CN115964123B

CN115964123B - Traffic planning space data processing method and device based on homeland space elements

Info

Publication number: CN115964123B
Application number: CN202211597235.4A
Authority: CN
Inventors: 顾明臣; 张硕; 王一宁; 刘宏; 孙硕; 王兰; 许哲; 吴学治; 熊慧嫄
Original assignee: Transport Planning And Research Institute Ministry Of Transport
Current assignee: Transport Planning And Research Institute Ministry Of Transport
Priority date: 2022-12-12
Filing date: 2022-12-12
Publication date: 2023-07-14
Anticipated expiration: 2042-12-12
Also published as: CN115964123A

Abstract

The invention provides a traffic planning space data processing method and device based on homeland space elements, which relate to the technical field of data processing and comprise the following steps: acquiring homeland space element data, comprehensive traffic basic space data, traffic analysis and calculation data, traffic statistics data and traffic unstructured data; the above data are fused to obtain homeland space and comprehensive traffic planning thematic data, and then an integrated virtual cluster of comprehensive traffic planning space data and business thematic application data is constructed; performing visualization processing on the integrated virtual cluster based on the expansion development request of the user to obtain a thematic data layer to be published; and performing multi-role applicable service release and management on the thematic data image layer through the GIS service platform. The traffic planning system realizes the business association and the topology association of the traffic planning space data and the attribute data, provides effective data support for traffic planning analysis, and provides a foundation for interconnection sharing of the traffic planning data.

Description

Traffic planning space data processing method and device based on homeland space elements

Technical Field

The invention relates to the technical field of data processing, in particular to a traffic planning space data processing method and device based on homeland space elements.

Background

The rapid promotion of the territorial space planning reform has more remarkable guiding and restraining effects on traffic planning space resources, and the traffic planning space data processing technology based on territorial space elements becomes a key whether the territorial space planning management and control requirements are met. Traffic planning space data based on homeland space elements is complex in source, and the service range covers homeland space basic data, various traffic transportation mode data, traffic planning service index data, socioeconomic data and the like, and the data type aspect comprises space topology data, statistical data, unstructured data and the like. In view of the fact that the deep 'one graph' fusion of the homeland space planning and the traffic planning business is a brand new technical requirement, particularly the processing, calculating and publishing requirements on space multisource data are high, the traditional single-machine batch and split-flow processing is mainly adopted in the comprehensive traffic planning at present, offline independent analysis and calculation are carried out, and finally the aggregate data of the homeland space planning and the traffic planning are subjected to space superposition, but the above mode cannot meet the constraint and control requirements, so that a complete processing method and device are provided for the traffic planning space data processing based on homeland space elements, the traffic planning refinement degree and the compiling efficiency are improved, and the problem to be solved by the person in the art is urgent.

Disclosure of Invention

The invention aims to provide a traffic planning space data processing method and device based on homeland space elements, so as to realize business association and topology association of traffic planning space data and attribute data, provide visual and convenient reference data for traffic planning, provide effective data support for traffic planning analysis and provide a foundation for interconnection sharing of traffic planning data.

In a first aspect, the present invention provides a traffic planning spatial data processing method based on a homeland space element, including: acquiring homeland space element data, comprehensive traffic basic space data, traffic analysis and calculation data, traffic statistics data and traffic unstructured data; the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic unstructured data are fused to obtain homeland space and comprehensive traffic planning thematic data; constructing an integrated virtual cluster of comprehensive traffic planning space data and business thematic application data based on the homeland space and the comprehensive traffic planning thematic data; performing visualization processing on the integrated virtual cluster based on an expansion development request of a user to obtain a thematic data layer to be published; and performing multi-role applicable service release and management on the thematic data image layer through a GIS service platform.

In an alternative embodiment, fusing the homeland space element data, the comprehensive traffic base space data, the traffic analysis calculation data, the traffic statistics class data and the traffic unstructured data includes: processing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic unstructured data into corresponding relational two-dimensional tables to obtain a relational two-dimensional table set; constructing an associated view of the topology primitive and the attribute index based on the relation type two-dimensional table set; carrying out space geographic information standardization processing on the associated view to obtain a comprehensive traffic planning geographic information diagram; modifying the comprehensive traffic planning geographic information map based on a preset traffic planning business rule to obtain a modified comprehensive traffic planning geographic information map; and updating space topology and attribute data based on the modified comprehensive traffic planning geographic information map to obtain the homeland space and comprehensive traffic planning thematic data.

