A reference network-based geospatial network edge path re-planning method

Abstract

The application provides a reference network-based geographical space network edge path replanning method and relates to the technical field of network space geography. The method comprises the following steps: preprocessing geographical space network data; constructing a vector reference network; and arranging edges of the preprocessed geographical space network data based on the vector reference network. The application can realize visual arrangement of edges of a geographical space network on the basis of a preconstructed reference network, thereby effectively reducing the visual confusion problem caused by a large-scale dense graph and being beneficial to cognizing the main structure features of the geographical space network from a macro category.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geographic information visualization, network information visualization and cyber geography, and particularly relates to a method for re-planning edge paths of a geographic spatial network based on a reference network. BACKGROUND

[0002] With the continuous expansion of human activities in space and the rapid development of various information technologies, a huge geographic spatial network has been constructed in modern society, as shown in the figure. For example, a geographic social network formed by coupling social relationship networks with geographic location data, a geographic network space formed by combining network space with geographic space, a flow space network formed by human flow, material flow and information flow based on information technology, and a geographic geometric network formed by a group of connected nodes and edges. Understanding and recognizing the geographic spatial network is very important for mining spatial correlation patterns and exploring spatial correlation rules. Figure 1

[0003] The geographic spatial network is essentially a graph G=(V, E) composed of nodes V={v i} with spatial locations and edges E={e i} with spatial locations. As the number of nodes |V| and edges |E| increases, |E|>>|V|. However, the complex correlation in large-scale dense graphs can cause serious visual confusion problems, making it difficult to distinguish correlation patterns and network structures, which is not conducive to exploring and mining the rules hidden behind the correlation big data. The main way to solve this problem is to keep the node positions unchanged, and continuously adjust the control point positions of the edges E={e i} through edge layout algorithms, so that edges with similar indicators are close to each other, thereby reducing the visual confusion problem and discovering the main link paths and correlation patterns of the correlation network. Although edge layout can alleviate the visual confusion problem of geographic spatial networks to a certain extent under the premise of fixed node positions, existing edge layout methods mainly adjust the control point positions based on spatial aesthetics standards, without considering the spatial distribution characteristics and network structure characteristics of geographic spatial networks, which is not conducive to exploring the relationship and mechanism between geographic spatial networks and geographic space environment and human behavior activities. SUMMARY

[0004] In view of the visual confusion problem caused by the complex correlation in the geographic spatial network, the present application proposes a method for re-planning edge paths of a geographic spatial network based on a reference network, which can realize the visual layout of the edges of the geographic spatial network through edge clustering, edge layout and edge smoothing processes based on the pre-constructed reference network, thereby effectively reducing the visual confusion problem caused by large-scale dense graphs and facilitating the recognition of the main structural characteristics of the geographic spatial network from a macro perspective. ​

[0005] In one aspect, the application provides a reference network-based geospatial network edge path re-planning method, comprising:

[0006] Step 1: preprocessing geospatial network data;

[0007] Step 2: constructing a vector reference network;

[0008] Step 3: edge layout based on the vector reference network for the preprocessed geospatial network data.

[0009] Further, step 1 specifically includes: coordinate conversion processing of geospatial network data and removal or completion of repeated values, default values and attribute data in geospatial network data.

[0010] Further, the removal or completion of repeated values, default values and attribute data in geospatial network data specifically includes:

[0011] According to the similarity between network space entities in geospatial network in spatial position distance, attribute field information and topological connection relationship, the same name network space entity is identified;

[0012] For network space entities with incomplete attribute field information, if there is a corresponding same name network space entity, the attribute field information of the same name network space entity is used for supplement; otherwise, the incomplete attribute field information in the network space entity is deleted;

[0013] For network space entities lacking spatial position information, if there is place name information describing network space entities in the attribute field information, the coordinates are matched through the place name information to complete the spatial position information of the network space entity.

[0014] Further, step 2 specifically includes: selecting the required vector reference network, simplifying the selected vector reference network data, and extracting the structure of the data-simplified vector reference network. Further, the vector reference network is established with a translation field, which is used to indicate the moving direction of the edge control point towards the vector reference network. The edge control point refers to the point on the geospatial network edge path except the starting node and the ending node.

