A gis-based railway transportation revenue spatial distribution visualization method and system

Abstract

The application discloses a GIS-based railway transportation income space distribution visualization method and system, which comprises the following steps: firstly, obtaining original ticket data in a preset time period; secondly, splitting the original ticket data according to identification information into the data of one or more transportation income parties; then, reconstructing the transportation income distribution of the one or more income parties based on the transportation income category and the data of the one or more transportation income parties; then, converting the coordinates of the one or more transportation income parties into GIS map geographic coordinates; finally, rendering the transportation income of the one or more income parties on a map in one or more display modes based on the converted GIS map geographic coordinates and the reconstructed transportation income distribution of the one or more income parties. Through the above method, efficient and accurate data processing, intuitive geographic visualization display and all-round decision support are realized.

Description

Technical Field This invention belongs to the field of rail transit technology, and specifically relates to a GIS-based method and system for visualizing the spatial distribution of railway transportation revenue. Background Technology

[0001] In existing railway transportation management, the statistics and analysis of transportation revenue are crucial. Accurately understanding the distribution of revenue among various freight forwarding companies, railway line sections, and stations helps railway transportation enterprises to rationally plan transportation routes and allocate transportation capacity resources, and also helps freight forwarding companies optimize their business layout and reduce operating costs.

[0002] However, traditional transportation revenue management methods have many shortcomings in data processing, visualization, and decision support: (1) The separation of economic indicators and spatial entities: Existing revenue displays mostly use tables or simple charts, which are not combined with Geographic Information System (GIS) and cannot intuitively reflect the distribution of revenue in geographic space, which is a gap in dynamic visualization; mainstream GIS freight monitoring systems only display train location / track, and lack rendering of economic indicators. The railway line width / station icons are fixed and cannot reflect the fluctuation of revenue scale; thus, there is a significant gap in the dynamic correlation analysis of economic data and geographic space, and it is urgent to break through the dynamic binding technology of revenue data and geographic entities. (2) Lack of multidimensional analysis capabilities: Station revenue, section revenue, and freight forwarding company revenue belong to different report pages, making it difficult to discover spatial correlation patterns and clearly present the revenue correlation between different entities; (3) Weak decision support function: It cannot simultaneously meet the differentiated needs of railway transportation enterprises and freight forwarding companies. Railway transport companies struggle to optimize the network revenue structure from a holistic perspective, and freight forwarding companies are unable to accurately understand the distribution of their business benefits across different lines and stations. Cross-entity decision-making and collaboration are inefficient and fail to meet the growing demand for intelligent management from enterprises.

[0003] Furthermore, the existing system primarily serves the overall operation and management of railway transportation companies, offering insufficient support for the personalized needs of freight forwarding companies. Simultaneously, it lacks dynamic analysis capabilities over a time dimension, failing to provide companies with historical data retrospectives and trend analysis, thus making it difficult to meet their transportation decision-making needs across different time periods. Summary of the Invention

[0004] To address the aforementioned issues, this invention provides a GIS-based method and system for visualizing the spatial distribution of railway transportation revenue, achieving efficient and accurate data processing, intuitive geographic visualization, and comprehensive decision support.

[0005] The purpose of this invention is to provide a GIS-based method for visualizing the spatial distribution of railway transportation revenue, including: Retrieve raw invoice data within a preset time period; The original invoice data is split according to the identification information, into data for one or more transportation beneficiaries; Based on the data of one or more transportation revenue categories and splits of one or more transportation revenue parties, reconstruct the transportation revenue distribution of one or more revenue parties; Convert the coordinates of one or more transportation beneficiaries into geographic coordinates on a GIS map; Based on the transformed GIS map geographic coordinates and the reconstructed transportation revenue distribution of one or more beneficiaries, the transportation revenue of one or more beneficiaries is rendered on the map using one or more display methods.

[0006] Furthermore, the original invoice data includes freight invoices and miscellaneous expense invoices.

[0007] Furthermore, the identification information includes one or more of the following: pricing section code, station code, and agent unit identifier from the original ticket data; Data from one or more transport revenue providers includes data from their respective pricing sections, stations, and / or agents.

