the initial edge of the initial triangle to obtain a first triangle group needing to be merged; then, the steps are carried out on the second triangles except the obtained triangle group needing to be merged, and the second triangle group needing to be merged is obtained; by analogy, at least one triangle group needing to be merged is obtained; and removing the edges of the roads which do not exist in the triangle groups to be merged, so as to realize the merging of the triangle groups and obtain the corresponding minimum connected blocks.

In an embodiment of the present disclosure, the third processing module is specifically configured to: acquiring the center point coordinates of each minimum connected block; for a first interest point in the region to be divided, determining the distance between the first interest point and the center point of each minimum connected block based on the coordinate of the first interest point and the coordinate of the center point of each minimum connected block; determining the minimum connected block to which the first interest point belongs according to the distance between the first interest point and the center point of each minimum connected block; and obtaining the division result of the area to be divided based on the minimum connected block to which each interest point belongs.

In an embodiment of the present disclosure, the apparatus further includes: the fourth processing module is used for classifying the minimum connected blocks in the division result based on a preset classification rule to obtain a classification result; and the determining module is used for determining the area attribute corresponding to each minimum connected block based on the classification result.

In an embodiment of the present disclosure, the fourth processing module is specifically configured to: acquiring feature data of each minimum connected block based on the interest points included in each minimum connected block; clustering the characteristic data of each minimum connected block by adopting a preset clustering algorithm to obtain a clustering result; and taking the clustering result as the classification result.

According to a further aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium storing a computer program for executing the method according to any one of the above-mentioned embodiments of the present disclosure.

According to still another aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including: a processor; a memory for storing the processor-executable instructions; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any of the above embodiments of the present disclosure.

According to yet another aspect of the embodiments of the present disclosure, there is provided a computer program product comprising a computer program/instructions which, when executed by a processor, implement the method according to any of the above-mentioned embodiments of the present disclosure.

The area dividing method and device, the electronic device and the storage medium provided by the disclosure are characterized in that triangulation is adopted for dividing based on area road network data of an area to be divided, a divided minimum connected block is a minimum connected closed block formed by roads, a block boundary is road constraint, and the roads are attached, so that a real geographic element is prevented from being divided into a plurality of blocks, more effective division of urban areas is realized, and the problems of poor dividing effectiveness and the like caused by easily dividing a real geographic element into a plurality of blocks are solved.

The technical solution of the present disclosure is further described in detail by the accompanying drawings and examples.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description, serve to explain the principles of the disclosure.

The present disclosure may be more clearly understood from the following detailed description, taken with reference to the accompanying drawings, in which:

fig. 1 is an exemplary application scenario of the region division method provided by the present disclosure;

fig. 2 is a flowchart illustrating a region dividing method according to an exemplary embodiment of the present disclosure;

FIG. 3 is a flowchart of step 201 provided by an exemplary embodiment of the present disclosure;

FIG. 4 is an exemplary schematic diagram of a constructed graph provided by an exemplary embodiment of the present disclosure;

FIG. 5 is an exemplary schematic diagram of a regional network graph provided by an exemplary embodiment of the present disclosure;

FIG. 6 is a schematic diagram of a Delaunay triangulation provided by an exemplary embodiment of the present disclosure;

FIG. 7 is a flowchart of step 204 provided by an exemplary embodiment of the present disclosure;

fig. 8 is an exemplary flowchart of a region dividing method according to an exemplary embodiment of the present disclosure;

fig. 9 is a schematic structural diagram of a region dividing apparatus provided in an exemplary embodiment of the present disclosure;

fig. 10 is a schematic structural diagram of a first obtaining module provided in an exemplary embodiment of the present disclosure;

fig. 11 is a schematic structural diagram of an area dividing apparatus according to another exemplary embodiment of the present disclosure;

fig. 12 is a schematic structural diagram of an application embodiment of the electronic device of the present disclosure.

Detailed Description

Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.

It will be understood by those of skill in the art that the terms "first," "second," and the like in the embodiments of the present disclosure are used merely to distinguish one element from another, and are not intended to imply any particular technical meaning, nor is the necessary logical order between them.

It is also understood that in embodiments of the present disclosure, "a plurality" may refer to two or more and "at least one" may refer to one, two or more.

It is also to be understood that any reference to any component, data, or structure in the embodiments of the disclosure, may be generally understood as one or more, unless explicitly defined otherwise or stated otherwise.

In addition, the term "and/or" in the present disclosure is only one kind of association relationship describing an associated object, and means that three kinds of relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" in the present disclosure generally indicates that the former and latter associated objects are in an "or" relationship.