[0015] Further, the simplification of the selected vector reference network data specifically includes: searching and constructing the path of the vector reference network according to the degree of each node in the selected vector reference network, and simplifying each path searched based on the Douglas-Pok algorithm.

[0016] Further, the extraction of the structure of the data-simplified vector reference network specifically includes:

[0017] Define a vector reference network G R Middle node v i and v j The correlation strength ω(i,j) between them is calculated, and the vector reference network G is computed. R Any node v i Total correlation strength S i :

[0018] ω(i,j)=ω ij +ω ji

[0019]

[0020] Among them, G R =(V R E R ), ω(i,j)=ω(j,i), ω ij and ω ji Representing edge e respectively ij and edge e ji The weight, e ij ,e ji ∈E R ;

[0021] Define spatial compactness T ij And according to the spatial density T ij The network structure filtering function is defined using information entropy f(i,k) to select data for the vector reference network; wherein, the network structure filtering function starts from node v i Initially, k lines are added sequentially with node v through iteration. i For edges that are related and have high spatial density, calculate the information entropy f(i,k) until the information entropy f(i,k) value is greater than the threshold ε, and then remove all other edges.

[0022]

[0023]

[0024] Where, d ij For node v i and v j The spatial distance between them; α is the preset spatial distance damping coefficient.

[0025] Furthermore, the establishment of a translation field for the vector reference network after structural thinning specifically includes:

[0026] A buffer Ω with radius σ is generated around the vector reference network to serve as the layout and drawing area for the edge control points;

[0027] Let ei ∈E is an edge path of the geospatial network, e j ∈E R is an edge path of the vector reference network, for an edge path e i on which any edge control point is calculated by calculating its characteristic transformation point on the edge path e j according to the following formula to construct a translation field;

[0028]

[0029] where λ(v) is the arc length distance of the node v from the starting point v s of the edge on which it is located, and represent the end nodes of the edge paths e i and e j respectively.

[0030] Further, step 3 specifically includes:

[0031] determining in the vector reference network the reference network path corresponding to each edge path in the geospatial network that needs to be approached;

[0032] displacing the connection control points in the preprocessed geospatial network to be located in the buffer Ω;

[0033] adjusting the position transformation of the edge control points to the corresponding reference network path according to the translation field to realize the layout of the geospatial network connection path, and performing smoothing processing on the laid-out edge path.

[0034] Further, the position of the position transformation of the connection control point v i is calculated according to the following formula

[0035]

[0036] where β ∈ [0, 1] is a control parameter, the larger the value of β is, the closer the edge control point is to the vector reference network, d is a distance calculation function between two points, σ is the buffer radius of the vector reference network, and p i represents the position of the connection control point v i before position transformation.

[0037] Further, the laid-out edge path is smoothed according to the following formula:

[0038]

[0039] where p′ j and p jThese represent the positions before and after smoothing the j-th edge control point, respectively. s is a rigidity parameter; a smaller value results in a smoother edge layout. N represents the edge path e. i The number of control points on the connected edges, and These represent the edge paths e respectively. i The positions of the start and end nodes.

[0040] On the other hand, the present invention provides a geospatial network edge path replanning system based on a reference network, including a data preprocessing module, a reference network construction module, and an edge layout module;

[0041] The data preprocessing module is used to preprocess geospatial network data;

[0042] The reference network building block is used to construct vector reference networks;

[0043] The edge layout module is used to perform edge layout on the preprocessed geospatial network data based on the vector reference network.