[0008] Furthermore, converting the coordinates of one or more transportation beneficiaries into geographic coordinates on a GIS map includes, Obtain the coordinates of each pricing section, station, and agency; Coordinate transformation between stations and agencies includes: Based on the station sign and the agent's client sign, query the latitude and longitude coordinates of the station and the agent's location in the coordinate table of the database; The return value for both the station and the agent is a single point coordinate object; The coordinate transformation of the pricing section includes: Multiple railway sections can be located by identifying the section markers of the pricing zones; Find the latitude and longitude coordinates of multiple sampling points in the coordinate table by using the section identifier of the railway section; The pricing segment returns a list of coordinate points.

[0009] Furthermore, based on the transportation revenue categories and the data of one or more transportation revenue providers, the transportation revenue distribution of one or more revenue providers is reconstructed, including: Transportation revenue is categorized into freight, miscellaneous charges, and agency fees. Calculate the transportation revenue of each agent, the transportation revenue of each pricing section and station of the railway line, and the revenue distribution of an individual agent on the railway line and station.

[0010] Furthermore, the transportation revenue distribution of one or more beneficiaries is reconstructed into a detailed revenue item list for pricing sections and stations, a detailed revenue item list for agents, and a detailed revenue list for pricing sections and operating stations included in the agent.

[0011] Furthermore, rendering the transportation revenue of one or more beneficiaries on the map using one or more display methods includes, Calculate the line width value of the pricing section and draw a line map on the GIS map to represent the revenue of the section; Calculate the scatter radius for all stations and plot a scatter plot to represent station revenue; and / or Calculate the radius of the pie chart or sector chart for all agents, and draw a pie chart or sector chart to represent the revenue of the agents. The radius of the pie chart represents the total revenue, and different colors represent different expense items.

[0012] Furthermore, the calculation of the scatter radius of the station includes, Retrieve the maximum (max) and minimum (min) values ​​from the list of station revenues; The radius adjustment amount is calculated based on the difference between the current station's miscellaneous fees and the maximum and minimum values ​​(max and min). Add the constant to the calculated radius adjustment to obtain the radius of the current station scatter points.

[0013] Furthermore, the calculation of the line width value for the pricing section includes: Get the maximum revenue (max) and minimum cost (min) of the list of all pricing intervals; Calculate the width of each pricing segment; Based on the cost and revenue values ​​of the current pricing segment, and the differences from the maximum revenue (max) and minimum cost (min), calculate the adjustment amounts for the width of the outer and inner lines respectively. Add the constant to the calculated external and internal line width adjustments respectively to obtain the external and internal line widths of the pricing section.

[0014] Furthermore, it also includes user interaction, including, Interact with time range query conditions, expense item query conditions, and the global or one or more beneficiary perspectives.

[0015] Furthermore, user interaction also includes calculating the map center point and zoom level to switch map views, specifically including... Set the magnification value; The calculation of the map center point includes, Determine the maximum and minimum ranges of latitude and longitude; Determine the longitude center point and the latitude center point, where the longitude center point is the average of the sum of the maximum and minimum longitude values, and the latitude center point is the average of the sum of the maximum and minimum latitude values. The map center point satisfies: [longitude center point, latitude center point].

[0016] Another objective of this invention is to provide a GIS-based spatial distribution visualization system for railway transportation revenue, comprising: The acquisition module is used to acquire raw invoice data within a preset time period; The processing and calculation module is used to split the original ticket data according to the identification information, dividing it into data for one or more transportation beneficiaries; and Based on the data of one or more transportation revenue categories and splits of one or more transportation revenue parties, reconstruct the transportation revenue distribution of one or more revenue parties; The spatial mapping module is used to convert the coordinates of one or more transportation beneficiaries into geographic coordinates on a GIS map. The visualization module is used to render the transportation revenue of one or more beneficiaries on the map using one or more display methods, based on the transformed GIS map geographic coordinates and the reconstructed distribution of transportation revenue for one or more beneficiaries.

[0017] Furthermore, it also includes a user interaction module for interacting with time range query conditions, cost item query conditions, and the global or one or more beneficiary perspectives.

[0018] The method of this invention acquires raw ticket data from the railway freight system and breaks it down according to identification information to subdivide transportation revenue. This enables precise calculation of the transportation revenue of each agent, the revenue of each pricing section and station on the railway line, and the revenue distribution of an individual agent on the railway line and at the station, significantly improving data processing efficiency and accuracy. Furthermore, by utilizing GIS technology and rendering the transportation revenue of one or more beneficiaries on a map using one or more display methods, the geographical spatial distribution of revenue is presented intuitively, allowing decision-makers to quickly obtain high-value information.

