CN113609208B - Railway OD data analysis visualization system and method - Google Patents
Railway OD data analysis visualization system and method Download PDFInfo
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- CN113609208B CN113609208B CN202110917732.7A CN202110917732A CN113609208B CN 113609208 B CN113609208 B CN 113609208B CN 202110917732 A CN202110917732 A CN 202110917732A CN 113609208 B CN113609208 B CN 113609208B
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Abstract
The invention discloses a railway OD data analysis visualization system and a method, which relate to the technical field of data visualization, wherein the system comprises a geographical traffic cell selection module for selecting a geographical traffic cell corresponding to a research demand, a category selection module for selecting a category corresponding to the research demand, an OD data analysis mode selection module for selecting an OD data analysis mode corresponding to the research demand, a traffic data determination module for determining OD data corresponding to the research demand and traffic data of a research area and/or research category by taking the geographical traffic cell, the category and the OD data analysis mode as constraint conditions, and a visualization module for displaying traffic distribution among OD pairs corresponding to the research demand based on the OD data corresponding to the research demand. The invention is convenient for the staff to quickly and intuitively know the traffic distribution of each area or each category.
Description
Technical Field
The invention relates to the technical field of data mining and visualization, in particular to a railway OD data analysis visualization system and method.
Background
OD (Origin-Destination) data is start-stop point data, is an important data type of reaction element flow and inter-region connection, such as population trip OD data, fund flow OD data and the like, and is widely applied to planning research and city perception.
The railway is an important infrastructure for the relationship of national and civil life, and along with the rapid development of the construction of a railway network in China, a multi-layer networking railway transportation network plays an important role in supporting and leading economic and social development, and the railway transportation becomes an important transportation mode for the travel of residents in China and the transportation of bulk goods, and is an important engine for the modern construction of China.
At present, the railways in China enter the data information era, a large amount of railway large data resources such as refined passenger and cargo traffic and the like are accumulated, and the problems of insufficient application scene depth, insufficient analysis of transportation characteristics, high-efficiency and poor usability of data and the like still exist in the application of the current railway OD data, so that a rapid and high-efficiency railway passenger and cargo traffic OD data analysis technical method is to be innovated and developed, the data value is fully mined, the data driving decision is realized, and the scientific and precise development of railway planning design is supported.
Disclosure of Invention
In view of the above, the invention provides a railway OD data analysis visualization system and a railway OD data analysis visualization method, which are convenient for operators to quickly and intuitively know the traffic distribution of each area or each category.
In order to achieve the above object, the present invention provides the following solutions:
a railway OD data analysis visualization system, comprising:
a geographic traffic cell selection module for: selecting a geographical traffic cell corresponding to the research demand according to different regional granularities; the regional granularity comprises a city group level, a region level, a provincial level, a city level, a county region level, a railway system custom level and a user custom level; the study requirements include a study area and/or a study category;
the class selection module is used for: selecting the category corresponding to the research requirement according to different classification granularities; the classification granularity comprises passenger transportation class, freight transportation class, passenger subclass and freight subclass;
an OD data analysis mode selection module for: selecting an OD data analysis mode corresponding to the research requirement; the OD data analysis mode is one of a global unconstrained OD data analysis mode, a self-defined one-end constrained OD data analysis mode and a self-defined two-end constrained OD data analysis mode; the total unconstrained OD data analysis mode refers to an OD data analysis mode which does not constrain both the initial region and the termination region; the self-defined one-end constraint OD data analysis mode refers to an OD data analysis mode for restraining a starting area or a terminating area; the self-defined two-end constraint OD data analysis mode refers to an OD data analysis mode for restraining both a starting area and a terminating area;
The traffic data determining module is used for:
taking a geographic traffic cell, a class and an OD data analysis mode corresponding to the research requirement as constraint conditions, and screening railway OD data in a database to determine OD data corresponding to the research requirement;
determining the volume of the study area and/or the study class based on the OD data corresponding to the study demand;
a visualization module for: and displaying the traffic distribution of the research area and/or the research category and the statistical result of various modes of the research area and/or the research category based on the OD data corresponding to the research requirement.
Optionally, the study requirement further comprises a study period;
the traffic data determining module specifically comprises:
a time period selection unit, configured to select a time period corresponding to the study requirement;
the OD data determining unit is used for screening railway OD data in a database by taking a geographic traffic cell, a class, an OD data analysis mode and a time period corresponding to the research requirement as constraint conditions so as to determine the OD data corresponding to the research requirement;
and the traffic determination unit is used for determining the traffic of the research area and/or the research category based on the OD data corresponding to the research requirement.
Optionally, the OD data analysis mode selection module specifically includes:
the OD data analysis mode first selection unit is used for selecting an OD data analysis mode corresponding to the research requirement;
the OD data analysis mode second selection unit is used for determining a first OD data analysis sub-mode corresponding to the research requirement when the OD data analysis mode is a self-defined one-end constraint OD data analysis mode and the geographic traffic cells are multiple; the first OD data analysis sub-mode comprises an uncombined geographic traffic cell sub-mode and a combined geographic traffic cell sub-mode; the non-merging geographic traffic cell sub-mode is a mode of determining each geographic traffic cell as an independent target and simultaneously carrying out OD data analysis on each geographic traffic cell, and the merging geographic traffic cell sub-mode is a mode of merging a plurality of geographic traffic cells into a virtual merging geographic traffic cell and carrying out overall OD data analysis on the virtual merging geographic traffic cell;
and the OD data determining unit is used for screening the railway OD data in the database by taking the geographic traffic cell, the class, the first OD data analysis sub-mode and the time period corresponding to the research requirement as constraint conditions so as to determine the OD data corresponding to the research requirement.
