Urban rail transit network planning method and device based on GIS

Abstract

The present invention provides a method and device for planning a network of urban rail transit based on GIS, including: acquiring geographic information data, classifying POI point data in the geographic information data by using a multivariate clustering algorithm to obtain the points of various residential groups in the current city; forming a current analysis point set with the points of various residential groups in the current city and other passenger flow distribution points, wherein the current analysis point set and the planning analysis point set together constitute an analysis point set in a surface point line hierarchical analysis method; storing the analysis point set in the form of a data list; wherein the analysis point set includes a point sequence number, a point name, an x-coordinate and a y-coordinate; obtaining a conceptual line network by using a minimum spanning tree algorithm for the analysis point set; and providing a quantitative basis for the division of urban groups, a quantitative basis for the calibration of important functional points in the city, and a quantitative basis for the network construction at the line level, thereby improving the scientificity and rationality of urban rail transit planning.

Description

Technical Field

[0001] The present invention relates to the technical field of rail transit network planning, and in particular to a method and device for urban rail transit network planning based on GIS. Background Art

[0002] In the specific practice of urban rail transit network planning in my country, different planning research institutions have formed their own planning ideas and methods, including the surface-point-line hierarchical analysis method, the point-line-surface element hierarchical analysis method, and the main passenger flow direction method, etc. Among them, the surface-point-line hierarchical analysis method is the most widely used in the actual urban rail transit network planning work in my country.

[0003] Although the traditional surface-point-line hierarchical analysis method solves the technical difficulties in the planning of urban rail transit network, such as quantitative determination of network form and hierarchical division of line functions, it has certain shortcomings in the process of scheme construction:

[0004] (1) At the point level, the quantitative level of identification of major passenger flow distribution points is limited. Generally speaking, in terms of point identification, the traditional surface-point-line hierarchical analysis method focuses more on large passenger flow distribution points that are emphasized at the planning level, such as planned new areas, large public buildings, and transportation hubs. It pays less attention to residential areas with concentrated populations in cities and lacks corresponding quantitative identification methods.

[0005] (2) At the line level, the construction of the conceptual line network is too subjective, and the operation process and results are also "non-standardized". After the main passenger flow distribution points are identified in the traditional surface-point-line hierarchical analysis method, the actual line network's morphological combination is not unique. In actual work, the main axis is often determined and the conceptual line network is constructed based on the planner's understanding and experience of the city, so the conceptual line network often has the characteristic of "one thousand faces for one thousand people".

[0006] In summary, the above shortcomings cause this method to be overly dependent on the user's subjective judgment of urban form and traffic conditions, and require a high level of urban rail transit planning skills and experience from the user. The final conclusions drawn by different planners using the Surface-Point-Line Hierarchy Analysis Method may vary greatly. Summary of the invention

[0007] In view of this, the purpose of the present invention is to provide a GIS-based urban rail transit network planning method and device, which can provide a quantitative basis for the division of urban clusters, provide a quantitative basis for the calibration of important functional points in the city, and provide a quantitative basis for network construction at the line level, thereby improving the scientificity and rationality of urban rail transit planning.

[0008] In a first aspect, an embodiment of the present invention provides a method for urban rail transit network planning based on GIS, the method comprising:

[0009] Acquire geographic information data, the geographic information data including administrative boundary data of the target city, road boundary data of the target city, population job distribution data of the target city, and POI point data of the target city;

[0010] Classify the POI point data using a multivariate clustering algorithm to obtain the points of each residential group in the current urban situation;

[0011] The points of each residential group in the current situation of the city and other passenger flow distribution points are combined into a current situation analysis point set, and the current situation analysis point set and the planning analysis point set together constitute the analysis point set in the surface point line hierarchical analysis method;

[0012] The analysis point set is stored in the form of a data list; wherein the analysis point set includes a point sequence number, a point name, an x ​​coordinate, and a y coordinate;

[0013] The analysis point set is passed through a minimum spanning tree algorithm to obtain a concept line network.