[0019] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A flowchart of a GIS-based method for visualizing the spatial distribution of railway transportation revenue is shown in an embodiment of the present invention. Figure 2 A flowchart of another GIS-based method for visualizing the spatial distribution of railway transportation revenue is shown in an embodiment of the present invention. Figure 3 This invention presents a diagram illustrating the overall revenue of various freight forwarding companies, stations, and pricing sections in an embodiment of the invention. Figure 4 This invention presents a revenue distribution diagram from the perspective of a freight forwarding company and a materials company in an embodiment of the invention. Figure 5 The pie chart shown in this embodiment of the invention is of a freight forwarding company; Figure 6 The diagram illustrates a GIS-based visualization system for the spatial distribution of railway transportation revenue, as described in an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] like Figure 1As shown in the illustration, this invention introduces a GIS-based method for visualizing the spatial distribution of railway transportation revenue. The method includes: first, acquiring raw ticket data within a preset time period; second, splitting the raw ticket data according to identification information into data for one or more transportation revenue recipients; third, reconstructing the transportation revenue distribution of one or more revenue recipients based on the transportation revenue categories and the split data of one or more revenue recipients; fourth, converting the coordinates of one or more transportation revenue recipients into geographic coordinates on a GIS map; and finally, rendering the transportation revenue of one or more revenue recipients on a map using one or more display methods based on the converted GIS map geographic coordinates and the reconstructed transportation revenue distribution of one or more revenue recipients. By acquiring raw ticket data from the railway freight system using the above method and splitting it according to identification information to subdivide transportation revenue, accurate calculations can be achieved for the transportation revenue of each agency unit, the revenue of each pricing section and station on the railway line, and the revenue distribution of a single agency unit on railway lines and stations, significantly improving data processing efficiency and accuracy. Furthermore, by utilizing GIS technology and rendering the transportation revenue of one or more revenue recipients on a map using one or more display methods, the geographic spatial distribution of revenue is presented intuitively, enabling decision-makers to quickly obtain high-value information.

[0024] Specifically, such as Figure 2 As shown, the first step is data acquisition. This involves allowing users to input time range query conditions to filter data within a corresponding time period (i.e., a preset time period). The original invoice data includes freight invoices and miscellaneous expense invoices. However, this is not limited to these; other types of invoices are also applicable to this invention. For example, a user inputs a time range query condition (such as "January 2025 - March 2025") to obtain the original data such as freight invoices and miscellaneous expense invoices within that time period.

[0025] Secondly, the original ticket data is processed and calculated. Specifically, this includes firstly, splitting the original ticket data according to identification information into data for one or more transportation beneficiaries; wherein, the identification information includes one or more of the following in the original ticket data: section code, station code, and agent unit (also known as freight forwarding company) identifier; but not limited to these, other identification information is also applicable to this invention. Thus, the original ticket data is split according to its pricing section, station, and agent unit, resulting in data for one or more transportation beneficiaries, that is, the data for one or more transportation beneficiaries includes data for its pricing section, station, and / or agent unit.

[0026] Then, based on the transportation revenue categories and the data of one or more transportation revenue providers, the transportation revenue distribution of one or more revenue providers is reconstructed. This is achieved by subdividing transportation revenue into freight, miscellaneous fees, agency fees, etc., according to preset revenue classification rules. These preset revenue classification rules are relevant regulations such as the charging management methods of transportation enterprises, and are not limited to stipulating that transportation revenue includes freight, miscellaneous fees, and agency fees. They also include, for example, defining loading and unloading fees and freight truck overtime parking fees as miscellaneous fees, and defining vehicle empty return fees, overload fees, and shunting fees as freight. Therefore, in this embodiment of the invention, transportation revenue is categorized into freight, miscellaneous fees, agency fees, etc.; the transportation revenue of each agency unit, the transportation revenue of each railway line's pricing section and station, and the revenue distribution of a single agency unit on railway lines and stations are calculated separately. Preferably, the reconstructed transportation revenue distribution of one or more revenue providers takes the form of detailed revenue items for pricing sections and stations, detailed revenue items for a specific agency unit, and a detailed list of revenue from pricing sections and operating stations included in that agency unit. For example, for a freight bill, the pricing sections and loading / unloading stations along its transportation route are determined, the affiliated agency is identified, and freight, miscellaneous charges, and / or agency fees are allocated to the corresponding beneficiaries for calculation using the method described above. The final result is presented as a detailed list of revenue items for the pricing sections and stations, as well as a detailed list of revenue items for a specific agency and a list of revenue details for the pricing sections and operating stations included in that agency. For example, as shown in Table 1-5: Table 1. Bill of Lading