Optionally, the OD data analysis mode selection module specifically includes:
the third selection unit of the OD data analysis mode is used for selecting the OD data analysis mode corresponding to the research requirement;
the OD data analysis mode fourth selection unit is used for determining a second OD data analysis sub-mode corresponding to the research requirement when the OD data analysis mode is a self-defined two-end constraint OD data analysis mode; the second OD data analysis sub-mode comprises a basic internal OD data analysis sub-mode and an internal and external OD data analysis sub-mode; the basic internal OD data analysis sub-mode is a mode for establishing a geographic traffic cell selection set and carrying out OD data analysis on a research area of which the initial area and the termination area belong to the geographic traffic cell selection set; the internal and external OD data analysis sub-mode is a mode for establishing a plurality of geographic traffic cell selection sets, selecting one geographic traffic cell selection set as an internal selection set, selecting other geographic traffic cell selection sets as external selection sets, carrying out OD data analysis on a research area in the internal selection set, and carrying out OD data analysis on a research area between the internal selection set and the external selection set;
And the OD data determining unit is used for screening the railway OD data in the database by taking the geographical traffic cell, the class, the second OD data analysis sub-mode and the time period corresponding to the research requirement as constraint conditions so as to determine the OD data corresponding to the research requirement.
Optionally, the study requirements further include endpoint analysis;
the OD data analysis mode selection module specifically includes:
an OD data analysis mode fifth selecting unit, configured to select an OD data analysis mode corresponding to the research requirement;
the sixth selection unit of the OD data analysis mode is configured to select an endpoint analysis mode corresponding to the research requirement when the OD data analysis mode is a custom one-end constraint OD data analysis mode;
the endpoint analysis mode comprises a sending mode, an arrival mode, a total arrival mode, a net arrival mode, a sending composition mode and an arrival composition mode; the sending mode is a mode for analyzing the total sending quantity of the specified product of the geographic traffic cell user corresponding to the research requirement; the arrival mode is a mode for analyzing the total arrival amount of the specified categories of the users in the geographic traffic cell corresponding to the research requirements; the total arrival mode is a mode for analyzing the total transmission quantity and the total arrival quantity of the user-specified goods of the geographic traffic cell corresponding to the research requirement; the net arrival mode is a mode for analyzing differences of the specified categories of the users in the geographic traffic cells corresponding to the research demands; the difference is the difference between the total transmission amount and the total arrival amount; the transmission composition mode is a mode for analyzing the transmission composition of the user-specified category of the geographic traffic cell corresponding to the research requirement; the arrival composition mode is a mode for analyzing arrival composition of the specified items of the geographic traffic cell users corresponding to the research requirements; the transmission structure is formed by the transmission traffic of each category and the transmission traffic proportion of each category; the arrival structure is composed of arrival traffic of each category and arrival traffic proportion of each category;
And the OD data determining unit is used for screening the railway OD data in the database by taking the geographic traffic cell, the class, the endpoint analysis mode and the time period corresponding to the research requirement as constraint conditions so as to determine the OD data corresponding to the research requirement.
Optionally, the visualization module is configured to:
displaying the research area and/or the traffic distribution of the research category in a map form in a way of representing the position of the geographic traffic cell by a circle and representing the interaction relation of each geographic traffic cell by a line based on the OD data corresponding to the research demand; the size and/or color of the circle represents the size of the total traffic of the geographic traffic cell; or displaying the traffic distribution of the research area and/or the research product in a statistical chart form based on the OD data corresponding to the research requirement; the statistical chart comprises a histogram and a line graph; statistics display the transportation statistics result of the research area and/or the research category in the histogram mode; the abscissa of the line graph is a research time period, and the ordinate is the transportation of the research area and/or the research category; or under the sending construction mode or the reaching construction mode, displaying the research area and/or the traffic distribution of the research product in a map form in a way of showing the position of the geographic traffic cell by a pie chart and showing the interactive relation of each geographic traffic cell by a line based on the OD data corresponding to the research requirement; wherein the size of the pie chart represents the size of the total traffic volume of the geographic traffic cell; the proportion of each sector of the pie chart represents the ratio of each category in the total traffic; the total traffic is the total transmission amount or the total arrival amount.
Optionally, the method further comprises: a data export module;
the data export module is used for exporting the transportation quantity of the research area and/or the research category in a set data structure form; the data output by the data export module is total traffic, class constitution, each end point traffic, each end point class constitution and OD quantity containing starting and ending point information and class.
Optionally, the passenger transportation classes comprise a plurality of subclasses, which are respectively a high-speed motor train unit train, an inter-city motor train unit train, a common motor train unit train, a direct express passenger train, an express passenger train, a fast passenger train, a common passenger express train and a common passenger express train; the shipping class includes a plurality of subclasses, respectively food, agriculture, energy, material, ore, container, and other totals; the other aggregate is freight class other than food, agriculture, energy, materials, ore, containers.