In an alternative embodiment, the processing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic statistics data and the traffic unstructured data into corresponding relational two-dimensional tables includes: converting the traffic unstructured data into traffic structured data; performing data quality check on the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic structural data to obtain a check result; under the condition that the verification result is determined to be passing, carrying out data cleaning and dimension reduction on the data passing the verification to obtain target multi-source data; wherein the target multi-source data comprises: target homeland space element data, target comprehensive traffic basic space data, target traffic analysis and calculation data, target traffic statistics data and target traffic structural data; converting the target multisource data into a corresponding initial relation type two-dimensional table; and under the condition that the initial relation type two-dimensional table meets the preset data quality requirement, taking the initial relation type two-dimensional table as the relation type two-dimensional table.

In an alternative embodiment, constructing an association view of the topology primitive and the attribute index based on the relational two-dimensional table set includes: establishing a business attribute relation rule, a space topology relation rule and an index calculation association rule of data based on the relation type two-dimensional table set; carrying out association fusion on the characteristic index data in the relational two-dimensional table set based on the business attribute relation rule to obtain basic index data of traffic planning based on multi-business source data; performing multi-index calculation on the traffic planning basic index data based on the index calculation association rule to obtain planning characteristic index data; and carrying out comprehensive space topological relation extraction on the traffic planning basic index data, the planning characteristic index data and the relational two-dimensional table set based on the space topological relation rule to obtain the association view.

In an alternative embodiment, constructing an integrated virtual cluster of comprehensive traffic planning space data and business topic application data based on the homeland space and comprehensive traffic planning topic data, including: classifying the territorial space and the comprehensive traffic planning thematic data to obtain comprehensive traffic planning space data and business thematic application data; respectively carrying out batch warehousing on the comprehensive traffic planning space data and the business thematic application data to obtain a comprehensive traffic planning space data entity cluster and a business thematic application data entity cluster; carrying out virtualization processing on the comprehensive traffic planning space data entity cluster and the business thematic application data entity cluster by utilizing a plurality of servers to obtain a corresponding virtualized entity cluster; and carrying out centralized scheduling and load balancing processing on all the virtualized entity clusters to obtain the integrated virtual cluster.

In an alternative embodiment, the visualization processing is performed on the integrated virtual cluster based on the extended development request of the user, including: extracting data resources of the integrated virtual cluster based on an expansion development request of a user to obtain service class data and space class data; performing visual form configuration on the service class data, and performing symbolization configuration on the space class data to obtain a target rendering strategy; and determining the thematic data layer to be published based on the target rendering strategy and the integrated virtual cluster.

In an alternative embodiment, before performing service distribution and management applicable to multiple roles on the thematic data layer through the GIS service platform, the method further includes: acquiring role configuration information for service release in a GIS service platform; and performing character configuration on the thematic data image layer to be distributed based on the character configuration information.

In a second aspect, the present invention provides a traffic planning spatial data processing device based on a homeland spatial element, including: the first acquisition module is used for acquiring homeland space element data, comprehensive traffic basic space data, traffic analysis and calculation data, traffic statistics data and traffic unstructured data; the fusion module is used for fusing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic unstructured data to obtain homeland space and comprehensive traffic planning thematic data; the construction module is used for constructing an integrated virtual cluster of comprehensive traffic planning space data and business thematic application data based on the homeland space and the comprehensive traffic planning thematic data; the visualization processing module is used for carrying out visualization processing on the integrated virtual cluster based on the expansion development request of the user to obtain a thematic data layer to be issued; and the issuing and managing module is used for issuing and managing the service applicable to the multi-role of the thematic data image layer through the GIS service platform.

In a third aspect, the present invention provides an electronic device, including a memory, and a processor, where the memory stores a computer program that can be executed on the processor, and the processor implements the steps of the traffic planning spatial data processing method based on the homeland space element according to any one of the foregoing embodiments when the processor executes the computer program.

In a fourth aspect, the present invention provides a computer readable storage medium storing computer instructions which, when executed by a processor, implement a method for processing traffic planning spatial data based on homeland space elements according to any one of the preceding embodiments.

According to the traffic planning space data processing method based on the homeland space elements, the traffic planning space data and the attribute data are subjected to a series of processing and operation such as fusion, visualization and service release according to the data characteristics and the service requirements by acquiring the multi-source heterogeneous homeland space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic statistics data and the traffic transport unstructured data, so that visual and convenient reference data are provided for traffic planning, effective data support is provided for traffic planning analysis, and a foundation is provided for interconnection sharing of the traffic planning data.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a traffic planning space data processing method based on a homeland space element provided by an embodiment of the invention;

FIG. 2 is a flow chart for fusing national space element data, comprehensive traffic basic space data, traffic analysis and calculation data, traffic statistics data and traffic unstructured data, which is provided by the embodiment of the invention;

FIG. 3 is a functional block diagram of a traffic planning spatial data processing device based on a homeland space element according to an embodiment of the present invention;

fig. 4 is a schematic diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. 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.