It should also be understood that the description of the various embodiments of the present disclosure emphasizes the differences between the various embodiments, and the same or similar parts may be referred to each other, so that the descriptions thereof are omitted for brevity.

Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.

The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses.

Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.

The disclosed embodiments may be applied to electronic devices such as terminal devices, computer systems, servers, etc., which are operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known terminal devices, computing systems, environments, and/or configurations that may be suitable for use with electronic devices, such as terminal devices, computer systems, servers, and the like, include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, networked personal computers, minicomputer systems, mainframe computer systems, distributed cloud computing environments that include any of the above, and the like.

Electronic devices such as terminal devices, computer systems, servers, etc. may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc. that perform particular tasks or implement particular abstract data types. The computer system/server may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices.

Fig. 1 is an exemplary application scenario of the region division method provided in the present disclosure.

In the housing field, in order to determine the attribute advantages of the building, it is generally necessary to know the characteristic attributes of the block where the building is located and the adjacent blocks, such as whether there is a school in the block, what school is in the block, whether there is a hospital, what hospital is in the block, whether traffic is convenient, and the like, so that more attribute advantages of the building can be provided for users, and users can be better attracted to watch the house, generate business opportunities, and the like. By utilizing the technical scheme provided by the disclosure, the block is a minimum communicated closed block formed by roads, the block boundary is road constraint and is attached to the roads, so that the real geographic element is prevented from being divided into a plurality of blocks, the urban area is effectively divided, and the problems of poor dividing effectiveness and the like caused by the fact that the real geographic element is easily divided into the plurality of blocks are solved. The method disclosed by the present disclosure may be implemented by a corresponding region dividing apparatus, which may be deployed on any implementable electronic device (such as a server), and the related personnel may trigger execution of the method disclosed by the present disclosure through a terminal device (such as a smartphone, a tablet, a desktop computer, etc. thereof). Optionally, the method disclosed by the present disclosure is not only applicable to the real estate field, but also applicable to any other field or scene in which a certain area needs to be divided.

Fig. 2 is a flowchart illustrating a region dividing method according to an exemplary embodiment of the present disclosure. The method comprises the following steps:

step 201, obtaining regional road network data of the region to be divided, wherein the regional road network data comprises road network node data of the region to be divided and road data among road network nodes.

The area to be divided can be an urban area or other areas needing to be divided, and can be specifically set according to actual requirements. The regional road network data is road network data of a region to be divided, and comprises road network node data of the region to be divided and road data among road network nodes, the road network nodes refer to intersections among roads, and the road network node data comprises coordinate data of the road network nodes, such as longitude and latitude coordinates of the road network nodes; road data between road network nodes is a set of coordinate points representing roads between road network nodes.

Step 202, triangulating the road network node data in the regional road network data to obtain a subdivision result, wherein the subdivision result comprises a plurality of triangles taking each road network node as a vertex.

The triangulation can be realized by any practicable triangulation algorithm, such as a Delaunay triangulation algorithm, and can be specifically set according to actual requirements.

The Delaunay triangulation algorithm is a preprocessing technique that is very important for numerical analysis (such as finite element analysis) and graphics, and is defined as follows:

triangulation: let V be a finite set of points (road network node set in this disclosure) in a two-dimensional real number domain, edge E be a closed line segment composed of points in the set of points as end points, and E be a set of E. Then a triangulation T ═ (V, E) of the set of points V is a plan G which satisfies the condition: a. edges in the plan view do not contain any points in the set of points, except for the endpoints; b. there are no intersecting edges; c. all the faces in the plan view are triangular faces, and the collection of all the triangular faces is the convex hull of the scatter set V. The Delaunay triangulation is a special triangulation, which is as follows:

delaunay edge: suppose an edge E (two endpoints are a and b) in E, and E is called a Delaunay edge if the following conditions are satisfied: a circle passes through two points a and b, and no other point in the point set V is contained in the circle (the maximum three points on the circle are in a common circle), which is also called a hollow circle characteristic.

Delaunay triangulation: if a triangulation T of the set of points V contains only Delaunay edges, the triangulation is referred to as a Delaunay triangulation.

In an optional example, any one of a flanging algorithm, a point-by-point interpolation algorithm, a segmentation and merging algorithm, a Bowyer-Watson algorithm, and the like in the Delaunay triangulation algorithm may be used to implement the subdivision, which is not limited in this embodiment.

And 203, merging the triangles in the subdivision result based on the road data in the regional road network data to obtain at least one minimum connected block, wherein each minimum connected block is a closed block formed by roads.