[0027] Table 2 Freight Rate Table

[0028] Table 3 Miscellaneous Fee Receipts

[0029] Table 4 Miscellaneous Expenses Table

[0030] Table 5. Detailed list of benefits for the beneficiary.

[0031] Then, spatial mapping is performed, including obtaining the coordinates of each pricing section, station, and agency, and converting these coordinates into GIS map geographic coordinate format. Specifically, the coordinate conversion for stations and agencies is done through dictionary mapping. Based on the station's `stationId` and the agency's `agentClientId`, the coordinates of the station and agency's location are retrieved from the database's coordinate table (a table specifically used to store the latitude and longitude coordinates of the station and agency's location). The return value for each station and agency is a single point coordinate object, for example, `{longitude:120.00131,latitude:38.122333}`. Furthermore, the coordinate transformation of the pricing section involves two mappings. First, multiple railway sections are located using the segmentId (segment identifier) ​​of the pricing section. A pricing section contains multiple railway sections. Second, the latitude and longitude coordinates of multiple sampling points within a railway section are found in the coordinate table using the sectionId (section identifier) ​​of that section. The pricing section returns a list of coordinate points, for example: [{longitude:120.00131,latitude:38.122333},{longitude:118.00131,latitude:38.622333},...].

[0032] Then, visualization rendering is performed, including rendering the transportation revenue of one or more beneficiaries on a map using one or more display methods, specifically including... Based on the calculated transportation revenue of each agency unit, the transportation revenue of each pricing section and station on the railway line, and the corresponding revenue value of an individual agency unit in the revenue distribution of the railway line and station, the line width value of the section is calculated, the scatter radius of all stations is calculated, and the radius of the annulus or sector diagram of all agencies is calculated. Furthermore, the calculation of the station scatter radius includes: First, obtain the maximum value (max) and minimum value (min) of the revenue list for all stations (i.e., the detailed or breakdown list mentioned above); const min = Math .min(...stationData.map(v =>v.sundryChargeStation)) const max = Math .max(...stationData.map(v =>v.sundryChargeStation)) This involves extracting the sundryChargeStation (a business field such as "station miscellaneous fees") for each station from all station data in the stationData array.

[0033] Then, calculate the scatter radius for each station: const sizeDiff = max == min ? 0 : (defaultDiffSize *(item.sundryCharge - min)) / (max - min) item.symbolSize = defaultSymbolSIze + sizeDiff Among them, defaultSymbolSize and defaultDiffSize are predefined constants. sizeDiff: The radius adjustment amount calculated based on the difference between the current station's sundryCharge and its maximum and minimum values. item.symbolSize: The final radius size of the scatter plot of the station (used for chart display).

[0034] The calculation of the line width value of the pricing section includes: First, take the maximum revenue (max) and minimum cost (min) from the list of all pricing intervals; const min = Math .min(...lineData.map(v =>v.benefitPlanSegment)) const max = Math .max(...lineData.map(v =>v.invoiceChargeSegment)) In the formula, lineData is an array that stores the relevant data objects for all pricing intervals, benefitPlanSegment corresponds to the "revenue" field, and invoiceChargeSegment corresponds to the "cost" field.

[0035] Then, calculate the width of each pricing segment: const widthOuterDiff = max == min ? 0 : ((item.invoiceChargeSegment -min) * defaultDiffWidth) / (max - min) const widthInnerDiff = max == min ? 0 : ((item.benefitPlanSegment -min) * defaultDiffWidth) / (max - min) const widthOuter = defaultLineWidth + widthOuterDiff const widthInner = defaultLineWidth + widthInnerDiff In the formula, defaultLineWidth and defaultDiffWidth are predefined constants, invoiceChargeSegment is the cost value of the pricing segment, benefitPlanSegment is the revenue value of the pricing segment, widthOuterDiff / widthInnerDiff: the adjustment amount of the outer and inner line widths calculated based on the current cost or revenue value of the pricing segment, and the difference from the maximum revenue value (max) and minimum cost value (min), respectively; widthOuter / widthInner: the final determined outer and inner line widths of the pricing segment (used for visualization, such as the outer line representing cost and the inner line representing revenue). The line is drawn by superimposing two line segments, inner and outer. The inner line segment represents the cost of the line, which is the value calculated by the company at the beginning of the year based on the company's operating situation. The system does not calculate this cost but only queries the company's reports to display this value. The outer line segment represents all the revenue of the line, and the revenue value is calculated by the system based on data such as freight invoices and miscellaneous expense invoices.