Some embodiments of the present invention are described in detail below with reference to the accompanying drawings. The following embodiments and features of the embodiments may be combined with each other without conflict.

The embodiment of the invention provides a traffic planning space data processing method and device based on the homeland space elements, which aims to solve the problem of multi-source heterogeneous traffic planning space data processing combined with the homeland space elements so as to enrich traffic planning decision information and further improve the scientificity and the rigor of traffic planning based on the homeland space elements.

Example 1

Fig. 1 is a flowchart of a traffic planning spatial data processing method based on homeland space elements, as shown in fig. 1, and the method specifically includes the following steps:

step S102, acquiring national and local space element data, comprehensive traffic basic space data, traffic analysis and calculation data, traffic statistics data and traffic unstructured data.

The data processing method provided by the embodiment of the invention firstly needs to acquire multi-source data related to the national and local space and the comprehensive traffic planning, wherein the multi-source data comprises the following steps: the system comprises homeland space element data, comprehensive traffic basic space data, traffic analysis and calculation data, traffic statistics data and traffic unstructured data. The data can be acquired by the modes of acquisition, real-time detection, intelligent identification, manual uploading and the like of planning related information through multiple data sources, so that data support is provided for traffic analysis and planning. Typically, the data is distributed across each existing database, and thus, may be obtained by resource interface matching with each associated database. The matching of the resource interfaces refers to classifying and summarizing data resources which come from various acquisition modes and are distributed in various systems, constructing a unified data resource center and exchanging interfaces with internal and external data by taking originality and uniqueness of data sources as principles, wherein the matching of the resource interfaces comprises the following steps: setting and adapting the database connection parameters, data service address configuration, sensor data interface protocol configuration and other resource acquisition channels.

In the embodiment of the invention, the homeland space element data comprises: the homeland space basic geographic information data, homeland space planning geographic information data and ecological protection area information data, for example: administrative division geographic information data, various protection area geographic information data and the like; infrastructure planning data such as highway networks, ports and the like needing traffic planning evaluation; natural environment data; environmental quality data; ecologically sensitive data; rare species data. Wherein, natural environment data such as land, water, forest, grassland, river and lake wetland, city, farmland, shoreline, fishery, travel, ecological resource data (geographic position, meteorological conditions, hydrology, silt, geological topography, etc.), etc. Environmental quality data such as sea area, ecology, water, atmosphere, sound, solid waste, etc.; ecologically sensitive zone data, such as natural protection zones, drinking water source protection zones, marine protection zones, aquatic germplasm resource protection zones, world cultural heritage, scenic tourism zones, forest parks, geological parks, wetland parks, fishing grounds, breeding zones and the like; rare species data such as national primary protected animals, secondary protected animals, rare wild animals, plant communities, and the like.

The comprehensive traffic basic space data is the result of spatial topology data standardization of 4 major categories of traffic basic current situation data, national comprehensive three-dimensional traffic network data, geographic space basic data and environmental protection target data, 132 items of data, wherein the traffic basic current situation data comprises the following steps: railway line data, highway line data, port data, channel data, airport data, etc.

The traffic analysis calculation data is calculated, processed and structurally expressed from time and space dimensions according to the calculation rule of traffic service characteristic index attributes, wherein the traffic service characteristic indexes include traffic flow, ship flow, passenger and cargo traffic, OD indexes and hour trip time.

Traffic statistics include: traffic survey data, passenger and freight related data, traffic control data, port planning data, traffic statistics report data, highway maintenance statistics data, port container throughput statistics data, railway freight volume data, airport throughput data, environment evaluation and monitoring data and other structured data.

The traffic unstructured data refers to data accessories and derived data attached to the data in the process of collecting and cleaning the data, and the traffic unstructured data comprises the following components: unstructured traffic transportation industry data such as patrol pictures, video monitoring, three-dimensional models, live-action data, texts and the like.

And step S104, the homeland space factor data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic unstructured data are fused to obtain homeland space and comprehensive traffic planning thematic data.

In view of the multi-source and heterogeneous characteristics of the data acquired in step S102, after the above-mentioned various data are acquired, service association and topology association of traffic planning space data and attribute data should be further implemented, which specifically includes: correlation of space data and service data, and attribute index correlation of different data characteristics of service. Wherein the association of the spatial data and the business data comprises: according to the topological association relation of the space data, an attribute index association corresponding rule of geographic point positions, line positions and area positions is established, geographic attributes of traffic planning service data are corresponding to the association, and geographic attribute information of unstructured service data is produced and associated.

The attribute index association of the different data features of the service comprises the following steps: according to the business attribute relation rule, aiming at the traffic attribute of the key traffic transportation business characteristic index, carrying out association calculation from time dimension and space dimension to form the traffic planning characteristic index based on multi-business source data.