Specifically, since triangulation is performed on road network nodes, some edges may not actually have roads in triangles of a subdivision result, each edge belongs to at most two triangles, and sub-domains corresponding to two triangles to which each edge belongs belong to connected domains, triangles belonging to the connected domains need to be merged to obtain a closed minimum connected block formed by the roads, that is, the boundary of the minimum connected block is road constraint, so that divided blocks are attached to the roads, and different blocks only share one edge without overlapping.

And 204, mapping each interest point of the area to be divided into each minimum connected block to obtain a division result of the area to be divided.

Specifically, after the minimum connected block is determined, the boundary of the divided blocks is determined, and then other geographic elements (referred to as interest points) in the region to be divided are mapped into the minimum connected blocks, so that the division result of the region to be divided can be obtained, wherein the division result comprises the boundary (road) of each minimum connected block and the interest points in each minimum connected block. The points of interest may include coordinate points or sets of coordinate points corresponding to geographic elements such as schools, hospitals, cells, bus stations, and the like.

The area dividing method provided by the embodiment of the disclosure divides the area road network data based on the area to be divided based on triangulation, the divided minimum connected block is a minimum connected closed block formed by roads, the block boundary is road constraint, and is attached to the roads, so that a real geographic element is prevented from being divided into a plurality of blocks, the urban area is divided more effectively, and the problems of poor dividing effectiveness and the like caused by easily dividing the real geographic element into the plurality of blocks are solved.

In an optional example, fig. 3 is a schematic flowchart of step 201 provided in an exemplary embodiment of the present disclosure, and in this example, step 201 may specifically include the following steps:

in step 2011, the coordinate point sets of the roads in the region to be divided and the intersections between the roads are obtained.

Specifically, the coordinate point sets of the roads in the area to be divided and the intersections between the roads may be extracted based on an OpenStreetMap (OSM for short), which is an open-source map database, mainly including layers of highways, railways, water systems, water areas, boundaries, buildings, and the like, and includes global data.

Step 2012, the intersection points between the roads are used as road network nodes, and the coordinate point sets of the roads are used as edges to construct a regional road network graph of the region to be divided.

In an alternative example, the regional network graph may be visualized. Illustratively, fig. 4 is an exemplary diagram of a constructed graph provided by an exemplary embodiment of the present disclosure, in this example, a graph (graph) refers to a collection of vertices that are paired (connected) by a series of edges. Vertices are represented by circles and edges are the lines between the circles. The vertexes are connected through edges. Fig. 5 is an exemplary schematic diagram of a regional network graph provided in an exemplary embodiment of the present disclosure.

And step 2013, using the regional road network graph as regional road network data.

In an optional example, after constructing a regional road network map of the region to be divided by using the intersection points between the roads as road network nodes and using the coordinate point sets of the roads as edges, the method of the present disclosure further includes: traversing the regional road network graph, removing invalid road network nodes, and connecting adjacent edges of the road network nodes to obtain a preprocessed first regional road network graph; the first regional network graph is used as regional network data.

Specifically, the invalid road network node refers to a road network node in the constructed regional road network graph that does not actually meet the preset road network node rule, and the preset road network node rule may be set according to actual requirements, for example, the constructed regional road network graph may have a road network node degree smaller than 2, and the degree of the road network node is equal to 2 and the two roads connected by the road network node are parallel, the degree of the road network node refers to the number of the edges connected by the road network node, the degree is less than 2, the road network node is not the intersection point of the two roads and is considered as an invalid road network node, the intersection of the two roads has at least 2 edges, such as the L-shaped road opening degree is 2, the T-shaped road opening degree is 3, the intersection degree is 4, however, if the degree is 2 and the two roads are parallel, it means that the road network node is not the intersection of the two roads, and the two roads are two parts of the same road, then the road network node is considered to be an invalid road network node. The concrete judgment of whether the road network nodes are effective can be set according to actual requirements, and the disclosure is not limited.

According to the method and the device, the constructed regional road network graph is preprocessed, and invalid road network nodes are removed, so that invalid nodes are reduced, the effectiveness of regional road network data is improved, the number of Delaunay triangulation nodes is reduced, and the data processing efficiency is improved.

In an optional example, triangulating the road network node data in the regional road network data to obtain a subdivision result, includes: triangulation is carried out on road network node data in the regional road network data based on a Delaunay triangulation algorithm, and a triangulation result is obtained. In an exemplary embodiment, the road network node data in the regional road network data may be triangulated based on a point-by-point insertion algorithm of the Delaunay triangulation algorithm, and a triangulation result is obtained.

