A Method for Analyzing the Job-Housing Coverage Rate of Public Transport Based on Multi-Source Data

Abstract

The present invention discloses a method for analyzing the coverage rate of residential and workplace locations in public transportation based on multi-source data, including the following steps. (1) Identify the number of residential population and employment positions within the range of base stations according to mobile signaling data; (2) Obtain the land use division data and building area data of the target area, and further subdivide the land into covering grids, and allocate the number of population and positions to the grids intersecting with the land; (3) Calculate the real-time path points from the centroid points of each grid to the public transportation stations based on the public transportation station data and path planning API data of the target area; (4) Calculate the three-dimensional path distance in combination with the DEM elevation data of the target area; (5) Set a coverage distance threshold, screen the centroid point elements within the threshold, calculate the residential population and employment positions covered by public transportation, and calculate the coverage rate of residential and workplace locations. The present invention is based on multi-source data and provides a tool basis for the analysis of the distribution of public service facilities, the design of urban road network forms, etc.

Description

Technical Field

[0001] The present invention relates to a method for analyzing the coverage rate of employment and residence in public transportation based on multi-source data, belonging to the technical fields of urban planning and urban transportation systems. Background Art

[0002] At present, the method for calculating the public transportation coverage rate mainly calculates the spatial buffer of stations. This calculation is proposed under the premise of an ideal grid road network and is measured based on the covered land area. Although this calculation method had certain convenience and adaptability in the past, nowadays, the country advocates "common prosperity" and "universal and inclusive public services". Reflecting on it, the static measurement of land space coverage cannot truly calculate the actual resident and employed population substantially covered by the bus system. Taking the covered population ratio as the main indicator, Singapore expects that 80% of households will live within a 10-minute walking distance of subway stations in 2030. As an important way to build a "bus metropolis", public transportation should strive to promote social fairness and achieve equality of development opportunities. Therefore, a new calculation method for the coverage rate of employment and residence in public transportation based on the distribution of population and jobs is needed.

[0003] Furthermore, the traditional calculation process of station buffer is either based on the ideal Euclidean distance or based on the cost matrix of the existing OD road network, without considering the dynamic changes of traffic flow in the actual road network operation. Nowadays, with the help of the electronic map path planning API, the real-time travel path can be obtained, which is more in line with the actual situation. However, the OD pair distance directly returned by the path planning API is based on the spatial projection distance of the coordinate system and does not consider the influence of factors such as elevation, resulting in a certain error. Therefore, it is necessary to perform secondary processing on its path points in the GIS platform, and the obtained three-dimensional travel distance is more in line with the travel distance actually perceived by residents. Summary of the Invention

[0004] The technical problem to be solved by the present invention: The traditional calculation method based on the station buffer is simple and rough, does not calculate the coverage for the employed and resident population, is not based on the actual road network, and does not consider the influence of the actual elevation.

[0005] To solve the above technical problems, the present invention provides a method for analyzing the coverage rate of employment and residence in public transportation (including subways) based on multi-source data. Using mobile phone signaling and Internet open platform data, combined with DEM data and building land data, it accurately and efficiently calculates the coverage rate of employment and residence of public transportation stations, providing a tool basis for the analysis of the distribution of public service facilities, the design of urban road network patterns, etc.

[0006] The technical solution adopted by the present invention to solve its technical problems is: A method for analyzing the coverage rate of public transportation based on multi-source data, and the analysis method includes the following steps:

[0007] S1. Obtain the mobile base station data of the target area, divide the Thiessen polygon centered on the base station as the service scope of the mobile base station, and identify the number of resident population and employment positions within the base station scope;

[0008] S2. Obtain the land use division data and building area data of the target area, count the total building area of each residential land and non-residential land, allocate the population and number of positions to the residential land and non-residential land, and estimate the number of resident population and employment positions of each plot;

[0009] S3. Conduct a coverage grid division on the target area, allocate the population and number of positions to the grids intersecting with the land use, and calculate the number of resident population and employment positions in each grid area;

[0010] S4. Calculate the real-time path points from the centroid point of each grid to the public transportation stations based on the public transportation station data and path planning API data of the target area;

[0011] S5. Calculate the three-dimensional path distance in combination with the DEM elevation data of the target area;

[0012] S6. Set a coverage distance threshold, filter the centroid point elements within the threshold, calculate the resident population and employment positions covered by public transportation, and calculate the job-housing coverage rate.