According to the embodiment of the invention, the association relation is analyzed and calculated for the space topological relation, the service attribute relation and the index of all data, and fusion is carried out according to the planning service association rule and the planning method, so that the homeland space and the comprehensive traffic planning thematic data are obtained.

And S106, constructing an integrated virtual cluster of comprehensive traffic planning space data and business thematic application data based on the homeland space and the comprehensive traffic planning thematic data.

After the homeland space and the comprehensive traffic planning thematic data are obtained, in order to realize unified management and scheduling of the data, the embodiment of the invention further needs to form the standard comprehensive traffic planning space data and the standard comprehensive traffic planning thematic data into an integrated virtual cluster of the business thematic application data through operations such as standardized database building, data cluster construction, data cluster scheduling and load balancing.

And step S108, carrying out visualization processing on the integrated virtual cluster based on the expansion development request of the user to obtain a thematic data layer to be published.

Step S110, service release and management applicable to multiple roles are carried out on the thematic data image layer through the GIS service platform.

Specifically, in order to provide visual and convenient reference data for traffic planning, sharing application of data processing results is realized. After the integrated virtual cluster is obtained, the embodiment of the invention further performs visualization processing on the integrated virtual cluster according to the expansion development request of the user to obtain the thematic data layer, wherein the visualization processing comprises data rendering scheme configuration and data symbolization configuration, and generates the thematic data layer of the service application.

After the thematic data image layer of the visual rendering configuration is obtained, the embodiment of the invention utilizes the universal GIS service platform to conduct multi-role applicable service release and management on the thematic data image layer, realizes the export and release of various data visual achievements such as pictures, documents, data services and the like, and supports the management and sharing of the data services. Management, i.e. background management, includes: operational response and temporary data processing.

In an alternative embodiment, as shown in fig. 2, step S104 above fuses the homeland space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic statistics data and the traffic unstructured data, and specifically includes the following steps:

Step S1041, processing the national space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic unstructured data into corresponding relation type two-dimensional tables to obtain a relation type two-dimensional table set.

The domestic space factor data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic statistics data and the traffic unstructured data are respectively acquired from various data sources and are data with different untreated formats, and abnormal data, redundant data and the like possibly exist, so that in order to fuse useful and effective data in the five data, the five data are respectively processed into corresponding relational two-dimensional tables, and the five relational two-dimensional tables form a relational two-dimensional table set, wherein the relational two-dimensional table set is the source data related to the domestic space and the comprehensive traffic planning, which accords with the specifications.

And step S1042, constructing an association view of the topology graphic primitive and the attribute index based on the relation type two-dimensional table set.

After obtaining the relational two-dimensional table corresponding to each data, the data contained in the five relational two-dimensional tables are correlated, and the correlation operation has been described in detail above and will not be repeated here. In order to further deepen the association relation of the data, the embodiment of the invention also generates index data of other traffic planning features based on the five relational two-dimensional tables, further uses the newly generated index data and the five relational two-dimensional tables together as source data for extracting the comprehensive space topological relation, and finally forms an association view associated with the topological primitive and the attribute index through the comprehensive space topological relation extraction. Wherein the associated view is a territorial space and comprehensive traffic planning space initialization data asset.

And step S1043, carrying out space geographic information standardization processing on the associated view to obtain a comprehensive traffic planning geographic information diagram.

After the associated view is obtained, it needs to be subjected to spatial geographic information standardization processing to form a "one-piece map", i.e. a comprehensive traffic planning geographic information map. The display form of the comprehensive traffic planning geographic information diagram comprises the following steps: upper map drop, heat sensitive map, expectation map, statistical map, etc.

Step S1044, modifying the comprehensive traffic planning geographical information map based on the preset traffic planning business rule to obtain a modified comprehensive traffic planning geographical information map.

Further, the visualized comprehensive traffic planning geographic information diagram is interactively adjusted and modified according to a preset traffic planning business rule, so that the modified comprehensive traffic planning geographic information diagram is obtained. The preset traffic planning business rules are rules formulated according to serial business requirements of traffic planning scheme compiling, current situation analysis, optimization adjustment, tracking evaluation and the like. For example: 1) Mileage of each transportation mode is occupied; 2) East-middle-west high-speed rail mileage; 3) Development of east, middle and west construction; 4) The number of lanes (4/6/8 or more) of the expressway and the ratio of more than the national road level two; 5) Covering county-level administrative areas in number, population, and GDP as a national percentage; 6) The number of the coverage ground-level administrative areas/population/GDP of the three-dimensional mode established/long-term planned line accounts for the national percentage; 7) The transportation strength of the passenger and freight transportation; 8) The capacity utilization rate of each transportation mode.