[0036] By using visualization technologies such as ECharts (Enterprise Charts) for dynamic rendering, line charts are drawn on GIS maps to represent the revenue of pricing segments. Thicker lines represent higher total transportation revenue for that segment, and the lines can be gradient lines. Scatter plots are drawn to represent station revenue; larger scatter points indicate higher total revenue for that station. Furthermore, heatmaps (larger bubbles for higher revenue) can be used to represent the total station revenue. Pie charts or sector charts are drawn to represent agency unit revenue, with the pie chart radius representing the total revenue. Different colors represent different expense items (clicking on a company displays its revenue spatial composition, such as the distribution of a freight forwarding company's revenue across stations and segments). Through these rendering methods, abstract revenue data is visually displayed on a geographic space, intuitively presenting the geographic spatial distribution of revenue, enabling decision-makers to quickly obtain high-value information. Figure 3The image shows the overall revenue of each freight forwarding company, station, and pricing section. Figure 3 In the bottom left corner, green represents station revenue, blue represents route revenue, yellow represents the route revenue indicator card, and orange represents the customer revenue composition. Figure 4 This is a revenue distribution presented from the perspective of freight forwarding companies and material companies, showing which stations and route pricing sections the company's main revenue is distributed in. Figure 5 The display shows a pie chart and explanation of the freight forwarding company's revenue composition. Since the company's geographical coordinates are known, the pie chart can be drawn based on the revenue composition at those coordinates. For aesthetic purposes, the pie chart radius is set to a fixed value instead of the actual total revenue. However, the angle ranges for different revenue items (freight, miscellaneous fees, agency fees) are calculated based on the actual values. The system supports calculating the pie chart radius based on total revenue, using the same method as calculating the section line width and station scatter point radius mentioned above.

[0037] Finally, the method also includes user interaction, including interaction based on time range query conditions, cost item query conditions, and the global or one or more beneficiary perspectives. While presenting the revenue distribution visualization results to users, they can also perform further interactive operations, such as switching time ranges, viewing detailed revenue data for specific entities (beneficiaries), and viewing the revenue of a specific cost item for a particular entity. Furthermore, it can process and update the display according to user commands, providing railway transportation enterprise decision-makers and agency clients with different perspectives on revenue distribution. Railway transportation enterprise decision-makers can view the revenue distribution of various agencies, railway pricing sections, and stations from a global perspective, analyze the network revenue structure, and optimize capacity resource allocation. Agency clients can switch perspectives using mouse operations. They can also calculate the map center point and zoom level based on the agency's coordinates and the corresponding station and pricing section coordinates, and switch to a suitable perspective, facilitating clients to view their company's revenue distribution and its distribution across various sections and stations, assess the rationality of their business layout, and formulate more scientific transportation decisions.

[0038] In this embodiment of the invention, the map is divided into an overall view and a freight forwarding company view. The overall view and zoom level are preset values, displaying all global elements. When the freight forwarding company icon is manually clicked to enter the freight forwarding company view, the system automatically calculates a new map center point. The new map center point is calculated by taking the average coordinates of the agency and related stations. The map view is then switched by calculating the map center point and zoom level. Further calculation of the map center point includes... First, determine the maximum and minimum ranges of latitude and longitude: const longitudeMax = Math.max(...stationData.map(v =>v.longitude),agentClient.longitude) const longitudeMin = Math .min(...stationData.map(v =>v.longitude),agentClient.longitude) const latitudeMax = Math .max(...stationData.map(v =>v.latitude),agentClient.latitude) const latitudeMin = Math.min(...stationData.map(v =>v.latitude),agentClient.latitude).