[0013] This application is further set as follows: In step S2, it includes the following steps:

[0014] S11. Clean the noise data such as ping-pong data and drift data in the mobile signaling data;

[0015] S12. Set the determination rules for the resident population and employment positions, determine the one-to-one correspondence between the base station and the mobile signaling data according to the base station code, and count the quantity information of the resident population and employment positions of the base station;

[0016] This application is further set as follows: In step S12, considering that some users will choose to turn off the phone, it is determined that as long as the distance between the base station where the signal was last received the previous day and the base station where the signal starts to be received the next day is less than 800m, its information will also be included in the resident population information;

[0017] This application is further set as follows: In step S2, it includes the following steps:

[0018] S21. Conduct a spatial association on the land use division data and building area data, associate the building area data to the land use division data, and summarize the building area to obtain the total building area data of each piece of land;

[0019] S22. Count the total building area of residential land and non-residential land within the base station scope, including the following two situations:

[0020] (1) If the residential land or non-residential land is completely included within the base station service area, then the total floor area of the residential land or non-residential land shall be fully included in the floor area served by the base station;

[0021] (2) If the residential land or non-residential land intersects with the base station service area but is not completely included, then the floor area of the intersection part between the two shall be recorded as the floor area served by the base station;

[0022] S23. Allocate the population and the number of jobs to the residential land and non-residential land covered by the base station, and estimate the residential population and the number of jobs for each plot;

[0023] The calculation formula is as follows;

[0024]

[0025] Among them, n is the residential population or the number of jobs of a certain plot, and m is the number of residential or non-residential plots intersecting with the base station service area; N i is the residential population or the number of jobs of a certain base station i; R i is the total floor area of the residential land or the total floor area of the non-residential land of a certain base station i; r i is the floor area of a certain residential land or non-residential land.

[0026] This application is further set as follows: In step S3, the following steps are included:

[0027] S31. Conduct a covering grid division on the target area, and the shapes and sizes of each grid are the same as each other;

[0028] S32. Overlay the grid area and the land division area according to the spatial position, allocate the population and the number of jobs to the grids intersecting with the land, and calculate the residential population and the number of jobs of each grid area, including the following two situations;

[0029] (1) If a certain grid completely contains a certain plot, then allocate all the population and the number of jobs of the plot to this grid;

[0030] (2) If a part of a certain plot is included in the boundary of a certain grid, then only record the population and the number of jobs of the intersection part as the population and the number of jobs of the grid;

[0031] The calculation formula is as follows:

[0032]

[0033] Among them, G is the residential population or the number of jobs of a certain grid; k is the number of plots intersecting with this grid; n j is the residential population or the number of jobs of plot j; S is the floor area of the residential land or non-residential land within the grid; S nIs the building area of the total residential or non-residential land use for a certain plot of land.

[0034] If a certain plot of land is completely within a certain grid, then S = S n .

[0035] This application is further set as follows: In step S4, it includes the following steps:

[0036] S41. Obtain the bus stop data of the target area;

[0037] S42. Extract the centroid points of each grid. Taking the centroid point of each grid as the starting point and the public transportation stop as the ending point, establish an OD pair, obtain the specific longitude and latitude information, and input it as part of the parameters into the API for walking path planning of the electronic map to obtain each real-time path point of the OD pair, denoted as the point set X = {(X r , Y r ), (X r , Y1), ……(X m+n , X m+n ), (X s , Y s )};

[0038] This application is further set as follows: In step S42, the point coordinates input into the electronic map path planning API need to be converted into the coordinate system required by the map;

[0039] This application is further set as follows: In step S5, it includes the following steps:

[0040] S51. Obtain the DEM data of the target area and perform `ArcGIS georegistration, extract the corresponding elevation values of each path point, and obtain a point set X' containing elevation data = {(X r , Y r , H r ), (X r ,, Y1, H1), ……(X m+n , X m+n , H m+n ), (X s , Y s , H s )}, as Figure 6 shown;

[0041] S52. Calculate the three-dimensional path distance, and the calculation formula is;

[0042]

[0043]

[0044] where, d nThe actual path distance of the road network between two adjacent points; D is the actual path distance of the road network from the starting point to the ending point; H n is the elevation value of a certain point; X n is the longitude coordinate of a certain point; Y n is the latitude coordinate of a certain point;

[0045] This application is further configured as follows: In step S51, before performing georegistration, each path point needs to be converted from a geographic coordinate system to a projected coordinate system;

[0046] This application is further configured as follows: In step S6, the following steps are included:

[0047] S61. Import the obtained OD travel shortest distance data into ArcGIS, and assign values to each dot matrix according to the spatial relationship;

[0048] S62. Perform spatial matching based on the dot matrix data and the grid cells to obtain the travel shortest distance data of each grid cell;

[0049] S63. Set a distance threshold, screen the grid elements within the threshold, and calculate the residential population and employment positions covered by public transportation:

[0050] The calculation formula is:

[0051]

[0052]

[0053]

[0054] Among them, p represents the number of residential population or employment positions covered by public transportation stations; G j is the number of residential population or employment positions of a certain grid j; w represents the weight. When the distance D from the grid centroid to the station is less than the coverage distance threshold l, w is 1, otherwise it is 0.