A railway OD data analysis visualization method, comprising:
selecting geographic traffic cells corresponding to research requirements according to different regional granularities; the regional granularity comprises a city group level, a region level, a provincial level, a city level, a county region level, a railway system custom level and a user self-definition level; the study requirements include a study area and/or a study category;
Selecting the category corresponding to the research requirement according to different classification granularities; the classification granularity comprises a passenger class and a freight class;
selecting an OD data analysis mode corresponding to the research requirement; the OD data analysis mode is one of an all-round unconstrained OD data analysis mode, a self-defined one-end constrained OD data analysis mode and a self-defined two-end constrained OD data analysis mode; the global unconstrained OD data analysis mode refers to an OD data analysis mode which does not constrain both the starting region and the ending region; the self-defined one-end constraint OD data analysis mode refers to an OD data analysis mode for restraining a starting area or a terminating area; the self-defined two-end constraint OD data analysis mode refers to an OD data analysis mode of restraining both a starting area and a terminating area;
taking a geographic traffic cell, a class and an OD data analysis mode corresponding to the research requirement as constraint conditions, and screening railway OD data in a database to determine OD data corresponding to the research requirement;
determining the volume of the study area and/or the study class based on the OD data corresponding to the study demand;
and displaying the traffic distribution of the research area and/or the research product and the multi-mode to volume statistics of the research area and/or the research product based on the OD data corresponding to the research requirement.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a railway OD data analysis visualization system and a method thereof; according to the invention, the geographical traffic cell, the class and the OD data analysis mode are determined based on the research requirements provided by the staff, so that the OD data corresponding to the research requirements are further researched, and the traffic distribution of the research area and/or the research class is displayed and stored based on the OD data corresponding to the research requirements, so that the staff can quickly and intuitively know the traffic distribution of each area or each class.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a railway OD data analysis visualization system according to the present invention;
FIG. 2 is a schematic diagram of a geographic traffic cell selection operation interface according to the present invention;
FIG. 3 is a schematic diagram of a class selection operation interface of the present invention;
FIG. 4 is a schematic diagram of an OD data analysis mode selection interface according to the present invention;
FIG. 5 is a graph showing the effect of the real machine in different OD data analysis modes according to the present invention; FIG. 5 (a) is a graph of effect presented by a real machine in a global unconstrained OD data analysis mode; FIG. 5 (b) shows the effect diagram of the real machine in the custom one-end constraint OD data analysis mode; FIG. 5 (c) shows an effect diagram of the real machine in a custom two-terminal constraint OD data analysis mode;
FIG. 6 is a graph showing the results of the distribution of the amounts of transportation of the study products in the predetermined area of the present invention (for example, shanghai city);
FIG. 7 is a diagram showing the effect of the real machine in the alternative mode of different OD endpoints according to the present invention; FIG. 7 (a) is a diagram of the effect of the real machine presentation in the send mode, the arrive mode and the total to send mode; FIG. 7 (b) shows an effect diagram of the real machine in the Net-to-Hair mode; FIG. 7 (c) shows the effect diagram of the real machine in the send composition mode and the arrive composition mode;
FIG. 8 is a diagram showing the effect of the present invention in different desired line selection modes; FIG. 8 (a) shows an effect diagram for a real machine in a send mode; FIG. 8 (b) shows an effect diagram of the real machine in the reach mode; FIG. 8 (c) shows an effect diagram for a real machine in a two-way mode;
FIG. 9 is a schematic flow chart of a method for visualizing railway OD data analysis according to the present invention;
Fig. 5 to 8 are partial maps of chinese maps.
Detailed Description
The following description of the embodiments of the present invention will be made with reference to the accompanying drawings, in which it is evident that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1
The embodiment provides a system for providing railway passenger transport OD analysis function, freight transport OD analysis function, statistics function and visualization function based on railway OD data.
The geographic traffic cell data in this embodiment includes boundaries and location points of different granularity regions, which are used to implement statistical analysis and visualization of railway OD data between different granularity regions (collectively referred to as geographic traffic cells), such as boundaries and location points of city group level, region level, province level, city level, county level. In addition, the geographic traffic cell data also comprises a special railway geographic traffic cell of the railway system and a user-defined geographic traffic cell. The railway OD data in this embodiment is a traffic volume recorded from a start point (O-terminal) to an end point (D-terminal) via a railway system within a certain statistical period (e.g., month, season, year, etc.). The traffic here includes passenger traffic and cargo traffic. The passenger traffic comprises traffic of different vehicle types, such as high-speed motor train unit trains (G-shaped heads), inter-city motor train unit trains (C-shaped heads), common motor train unit trains (D-shaped heads), direct express passenger trains (Z-shaped heads), express passenger trains (T-shaped heads), express passenger trains (K-shaped heads), common passenger express trains (express) and train classification traffic of common passenger express trains; the freight volume comprises the classified freight volume of 108 items of different goods, such as grains, coal, fertilizer, rubber, plastics and the like. The passenger class and the freight class are collectively referred to as "class" in this embodiment.
Referring to fig. 1, the railway OD data analysis and visualization system provided in this embodiment includes:
a geographic traffic cell selection module 101 for: selecting geographic traffic cells corresponding to research requirements according to different regional granularities; the regional granularity comprises a city group level, a region level, a provincial level, a city level, a county region level, a railway system custom level and a user custom level; the study requirements include a study area and/or a study category; the research requirement is a requirement determined by staff; the geographic traffic cell is one of a city group-level geographic traffic cell, a region-level geographic traffic cell, a provincial-level geographic traffic cell, a city-level geographic traffic cell, a county-level geographic traffic cell, a railway geographic traffic cell special for a railway system and a user-defined geographic traffic cell. The geographical traffic cell selection operation interface is shown in fig. 2.
A category selection module 102 for: selecting the category corresponding to the research requirement according to different classification granularities; the classification granularity comprises passenger transportation class, freight transportation class, passenger subclass and freight subclass; the passenger transportation class comprises a high-speed motor train unit train (G-shaped head), an inter-city motor train unit train (C-shaped head), a common motor train unit train (D-shaped head), a direct express passenger train (Z-shaped head), a express passenger train (T-shaped head), a fast passenger train (K-shaped head), a common passenger express train (ordinary) and a common passenger express train; freight categories include food, agriculture, energy, materials, ores, containers, and other totals; food including grains, salt, etc.; the agriculture comprises cotton, chemical fertilizers, pesticides and the like; energy sources include coal, petroleum, coke, and the like; the material comprises metal ore, nonmetallic ore, phosphate ore and the like; the other aggregate is freight class other than food, agriculture, energy, materials, ore, containers. The category selection operation interface is shown in fig. 3.