[0014] Furthermore, the analysis point set is subjected to a minimum spanning tree algorithm to obtain a concept line network, including:

[0015] Importing the analysis point set into matlab to generate an array;

[0016] Store the array into a csv file to obtain an array storage file;

[0017] Constructing a weighted adjacency matrix of the analysis point set according to the array;

[0018] The weighted adjacency matrix is ​​subjected to Prim's algorithm or Kruskal's algorithm to obtain a minimum spanning tree matrix of the analysis point set;

[0019] The minimum spanning tree matrix and the array are stored in the csv file, and an interface file with the GIS platform is constructed;

[0020] Add the array storage file to the GIS platform, and generate a point layer using the xy point conversion function;

[0021] Add the minimum spanning tree interface file to the GIS platform, and use the xy to line function to generate a line layer;

[0022] The concept line network is obtained according to the point layer and the line layer.

[0023] Furthermore, the POI point data is classified by a multivariate clustering algorithm to obtain the points of each residential group in the current urban situation, including:

[0024] A group of points that are close in distance and concentrated are selected from the POI point data as a residential group, and the centroid of the residential group is used as a representative;

[0025] The longitude, latitude or plane x, y coordinates of each residential POI point are used as distance parameters;

[0026] The distance parameter is input into the GIS platform, and the GIS platform clusters the multiple residential groups according to the distance parameter to obtain the location of each residential group in the current situation of the city.

[0027] Furthermore, the method further comprises:

[0028] Cleaning the geographic information data to obtain cleaned geographic information data;

[0029] The cleaned geographic information data is imported into the GIS platform.

[0030] Furthermore, the method further comprises:

[0031] Obtaining the population job distribution data from mobile phone signaling data;

[0032] The administrative boundary data, the road boundary data and the POI point data are obtained from an electronic map.

[0033] Furthermore, the method further comprises:

[0034] In the GIS platform, the geographic information data is drawn according to the contour line control operation to obtain the population and job distribution contour lines of the target city;

[0035] Taking any of the distribution contour lines of the distribution positions as a reference, the population of the target city is divided into a plurality of cluster areas;

[0036] The analysis boundary of the surface level in the rail transit network analysis is determined based on the multiple cluster areas.

[0037] In a second aspect, an embodiment of the present invention provides a GIS-based urban rail transit network planning device, the device comprising:

[0038] A geographic information data acquisition module, used to acquire geographic information data, wherein the geographic information data includes administrative boundary data of a target city, road boundary data of the target city, population job distribution data of the target city, and POI point data of the target city;

[0039] A classification module is used to classify the POI point data through a multivariate clustering algorithm to obtain the points of each residential group in the current urban situation;

[0040] An analysis point set acquisition module is used to form a current analysis point set from the points of each residential group in the current city and other passenger flow distribution points. The current analysis point set and the planning analysis point set together constitute the analysis point set in the surface-point-line hierarchical analysis method;

[0041] A storage module, used to store the analysis point set in the form of a data list; wherein the analysis point set includes a point sequence number, a point name, an x ​​coordinate and a y coordinate;

[0042] The concept line network acquisition module is used to obtain the concept line network by applying the minimum spanning tree algorithm to the analysis point set.

[0043] Furthermore, the concept line network acquisition module is specifically used for:

[0044] Importing the analysis point set into matlab to generate an array;

[0045] Store the array into a csv file to obtain an array storage file;

[0046] Constructing a weighted adjacency matrix of the analysis point set according to the array;

[0047] The weighted adjacency matrix is ​​subjected to Prim's algorithm or Kruskal's algorithm to obtain a minimum spanning tree matrix of the analysis point set;

[0048] The minimum spanning tree matrix and the array are stored in the csv file, and an interface file with the GIS platform is constructed;

[0049] Add the array storage file to the GIS platform, and generate a point layer using the xy point conversion function;

[0050] Add the minimum spanning tree interface file to the GIS platform, and use the xy to line function to generate a line layer;

[0051] The concept line network is obtained according to the point layer and the line layer.

[0052] In a third aspect, an embodiment of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor implements the method described above when executing the computer program.

[0053] In a fourth aspect, an embodiment of the present invention provides a computer-readable medium having a non-volatile program code executable by a processor, wherein the program code enables the processor to execute the method as described above.