[0044] The beneficial effects of this invention are:

[0045] The edge path replanning method and system provided by this invention can realize the visual layout of geospatial network edges based on a pre-constructed reference network, taking into account the spatial distribution and network structure characteristics of the geospatial network. Through edge clustering, edge layout, and edge smoothing, the method effectively reduces the visual confusion caused by large-scale dense graphs and helps to understand the main structural characteristics of the geospatial network from a macro perspective. Attached Figure Description

[0046] Figure 1 A schematic diagram of a geospatial network provided in an embodiment of the present invention;

[0047] Figure 2 A flowchart illustrating a geospatial network edge replanning method based on a reference network, provided in an embodiment of the present invention;

[0048] Figure 3 A flowchart of vector reference network path simplification provided for embodiments of the present invention;

[0049] Figure 4 Translation field of the vector reference network provided in the embodiments of the present invention;

[0050] Figure 5 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0051] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be clearly described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0052] The present application provides a reference network-based geographical space network edge path re-planning method, mainly through key links such as geographical space network data preprocessing, reference network construction, network edge layout, on the basis of considering network structure characteristics and spatial distribution characteristics, the edge path re-planning of the geographical space network is realized, so as to highlight the network skeleton structure characteristics, and effectively reduce the visual confusion problem caused by complex edge interweaving.

[0053] In order to achieve the above-mentioned object, the overall technical scheme adopted by the embodiments of the present application is as shown in Figure 2 The specific process is as follows:

[0054] S101: Preprocess the geographical space network data; specifically including: coordinate conversion processing of the geographical space network data and removing or completing the repeated values, default values and attribute data in the geographical space network data;

[0055] Specifically, the spatial coordinate conversion processing realizes the unification of data space reference. Specifically, since the subsequent edge position translation needs to be carried out in the plane rectangular coordinate system, it is necessary to convert the geographical space network longitude and latitude coordinates into projection coordinates. For the geographical space network, since the edge is associated with the starting node and the ending node by reference, only the longitude and latitude coordinates of the node need to be converted, that is, the longitude and latitude coordinates are converted into rectangular coordinates (x, y).

[0056] The removal or completion of the geographical space network data mainly removes or completes the data of the repeated nodes and edges (P1), the incomplete attribute field information (P2), the lack of spatial position information (P3), and checks the data logical consistency according to the graph model data structure characteristics. Mainly includes the following process:

[0057] For P1, according to the similarity of the network space entities in the geographical space network in the spatial position distance, attribute field information and topological connection relationship, the same name network space entity is identified.

[0058] For the P2 case and the P3 case, for the network space entity with incomplete attribute field information, if a corresponding network space entity with the same name exists, the attribute field information of the network space entity with the same name is used for supplement; otherwise, the incomplete attribute field information in the network space entity is deleted; in addition, for the network space entity lacking spatial position information, if the attribute field information of the network space entity contains place name information describing the network space entity, the spatial position information of the network space entity is supplemented by matching the coordinates according to the place name information.

[0059] S102: Construct a vector reference network; specifically comprising: selecting a required vector reference network, simplifying the selected vector reference network data; thinning the structure of the vector reference network after data simplification to remove less important nodes and edges; generating a buffer zone of a specific radius based on the structure-thinned vector reference network to establish a translation field, the translation field being used to indicate the moving direction of the edge control point of the vector reference network towards the vector reference network, and the edge control point being a point on the path of the geographic space network edge other than the starting node and the ending node.

[0060] S103: Based on the vector reference network, the edge layout of the preprocessed geographic space network data is performed; specifically comprising: determining the reference network path that needs to be approached corresponding to each edge path in the geographic space network in the vector reference network, that is, finding a corresponding connection path in the reference network for each path in the geographic space network, to prepare for subsequent edge layout; displacing the connection control point in the preprocessed geographic space network to the buffer zone; adjusting the position of the edge control point according to the translation field to realize the layout of the connection path of the geographic space network, and smoothing the laid-out edge path.

[0061] The method for re-planning the edge path of the geographic space network based on the reference network provided by the embodiment can realize the visual layout of the edge of the geographic space network through edge clustering, edge layout, edge smoothing and other processes based on the pre-constructed vector reference network, thereby effectively reducing the visual confusion problem caused by large-scale dense graphs and being conducive to recognizing the main structural features of the geographic space network from a macro perspective.