[0039] First, extract the longitude of all relevant stations using stationData.map(v =>v.longitude), then add the longitude of the agent unit agentClient.longitude, and then use Math.max and Math.min to find the maximum value (longitudeMax) and minimum value (longitudeMin) of these longitudes respectively.

[0040] The calculation logic for latitude is exactly the same, yielding the maximum (latitudeMax) and minimum (latitudeMin) latitude values.

[0041] Then, calculate the coordinates of the center point: const centerValue = [(longitudeMax + longitudeMin) / 2, (latitudeMax+ latitudeMin) / 2].

[0042] Longitude center point: (maximum longitude + minimum longitude) / 2 (i.e., the exact middle of the longitude range of all related elements), Latitude center point: (maximum latitude + minimum latitude) / 2 (i.e., the exact middle of the latitude range of all related elements), and finally centerValue is an array containing "center point longitude and center point latitude", which serves as the new center point from the perspective of the freight forwarding company.

[0043] The above methods provide railway transport companies and freight forwarding companies with differentiated perspectives. Railway transport companies can optimize the network revenue structure from a global perspective, while freight forwarding companies can accurately grasp the profitability of their own business in different regions. Simultaneously, it supports dynamic querying of revenue distribution changes by time range, meeting the needs of periodic transportation decisions and improving the efficiency of cross-entity decision-making collaboration.

[0044] like Figure 6 As shown in the embodiments of the present invention, a GIS-based spatial distribution visualization system for railway transportation revenue capable of executing the above-described method is also introduced. The system includes an acquisition module, a processing and calculation module, a spatial mapping module, and a visualization module. The acquisition module acquires raw ticket data within a preset time period. The processing and calculation module splits the raw ticket data according to identification information, dividing it into data for one or more transportation revenue recipients. Based on the transportation revenue category and the split data of one or more transportation revenue recipients, it reconstructs the transportation revenue distribution of one or more revenue recipients. The spatial mapping module converts the coordinates of one or more transportation revenue recipients into geographic coordinates on a GIS map. The visualization module renders the transportation revenue of one or more revenue recipients on a map using one or more display methods based on the converted GIS map geographic coordinates and the reconstructed transportation revenue distribution of one or more revenue recipients.

[0045] The system also includes a user interaction module for interacting with time range query conditions, expense item query conditions, and the global or one or more beneficiary perspectives.

[0046] The aforementioned system addresses the shortcomings of existing technologies in data processing, visualization, and decision support by constructing a multi-dimensional data processing model and a geographic visualization system. Furthermore, it provides differentiated perspectives for railway transport companies and freight forwarding companies. Railway transport companies can optimize the network revenue structure from a global perspective, while freight forwarding companies can accurately grasp the profitability of their business in different regions. Simultaneously, it supports dynamic querying of revenue distribution changes by time range, meeting the needs of periodic transportation decisions and improving the efficiency of cross-entity decision-making collaboration.

[0047] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A GIS-based method for visualizing the spatial distribution of railway transportation revenue, characterized in that, include, Retrieve raw invoice data within a preset time period; The original invoice data is split according to the identification information, into data for one or more transportation beneficiaries; Based on the data of one or more transportation revenue categories and splits of one or more transportation revenue parties, reconstruct the transportation revenue distribution of one or more revenue parties; Convert the coordinates of one or more transportation beneficiaries into geographic coordinates on a GIS map; Based on the transformed GIS map geographic coordinates and the reconstructed transportation revenue distribution of one or more beneficiaries, the transportation revenue of one or more beneficiaries is rendered on the map using one or more display methods.

2. The GIS-based method for visualizing the spatial distribution of railway transportation revenue according to claim 1, characterized in that, The original invoice data includes freight invoices and miscellaneous expense invoices.

3. The GIS-based spatial distribution visualization method for railway transportation revenue according to claim 1, characterized in that, The identification information includes one or more of the following: pricing section code, station code, and agent unit identifier from the original ticket data; Data from one or more transport revenue providers includes data from their respective pricing sections, stations, and / or agents.

4. The GIS-based spatial distribution visualization method for railway transportation revenue according to claim 3, characterized in that, Converting the coordinates of one or more transportation beneficiaries into geographic coordinates on a GIS map includes, Obtain the coordinates of each pricing section, station, and agency; Coordinate transformation between stations and agencies includes: Based on the station sign and the agent's client sign, query the latitude and longitude coordinates of the station and the agent's location in the coordinate table of the database; The return value for both the station and the agent is a single point coordinate object; The coordinate transformation of the pricing section includes: Multiple railway sections can be located by identifying the section markers of the pricing zones; Find the latitude and longitude coordinates of multiple sampling points in the coordinate table by using the section identifier of the railway section; The pricing segment returns a list of coordinate points.