OD data analysis mode selection module 103 for: selecting an OD data analysis mode corresponding to the research requirement; the OD data analysis mode is one of a global unconstrained OD data analysis mode, a self-defined one-end constrained OD data analysis mode and a self-defined two-end constrained OD data analysis mode; the global unconstrained OD data analysis mode refers to an OD data analysis mode which does not constrain both the starting area and the ending area, and is used for analyzing, counting and visualizing traffic distribution characteristics among all OD pairs. The self-defined one-end constraint OD data analysis mode refers to an OD data analysis mode for restraining a starting area or a terminating area, and is used for analyzing, counting and visualizing the traffic distribution characteristics among OD pairs sent out or reached by a restraining area (or called a restraining end); the constraint area is a constraint starting area or a constraint ending area; the self-defined two-end constraint OD data analysis mode refers to an OD data analysis mode for restraining both the starting area and the ending area, and the self-defined two-end constraint OD data analysis mode is used for analyzing, counting and visualizing the traffic distribution characteristics between OD pairs of the starting area and the ending area. The OD data analysis mode selection operation interface is shown in fig. 4, and the effect of the real machine presentation in different OD data analysis modes is shown in fig. 5.
The traffic data determination module 104 is configured to:
and screening railway OD data in a database by taking a geographic traffic cell, a class and an OD data analysis mode corresponding to the research requirement as constraint conditions so as to determine the OD data corresponding to the research requirement.
And determining the transportation quantity of the research area and/or the research product based on the OD data corresponding to the research requirement.
A visualization module 105 for: and displaying the traffic distribution of the research area and/or the research product class and the multi-mode to-volume statistics of the research area and/or the research product class based on the OD data corresponding to the research requirement.
For example: if the research requirement is the traffic distribution of the food in the visual global area, the geographic traffic cell is the global area, the food in the freight type is the food in the OD data analysis mode is the global unconstrained OD data analysis mode, and the visual module displays the traffic distribution among the OD pairs of the food in the global area.
If the research requirement is that the traffic distribution of coal in Shanxi province is visualized, the geographical traffic district is Shanxi province, the class is coal in freight class, the OD data analysis mode is a self-defined one-end constraint OD data analysis mode, the visualization module displays that the starting area or the ending area is Shanxi province, and the class is the traffic distribution characteristic among the OD pairs of the coal.
If the research requirement is that the visual initial area is the transport capacity distribution of the high-speed motor train unit trains in the Shijiu city, the ending area is the Beijing city, the geographic traffic area is the area in which the initial area is the Shijiu city, the ending area is the Beijing city, the category is the high-speed motor train unit trains in the passenger transportation category, the OD data analysis mode is self-defined, the two-end constraint OD data analysis mode, the visual module displays the transport capacity distribution characteristics among the OD pairs of the high-speed motor train unit trains in the initial area is the Shijiu city, the ending area is the Beijing city.
The result of the distribution of the sample traffic in the predetermined area (for example, shanghai city) is shown in fig. 6.
Further, the research requirement further includes a research period, so the traffic data determining module 104 in this embodiment specifically includes:
and the time period selection unit is used for selecting the time period corresponding to the research requirement.
And the OD data determining unit is used for screening the railway OD data in the database by taking the geographic traffic cell, the class, the OD data analysis mode and the time period corresponding to the research requirement as constraint conditions so as to determine the OD data corresponding to the research requirement.
And the traffic determination unit is used for determining the traffic of the research area and/or the research category based on the OD data corresponding to the research requirement.
Because the user-defined one-end constraint OD data analysis mode needs a user to input a constraint area, namely a constraint end, the traffic distribution characteristics starting from or arriving at the constraint area are analyzed. Taking the city level as an example, a user inputs a city into the system and selects a study category, and the system visually displays the traffic distribution associated with the city. The user can define the statistical granularity of the unconstrained end, such as analyzing the traffic distribution situation among cities, various cities, provinces/autonomous regions and regions.
When the user selects a plurality of geographic traffic cells, two sub-mode analysis functions of non-merging geographic traffic cells and merging geographic traffic cells can be provided, namely, the self-defined one-end constraint OD data analysis mode comprises a non-merging geographic traffic cell sub-mode and a merging geographic traffic cell sub-mode.
Geographic traffic cell sub-patterns are not consolidated: each geographic traffic cell is considered to be independent, and the traffic distribution situation among the OD pairs of each geographic traffic cell is analyzed and visualized at the same time. Merging geographical traffic cell sub-models: and regarding the plurality of geographic traffic cells as a whole, namely regarding the geographic traffic cells as a virtual fusion geographic traffic cell, performing matrix addition on the traffic distribution results among the OD pairs of each geographic traffic cell, and analyzing and visualizing the traffic distribution situation among the whole OD pairs of the virtual fusion geographic traffic cell.
Further, the OD data analysis mode selection module 103 includes:
and the OD data analysis mode first selection unit is used for selecting an OD data analysis mode corresponding to the research requirement.
The OD data analysis mode second selection unit is used for determining a first OD data analysis sub-mode corresponding to the research requirement when the OD data analysis mode is a self-defined one-end constraint OD data analysis mode and the geographic traffic cells are multiple; the first OD data analysis sub-mode comprises an uncombined geographic traffic cell sub-mode and a combined geographic traffic cell sub-mode; the non-merging geographic traffic cell sub-mode is a mode of determining each geographic traffic cell as an independent target and simultaneously carrying out OD data analysis on each geographic traffic cell, and the merging geographic traffic cell sub-mode is a mode of merging a plurality of geographic traffic cells into a virtual merging geographic traffic cell and carrying out overall OD data analysis on the virtual merging geographic traffic cell.
At this time, the OD data determining unit is configured to screen the railway OD data in the database with the geographical traffic cell, the class, the first OD data analysis sub-mode and the time period corresponding to the research requirement as constraint conditions, so as to determine the OD data corresponding to the research requirement.
The OD data analysis mode is used for analyzing the traffic distribution characteristics among the OD pairs in a local area due to the self-definition of the two-end constraint. If the user selects a plurality of places, the analysis and visualization starting and ending points belong to the traffic distribution characteristics of the selected places.
The self-defined two-end constraint OD data analysis mode comprises two sub-modes, namely a basic internal OD data analysis sub-mode and an internal and external OD data analysis sub-mode.