Specifically, the Delaunay triangulation process includes: firstly, constructing a maximum triangle and putting the maximum triangle into a triangle queue, so that all road network nodes in a point set of the road network nodes to be split fall into the triangle; secondly, inserting each road network node one by one, finding out triangles (called as the influence triangles of the insertion points) of which the circumscribed circles contain the insertion points in the triangle queues when each road network node is inserted, deleting the common edges of the influence triangles, connecting the insertion points with all vertexes of the influence triangles to form a plurality of new triangles taking the insertion points as the common vertexes, putting the new triangles into the triangle queues, completing the insertion of one point in the Delaunay triangle queues, and so on until all road network nodes are inserted, thus completing the triangulation of the area to be divided.

Exemplarily, fig. 6 is a schematic diagram of Delaunay triangulation provided in an exemplary embodiment of the present disclosure.

In an optional example, the merging triangles in the subdivision result based on the road data in the regional road network data in step 203 to obtain at least one minimum connected block includes: traversing triangles in the subdivision result by adopting a depth-first traversal mode, judging whether the sides of the first triangles have corresponding roads or not according to the first triangles and the road data in the regional road network data, and judging whether the second sides of the adjacent triangles of the first sides have corresponding roads or not if the first sides of the first triangles do not have corresponding roads; if the first edge has a corresponding road, continuously judging the next edge of the first edge in the first triangle, and so on until returning to the initial edge of the initial triangle to obtain a first triangle group needing to be merged; then, the steps are carried out on the second triangles except the obtained triangle group needing to be merged, and the second triangle group needing to be merged is obtained; by analogy, at least one triangle group needing to be merged is obtained; and removing the edges of the triangle groups which do not have the corresponding roads in the triangle groups to be combined, realizing the combination of the triangle groups and obtaining the corresponding minimum connected block.

Specifically, each triangle in the triangulation consists of a vertex and an edge, the result of the triangulation is only to divide the area to be divided into a plurality of small blocks based on the road network nodes, and no road constraint is utilized. Specifically, the triangles in the subdivision result are traversed with depth first, whether a real road exists on each triangle side is found out, specifically, coordinates of the sides are determined according to vertex coordinates of the triangles, and the coordinates of the sides are compared with road coordinates between road nodes corresponding to the vertex coordinates in the road data to determine whether the real road exists on the sides. If no real road exists, searching the adjacent triangle of the side, if the real road exists, searching the next side of the side in the triangle until the initial side of the first triangle is completely returned, in the process, the triangles which are deeply searched are the sub-domains which are communicated with each other, taking the group of triangles as a triangle group, and so on, determining all the triangle groups which are communicated with each other. Finally, the triangles in each triangle group are merged, and the minimum connected block is obtained.

The depth-first traversal is one of tree and graph algorithms, starting from an initial access node, the initial access node may have a plurality of adjacent nodes, and the strategy of the depth-first traversal is to access a first adjacent node first, and then to access its first adjacent node with the accessed adjacent node as the initial node, that is, to access the first adjacent node of the current node first after the current node is accessed.

The present disclosure determines connected triangle groups based on depth-first traversal, whose access policy is to preferentially drill down deep longitudinally rather than laterally access all adjacent nodes of a node. Therefore, whether the subdomains of the plurality of triangles are connected or not can be effectively explored.

In an alternative example, fig. 7 is a flowchart of step 204 provided by an exemplary embodiment of the present disclosure. In this example, step 204 may specifically include the following steps:

step 2041, obtaining the coordinates of the center point of each minimum connected block.

Specifically, the center point coordinate of each minimum connected block may be obtained according to the boundary coordinate of the minimum connected block (i.e., the road coordinate closing the minimum connected block), for example, the center point coordinate is obtained by performing addition and averaging according to the boundary coordinate, and the determination mode of the center point coordinate may be set according to actual requirements.

Step 2042, determining the distance between the first interest point and the center point of each minimum connected block based on the coordinate of the first interest point and the coordinate of the center point of each minimum connected block for the first interest point in the region to be divided.

The first interest point may be any interest point in the region to be divided, and the coordinate of the first interest point may be one coordinate point or a coordinate point set formed by a plurality of coordinate points. For example, the first interest point is a school, the school occupies a certain area, and according to actual needs, the school can be represented as one coordinate point or a plurality of coordinate points with a certain area, which is not limited in the disclosure. The distance between the first interest point and the center point of the minimum connected block is obtained by calculating the coordinates of the first interest point and the coordinates of the center point of the minimum connected block, and the specific calculation mode may be any implementable mode, which is not limited in this embodiment.

Step 2043, the minimum connected block to which the first interest point belongs is determined according to the distance between the first interest point and the center point of each minimum connected block.