[0062] In one embodiment, the closeness of the spatial position distance can refer to formula 1:

[0063]

[0064] The similarity of the attribute field information needs to be determined according to the mixed attribute similarity method, and the specific calculation method can refer to formula 2:

[0065]

[0066] wherein, represents the kth attribute difference between the network space entity x i and x j . When k is a categorical attribute or a binary attribute, x i and x j are compared in the value of the kth attribute, and if equal, then otherwise When k is a numerical attribute, the maximum and minimum values of the kth attribute are calculated, and then When k is a character attribute, the proportion of the number of characters that are the same is calculated.

[0067] The topological connection relationship similarity judgment can be determined according to the degree or centrality index of the node.

[0068] In one embodiment, a geographic geometric network is used as a vector reference network. It can be understood that the vector reference network G R = (V R , E R ) is essentially a graph structure, except that E R is a path formed by connecting edges end to end, and the intermediate nodes of the path have a degree of 2 except for the first and last end points. Therefore, according to this feature, the embodiment of the present application searches and constructs the path of the vector reference network by the node degree, and simplifies each path based on the Douglas-Peucker (DP) algorithm, and the flowchart is as shown in Figure 3 .

[0069] First, according to the input vector reference network G R = (V R , E R ), a "point chain" topological structure is constructed, and the starting and ending nodes of each chain and the chain list passing through the nodes are recorded. Then, the degree of each node is calculated and recorded. Again, starting from any node with a degree not equal to 2, a path is searched until the next node with a degree not equal to 2, a path is constructed and the nodes in the path are removed from the node set. After the traversal is completed, it is determined whether the node set is empty. If it is empty, it means that all path searches are complete, and the traversal path set can be compressed according to the Douglas-Peucker algorithm; otherwise, it means that the remaining nodes in the set should all belong to closed paths, and the path can be searched from any node until the node is reached again.

[0070] In one embodiment, a spatial distribution feature and a topological structure feature of the associated network (i.e., a geographic spatial network that needs to be re-planned for edge path) are used to simplify the structure of the vector reference network, so as to facilitate subsequent edge clustering and displacement processing.

[0071] Definition e ij and e ji The weights of and e ij and ω ji respectively, the association strength between nodes v i and v j is defined as:

[0072] ω(i,j)=ω(j,i)=ω ij +ω ji (3)

[0073] The sum of the weights of all edges passing through node v i is defined as the total amount of association strength of node v i :

[0074]

[0075] On the basis of the network association strength, a spatial damping function is added to represent the feature that the association strength between geographic elements or entities gradually decays with the increase of spatial distance, that is, the spatial tightness is obtained:

[0076]

[0077] Wherein, d ij is the spatial distance between nodes v i and v j ; α is a preset spatial distance damping coefficient, the value of which is related to the semantic characteristics of the association network. For example, through massive data demonstration, the value of α of the social association network is generally 0.5.

[0078] In order to facilitate the selection of vector reference network data, the embodiment of the application defines a network structure filtering function on the basis of information entropy (information entropy) in combination with spatial tightness T ij for selecting data of the vector reference network:

[0079]

[0080] The filtering function means that starting from node v i , k edges associated with node v i and having high spatial tightness are sequentially added through iteration, and the information entropy f(i,k) is calculated until the value is greater than the threshold value ε, and all other edges are removed.

[0081] In one embodiment, to facilitate the implementation of the edge layout, this embodiment uses the following process to establish a translation field for the vector reference network after structural thinning. First, a buffer Ω with a radius of σ is generated around the vector reference network to serve as the layout and drawing area for the edge control points. The buffer Ω is then:

[0082] Ω={p∈R 2 |d(p,G R )≤σ} (7)

[0083] Where p is any point within the buffer region Ω, d(p,G) R ) represents the distance from p to the vector reference network, and σ is the buffer radius. Subsequent edge layout processing needs to be completed within the buffer Ω.

[0084] like Figure 4 As shown, let e i ∈E represents the edge path of the associated network to be processed in the layout, e j ∈E R For the edge paths of the vector reference network, this embodiment of the invention establishes a translation field between them to adjust the movement of the control points. For the edge path e... i Any control point v on the edge i x Its position on the connecting path e is calculated according to the following formula. j Feature transformation points on To construct the translation field;

[0085]

[0086] Where λ(v) is the distance from node v to the starting point v of its connected edge. s The arc length, and These represent the path length e of the connecting edges. i and e j Termination node

[0087] By calculating the characteristic transformation points of the corresponding control points, the translation field of the vector reference network can be constructed. Therefore, based on the translation field, the vector reference network can be constructed along the vector... The direction of translation control point.