[0055] S64. Calculate the job-housing coverage rate of a certain area. The calculation formula is:

[0056]

[0057] Among them, s represents the coverage rate of the residential population or employment positions of public transportation stations in a certain area; p represents the number of residential population or employment positions covered by public transportation stations; N i is the number of residential population or employment positions of a certain base station i. Among them, s represents the coverage rate of the residential population or employment positions of public transportation stations in a certain area;

[0058] Compared with the prior art, the beneficial technical effects of the present invention are:

[0059] The present invention utilizes big data such as mobile phone signaling data and Internet map data, as well as traditional DEM elevation data, building area measurement data, etc., to construct a more accurate and user-friendly calculation method for the job-housing coverage rate of public transportation, quantifying the specific job positions and resident population covered by public transportation. The new calculation method for the job-housing coverage rate enriches the definition of the coverage rate of bus stops (including subways), makes up for the problems of slow update and time-consuming effort of traditional geographical data, and can provide a tool basis for the analysis of the distribution of public service facilities, the design of urban road network patterns, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 FIG. is a flowchart of the method for analyzing the job-housing coverage rate of public transportation stations based on multi-source data according to the present invention.

[0061] Figure 2 FIG. is a process diagram for calculating the number of resident population and job positions in plots according to the present invention.

[0062] Figure 3 FIG. is a distribution map of the resident population of each plot in a specific example of the present invention.

[0063] Figure 4 FIG. is a distribution map of the job positions of each plot in a specific example of the present invention.

[0064] Figure 5 FIG. is a layout map of the distribution of bus stops in a specific example of the present invention.

[0065] Figure 6 FIG. is a three-dimensional distance relationship diagram of each path point in the OD pairs collected according to the present invention.

[0066] Figure 7 FIG. is a distribution map of the bus-covered resident population within 500 m in a specific example of the present invention.

[0067] Figure 8 FIG. is a distribution map of the bus-covered job positions within 500 m in a specific example of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0068] The following further elaborates on the specific embodiments of the present invention in conjunction with the accompanying drawings of the specification and examples.

[0069] The present invention designs a method for analyzing the job-housing coverage rate of public transportation stations based on multi-source data, and its implementation flowchart is as shown in Figure 1 FIG. Taking the analysis of the job-housing coverage rate of bus stops in Kunshan City, Jiangsu Province as an example, a specific description is given as follows, including the following steps:

[0070] In the first step, obtain the mobile base station data of the target area. Divide the Thiessen polygons centered on the base stations as the service scopes of the mobile base stations, and define unique numbers for each scope, which are 1, 2, 3, …, i.

[0071] In this example, Thiessen polygons are divided for China Mobile base stations within the administrative scope of Kunshan City. There are 2,602 research units in total, among which 974 research units cover the urban core area.

[0072] In the second step, obtain the mobile signaling data of the target area, clean the data, set the judgment rules for the resident population and employment positions within the base station scope, and identify the number of resident population and employment positions within the base station scope; see Figure 2 as shown.

[0073] In this example, after cleaning redundant data, ping-pong data, drift data, etc., the daily average effective data volume is 558.2 million.

[0074] In this example, the user information monitored and staying from 1:00 - 7:00 am on average is determined as the resident population information of this base station, which is dataset A; the working periods are set as 9:00–11:30 and 14:00–17:00 on weekdays, and the user information with the average daily connection time to the base station exceeding 3 hours is determined as the employment population information of this base station, which is dataset B;

[0075] In this example, for users who choose to turn off their phones at night, it is necessary to determine the distance between the base station where they received the last signal the previous day and the base station where they start receiving signals the next day. If it is less than 800m, it will be determined as the resident population information of the base station where they received the last signal the previous day;

[0076] In this example, based on the mobile signaling data, the identified resident population is approximately 400,000, and the employment positions are approximately 210,000.