Specifically, a minimum connected block closest to the first interest point may be used as the minimum connected block to which the first interest point belongs, but since the shape of the minimum connected block may not be a regular shape, its center point is not necessarily located inside the minimum connected block, for example, the center point coordinate of the "concave" shaped block may be outside the block, even inside other blocks, which may easily cause the interest point to be wrongly attributed.

Step 2044, based on the minimum connected block to which each interest point belongs, a division result of the region to be divided is obtained.

After the minimum connected block to which each interest point belongs is determined, the boundary (namely, the road) of each minimum connected block divided by the area to be divided and the geographic elements (interest points) contained in the blocks are determined, so that the division of the area to be divided is realized.

According to the method and the device, the possible affiliation of the first interest point is screened out firstly through the central point of the minimum connected block, and then further confirmation is carried out, so that the first interest point is prevented from being matched with each minimum connected block one by one, and the data processing efficiency is effectively improved.

In an optional example, when the interest point is mapped to the minimum connected block, a spatial index technique may be used for efficient retrieval, and the spatial index technique may be, for example, a KD-Tree, a Ball-Tree, or the like, and may be specifically set according to actual requirements. Specifically, a spatial index of the minimum connected block identifier and a central coordinate thereof, road network node coordinates and a road coordinate point set is established based on a spatial index technology, efficient retrieval is performed based on the established spatial index to determine the minimum connected block to which the interest point belongs, and retrieval efficiency is effectively improved.

In an optional example, after mapping each interest point of the region to be divided into each minimum connected block and obtaining the division result of the region to be divided, the method of the present disclosure further includes: classifying the minimum connected blocks in the division result based on a preset classification rule to obtain a classification result; and determining the region attribute corresponding to each minimum connected block based on the classification result.

The preset classification rule may be set according to actual requirements, for example, a clustering algorithm may be used for classification, or other classification rules may also be used, which is not limited in this embodiment. The area attribute may be set according to actual requirements, and may include a school district attribute, a transportation convenience attribute, a medical convenience attribute, and the like. For example, a minimum connected block includes 2 schools, which are classified as school zone attributes. The data based on the classification is the point of interest situation included in each minimum connected block, for example, including 2 schools, 3 hospitals, 5 bus stations, and the like, and may be specifically set according to actual requirements.

In an optional example, classifying the minimum connected block in the division result based on a preset classification rule to obtain a classification result, including: acquiring feature data of each minimum connected block based on the interest points included in each minimum connected block; clustering the characteristic data of each minimum connected block by adopting a preset clustering algorithm to obtain a clustering result; and taking the clustering result as a classification result.

The feature data of the minimum connected block is the feature of the interest point obtained by performing statistical analysis on the interest point in the minimum connected block, for example, a certain minimum connected block includes 2 schools, 3 hospitals, and 5 bus stations, and the feature data of the minimum connected block formed is a 3-dimensional vector [ school: 2, hospital: 3, bus station 5 ]. After the feature data of each minimum connected block is obtained, the feature data can be clustered by adopting a preset clustering algorithm, so that the classification of each minimum connected block is realized.

In an optional example, the preset clustering algorithm may adopt any one of K-means, hierarchical clustering, a GMM gaussian mixture model, and the like, and may be specifically set according to actual requirements.

The clustering algorithm is unsupervised learning, only needs data and does not need marking results, and is used for finding a common group through learning training. Given n training samples (unlabeled), such as: { X1, X2.., Xn }, given the number of clusters, K. The target is as follows: the method comprises the steps of clustering relatively close samples into a cluster class (cluster) to obtain K cluster classes (cluster) in total, wherein the clustering aims to aggregate minimum connected blocks through characteristic attributes to obtain the minimum connected block cluster class with the same area attribute.

In an optional example, the division result of the region to be divided can be visually displayed.

Exemplarily, fig. 8 is an exemplary flowchart illustrating a region dividing method according to an exemplary embodiment of the present disclosure. In this example, the method comprises the steps of:

1. and obtaining the map data of the area to be divided from the OSM map database.

2. And extracting the coordinate point set of each road of the region to be divided and the intersection point between the roads from the map data of the region to be divided, and constructing a regional road network map of the region to be divided.

3. And preprocessing the obtained regional road network graph, removing invalid road network nodes, and obtaining a first regional road network graph as regional road network data.

4. Road network nodes are extracted from regional road network data to carry out Delaunay triangulation, and a triangle set is obtained.

5. And (4) extracting road data from the regional road network data, and performing regional growth on the triangle set obtained in the step (4) to form a minimum connected block.

6. And merging the POI (point of interest) of the area to be divided into the minimum connected block (namely mapping the POI to the corresponding minimum connected block), and obtaining the dividing result of the area to be divided.