[0088] In one embodiment, vector reference network path search involves determining the nearest reference network path for each edge in the geospatial network. First, it's necessary to search for the vector reference network node whose starting and ending nodes are closest to each edge in the geospatial network. Then, the shortest path in the vector reference network is obtained using a shortest path search algorithm, which serves as the nearest reference network path for the current edge.

[0089] In one embodiment, a control point translation position model is constructed on the basis of the vector reference network translation field, so that the control points are arranged within the buffer area Ω, and the tightness of the edge layout is regulated by a simple position parameter α. The spatial position calculation model of the control point v i based on the vector reference network translation field is:

[0090]

[0091] where β ∈ [0, 1] is a regulation parameter, and the larger the value is, the closer the edge control point (or the edge path where it is located) is to the vector reference network; d is a distance calculation function between two points; σ is the buffer radius of the vector reference network, and p i represents the position of the control point v i before position transformation.

[0092] The path re-planning based on the vector reference network may cause a so-called "skeleton effect", that is, a rigid spatial network structure is visually produced, which does not meet the requirements of spatial aesthetics standards and also destroys the continuity of the geographical spatial network in spatial perception. In one embodiment, the following model is used to smooth the edge layout after the layout:

[0093]

[0094] where p′ j and p j represent the positions of the jth edge control point after and before the smoothing processing, respectively, s is a rigidity parameter, and the smaller the value is, the smoother the edge layout result is; N is the number of edge control points on the edge path e i , and represent the positions of the start node and the end node of the edge path e i , respectively.

[0095] Figure 5 An example of a schematic diagram of an entity structure of an electronic device is shown in Figure 5 , which can include a processor 501, a communications interface 502, a memory 503, and a communications bus 504, wherein the processor 501, the communications interface 502, and the memory 503 complete mutual communication through the communications bus 504. The processor 501 can invoke a logical instruction in the memory 503 to execute an edge path re-planning method, which includes: step 1: pre-processing geographical spatial network data; step 2: constructing a vector reference network; and step 3: performing edge layout on the pre-processed geographical spatial network data based on the vector reference network.

[0096] Further, the logical instructions in the memory 503 described above are implemented in the form of software function units and sold or used as independent products, which can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application or the parts of the present application that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0097] The embodiments of the present application also provide a computer program product, which includes a computer program stored on a non-transitory computer readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the method provided by the above-mentioned method embodiments, for example, including: step 1, preprocessing geospatial network data; step 2, constructing a vector reference network; and step 3, performing edge layout based on the vector reference network on the preprocessed geospatial network data.

[0098] The embodiments of the present application also provide a non-transitory computer readable storage medium, which stores a computer program. When the computer program is executed by a processor, the method provided by the above-mentioned method embodiments is implemented, for example, including: step 1, preprocessing geospatial network data; step 2, constructing a vector reference network; and step 3, performing edge layout based on the vector reference network on the preprocessed geospatial network data.

[0099] Through the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be implemented by means of software plus necessary general hardware platforms, and of course, can also be implemented by hardware. Based on such understanding, the above technical solutions or the parts of the present application that essentially contribute to the prior art can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0100] It should be pointed out finally that the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit the same; and although the present application has been described in detail with reference to the foregoing embodiments, it should be appreciated by those skilled in the art that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features thereof can be replaced equivalently; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for replanning edge connection paths in a geospatial network based on a reference network, characterized in that, include: Step 1: Preprocess the geospatial network data; Step 2: Construct a vector reference network; Specifically, this includes: selecting a geographic geometric network as a vector reference network; simplifying the selected vector reference network data, including: searching and constructing paths for the vector reference network based on the degree of each node in the selected vector reference network; simplifying each searched path based on the Douglas-Puk algorithm; thinning the structure of the simplified vector reference network; and establishing a translation field for the thinned vector reference network, wherein the translation field is used to indicate the direction of movement of the edge control points toward the vector reference network, and the edge control points refer to the points on the edge paths of the geospatial network other than the starting and ending nodes. Step 3: Based on the vector reference network, perform edge layout on the preprocessed geospatial network data; specifically including: In the vector reference network, determine the reference network path that needs to be approached for each edge path in the geospatial network; Displace the connection control points in the preprocessed geospatial network so that they are located in the buffer Ω; The control points of the edge connection are adjusted according to the translation field to transform their positions to the corresponding reference network path in order to realize the layout of the geospatial network connection path, and the edge connection path after the layout is smoothed.