[0077] In the third step, perform spatial association on the land use division data and the building area data, associate the building area data to the land use division data, and summarize the building areas to obtain the total building area data for each piece of land; count the total building areas of residential land and non-residential land within the base station scope, and record them as dataset C and dataset D respectively, including the following two situations:

[0078] (1) If the residential land or non-residential land is completely included within the base station service scope, then all the building areas of this residential land or non-residential land are included in the building areas served by the base station;

[0079] (2) If the residential land or non-residential land intersects with the base station service scope but is not completely included, then the building area of the intersection part of the two is recorded as the building area served by the base station;

[0080] Allocate the population and the number of jobs to the residential and non-residential lands covered by the base stations, and estimate the resident population and the number of jobs in each plot, which are respectively recorded as dataset E and dataset F;

[0081] The calculation formula is;

[0082]

[0083] Among them, n is the resident population or the number of jobs in a certain plot, and m is the number of residential or non-residential plots intersecting with the base station service area; N i is the resident population or the number of jobs of a certain base station i; R i is the total building area of the residential land or the total building area of the non-residential land of a certain base station i; r i is the building area of a certain residential land or non-residential land.

[0084] In this example, the distribution of the resident population and the number of jobs allocated to each plot is as shown in Figure 3 、 4 ;

[0085] In practical applications, the third step includes the following steps;

[0086] In this example, through tools such as Intersect and Identify in ArcGIS, the building area data is associated with the land division data. The building area of the residential land in the core area of Kunshan City is about 2,154 hectares, and the building area of the non-residential land (excluding park green spaces, road facilities land, etc.) is about 2,651 hectares;

[0087] Fourth step, conduct a covering grid division on the target area, and the shapes and sizes of each grid are the same. Superimpose each grid area and the land division area according to the spatial position, allocate the population and the number of jobs to the grids intersecting with the land, and calculate the resident population and the number of jobs in each grid area, which are recorded as dataset G and dataset H, including the following two situations;

[0088] (1) If a certain grid completely contains a certain plot, then allocate all the population and the number of jobs of that plot to that grid;

[0089] (2) If a part of a certain plot is contained in the boundary of a certain grid, then only record the population and the number of jobs of the intersecting part as the population and the number of jobs of the grid;

[0090] The calculation formula for the resident population and the number of jobs in each grid area is:

[0091]

[0092] Among them, G is the resident population or the number of jobs in a certain grid; k is the number of plots intersecting with that grid; n jis the number of residential population or employment positions in plot j; S is the building area of residential land or non-residential land within the grid; S n is the total building area of residential land or non-residential land of a certain plot.

[0093] If a certain plot is completely located within a certain grid, then S = S n .

[0094] In this example, the target area is divided into grids of 30m * 30m.

[0095] Step 5: Obtain the public transportation station data of the target area; extract the centroid points of each grid, and the centroid contains the number of residential population and employment positions of each grid. Taking the centroid point of each plot as the starting point and the public transportation station as the ending point to establish OD pairs, obtain the specific longitude and latitude information, and input it as part of the parameters into the API of the electronic map walking path planning to obtain each real-time path point of the OD pair, denoted as the point set X = {(X r , Y r ), (X r , Y1), ……(X m+n , X m+n ), (X s , Y s );

[0096] In this example, through Python programming, using the "Search Service API" of Amap, with "public transportation station" as the keyword, polygon search is used to obtain 1497 public transportation stations within the 500-meter buffer of the research scope. Among them, 1197 are completely within the research scope. The distribution map of bus stops within the research scope is as shown in Figure 5 .

[0097] In practical applications, path planning API interfaces provided by map companies such as Baidu and Amap can be used, but it is necessary to ensure that the OD point pair data is converted into the coordinate system required by the corresponding API. For the returned commuting data in JSON format, directly obtain each real-time path point of the OD pair by accessing the keys of the JSON;

[0098] In this example, the longitude and latitude of the starting and ending points are converted into the Mars coordinate system and then input into the API of the electronic map walking path planning.