[0054] The embodiment of the present invention provides a GIS-based urban rail transit network planning method and device, including: acquiring geographic information data, the geographic information data including administrative boundary data of a target city, road boundary data of a target city, population job distribution data of a target city and POI point data of a target city; classifying the POI point data by a multivariate clustering algorithm to obtain the points of each residential group in the current situation of the city; forming a current situation analysis point set with the points of each residential group in the current situation of the city and other passenger flow distribution points, and the current situation analysis point set and the planning analysis point set together constitute an analysis point set in a surface point line hierarchical analysis method; storing the analysis point set in the form of a data list; wherein the analysis point set includes a point sequence number, a point name, an x-coordinate and a y-coordinate; obtaining a conceptual line network by a minimum spanning tree algorithm for the analysis point set; providing a quantitative basis for the division of urban groups, providing a quantitative basis for the calibration of important functional points in the city, providing a quantitative basis for the network construction at the line level, and improving the scientificity and rationality of urban rail transit planning.

[0055] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0056] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0058] Figure 1 A flow chart of a method for planning a urban rail transit network based on GIS provided in the first embodiment of the present invention;

[0059] Figure 2 This is a schematic diagram of a GIS-based urban rail transit network planning device provided in Example 2 of the present invention. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] To facilitate understanding of this embodiment, the embodiment of the present invention is described in detail below.

[0062] Embodiment 1:

[0063] Figure 1 A flow chart of a GIS-based urban rail transit network planning method provided in Example 1 of the present invention.

[0064] Reference Figure 1 , the method comprises the following steps:

[0065] Step S101, obtaining geographic information data, the geographic information data including administrative boundary data of the target city, road boundary data of the target city, population job distribution data of the target city and POI point data of the target city;

[0066] Step S102, classifying the POI point data by a multivariate clustering algorithm to obtain the points of each residential group in the current urban situation;

[0067] Step S103, the points of each residential group in the current situation of the city and other passenger flow distribution points are combined into a current situation analysis point set, and the current situation analysis point set and the planning analysis point set together constitute the analysis point set in the surface point line hierarchical analysis method;

[0068] Step S104, storing the analysis point set in the form of a data list; wherein the analysis point set includes a point sequence number, a point name, an x ​​coordinate, and a y coordinate;

[0069] Step S105, the analysis point set is subjected to a minimum spanning tree algorithm to obtain a concept line network.

[0070] Furthermore, the method also includes:

[0071] Step S201, obtaining population job distribution data from mobile phone signaling data; wherein, it is recommended that the granularity of population job distribution data should not be higher than 500m×500m;

[0072] Step S202, obtaining administrative boundary data, road boundary data and POI point data from the electronic map.

[0073] Here, the administrative boundary data and road boundary data of the target city can be obtained through the API of the electronic map; the POI point data of the target city can be obtained in batches through the API open to the electronic map. Among them, the source of population job distribution data and POI point data can also be changed.

[0074] Furthermore, the method further comprises the following steps:

[0075] Step S301, cleaning the geographic information data to obtain cleaned geographic information data;

[0076] Step S302, importing the cleaned geographic information data into the GIS platform.

[0077] Here, after acquiring geographic information data, data cleaning should be performed first, and the required geographic information data should be processed and imported into the GIS platform. Data cleaning mainly checks the consistency of data and handles invalid values ​​and missing values.

[0078] Furthermore, the method further comprises the following steps:

[0079] Step S401, in the GIS platform, the geographic information data is drawn according to the contour line control operation to obtain the population and job distribution contour lines of the target city;

[0080] Step S402, dividing the population of the target city into a plurality of cluster areas with reference to any contour line in the distribution contour lines of the distribution positions;

[0081] Step S403, determining the analysis boundary of the surface level in the rail transit network analysis according to the multiple cluster areas.

[0082] Specifically, in the GIS platform (geographic information platform), the contour line control operation ("3DAnalyst Tools - Raster Surface - Contour Line") can be used to draw the population and job distribution contour lines of the target city. Using a certain contour line as a reference, the target city can be divided into several clusters with concentrated population and jobs.