2. The method for replanning edge paths in a geospatial network based on a reference network according to claim 1, characterized in that, Step 1 specifically includes: performing coordinate transformation on the geospatial network data and removing or completing duplicate, missing, and attribute data in the geospatial network data; specifically including: Identify network spatial entities with the same name based on the similarity between network spatial entities in the geospatial network in terms of spatial location distance, attribute field information, and topological connection relationship; For network space entities with incomplete attribute field information, if a corresponding network space entity with the same name exists, the attribute field information of the corresponding network space entity is used to supplement it; otherwise, the incomplete attribute field information in the network space entity is deleted. For cyberspace entities that lack spatial location information, if their attribute fields contain place name information describing the cyberspace entity, then the coordinates are matched using the place name information to complete the spatial location information of the cyberspace entity.

3. The method for replanning edge paths in a geospatial network based on a reference network according to claim 1, characterized in that, The aforementioned thinning of the simplified vector reference network structure specifically includes: Define a vector reference network G R Middle node v i and v j The correlation strength ω(i,j) between them is calculated, and the vector reference network G is computed. R Any node v i Total correlation strength S i : ω(i,j)=ω ij +oh ji Among them, G R =(V R E R ), ω(i,j)=ω(j,i), ω ij and ω ji Representing edge e respectively ij and edge e ji The weight, e ij ,e ji ∈E R ; Define spatial compactness T ij And according to the spatial density T ij The network structure filtering function is defined using information entropy f(i,k) to select data for the vector reference network; wherein, the network structure filtering function starts from node v i Initially, k lines are added sequentially with node v through iteration. i For edges that are related and have high spatial density, calculate the information entropy f(i,k) until the information entropy f(i,k) value is greater than the threshold ε, and then remove all other edges. Where, d ij For node v i and v j The spatial distance between them; α is the preset spatial distance damping coefficient.

4. The method for replanning edge paths in a geospatial network based on a reference network according to claim 1, characterized in that, The establishment of a translation field for the vector reference network after structural thinning specifically includes: A buffer Ω with radius σ is generated around the vector reference network to serve as the layout and drawing area for the edge control points; Let e i ∈E represents the edge path of the geospatial network, e j ∈E R For the edge paths of the vector reference network, regarding edge path e i Any control point on the edge Its position on the connecting path e is calculated according to the following formula. j Feature transformation points on To construct the translation field; Where λ(v) is the distance from node v to the starting point v of its connected edge. s arc length distance, and These represent the path length e of the connecting edges. i and e j The termination node.

5. The method for replanning edge paths in a geospatial network based on a reference network according to claim 1, characterized in that, Calculate the connection control point v according to the following formula. i Position change Where β∈[0,1] is the control parameter, the larger the value of β, the closer the control point of the connection is to the vector reference network, d is the distance calculation function between the two points, σ ​​is the buffer radius of the vector reference network, and p i Indicates connection to control point v i Position before the position change.

6. The method for replanning edge paths in a geospatial network based on a reference network according to claim 1, characterized in that, The edge paths after layout are smoothed according to the following formula: Where, p′ j and p j These represent the positions before and after smoothing the j-th edge control point, respectively. s is a rigidity parameter; a smaller value results in a smoother edge layout. N represents the edge path e. i The number of control points on the connected edges, and These represent the edge paths e respectively. i The positions of the start and end nodes.

Images