7. And characterizing the minimum connected blocks of the division result, namely acquiring the characteristic data of each minimum connected block.

8. And clustering the minimum connected blocks to obtain a classification result.

According to the region dividing method, roads and nodes of a region (such as a certain city) to be divided are analyzed and extracted through an OpenStreetMap to construct a road network graph, and a city space constructed by road network nodes is divided into a minimum element space composed of triangles with maximized minimum angle properties by adopting Delaunay triangulation. Due to the property of the Delaunay triangulation, the minimum element space of the triangulation has the properties of uniqueness, optimality, closest approximation and the like, and the basic requirement for dividing the minimum area can be met. And growing the minimum connected block in the meta-space by a search method (depth first search) in combination with graph attributes (edges). The boundary of the obtained minimum connected block is road constraint, the road is naturally attached, and different blocks only share one edge, so that the generation of the boundary of fine-grained blocks under the constraint of a road network is realized, the boundary is not overlapped, urban fine-grained division with geographic significance can be constructed, efficient retrieval is carried out by combining a spatial index (KD-Tree, Ball-Tree and the like) technology, urban interest points and the divided blocks can be associated, further, the characteristic vector representation of each division is obtained, a group of characteristic vectors mapped to the same space is obtained, finally, the blocks are classified through clustering, the area attribute of each block is determined, the area attribute of each block can be displayed, so that relevant personnel can conveniently check and know the area attribute of each block, for example, in the field of real estate, each real estate broker can know the area attribute of the block where each floor is located, the service is better provided for users, such as the building is a study room, the transportation is convenient, the medical treatment is convenient, and the like. The method solves the problems that the city is divided on a coarse granularity, the precision is low, the same geographic element is easily divided into a plurality of blocks, the blocks influencing the actual geographic condition are possibly divided, the effectiveness of the division result is poor, and the like.

Any of the region partitioning methods provided by the embodiments of the present disclosure may be performed by any suitable device having data processing capability, including but not limited to: terminal equipment, a server and the like. Alternatively, any of the region division methods provided by the embodiments of the present disclosure may be executed by a processor, for example, the processor may execute any of the region division methods mentioned in the embodiments of the present disclosure by calling a corresponding instruction stored in a memory. And will not be described in detail below.

Fig. 9 is a schematic structural diagram of an area dividing apparatus according to an exemplary embodiment of the present disclosure. The apparatus of this embodiment may be used to implement the corresponding method embodiment of the present disclosure, and the apparatus shown in fig. 9 includes: a first obtaining module 501, a first processing module 502, a second processing module 503 and a third processing module 504.

The first obtaining module 501 is configured to obtain regional road network data of a region to be divided, where the regional road network data includes road network node data of the region to be divided and road data between road network nodes.

The first processing module 502 is configured to triangulate road network node data in the regional road network data acquired by the first acquiring module 501, and acquire a subdivision result, where the subdivision result includes a plurality of triangles with each road network node as a vertex.

The second processing module 503 is configured to merge triangles in the subdivision result obtained by the first processing module 502 based on road data in the regional road network data obtained by the first obtaining module 501, so as to obtain at least one minimum connected block, where each minimum connected block is a closed block formed by roads.

A third processing module 504, configured to map each interest point of the region to be divided into each minimum connected block obtained by the second processing module 503, so as to obtain a division result of the region to be divided.

In an alternative example, fig. 10 is a schematic structural diagram of a first obtaining module provided in an exemplary embodiment of the present disclosure. The first acquisition module 501 may specifically include a first acquisition unit 5011, a first processing unit 5012, and a second processing unit 5013. A first obtaining unit 5011, configured to obtain a set of coordinate points of each road in an area to be divided and an intersection point between the roads; the first processing unit 5012 is configured to construct an area road network map of an area to be divided by using intersections between the roads acquired by the first acquiring unit 5011 as road network nodes and using coordinate point sets of the roads as edges; the second processing unit 5013 is configured to use the regional network graph constructed by the first processing unit 5012 as regional network data.

In an optional example, the first processing unit 5012 is further configured to traverse the regional road network graph, remove an invalid road network node, and connect neighboring edges of the road network node to obtain a preprocessed first regional road network graph; the second processing unit 5013 is further configured to use the first regional network graph as regional network data.

In an alternative example, the first processing module 502 is specifically configured to: and triangulating the road network node data in the regional road network data based on a Delaunay triangulation algorithm to obtain a subdivision result. In an exemplary embodiment, the first processing module 502 may be configured to triangulate the road network node data in the regional road network data based on a point-by-point interpolation algorithm of the Delaunay triangulation algorithm, and obtain a triangulation result.