[0083] The output of this step is the analysis boundary of the surface level in the rail transit network analysis, which can be intuitively displayed in the geographic information platform and is the quantitative expression of the "surface" in the "surface-point-line" multi-level analysis method.

[0084] Further, step S102 includes the following steps:

[0085] Step S501, selecting a group of points that are close in distance and concentrated from the POI point data as a residential group, and taking the centroid of the residential group as a representative;

[0086] Step S502, using the longitude, latitude or plane x, y coordinates of each residential POI point as a distance parameter;

[0087] Step S503, input the distance parameter into the GIS platform, and the GIS platform clusters multiple residential groups according to the distance parameter to obtain the location of each residential group in the current urban situation.

[0088] Specifically, POI point data is classified. According to the practical experience of urban rail transit network planning, POI point data of general cities can be divided into residential, catering and commercial, transportation hub, institution, public building, etc. For special cities, POI points can be appropriately supplemented according to the actual situation of the city. For example, tourist cities can further supplement cultural and tourist attractions and hotels.

[0089] For transportation hubs, institutions, and public buildings, since the locations are few and clear, the corresponding POI coordinates can be determined by screening and checking the corresponding points determined by the city's overall plan.

[0090] For residential population aggregation, since the number of points involved is large and widely distributed, and they are not of the same order of magnitude as other points, further clustering and integration are needed.

[0091] According to actual experience, the number of residential POI points in a city is generally in the tens of thousands or hundreds of thousands. On the one hand, the number of these residential POI points is too large. If they are used directly as "points" in network planning analysis, there will be too many points and the real information will be blurred. On the other hand, the weight of a single residential point is not at the same level as other important passenger flow distribution points and cannot be analyzed together.

[0092] Therefore, this application proposes to use the concept of residential clusters to streamline and integrate residential POI points, select a group of points that are close in distance and concentrated from the POI point data as a residential cluster, and use the centroid of this residential cluster to represent the residential cluster.

[0093] In practical applications, the above process can be realized by adopting a multivariate clustering algorithm, taking the longitude, latitude or plane x, y coordinates of each residential POI point as the distance parameter, and using the spatial multivariate distance tool in the GIS software to quickly realize the above process. According to relevant practices, the general urban point density is recommended to be controlled at 0.5 to 2 per square kilometer. Among them, by changing the clustering method of POI points, including the parameters in the clustering process, similar technical effects can also be obtained, and the analysis results will not produce substantial differences.

[0094] Through the above steps, the locations of various residential clusters in the city are obtained, and together with other important passenger flow distribution points POIs of the current status and planning, they constitute the analysis point set V(G) in the surface-point-line hierarchical analysis method.

[0095] To facilitate data processing, the analysis point set V(G) is stored in the form of a data list, which contains four fields: "point number", "point name", "x coordinate" and "y coordinate". Each record represents a point, and the corresponding data is stored in a csv file (other formats such as xlsx, txt, etc. are also applicable).

[0096] Further, step S105 includes the following steps:

[0097] Step S601, import the analysis point set into MATLAB to generate an array;

[0098] Step S602, storing the array into a csv file to obtain an array storage file;

[0099] Step S603, constructing a weighted adjacency matrix of the analysis point set according to the array;

[0100] Step S604, applying the weighted adjacency matrix to the Prim algorithm or the Kruskal algorithm to obtain a minimum spanning tree matrix of the analysis point set;

[0101] Step S605, storing the minimum spanning tree matrix and array into a csv file, and constructing an interface file with the GIS platform;

[0102] Here, in the process of constructing the minimum spanning tree network at the online level, similar technical effects can be obtained by changing the format of the interface files at each stage, adding and adjusting the fields contained in the files. In addition, the generation of the minimum spanning tree network by other software or the use of GIS secondary development plug-ins can also complete the entire analysis process similar to this application in the GIS platform, which will not be repeated here.

[0103] Step S606, adding the array storage file to the GIS platform, and generating a point layer using the xy point conversion function;

[0104] Step S607, adding the minimum spanning tree interface file to the GIS platform, and using the xy to line function to generate a line layer;

[0105] Step S608, obtaining a conceptual line network according to the point layer and the line layer.