[0099] Step 6: Obtain the DEM data of the target area and perform ArcGIS georegistration, extract the corresponding elevation values of each path point, and obtain the point set X' containing elevation data = {(X r , Y r , H r ), (X r , Y1, H1), ……(X m+n , X m+n , H m+n), (X s , Y s , H s )}, ; Calculate the three-dimensional path distance, and the calculation formula is;

[0100]

[0101]

[0102] Among them, d n is the actual path distance of the road network between two adjacent points; D is the actual path distance of the road network from the starting point to the end point; H n is the elevation value of a certain point; X n is the longitude coordinate of a certain point; Y n is the latitude coordinate of a certain point;

[0103] In this example, before performing georegistration, it is necessary to convert the WGS geographic coordinate system into the UTM projected coordinate system;

[0104] Step 7: Import the obtained OD travel shortest distance data into ArcGIS, assign values to each dot matrix according to the spatial relationship, perform spatial matching based on the dot matrix data and grid cells, and obtain the travel shortest distance data of each grid cell. Set the coverage distance threshold, filter the centroid point features within the threshold, calculate the resident population and employment positions covered by public transportation, and calculate the job-housing coverage rate.

[0105] The number of resident population and employment positions covered by public transportation, the calculation formula is:

[0106]

[0107]

[0108]

[0109] Among them, p represents the number of resident population or employment positions covered by public transportation stations; G j is the number of resident population or employment positions of a certain grid j; w represents the weight. When the distance D from the grid centroid to the station is less than the coverage distance threshold l, w is 1, otherwise it is 0.

[0110] S64. Calculate the job-housing coverage rate of a certain area, and the calculation formula is:

[0111]

[0112] Among them, s represents the coverage rate of the resident population or employment positions of public transportation stations in a certain area; p represents the number of resident population or employment positions covered by public transportation stations; N iis the number of residents or job positions of a certain base station i. Among them, s represents the coverage rate of residents or job positions at public transportation stations in a certain area;

[0113] In this example, the dot matrix data is associated with the grid cell features through the connection function based on spatial location in ArcGIS; in this example, the distance thresholds are set to 300m, 400m, and 500m respectively. The distribution of the resident population covered by public transportation and the distribution of job positions within 500m are as Figure 7 , 8 shown;

[0114] In this example, as shown in Table 1, the difference between the resident population and job positions covered within 500 meters in the core area of Kunshan is not significant, about 77%. The coverage rate of the resident population within 400 meters is about 58%, and the coverage rate of job positions is 78%. The coverage rate of the resident population within 300 meters is 40%, and the coverage rate of job positions is 65%. Generally speaking, the coverage rate of job positions in the core area is greater than the coverage rate of the resident population.

[0115] Table 1 Public transportation job-housing coverage rate in the core area of Kunshan

[0116]

[0117]

[0118] There are many specific implementation methods and approaches for the present invention. The above description is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention. Each component not clearly defined in this embodiment can be implemented by the prior art.

Claims

1. A method for analyzing the job-housing coverage rate of public transportation based on multi-source data, characterized in that, The analysis method belongs to the following steps: S1. Obtain the mobile base station data of the target area, divide the Thiessen polygon centered on the base station as the service range of the mobile base station, and identify the number of resident population and employment positions within the base station range; S2. Obtain the land use division data and building area data of the target area, count the total building area of each residential land and non-residential land, allocate the population and number of positions to the residential land and non-residential land, and estimate the number of resident population and employment positions of each plot; S3. Conduct a coverage grid division on the target area, allocate the population and number of positions to the grids intersecting with the land use, and calculate the number of resident population and employment positions in each grid area; S4. Calculate the real-time path points from the centroid point of each grid to the public transportation stations based on the public transportation station data and path planning API data of the target area; S5. Calculate the three-dimensional path distance in combination with the DEM elevation data of the target area; S6. Set a coverage distance threshold, screen the centroid point elements within the threshold, calculate the resident population and employment positions covered by public transportation, and calculate the employment-residence coverage rate.

2. The method for analyzing the job-housing coverage rate of public transportation based on multi-source data according to claim 1, wherein In step S1, the following steps are included: S11. Clean the noise data in the mobile signaling data, including: ping-pong data, drift data; S12. Set the determination rules for the resident population and employment positions, determine the one-to-one correspondence between the base station and the mobile signaling data according to the base station code, and count the information on the number of resident population and employment positions of the base station.

3. The method for analyzing the job-housing coverage rate of public transportation based on multi-source data according to claim 2, wherein In step S12, considering that some users will choose to turn off the phone, it is determined that as long as the distance between the base station where the signal was last received the previous day and the base station where the signal starts to be received the next day is less than 800m, its information will also be included in the resident population information.