In an optional example, the second processing module 503 is specifically configured to: traversing triangles in the subdivision result by adopting a depth-first traversal mode, judging whether the sides of the first triangles have corresponding roads or not according to the first triangles and the road data in the regional road network data, and judging whether the second sides of the adjacent triangles of the first sides have corresponding roads or not if the first sides of the first triangles do not have corresponding roads; if the first edge has a corresponding road, continuously judging the next edge of the first edge in the first triangle, and so on until returning to the initial edge of the initial triangle to obtain a first triangle group needing to be merged; then, the steps are carried out on the second triangles except the obtained triangle group needing to be merged, and the second triangle group needing to be merged is obtained; by analogy, at least one triangle group needing to be merged is obtained; and removing the edges of the triangle groups which do not have the corresponding roads in the triangle groups to be combined, realizing the combination of the triangle groups and obtaining the corresponding minimum connected block.

In an optional example, the third processing module 504 is specifically configured to: acquiring the center point coordinates of each minimum connected block; determining the distance between a first interest point and the center point of each minimum connected block based on the coordinate of the first interest point and the coordinate of the center point of each minimum connected block aiming at the first interest point in the region to be divided; determining the minimum connected block to which the first interest point belongs according to the distance between the first interest point and the center point of each minimum connected block; and obtaining a dividing result of the area to be divided based on the minimum connected block to which each interest point belongs.

In an alternative example, fig. 11 is a schematic structural diagram of an area dividing apparatus according to another exemplary embodiment of the present disclosure. In this example, the apparatus of the present disclosure further comprises: a fourth processing module 505 and a determination module 506. A fourth processing module 505, configured to classify the minimum connected block in the division result based on a preset classification rule, so as to obtain a classification result; a determining module 506, configured to determine, based on the classification result, an area attribute corresponding to each minimum connected block.

In an optional example, the fourth processing module 505 is specifically configured to: acquiring feature data of each minimum connected block based on the interest points included in each minimum connected block; clustering the characteristic data of each minimum connected block by adopting a preset clustering algorithm to obtain a clustering result; and taking the clustering result as a classification result.

In addition, an embodiment of the present disclosure also provides an electronic device, including: a memory for storing a computer program; a processor, configured to execute the computer program stored in the memory, and when the computer program is executed, implement the region dividing method according to any of the above embodiments of the present disclosure.

Fig. 12 is a schematic structural diagram of an embodiment of an application of the electronic device of the present disclosure. As shown in fig. 12, the electronic device includes one or more processors and memory.

The processor may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

The memory may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium and executed by a processor to implement the region partitioning methods of the various embodiments of the present disclosure described above and/or other desired functions.

In one example, the electronic device may further include: an input device and an output device, which are interconnected by a bus system and/or other form of connection mechanism (not shown).

The input device may also include, for example, a keyboard, a mouse, and the like.

The output device may output various information including the determined distance information, direction information, and the like to the outside. The output devices may include, for example, a display, speakers, a printer, and a communication network and remote output devices connected thereto, among others.

Of course, for simplicity, only some of the components of the electronic device relevant to the present disclosure are shown in fig. 12, omitting components such as buses, input/output interfaces, and the like. In addition, the electronic device may include any other suitable components, depending on the particular application.

In addition to the above-described methods and apparatus, embodiments of the present disclosure may also be a computer program product comprising computer program instructions that, when executed by a processor, cause the processor to perform the steps in the region partitioning method according to various embodiments of the present disclosure described in the above-mentioned part of the specification.

The computer program product may write program code for carrying out operations for embodiments of the present disclosure in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server.

Furthermore, embodiments of the present disclosure may also be a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, cause the processor to perform the steps in the region partitioning method according to various embodiments of the present disclosure described in the above section of the present specification.

The computer-readable storage medium may take any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.

The foregoing describes the general principles of the present disclosure in conjunction with specific embodiments, however, it is noted that the advantages, effects, etc. mentioned in the present disclosure are merely examples and are not limiting, and they should not be considered essential to the various embodiments of the present disclosure. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the disclosure is not intended to be limited to the specific details so described.

In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts in the embodiments are referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The block diagrams of devices, apparatuses, systems referred to in this disclosure are only given as illustrative examples and are not intended to require or imply that the connections, arrangements, configurations, etc. must be made in the manner shown in the block diagrams. These devices, apparatuses, devices, systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art. Words such as "including," "comprising," "having," and the like are open-ended words that mean "including, but not limited to," and are used interchangeably therewith. The words "or" and "as used herein mean, and are used interchangeably with, the word" and/or, "unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".