Step S1045, updating the space topology and the attribute data based on the modified geographic information map of the comprehensive traffic planning to obtain homeland space and comprehensive traffic planning thematic data.

In an optional embodiment, the step S1041 processes the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic unstructured data into a corresponding relational two-dimensional table, and specifically includes the following steps:

step S10411, converting the traffic unstructured data into traffic structured data.

The known domestic space element data, the comprehensive traffic basic space data, the traffic analysis calculation data and the traffic statistics data belong to the structured data, so that in order to process all the data by adopting the same technical means, the traffic unstructured data are firstly converted into the traffic structured data. If the obtained traffic unstructured data is not electronic data, the electronic processing should be performed first, and then the structuring processing should be performed.

Step S10412, performing data quality check on the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic structural data to obtain a check result.

In an embodiment of the present invention, the data quality check includes: and (5) performing universality checksum arithmetic verification. The normalization, the integrity, the accuracy and the consistency of the data can be ensured through the data quality check. Specifically, the universality check means: and checking the data according to the data exchange standard. Since traffic routes are typically linear space elements, arithmetic verification refers to: and (3) checking and comparing the map length (the space shape proportion length) of the route with the mileage value (the actual mileage length) in the field record list, and checking whether the automatically calculated result is consistent with the filling value.

That is, according to the characteristics of the data, developing a related data quality auditing rule program, and performing universality verification on the data, wherein the universality verification comprises: null value, repetition, format anomalies, value field anomalies, spatial reference anomalies, and the like. For example: data field type check, exchange criteria are text type, cannot contain digits, such as: ten thousand cannot be represented by 10000 arabic numerals, and similarly, if the field type is numerals, letters cannot be filled in. In addition, after the field type check is passed, the field content is empty, or there are two repeated records in a table, and the field content is as follows: the paving type can be cement and asphalt, and other types of contents cannot appear, and the value range is checked. Format anomaly: if the data format is a shape format as agreed in the exchange data standard, the data cannot be found to be in coverage format after the resource interfaces (data pipes) are successfully matched. Arithmetic checking such as: judging whether the variation coefficient is too high.

If the verification result is not passed, a specific problem is displayed through the page, such as: the format of a certain table is E00 format, which does not accord with the agreed shape format in the exchange standard; the field type is character type, the specific non-compliance content such as text type requirement in the exchange standard is not met, the data acquisition is terminated, the error information is recorded in the log, at the moment, the user can correct the entry which is not passed by the verification through the man-machine interaction page, and finally, all the data can pass the verification.

And step S10413, carrying out data cleaning and dimension reduction on the data passing the verification under the condition that the verification result is determined to be passing, and obtaining the target multi-source data.

Furthermore, in order to solve the technical problems of different formats, scattered positions and large caliber difference of the basic data resources, standardized guarantee is provided for data service and application. After the data verification is passed, the data cleaning is needed, and the embodiment of the invention does not specifically limit the rule of the data cleaning, and the user can set the rule according to actual requirements, for example, the data format is converted from the shape format to the GDB format; overhang point cleaning: the road network line shape data is not ended at the end of a broken road or a road, other lines are intersected with the road network line shape data at the starting point or the end point of one line, and the situation that the road network data is suspected to be abnormally communicated is found out through the data cleaning rule; topology logic cleaning: i.e. the point is not on the line, such as: the intermodulation station should be on the route, may not be on the route, etc.; and (3) cleaning attribute codes: the data are cleaned through the attribute codes of administrative areas and lines, and are used for distinguishing the data of different administrative grades such as provinces, cities, counties, villages and the like, and the data granularity is unified.

After the data is cleaned, the embodiment of the invention further carries out data dimension reduction, constructs a dimension reduction method applicable to the global and the local according to the data characteristics, and carries out heterogeneous dimension reduction processing on the data. Specifically, the principal component analysis PCA method is used to process the data, merge repeated information and delete invalid information. After the series of processing, the target multi-source data can be obtained, wherein the target multi-source data comprises: target homeland space element data, target comprehensive traffic basic space data, target traffic analysis and calculation data, target traffic statistics data and target traffic structural data. The target national space element data represents data after data quality check, data cleaning and data dimension reduction are carried out on the national space element data, the target comprehensive traffic basic space data represents data after data quality check, data cleaning and data dimension reduction are carried out on the comprehensive traffic basic space data, and the like.

Step S10414, converting the target multisource data into a corresponding initial relational two-dimensional table.

After the target multi-source data is obtained, the embodiment of the invention further converts the target multi-source data into a corresponding initial relational two-dimensional table, and the operation of conversion can be also understood as a data structuring process, specifically, the service indexing structure process is performed on the data, and the data with various sources and various expression modes are digitized and tabulated, so that the data content conforming to the structural rules of the library table, such as: the statistical form in the paper statistical yearbook is recognized into an electronic form by the OCR of a computer, and the statistical form is manually processed into a data format of single row and single column.