Basic internal OD data analysis sub-pattern: the user needs to establish a geographical traffic cell selection set, and the analysis and visualization starting area and the termination area belong to the traffic distribution characteristics among the OD pairs of the established geographical traffic cell selection set.
Internal and external OD data analysis submode: the user can establish a plurality of geographic traffic cell selection sets, wherein one geographic traffic cell selection set is selected as an internal selection set, other geographic traffic cell selection sets are selected as external selection sets, and the traffic distribution characteristics among the OD pairs among the geographic traffic cells in the internal selection set and the traffic distribution characteristics among the OD pairs between the internal selection set and the external selection set are analyzed and visualized.
Further, the OD data analysis mode selection module 103 specifically includes:
And the third selection unit of the OD data analysis mode is used for selecting the OD data analysis mode corresponding to the research requirement.
The OD data analysis mode fourth selection unit is used for determining a second OD data analysis sub-mode corresponding to the research requirement when the OD data analysis mode is a self-defined two-end constraint OD data analysis mode; the second OD data analysis sub-mode comprises a basic internal OD data analysis sub-mode and an internal and external OD data analysis sub-mode; the basic internal OD data analysis sub-mode is a mode for establishing a geographic traffic cell selection set and carrying out OD data analysis on a research area of which the initial area and the termination area belong to the geographic traffic cell selection set; the internal and external OD data analysis sub-mode is a mode for establishing a plurality of geographic traffic cell selection sets, selecting one geographic traffic cell selection set as an internal selection set, selecting other geographic traffic cell selection sets as external selection sets, carrying out OD data analysis on a research area in the internal selection set, and carrying out OD data analysis on a research area between the internal selection set and the external selection set.
At this time, the OD data determining unit is configured to screen the railway OD data in the database with the geographical traffic cell, the class, the second OD data analysis sub-mode and the time period corresponding to the research requirement as constraint conditions, so as to determine the OD data corresponding to the research requirement.
As a preferred embodiment, the railway OD data analysis visualization system provided in the present embodiment further includes an endpoint analysis function; the endpoint analysis function includes six modes of send, arrive, total send, net send, send composition, arrive composition. The endpoint is an OD endpoint.
Transmission mode: the total amount of transmissions of the user-specified categories of geographic traffic cells is analyzed. The color and size of the bubble represent the traffic size, and the user can adjust the color band and the bubble size. Arrival mode: the total reach of the user-specified category of the geographic traffic cell is analyzed. The color and size of the bubble represent the traffic size, and the user can adjust the color band and the bubble size. Total hair mode: the total amount of transmission and total amount of arrival of the user-specified category of the geographic traffic cell is analyzed. The color and size of the bubble represent the traffic size, and the user can adjust the color band and the bubble size. Clean to send mode: the difference between the total transmission amount and the total arrival amount of the class designated by the user in the geographic traffic cell is analyzed, and the difference is a net output amount if the difference is positive, and is a net input amount if the difference is negative. The bubble is displayed on the map in a bubble map at a location point of the geographic traffic cell, the size of the bubble representing the traffic size, the color representing the net output or net input, the color band and the bubble size being user-adjustable. Transmission configuration mode: and analyzing the sending constitution condition of the specified class of the user in the geographic traffic district, namely the traffic volume and the duty ratio of each class. The size of the pie chart is represented by the total traffic volume, the proportion of each sector of the pie chart is represented by the ratio of each category in the total traffic volume, and the size of the pie chart can be adjusted by a user. Reaching the composition mode: and analyzing the arrival composition condition of the user-specified category of the geographic traffic district, namely the traffic volume and the duty ratio of each category. The size of the pie chart is represented by the total traffic volume, the proportion of each sector of the pie chart is represented by the ratio of each category in the total traffic volume, and the size of the pie chart can be adjusted by a user.
Further, the research requirements described in this embodiment also include endpoint analysis;
the OD data analysis mode selection module 103 specifically includes:
and the fifth selection unit of the OD data analysis mode is used for selecting the OD data analysis mode corresponding to the research requirement.
And the sixth selection unit of the OD data analysis mode is used for selecting an endpoint analysis mode corresponding to the research requirement when the OD data analysis mode is a custom one-end constraint OD data analysis mode.
The endpoint analysis modes include a send mode, an arrive mode, an always-to-send mode, a net-to-send mode, a send composition mode, and an arrive composition mode.
And the sending mode is a mode for analyzing the total sending quantity of the specified goods of the geographic traffic district user corresponding to the research requirement. And the arrival mode is a mode for analyzing the total arrival quantity of the class specified by the user of the geographic traffic cell corresponding to the research requirement. And the total arrival mode is a mode for analyzing the total transmission quantity and the total arrival quantity of the user-specified items of the geographic traffic cell corresponding to the research requirement. The net arrival mode is a mode for analyzing differences of user-specified categories of the geographic traffic cells corresponding to the research demands; the difference is the difference between the total transmission amount and the total arrival amount. And the transmission composition mode is a mode for analyzing the transmission composition of the user-specified items of the corresponding geographic traffic cell required by the research. And the arrival composition mode is a mode for analyzing the arrival composition of the user-specified category of the geographic traffic cell corresponding to the research requirement. The transmission structure is formed by the transmission traffic of each category and the transmission traffic proportion of each category; the arrival structure is composed of arrival traffic of each category and arrival traffic ratio of each category.
At this time, the OD data determining unit is configured to screen the railway OD data in the database with the geographical traffic cell, the class, the endpoint analysis mode and the time period corresponding to the research requirement as constraint conditions, so as to determine the OD data corresponding to the research requirement.
The effect of the real machine presentation in the optional mode of different OD endpoints is shown in fig. 7.
As a preferred embodiment, the visualization module 105 of the present embodiment is configured to:
and displaying the traffic distribution of the research area and/or the research category in a map form or a statistical chart form based on the OD data corresponding to the research requirement.