The methods and apparatus of the present disclosure may be implemented in a number of ways. For example, the methods and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for the steps of the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above unless specifically stated otherwise. Further, in some embodiments, the present disclosure may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.

It is also noted that in the devices, apparatuses, and methods of the present disclosure, each component or step can be decomposed and/or recombined. These decompositions and/or recombinations are to be considered equivalents of the present disclosure.

The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit embodiments of the disclosure to the form disclosed herein. While a number of example aspects and embodiments have been discussed above, those of skill in the art will recognize certain variations, modifications, alterations, additions and sub-combinations thereof.

Claims

1. A method of region partitioning, comprising:

acquiring regional road network data of a region to be divided, wherein the regional road network data comprises road network node data of the region to be divided and road data among road network nodes;

triangulating the road network node data in the regional road network data to obtain subdivision results, wherein the subdivision results comprise a plurality of triangles taking each road network node as a vertex;

merging triangles in the subdivision results based on road data in the regional road network data to obtain at least one minimum connected block, wherein each minimum connected block is a closed block formed by roads;

and mapping each interest point of the area to be divided into each minimum connected block to obtain a division result of the area to be divided.

2. The method according to claim 1, wherein said obtaining regional road network data of the regions to be divided comprises:

acquiring a coordinate point set of each road of a region to be divided and an intersection point between the roads;

constructing a regional road network graph of the region to be divided by taking intersection points among roads as road network nodes and coordinate point sets of the roads as edges;

and taking the regional road network graph as the regional road network data.

3. The method according to claim 2, wherein after constructing the regional road network map of the region to be divided by taking the intersection points between the roads as road network nodes and taking the coordinate point set of each road as an edge, the method further comprises:

traversing the regional road network graph, removing invalid road network nodes, and connecting adjacent edges of the road network nodes to obtain a preprocessed first regional road network graph;

and taking the first regional network graph as the regional network data.

4. The method according to claim 1, wherein said triangulating the road network node data in the regional road network data to obtain a subdivision result comprises:

and triangulating the road network node data in the regional road network data based on a Delaunay triangulation algorithm to obtain a subdivision result.

5. The method according to claim 1, wherein said merging triangles in said split result based on road data in said regional road network data to obtain at least one minimum connected block comprises:

traversing the triangles in the subdivision result in a depth-first traversal mode, judging whether the sides of the first triangles have corresponding roads or not according to the first triangles and the road data in the regional road network data, and judging whether the second sides of the adjacent triangles of the first sides have corresponding roads or not if the first sides of the first triangles do not have corresponding roads; if the first edge has a corresponding road, continuously judging the next edge of the first edge in the first triangle, and so on until returning to the initial edge of the initial triangle to obtain a first triangle group needing to be merged; then, the steps are carried out on the second triangles except the obtained triangle group needing to be merged, and the second triangle group needing to be merged is obtained; by analogy, at least one triangle group needing to be merged is obtained;

and removing the edges of the roads which do not exist in the triangle groups to be merged, so as to realize the merging of the triangle groups and obtain the corresponding minimum connected blocks.

6. The method according to claim 1, wherein the mapping each interest point of the region to be divided into minimum connected blocks to obtain the division result of the region to be divided comprises:

acquiring the center point coordinates of each minimum connected block;

for a first interest point in the region to be divided, determining the distance between the first interest point and the center point of each minimum connected block based on the coordinate of the first interest point and the coordinate of the center point of each minimum connected block;

determining the minimum connected block to which the first interest point belongs according to the distance between the first interest point and the center point of each minimum connected block;

and obtaining the division result of the area to be divided based on the minimum connected block to which each interest point belongs.

7. The method according to any one of claims 1 to 6, wherein after mapping each interest point of the region to be divided into minimum connected blocks and obtaining the division result of the region to be divided, the method further comprises:

classifying the minimum connected blocks in the division result based on a preset classification rule to obtain a classification result;

and determining the region attribute corresponding to each minimum connected block based on the classification result.

8. The method according to claim 7, wherein the classifying the smallest connected block in the division result based on a preset classification rule to obtain a classification result comprises:

acquiring feature data of each minimum connected block based on the interest points included in each minimum connected block;

clustering the characteristic data of each minimum connected block by adopting a preset clustering algorithm to obtain a clustering result;

and taking the clustering result as the classification result.

9. An electronic device, comprising:

a memory for storing a computer program;

a processor for executing a computer program stored in the memory, and when executed, implementing the method of any of the preceding claims 1-8.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method of any one of the preceding claims 1 to 8.

11. A computer program product comprising computer programs/instructions, characterized in that the computer programs/instructions, when executed by a processor, implement the method of any of the preceding claims 1-8.