5. The GIS-based spatial distribution visualization method for railway transportation revenue according to claim 4, characterized in that, Based on the data of transportation revenue categories and one or more transportation revenue providers, reconstruct the transportation revenue distribution of one or more revenue providers, including: Transportation revenue is categorized into freight, miscellaneous charges, and agency fees. Calculate the transportation revenue of each agent, the transportation revenue of each pricing section and station of the railway line, and the revenue distribution of an individual agent on the railway line and station.

6. The GIS-based spatial distribution visualization method for railway transportation revenue according to claim 5, characterized in that, The transportation revenue distribution of one or more beneficiaries is reconstructed into detailed revenue items for pricing sections and stations, detailed revenue items for agents, and a detailed list of revenue items for pricing sections and operating stations included in the agent.

7. The GIS-based spatial distribution visualization method for railway transportation revenue according to claim 6, characterized in that, The transportation revenue of one or more beneficiaries is rendered on the map using one or more display methods, including... Calculate the line width value of the pricing section and draw a line map on the GIS map to represent the revenue of the section; Calculate the scatter radius for all stations and plot a scatter plot to represent station revenue; and / or Calculate the radius of the pie chart or sector chart for all agents, and draw a pie chart or sector chart to represent the revenue of the agents. The radius of the pie chart represents the total revenue, and different colors represent different expense items.

8. The GIS-based spatial distribution visualization method for railway transportation revenue according to claim 7, characterized in that, The calculation of the scatter radius of the station includes, Retrieve the maximum (max) and minimum (min) values ​​from the list of station revenues; The radius adjustment amount is calculated based on the difference between the current station's miscellaneous fees and the maximum and minimum values ​​(max and min). Add the constant to the calculated radius adjustment to obtain the radius of the current station scatter points.

9. The GIS-based spatial distribution visualization method for railway transportation revenue according to claim 7, characterized in that, The calculation of the line width value of the pricing section includes: Get the maximum revenue (max) and minimum cost (min) of the list of all pricing intervals; Calculate the width of each pricing segment; Based on the cost and revenue values ​​of the current pricing segment, and the differences from the maximum revenue (max) and minimum cost (min), calculate the adjustment amounts for the width of the outer and inner lines respectively. Add the constant to the calculated external and internal line width adjustments respectively to obtain the external and internal line widths of the pricing section.

10. The GIS-based spatial distribution visualization method for railway transportation revenue according to any one of claims 1-9, characterized in that, It also includes user interaction, including, Interact with time range query conditions, expense item query conditions, and the global or one or more beneficiary perspectives.

11. The GIS-based spatial distribution visualization method for railway transportation revenue according to claim 10, characterized in that, User interaction also includes calculating the map's center point and zoom level to switch map views, specifically including... Set the magnification value; The calculation of the map center point includes, Determine the maximum and minimum ranges of latitude and longitude; Determine the longitude center point and the latitude center point, where the longitude center point is the average of the sum of the maximum and minimum longitude values, and the latitude center point is the average of the sum of the maximum and minimum latitude values. The map center point satisfies: [longitude center point, latitude center point].

12. A GIS-based spatial distribution visualization system for railway transportation revenue, characterized in that, include, The acquisition module is used to acquire raw invoice data within a preset time period; The processing and calculation module is used to split the original ticket data according to the identification information, dividing it into data for one or more transportation beneficiaries; and Based on the data of one or more transportation revenue categories and splits of one or more transportation revenue parties, reconstruct the transportation revenue distribution of one or more revenue parties; The spatial mapping module is used to convert the coordinates of one or more transportation beneficiaries into geographic coordinates on a GIS map. The visualization module is used to render the transportation revenue of one or more beneficiaries on the map using one or more display methods, based on the transformed GIS map geographic coordinates and the reconstructed distribution of transportation revenue for one or more beneficiaries.

13. The GIS-based spatial distribution visualization system for railway transportation revenue according to claim 12, characterized in that, It also includes a user interaction module for interacting with time range query conditions, expense item query conditions, and the global or one or more beneficiary perspectives.

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