[0106] Specifically, after the analysis point set is determined, how to connect these points to construct a conceptual line network is the key issue to be answered in line-level analysis. Different from the traditional method of "stringing lines" based on the urban transportation axis in the surface-point-line hierarchical analysis method, this application uses the minimum spanning tree as the theoretical basis for constructing a conceptual line network, that is, first constructing a minimum spanning tree based on the analysis point set in a quantitative way to ensure that all points in the point set are connected at the lowest cost from a spatial perspective, thereby forming a connected network, and this network is the most basic skeleton of the urban rail transit network, that is, the conceptual line network in the surface-point-line hierarchical analysis method.

[0107] Import the data file of the analysis point set V(G) into MATLAB to form an array coorl, in which the first column stores the x-coordinate, the second column stores the y-coordinate, and the row number is consistent with the point number.

[0108] According to the array coorl, a weighted adjacency matrix D based on the analysis point set V(G) is constructed, where the row and column numbers correspond to the row numbers in coorl, indicating the number of the point, and D(i, j) represents the Euclidean distance between point i and point j.

[0109] Based on the weighted adjacency matrix D, the minimum spanning tree matrix T of the analysis point set V(G) is obtained through the Prim algorithm or the Kruskal algorithm, where each record represents an edge in the minimum spanning tree, and the fields QD and ZD store the starting number and end number of each edge respectively.

[0110] According to the minimum spanning tree matrix T and array coorl, the interface file mt_gis.csv with the GIS software is established. The interface file contains QD, ZD, QDx, QDy, ZDx, and ZDy, which represent the starting and ending numbers and corresponding coordinates of the minimum spanning tree, respectively. That is, QD represents the starting number, ZD represents the ending number, QDx represents the horizontal coordinate of the starting number, QDy represents the vertical coordinate of the starting number, ZDx represents the horizontal coordinate of the ending number, and ZDy represents the vertical coordinate of the ending number.

[0111] Add the array storage file coorl.csv file to the GIS platform, use the xy to point function to generate a point layer, add the minimum spanning tree interface file to the GIS platform, and use the xy to line function to generate a line layer, so as to intuitively generate a skeleton concept line network based on the minimum cost of the analysis point set V(G). On this basis, planners can further improve the connectivity of the network by increasing the connection between points and construct different comparison plans.

[0112] Compared with the traditional urban rail transit surface point line analysis method, this application has the following advantages:

[0113] 1. It can provide a quantitative basis for the division of urban clusters

[0114] In the traditional urban rail transit surface point line analysis method, there are two main methods for demarcating the boundaries of urban clusters: one is to demarcate clusters based on administrative boundaries, road boundaries, natural barriers, etc.; the other is to demarcate a cluster with a relatively vague boundary based on the conventional concept of districts. Both of the above division methods are subjective.

[0115] This application is based on mobile phone signaling data and quantitatively divides the boundaries of population-concentrated clusters and job-concentrated clusters based on population or job number, providing scientific data support for planners to judge the distribution of population-concentrated areas and job-concentrated areas.

[0116] 2. It can provide quantitative basis for the calibration of important functional points in the city

[0117] In the traditional urban rail transit surface, point and line analysis method, the data calibration method of important urban functional points is manual selection and judgment. This method has the following disadvantages: 1) The workload of manual judgment of important functional points is large; 2) Planners need to have a more accurate and profound understanding of the city’s economic and social conditions; 3) Manual point judgment lacks sufficient quantitative basis, which is not conducive to forming a relatively consistent underlying consensus.

[0118] This application is based on big data analysis and multivariate clustering methods to obtain important functional points in the city, supporting planners to determine the distribution of important nodes in the city. Through big data analysis, the number of points and point selection criteria are guaranteed, the workload of manually determining points one by one is reduced, and the distribution of important nodes in the city is presented more objectively.