In step S10415, when it is determined that the initial relationship type two-dimensional table meets the preset data quality requirement, the initial relationship type two-dimensional table is used as the relationship type two-dimensional table.

The step S10414 is completed to obtain five initial relationship type two-dimensional tables, and in order to determine whether the data quality of the initial relationship type two-dimensional tables meets the basic logic rule of the service and the warehousing standard, further performing secondary data quality verification on all the initial relationship type two-dimensional tables, if the verification is passed, the verification meets the preset data quality requirement, so that the initial relationship type two-dimensional tables can be used as the relationship type two-dimensional tables used in the subsequent operation steps. If the verification is not passed, the steps of data cleaning, dimension reduction and structuring are needed to be carried out again, and finally the source data which accords with the standard and is related to the national and local space and the comprehensive traffic planning are obtained.

In an optional embodiment, step S1042, above, constructs an association view of a topology primitive and an attribute index based on a set of relational two-dimensional tables, specifically includes the following steps:

step S10421, establishing a business attribute relation rule, a space topology relation rule and an index calculation association rule of the data based on the relation type two-dimensional table set.

Specifically, according to the common traffic basic attribute indexes of different spaces, different times, different granularities and different samples expressed in 5 types of data of a relational two-dimensional table set, establishing a traffic planning basic index processing and mapping relation based on a certain (or a plurality of) expression dimension, and forming a business attribute relation rule; for example: and (3) calculating bidirectional average natural traffic flow of the segments K300+000 to K345+000 of the G101 national road at the time of 17:30 of 10 months of 2022, and carrying out mapping processing such as sample expansion, vehicle type proportion estimation, track data playback and the like by adopting cross section intermodulation traffic flow data, two-passenger one-danger GPS data, mobile phone signaling data and truck overload overrun data to obtain the average natural traffic flow value of the road at the moment.

And according to element characteristic data expressing space points, lines and planes of the traffic planning in the 5-class data, establishing adjacency, association, position and inclusion relation among the element characteristic data to form a space topological relation rule.

And according to the 5-class data, data meeting the requirements of comprehensive traffic planning optimization, evaluation and analysis can be calculated, predicted or derived, a planning characteristic index calculation generating relation for optimization, evaluation and analysis is established, and an index calculation association rule is formed. For example, road traffic volume = road traffic flow volume x travel mileage.

And step S10422, carrying out association fusion on the characteristic index data in the relation type two-dimensional table set based on the business attribute relation rule to obtain the traffic planning basic index data based on the multi-business source data.

Specifically, feature index data in the relational two-dimensional table set is subjected to association processing, mapping and fusion from dimensions of administrative region space attributes, time attributes and planning business demand attributes according to business attribute relation rules to form traffic planning basic index data based on multi-business source data.

And step S10423, performing multi-index calculation on the basic index data of the traffic planning based on the index calculation association rule to obtain planning characteristic index data.

After the basic index data of the traffic planning are obtained, the association rule is further calculated according to the indexes, and multi-index calculation is carried out according to the deep requirements of the traffic planning and the mutual expression relation of the traffic indexes so as to generate planning characteristic index data for planning analysis, evaluation and tracking evaluation.

And step S10424, extracting comprehensive space topological relation from the traffic planning basic index data, the planning characteristic index data and the relation type two-dimensional table set based on the space topological relation rule to obtain a correlation view.

After the basic index data of traffic planning, the planning characteristic index data and the 7-class data of the relational two-dimensional table set are obtained, the comprehensive space topological relation extraction can be performed. Specifically, for service attribute data without a topological structure, firstly establishing an association relation among multiple attribute data table items, then establishing a spatial index field by encoding, and finally forming an association view of a topological graphic primitive and an attribute index by associating the spatial index field with data with the existing topological structure, thereby forming a domestic soil space and a comprehensive traffic planning space initialization data asset.

In an optional embodiment, the step S106 builds an integrated virtual cluster of comprehensive traffic planning space data and business topic application data based on the homeland space and the comprehensive traffic planning topic data, and specifically includes the following steps:

step S1061, classifying the territorial space and the comprehensive traffic planning thematic data to obtain comprehensive traffic planning space data and business thematic application data.