4. The method for analyzing the job-housing coverage rate of public transportation based on multi-source data according to claim 1, wherein In step S2, the following steps are included: S21. Conduct a spatial association on the land use division data and the building area data, associate the building area data to the land use division data, and summarize the building area to obtain the total building area data of each piece of land; S22. Count the total building area of residential land and non-residential land within the base station range, including the following two situations: (1) If the residential land or non-residential land is completely included within the base station service range, then the building area of the residential land or non-residential land will be fully included in the building area served by the base station; (2) If the residential land or non-residential land intersects with the base station service range but is not completely included, then the building area of the intersection part between the two will be recorded as the building area served by the base station; S23. Allocate the population and number of positions to the residential land and non-residential land covered by the base station, and estimate the number of resident population and employment positions of each plot. The calculation formula is; Among them, n is the number of residential population or employment positions in a certain plot, and m is the number of residential or non-residential plots intersecting with the base station service area; N i is the number of residential population or employment positions of a certain base station i; R i is the total building area of residential land or the total building area of non-residential land of a certain base station i; r i is the total building area of a certain residential land or non-residential land.

5. The method for analyzing the job-housing coverage rate of public transportation based on multi-source data according to claim 1, wherein In step S3, the following steps are included: S31. Conduct a coverage grid division on the target area, and the shape and size of each grid are the same as each other; S32. Overlay the grid area and the land use division area according to the spatial position, allocate the population and number of positions to the grids intersecting with the land use, and calculate the number of resident population and employment positions in each grid area, including the following two situations; (1) If a certain grid completely contains a certain plot, then all the population and number of positions of the plot will be allocated to the grid; (2) If a grid boundary contains a part of a plot, only the population and number of jobs in the intersecting part are recorded as the population and number of jobs of the grid; The calculation formula is: Among them, G is the number of resident population or employment positions in a certain grid; K is the number of plots intersecting with this grid; n j is the number of resident population or employment positions in plot j; S is the building area of residential land or non-residential land within the grid; S n is the total building area of residential land or non-residential land of a certain plot; If a certain plot of land is completely within a certain grid, then S = S n .

6. The method for analyzing the job-housing coverage rate of public transportation based on multi-source data according to claim 1, wherein, In step S4, the following steps are included: S41. Obtain the bus stop data of the target area; S42. Extract the centroid points of each grid. Taking the centroid point of each grid as the starting point and the public transportation station as the ending point, establish OD pairs, obtain the specific longitude and latitude information, and input it as part of the parameters into the API for pedestrian path planning on the electronic map to obtain each real-time path point of the OD pair, denoted as the point set X = {(X r , Y r ), (X1, Y1), …… (X m+n , X m+n ), (X s , Y s )}.

7. A method for analyzing the job-housing coverage rate of public transportation based on multi-source data according to claim 1, characterized in that In step S42, the point coordinates input into the electronic map path planning API need to be converted into the coordinate system required by the map.

8. A method for analyzing the job-housing coverage rate of public transportation based on multi-source data according to claim 1, characterized in that, In step S5, the following steps are included: S51. Obtain the DEM data of the target area and perform ArcGIS georegistration, extract the corresponding elevation values of each path point, and obtain a point set X' = {(X r , Y r , H r ), (X1, Y1, H1), …… (X m+n , Y m+n ,, H m+n ), (X s , Y s , H s )}; S52. Calculate the three-dimensional path distance, and the calculation formula is; where d n is the actual path distance of the road network between two adjacent points; D is the actual path distance of the road network from the starting point to the ending point; H n is the elevation value of a certain point; X n is the longitude coordinate of a certain point; Y n is the latitude coordinate of a certain point.

9. The method for analyzing the job-housing coverage rate of public transportation based on multi-source data according to claim 8, wherein In step S5, each path point needs to be converted into a projection coordinate system.

10. The method for analyzing the job-housing coverage rate of public transportation based on multi-source data according to claim 1, wherein In step S6, the following steps are included: S61. Import the obtained OD travel shortest distance data into ArcGIS and assign values to each dot matrix according to the spatial relationship; S62. Based on the dot matrix data and grid cells, perform spatial matching to obtain the travel shortest distance data of each grid cell; S63. Set a distance threshold, filter the grid elements within the threshold, and calculate the resident population and employment positions covered by public transportation. The calculation formula is: where p represents the number of resident population or employment positions covered by a public transportation stop; G j is the number of resident population or employment positions in a certain grid j; w represents the weight, which is 1 when the distance D from the grid centroid to the stop is less than the coverage distance threshold l, and 0 otherwise; S64. Calculate the job-housing coverage rate of a certain area, and the calculation formula is: Among them, s represents the coverage rate of the resident population or employment positions at the public transportation stations in a certain area; N i is the number of the resident population or employment positions of a certain base station i.

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