[0119] 3. Provides a quantitative basis for network construction at the line level

[0120] The traditional surface-point-line hierarchical analysis method mainly relies on qualitative analysis in the process of constructing the conceptual line network, which leads to the lack of a quantitative basis for the basic structure of the conceptual line network, and the whole process is highly subjective. This application establishes a quantitative basis for line-level analysis by constructing a weighted adjacency matrix between points. The minimum spanning tree network (backbone conceptual line network) constructed on this basis represents the minimum cost network required to ensure the connectivity of the analysis point set V(G), and is the common basis for all conceptual line network comparison schemes. Further research on the scheme based on this network can effectively build consensus, avoid excessive divergence of the scheme, and improve the quantitative level in the process of constructing the conceptual line network. At the same time, the establishment of a standardized processing flow for the entire process and the clarification of interface documents between each link greatly improve the efficiency of the entire analysis process.

[0121] In summary, this application is a practical, quantifiable, and standardized data automatic processing process based on the urban rail transit network planning stage. Quantitative data analysis replaces the subjective judgment of planners, which helps to improve the scientificity and rationality of urban rail transit planning.

[0122] Embodiment 2:

[0123] Figure 2 A schematic diagram of a GIS-based urban rail transit network planning device provided in an embodiment of the present invention.

[0124] Reference Figure 2 , the device comprises:

[0125] A geographic information data acquisition module is used to acquire geographic information data, which includes administrative boundary data of a target city, road boundary data of a target city, population job distribution data of a target city, and POI point data of a target city;

[0126] The classification module is used to classify the POI point data through a multivariate clustering algorithm to obtain the points of each residential group in the current urban situation;

[0127] The analysis point set acquisition module is used to form the current situation analysis point set from the points of each residential group in the city and other passenger flow distribution points. The current situation analysis point set and the planning analysis point set together constitute the analysis point set in the surface point line hierarchical analysis method;

[0128] A storage module, used to store the analysis point set in the form of a data list; wherein the analysis point set includes a point sequence number, a point name, an x ​​coordinate and a y coordinate;

[0129] The conceptual line network acquisition module is used to obtain the conceptual line network by passing the analysis point set through the minimum spanning tree algorithm.

[0130] Furthermore, the concept line network acquisition module is specifically used for:

[0131] Importing the analysis point set into matlab to generate an array;

[0132] Store the array into a csv file to obtain an array storage file;

[0133] Constructing a weighted adjacency matrix of the analysis point set according to the array;

[0134] The weighted adjacency matrix is ​​passed through the Prim algorithm or the Kruskal algorithm to obtain the minimum spanning tree matrix of the analysis point set;

[0135] The minimum spanning tree matrix and the array are stored in a csv file, and an interface file with the GIS platform is constructed;

[0136] Add the array storage file to the GIS platform, and generate a point layer using the xy point conversion function;

[0137] Add the minimum spanning tree interface file to the GIS platform and use the xy to line function to generate a line layer;

[0138] Based on the point layer and the line layer, a conceptual line network is obtained.

[0139] An embodiment of the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the GIS-based urban rail transit network planning method provided in the above embodiment are implemented.

[0140] An embodiment of the present invention also provides a computer-readable medium having a non-volatile program code executable by a processor, wherein a computer program is stored on the computer-readable medium, and when the computer program is executed by the processor, the steps of the GIS-based urban rail transit network planning method of the above embodiment are executed.

[0141] The computer program product provided in the embodiment of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the method described in the previous method embodiment. The specific implementation can be found in the method embodiment and will not be repeated here.

[0142] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system and device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0143] In addition, in the description of the embodiments of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0144] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0145] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0146] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes 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 invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A GIS-based urban rail transit network planning method, characterized in that: The method comprises: Acquire geographic information data, the geographic information data including administrative boundary data of the target city, road boundary data of the target city, population job distribution data of the target city, and POI point data of the target city; Classify the POI point data using a multivariate clustering algorithm to obtain the points of each residential group in the current urban situation; The points of each residential group in the current situation of the city and other passenger flow distribution points are combined into a current situation analysis point set, and the current situation analysis point set and the planning analysis point set together constitute the analysis point set in the surface point line hierarchical analysis method; The analysis point set is stored in the form of a data list; wherein the analysis point set includes a point sequence number, a point name, an x ​​coordinate, and a y coordinate; The analysis point set is passed through a minimum spanning tree algorithm to obtain a conceptual line network.