In the process of integrated virtual cluster construction, firstly, the homeland space and the comprehensive traffic planning thematic data are extracted and divided, and specifically, the homeland space and the comprehensive traffic planning thematic application data are extracted and divided into: and integrating two types of traffic planning space data and business thematic application data. The basic and common traffic planning business demand data are comprehensive traffic planning space data, such as current comprehensive traffic network scheme evaluation, comprehensive traffic facility adaptability analysis, comprehensive traffic planning demand prediction and the like; traffic planning business requirement data with strong thematic application scene are business thematic application data, for example: comprehensive traffic three-dimensional network evaluation, comprehensive hub evaluation and the like.

Step S1062, the comprehensive traffic planning space data and the business thematic application data are respectively put into a batch warehouse to obtain a comprehensive traffic planning space data entity cluster and a business thematic application data entity cluster.

And then, carrying out batch warehousing on the comprehensive traffic planning space data according to the planning space attribute as a main part and the service attribute as an auxiliary part to form a comprehensive traffic planning space data entity cluster, and carrying out batch warehousing on the service thematic application data according to the planning service attribute as a main part and the time and space attribute as an auxiliary part to form a service thematic application data entity cluster. Entity clusters refer to clusters of physical machines that primarily provide hardware resources, such as: IBM servers, data storage, etc.

Step S1063, a plurality of servers are utilized to virtualize the comprehensive traffic planning space data entity cluster and the business thematic application data entity cluster, and corresponding virtualized entity clusters are obtained.

Then, the existing two entity clusters are virtualized by utilizing a plurality of servers, and corresponding virtualized entity clusters are obtained. One part of the virtual machine servers are used for installing the database, the other part of the virtual machine servers are used for dynamically distributing the computing capacity of computing analysis, and the other part of the virtual machine servers are used for storing and analyzing computing tasks and managing the computing tasks to form a cache library.

Step S1064, performing centralized scheduling and load balancing processing on all virtualized entity clusters to obtain an integrated virtual cluster.

The virtualized entity clusters are subjected to centralized scheduling and load balancing, the data exchange nodes support application system cluster deployment and balanced load deployment, large data volume and large concurrent transmission requirements can be supported, and the system is subjected to fault transfer under the condition of network faults or server faults, so that high reliability of the system is supported. And finally, an integrated virtual cluster of comprehensive traffic planning space data and business thematic application data is formed, and unified management and scheduling are realized.

In an optional embodiment, the step S108 performs a visualization process on the integrated virtual cluster based on the extended development request of the user, and specifically includes the following steps:

step S1081, based on the user expansion development request, extracting the data resources of the integrated virtual cluster to obtain service class data and space class data.

To perform visualization processing on the integrated virtual cluster, firstly, according to the secondary expansion development requirement of the external user of the third party, the integrated virtual cluster is subjected to data resource extraction and screening from two dimensions of service class and space class according to user authority, expansion development permission conditions, technical environment and the like, so as to obtain service class data and space class data.

Step S1082, performing visual form configuration on the service class data, and performing symbolization configuration on the space class data to obtain the target rendering strategy.

Next, a target rendering policy needs to be determined, specifically, a rendering scheme is formed for the extracted and screened service class data, and a visual form of the service class data is configured, such as a category (a line graph, a histogram, a pie chart, a radar chart, a waterfall chart, etc.), a color, a font, etc. of the analysis chart. And the extracted and screened space data are symbolized and configured, and the symbol is similar to a filling station symbol, a marker symbol such as a store pharmacy, a road linear symbol and the like which can be seen in a hundred-degree map, and the specific symbols are expressed on railways, highways, channels, ports, airports and traffic infrastructures in planning in traffic.

Step S1083, determining a thematic data layer to be published based on the target rendering strategy and the integrated virtual cluster.

After the target rendering strategy is determined, the target rendering strategy is matched with the data resources in the integrated virtual cluster, so that a thematic data layer to be issued can be generated, and remote visualization, spatial integrated display and calling of the data are realized.

In an alternative embodiment, before executing step S110, the method of the present invention further includes the following steps of:

Step S1091, role configuration information for service release in the GIS service platform is obtained.

Step S1092, performing role configuration on the thematic data layers to be released based on the role configuration information.

Specifically, in order to perform role configuration and use on the distributed thematic data image layer from three dimensions of a user, a role and an authority according to different user identities, role configuration information for service distribution on a GIS service platform is required to be acquired before service distribution is performed on the thematic data image layer, so that role configuration information is utilized to perform role configuration on the thematic data image layer to be distributed. After being configured and subjected to service release through the GIS service platform, the user belongs to a certain role, and different roles have different operation rights on system functions and data. For example: the system administrator can maintain the system cluster data, and the common user can only maintain the data and services uploaded by the common user.

In addition, the databases involved in the method of the present invention are logically divided into an intermediate buffer database, a base database, and an application database. The intermediate buffer database is used for temporarily storing data before ETL data cleaning or as a data exchange prepositive database to be in butt joint with the target database. The basic database is a standardized data resource for data cleaning and warehousing according to the data resource demand catalog, and is the basis of all system data services. The application database is a database which is mined and optimized according to service requirements, is a database which finally provides high-efficiency data support and call for a system, and is matched with a traditional structured database cluster and Hadoop related service technology.