Further, the visualization module 105 is configured to:
displaying the research area and/or the traffic distribution of the research category in a map form in a way of representing the position of the geographic traffic cell by a circle and representing the interaction relation of each geographic traffic cell by a line based on the OD data corresponding to the research demand; the size and/or color of the circle represents the size of the total traffic of the geographic traffic cell.
Or based on the OD data corresponding to the research requirement, displaying the research area and/or the traffic distribution of the research category in a statistical chart form; the statistical chart comprises a histogram and a line graph; statistics in the histogram mode show the traffic statistics of the study area and/or the study class; the abscissa of the line graph represents the study period and the ordinate represents the volume of the study area and/or the study class.
Or in the transmission construction mode or the arrival construction mode, displaying the research area and/or the traffic distribution of the research category in a map form in a way of using a pie chart to represent the positions of the geographic traffic cells and using lines to represent the interaction relation of each geographic traffic cell based on the OD data corresponding to the research requirement; wherein the size of the pie chart represents the size of the total traffic volume of the geographic traffic cell; the proportion of each sector of the pie chart represents the ratio of each category in the total traffic; the total traffic is the total transmission amount or the total arrival amount.
As a preferred specific implementation manner, the system provided in this embodiment further includes: the data export module.
The data export module is used for exporting the traffic of the research area and/or the research category in the form of a set data structure.
The data output by the data export module is total traffic, class constitution, each end point traffic, each end point class constitution and OD quantity containing starting and ending point information and class.
In the global unconstrained OD data analysis mode, the data output by the data deriving module is global total traffic (i.e., total traffic of a global area), global category composition (i.e., traffic ratio of each category in the global area), global traffic composition (i.e., traffic ratio of each category in each geographic traffic cell in the global area), and total traffic of each endpoint (i.e., total traffic of each geographic traffic cell in the global area).
In the self-defined one-end constraint OD data analysis mode, the data of the constraint end output by the data deriving module is a total traffic volume (i.e. the total traffic volume of the constraint area) and a class composition (i.e. the traffic volume ratio of each class in the constraint area), and the data of the unconstrained end output by the data deriving module is a total traffic volume of each endpoint (i.e. the total traffic volume of each geographic traffic cell in the unconstrained area), a traffic volume composition of each endpoint (i.e. the traffic volume ratio of each class in each geographic traffic cell in the unconstrained area) and a class composition of each endpoint (i.e. the traffic volume ratio of each class in the unconstrained area).
And under the self-defined two-end constraint OD data analysis mode, the data export module outputs the total traffic of each endpoint (the total traffic of each geographic traffic cell in the starting area and the total traffic of each geographic traffic cell in the ending area), and the class composition of each endpoint (the transmission traffic ratio of each class in the starting area and the arrival traffic ratio of each class in the ending area).
In addition, the railway OD data analysis and visualization system provided by the embodiment further comprises a desired line analysis function and a desired line filtering function.
The expected line is a line connecting the start and end points of the OD pairs for visually visualizing the traffic characteristics between the OD pairs on the map. The desired line may be selected from a straight line and an arc line.
The expected line analysis function provided in this embodiment specifically includes:
traffic pattern: the expected line visually visualizes the traffic between OD pairs, and the traffic is characterized by color, thickness.
Duty cycle mode: the expected line visual visualization OD is used for visually visualizing the proportion of the class traffic selected by the user among the pairs to all the class traffic, and the proportion is represented by colors and thickness.
A wire filtering function is desired: in order to improve the visualization efficiency of the system and meet the requirement of the user on adjusting the visualization effect, the system in the embodiment provides a function of filtering the expected line threshold, and the visualized expected line can be filtered in different areas according to the number set by the user.
Wherein the actual rendering effect in different desired line selectable modes is shown in fig. 8.
The railway OD data analysis visualization system provided by the embodiment further includes a region analysis function. The railway OD data analysis visualization system provided by the embodiment provides two functions of synchronous analysis and differential analysis.
Region and endpoint synchronization analysis function: the statistical index of the area (geographic traffic cell) is the same as the end point, the area is filled with different colors and transparencies, and the traffic distribution characteristics among the OD pairs of the area are visualized. The user can customize the color effect, transparency.
Region and endpoint difference analysis function: the region and endpoint statistics are different from the endpoint, and the user may select different statistics for the endpoint and region, respectively. The region indicators fill the region with different colors, transparencies, and visualize the traffic distribution characteristics between the OD pairs of the region. The user can customize the color effect, transparency.
Example two
Referring to fig. 9, the present embodiment provides a railway OD data analysis and visualization method, including:
step 901: selecting geographic traffic cells corresponding to research requirements according to different regional granularities; the regional granularity comprises a city group level, a region level, a province level, a city level, a county region level, a railway system custom level and a user custom level; the study requirements include a study area and/or a study category.
Step 902: selecting the category corresponding to the research requirement according to different classification granularities; the classification granularity includes a passenger class and a cargo class.
Step 903: selecting an OD data analysis mode corresponding to the research requirement; the OD data analysis mode is one of a global unconstrained OD data analysis mode, a self-defined one-end constrained OD data analysis mode and a self-defined two-end constrained OD data analysis mode; the global unconstrained OD data analysis mode refers to an OD data analysis mode which does not constrain both the starting region and the ending region; the self-defined one-end constraint OD data analysis mode refers to an OD data analysis mode for restraining a starting area or a terminating area; the self-defined two-end constraint OD data analysis mode refers to an OD data analysis mode for constraining both a starting area and a terminating area.
Step 904: and screening railway OD data in a database by taking a geographic traffic cell, a class and an OD data analysis mode corresponding to the research demand as constraint conditions to determine OD data corresponding to the research demand, and determining the research area and/or the traffic of the research class based on the OD data corresponding to the research demand.
Step 905: and displaying the traffic distribution of the research area and/or the research product class and the multi-mode to volume statistics of the research area and/or the research product class based on the OD data corresponding to the research requirement.