2. The GIS-based urban rail transit network planning method according to claim 1 is characterized in that: The analysis point set is passed through the minimum spanning tree algorithm to obtain a concept line network, including: Importing the analysis point set into matlab to generate an array; Store the array into a csv file to obtain an array storage file; Constructing a weighted adjacency matrix of the analysis point set according to the array; The weighted adjacency matrix is ​​subjected to Prim's algorithm or Kruskal's algorithm to obtain a minimum spanning tree matrix of the analysis point set; The minimum spanning tree matrix and the array are stored in the csv file, and an interface file with the GIS platform is constructed; Add the array storage file to the GIS platform, and generate a point layer using the xy point conversion function; Add the minimum spanning tree interface file to the GIS platform, and use the xy to line function to generate a line layer; The concept line network is obtained according to the point layer and the line layer.

3. The GIS-based urban rail transit network planning method according to claim 1 is characterized in that: The POI point data is classified by a multivariate clustering algorithm to obtain the points of each residential group in the current urban situation, including: A group of points that are close in distance and concentrated are selected from the POI point data as a residential group, and the centroid of the residential group is used as a representative; The longitude, latitude or plane x, y coordinates of each residential POI point are used as distance parameters; The distance parameter is input into the GIS platform, and the GIS platform clusters the multiple residential groups according to the distance parameter to obtain the location of each residential group in the current situation of the city.

4. The GIS-based urban rail transit network planning method according to claim 1, characterized in that: The method further comprises: Cleaning the geographic information data to obtain cleaned geographic information data; The cleaned geographic information data is imported into the GIS platform.

5. The GIS-based urban rail transit network planning method according to claim 1, characterized in that: The method further comprises: Obtaining the population job distribution data from mobile phone signaling data; The administrative boundary data, the road boundary data and the POI point data are obtained from an electronic map.

6. The GIS-based urban rail transit network planning method according to claim 1, characterized in that: The method further comprises: In the GIS platform, the geographic information data is drawn according to the contour line control operation to obtain the population and job distribution contour lines of the target city; Taking any of the distribution contour lines of the distribution positions as a reference, the population of the target city is divided into a plurality of cluster areas; The analysis boundary of the surface level in the rail transit network analysis is determined based on the multiple cluster areas.

7. A GIS-based urban rail transit network planning device, characterized in that: The device comprises: A geographic information data acquisition module, used to acquire geographic information data, wherein the geographic information data includes administrative boundary data of a target city, road boundary data of the target city, population job distribution data of the target city, and POI point data of the target city; A classification module is used to classify the POI point data through a multivariate clustering algorithm to obtain the points of each residential group in the current urban situation; An analysis point set acquisition module is used to form a current analysis point set from the points of each residential group in the current city and other passenger flow distribution points. The current analysis point set and the planning analysis point set together constitute the analysis point set in the surface-point-line hierarchical analysis method; A storage module, used to store the analysis point set in the form of a data list; wherein the analysis point set includes a point sequence number, a point name, an x ​​coordinate and a y coordinate; The concept line network acquisition module is used to obtain the concept line network by applying the minimum spanning tree algorithm to the analysis point set.

8. The GIS-based urban rail transit network planning device according to claim 7, characterized in that: The concept line network acquisition module is specifically used for: Importing the analysis point set into matlab to generate an array; Store the array into a csv file to obtain an array storage file; Constructing a weighted adjacency matrix of the analysis point set according to the array; The weighted adjacency matrix is ​​subjected to Prim's algorithm or Kruskal's algorithm to obtain a minimum spanning tree matrix of the analysis point set; The minimum spanning tree matrix and the array are stored in the csv file, and an interface file with the GIS platform is constructed; Add the array storage file to the GIS platform, and generate a point layer using the xy point conversion function; Add the minimum spanning tree interface file to the GIS platform, and use the xy to line function to generate a line layer; The concept line network is obtained according to the point layer and the line layer.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

10. A computer readable medium having a non-volatile program code executable by a processor, characterized in that: The program code enables the processor to execute the method according to any one of claims 1 to 6.

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