Step 905 specifically includes:
based on the OD data corresponding to the research requirement, representing the total traffic volume (total transmission volume and/or total arrival volume) of the geographic traffic cells by using characterization marks such as points, bubbles, pie charts, regular areas or irregular areas on a web map, and representing the directed or undirected OD connection volume between the geographic traffic cells by using a connecting line between the two characterization marks. The size and/or the color of the characterization mark represents the total traffic of the geographic traffic cell, and the OD (optical density) contact quantity is characterized by the color and the thickness of the connecting line.
Based on the OD data corresponding to the research requirements, representing the total transportation quantity (total sending quantity and/or total arrival quantity) of the set research products in the geographic traffic cell by using characterization marks such as points, bubbles, cake charts, regular areas or irregular areas on a web map, and representing the directed or undirected OD connection quantity between the set research products in the geographic traffic cell by using a connecting line between the two characterization marks.
Displaying the traffic distribution of the research area and/or the research category in a statistical chart form based on the OD data corresponding to the research requirement; the statistical chart comprises a histogram and a line graph; statistics in the histogram mode show the traffic statistics of the study area and/or the study class; the abscissa of the fold line graph is the study period, and the ordinate is the transport capacity of the study area and/or the study class.
In the transmission construction mode or the arrival construction mode, displaying the research area and/or the traffic distribution of the research category in a map form based on the OD data corresponding to the research requirement in a manner of using a pie chart to represent the position of the geographic traffic cell and using lines to represent the interactive relation of each geographic traffic cell; wherein the size of the pie chart represents the size of the total traffic volume of the geographic traffic cell; the proportion of each sector of the pie chart represents the ratio of each category in the total traffic; the total traffic is total traffic or total arrival.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (10)
1. A railway OD data analysis visualization system, comprising:
a geographic traffic cell selection module for: selecting geographic traffic cells corresponding to research requirements according to different regional granularities; the regional granularity comprises a city group level, a region level, a provincial level, a city level, a county region level, a railway system custom level and a user custom level; the study requirements include a study area and/or a study category;
the class selection module is used for: selecting the category corresponding to the research requirement according to different classification granularities; the classification granularity comprises passenger transportation class, freight transportation class, passenger subclass and freight subclass;
an OD data analysis mode selection module for: selecting an OD data analysis mode corresponding to the research requirement; the OD data analysis mode is one of a global unconstrained OD data analysis mode, a self-defined one-end constrained OD data analysis mode and a self-defined two-end constrained OD data analysis mode; the global unconstrained OD data analysis mode refers to an OD data analysis mode which does not constrain both the starting region and the ending region; the self-defined one-end constraint OD data analysis mode refers to an OD data analysis mode for restraining a starting area or a terminating area; the self-defined two-end constraint OD data analysis mode refers to an OD data analysis mode for restraining both a starting area and a terminating area;
The traffic data determining module is used for:
taking geographic traffic cells, categories and OD data analysis modes corresponding to the research demands as constraint conditions, and screening railway OD data in a database to determine OD data corresponding to the research demands;
determining the volume of the study area and/or the study class based on the OD data corresponding to the study demand;
a visualization module for: and displaying the traffic distribution of the research area and/or the research product class and the multi-mode to volume statistics of the research area and/or the research product class based on the OD data corresponding to the research requirement.
2. The railway OD data analysis visualization system of claim 1, wherein the research requirements further comprise a research period;
the traffic data determining module specifically comprises:
a time period selection unit, configured to select a time period corresponding to the study requirement;
the OD data determining unit is used for screening railway OD data in a database by taking a geographic traffic cell, a class, an OD data analysis mode and a time period corresponding to the research requirement as constraint conditions so as to determine the OD data corresponding to the research requirement;
And the traffic determination unit is used for determining the traffic of the research area and/or the research product class based on the OD data corresponding to the research requirement.
3. The railway OD data analysis visualization system of claim 2, wherein the OD data analysis mode selection module specifically comprises:
the OD data analysis mode first selection unit is used for selecting an OD data analysis mode corresponding to the research requirement;
the OD data analysis mode second selection unit is used for determining a first OD data analysis sub-mode corresponding to the research requirement when the OD data analysis mode is a self-defined one-end constraint OD data analysis mode and the geographic traffic cells are multiple; the first OD data analysis sub-mode comprises a non-merging geographical traffic cell sub-mode and a merging geographical traffic cell sub-mode; the non-merging geographic traffic cell sub-mode is a mode of determining each geographic traffic cell as an independent target and simultaneously carrying out OD data analysis on each geographic traffic cell, and the merging geographic traffic cell sub-mode is a mode of merging a plurality of geographic traffic cells into a virtual merging geographic traffic cell and carrying out overall OD data analysis on the virtual merging geographic traffic cell;
And the OD data determining unit is used for screening the railway OD data in the database by taking the geographic traffic cell, the class, the first OD data analysis sub-mode and the time period corresponding to the research requirement as constraint conditions so as to determine the OD data corresponding to the research requirement.
4. The railway OD data analysis visualization system of claim 2, wherein the OD data analysis mode selection module specifically comprises:
the third selection unit of the OD data analysis mode is used for selecting the OD data analysis mode corresponding to the research requirement;
the OD data analysis mode fourth selection unit is used for determining a second OD data analysis sub-mode corresponding to the research requirement when the OD data analysis mode is a self-defined two-end constraint OD data analysis mode; the second OD data analysis sub-mode comprises a basic internal OD data analysis sub-mode and an internal and external OD data analysis sub-mode; the basic internal OD data analysis sub-mode is a mode for establishing a geographical traffic cell selection set and carrying out OD data analysis on a research area of which the initial area and the termination area belong to the geographical traffic cell selection set; the internal and external OD data analysis sub-mode is a mode for establishing a plurality of geographic traffic cell selection sets, selecting one geographic traffic cell selection set as an internal selection set, selecting other geographic traffic cell selection sets as external selection sets, carrying out OD data analysis on a research area in the internal selection set, and carrying out OD data analysis on a research area between the internal selection set and the external selection set;
And the OD data determining unit is used for screening the railway OD data in the database by taking the geographical traffic cell, the class, the second OD data analysis sub-mode and the time period corresponding to the research requirement as constraint conditions so as to determine the OD data corresponding to the research requirement.
5. A railroad OD data analysis visualization system as in claim 2, wherein the research requirements further include endpoint analysis;
the OD data analysis mode selection module specifically includes:
an OD data analysis mode fifth selecting unit, configured to select an OD data analysis mode corresponding to the research requirement;
the sixth selection unit of the OD data analysis mode is configured to select an endpoint analysis mode corresponding to the research requirement when the OD data analysis mode is a custom one-end constraint OD data analysis mode;
the endpoint analysis mode comprises a sending mode, an arrival mode, a total arrival mode, a net arrival mode, a sending composition mode and an arrival composition mode;
the sending mode is a mode for analyzing the total sending quantity of the specified product of the geographic traffic cell user corresponding to the research requirement;
the arrival mode is a mode for analyzing the total arrival amount of the specified categories of the users in the geographic traffic cell corresponding to the research requirements;
The total arrival mode is a mode for analyzing the total transmission quantity and the total arrival quantity of the user-specified goods of the geographic traffic cell corresponding to the research requirement;
the net arrival mode is a mode for analyzing differences of user-specified categories of the geographic traffic cells corresponding to the research demands; the difference is the difference between the total transmission amount and the total arrival amount;
the transmission composition mode is a mode for analyzing the transmission composition of the user-specified class of the geographic traffic cell corresponding to the research requirement;
the arrival composition mode is a mode for analyzing arrival composition of the user-specified category of the geographic traffic cell corresponding to the research requirement;
the transmission structure is formed by the transmission traffic of each category and the transmission traffic proportion of each category; the arrival structure is composed of arrival traffic of each category and arrival traffic proportion of each category;
and the OD data determining unit is used for screening the railway OD data in the database by taking the geographic traffic cell, the class, the endpoint analysis mode and the time period corresponding to the research requirement as constraint conditions so as to determine the OD data corresponding to the research requirement.
6. A railway OD data analysis visualization system according to claim 1, wherein,
The visualization module is used for:
and displaying the traffic distribution of the research area and/or the research category in a map form or a statistical chart form based on the OD data corresponding to the research requirement.
7. A railway OD data analysis visualization system according to claim 5, wherein,
the visualization module is used for:
displaying the research area and/or the traffic distribution of the research category in a map form in a way of representing the position of the geographic traffic cell by a circle and representing the interaction relation of each geographic traffic cell by a line based on the OD data corresponding to the research demand; the size and/or color of the circle represents the size of the total traffic of the geographic traffic cell;
or based on the OD data corresponding to the research requirement, displaying the research area and/or the traffic distribution of the research category in a statistical chart form; the statistical chart comprises a histogram and a line graph; statistics in the histogram mode show the traffic statistics of the study area and/or the study class; the abscissa of the line graph is a research time period, and the ordinate is the transportation of the research area and/or the research category;
Or in the sending construction mode or the arrival construction mode, displaying the research area and/or the traffic distribution of the research category in a map form in a way of showing the position of the geographic traffic cells in a pie chart and showing the interaction relation of each geographic traffic cell in a line based on the OD data corresponding to the research requirement; wherein the size of the pie chart represents the size of the total traffic volume of the geographic traffic cell; the proportion of each sector of the pie chart represents the ratio of each category in the total traffic; the total traffic is the total transmission amount or the total arrival amount.
8. A railway OD data analysis visualization system as in claim 1 or 2, further comprising: a data export module;
the data export module is used for exporting the transportation quantity of the research area and/or the research category in a set data structure form;
the data output by the data export module is total traffic, class constitution, each end point traffic, each end point class constitution and OD quantity containing starting and ending point information and class.
9. The railway OD data analysis visualization system of claim 1, wherein the passenger classes include a plurality of subclasses, each of a high speed motor train unit train, an intercity motor train unit train, a common motor train unit train, a direct express passenger train, an express passenger train, a regular passenger express train, and a regular passenger express train; the shipping class includes a plurality of subclasses, respectively food, agriculture, energy, material, ore, container, and other totals; the other aggregate is freight class other than food, agriculture, energy, materials, ore, containers.
10. A method for visualizing railway OD data analysis, comprising:
selecting geographic traffic cells corresponding to research requirements according to different regional granularities; the regional granularity comprises a city group level, a region level, a provincial level, a city level, a county region level, a railway system custom level and a user custom level; the study requirements include a study area and/or a study category;
selecting the category corresponding to the research requirement according to different classification granularities; the classification granularity comprises a passenger class and a freight class;
selecting an OD data analysis mode corresponding to the research requirement; the OD data analysis mode is one of a global unconstrained OD data analysis mode, a self-defined one-end constrained OD data analysis mode and a self-defined two-end constrained OD data analysis mode; the global unconstrained OD data analysis mode refers to an OD data analysis mode which does not constrain both the starting region and the ending region; the self-defined one-end constraint OD data analysis mode refers to an OD data analysis mode for restraining a starting area or a terminating area; the self-defined two-end constraint OD data analysis mode refers to an OD data analysis mode for restraining both a starting area and a terminating area;
Taking geographic traffic cells, categories and OD data analysis modes corresponding to the research demands as constraint conditions, and screening railway OD data in a database to determine OD data corresponding to the research demands;
determining the volume of the study area and/or the study class based on the OD data corresponding to the study demand;
and displaying the traffic distribution of the research area and/or the research product class and the multi-mode to volume statistics of the research area and/or the research product class based on the OD data corresponding to the research requirement.
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