Example two

The embodiment of the invention also provides a traffic planning space data processing device based on the homeland space element, which is mainly used for executing the traffic planning space data processing method based on the homeland space element provided by the embodiment one, and the traffic planning space data processing device based on the homeland space element provided by the embodiment of the invention is specifically introduced below.

Fig. 3 is a functional block diagram of a traffic planning spatial data processing device based on homeland space elements according to an embodiment of the present invention, as shown in fig. 3, the device mainly includes: the system comprises a first acquisition module 10, a fusion module 20, a construction module 30, a visualization processing module 40, a release and management module 50, wherein:

the first acquisition module 10 is used for acquiring homeland space element data, comprehensive traffic basic space data, traffic analysis and calculation data, traffic statistics data and traffic unstructured data.

The fusion module 20 is configured to fuse the homeland space factor data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic statistics data and the traffic unstructured data to obtain homeland space and comprehensive traffic planning thematic data.

The construction module 30 is configured to construct an integrated virtual cluster of comprehensive traffic planning space data and business topic application data based on the homeland space and the comprehensive traffic planning topic data.

And the visualization processing module 40 is used for performing visualization processing on the integrated virtual cluster based on the expansion development request of the user to obtain a thematic data layer to be published.

The distribution and management module 50 is configured to distribute and manage services applicable to multiple roles for the thematic data layer through the GIS service platform.

According to the traffic planning space data processing device based on the homeland space elements, the traffic planning space data and the attribute data are subjected to a series of processing and operation such as fusion, visualization and service release according to the data characteristics and the service requirements by acquiring multi-source heterogeneous homeland space element data, comprehensive traffic basic space data, traffic analysis calculation data, traffic statistics data and traffic unstructured data, so that visual and convenient reference data are provided for traffic planning, effective data support is provided for traffic planning analysis, and a foundation is provided for interconnection sharing of traffic planning data.

Optionally, the fusion module 20 includes:

and the processing unit is used for processing the national and local space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic unstructured data into corresponding relational two-dimensional tables to obtain a relational two-dimensional table set.

And the construction unit is used for constructing an association view of the topology primitive and the attribute index based on the relation type two-dimensional table set.

And the normalization unit is used for carrying out space geographic information normalization processing on the associated view to obtain a comprehensive traffic planning geographic information diagram.

And the modification unit is used for modifying the comprehensive traffic planning geographic information diagram based on the preset traffic planning business rule to obtain a modified comprehensive traffic planning geographic information diagram.

And the updating unit is used for updating the space topology and the attribute data based on the modified comprehensive traffic planning geographic information diagram to obtain homeland space and comprehensive traffic planning thematic data.

Optionally, the processing unit is specifically configured to:

and converting the traffic unstructured data into traffic structured data.

And carrying out data quality verification on the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic structured data to obtain a verification result.

Under the condition that the verification result is determined to be passing, carrying out data cleaning and dimension reduction on the data passing the verification to obtain target multi-source data; wherein the target multi-source data comprises: target homeland space element data, target comprehensive traffic basic space data, target traffic analysis and calculation data, target traffic statistics data and target traffic structural data.

And converting the target multisource data into a corresponding initial relation type two-dimensional table.

And under the condition that the initial relation type two-dimensional table meets the preset data quality requirement, taking the initial relation type two-dimensional table as the relation type two-dimensional table.

Optionally, the construction unit is specifically configured to:

and establishing a business attribute relation rule, a space topological relation rule and an index calculation association rule of the data based on the relation type two-dimensional table set.

And carrying out association fusion on the characteristic index data in the relational two-dimensional table set based on the business attribute relation rule to obtain the traffic planning basic index data based on the multi-business source data.

And performing multi-index calculation on the traffic planning basic index data based on the index calculation association rule to obtain planning characteristic index data.

And carrying out comprehensive space topological relation extraction on the traffic planning basic index data, the planning characteristic index data and the relational two-dimensional table set based on the space topological relation rule to obtain a correlation view.

Optionally, the construction module 30 is specifically configured to:

and classifying the territorial space and the comprehensive traffic planning thematic data to obtain comprehensive traffic planning space data and business thematic application data.

And respectively carrying out batch warehousing on the comprehensive traffic planning space data and the business thematic application data to obtain a comprehensive traffic planning space data entity cluster and a business thematic application data entity cluster.

And carrying out virtualization processing on the comprehensive traffic planning space data entity cluster and the business thematic application data entity cluster by utilizing a plurality of servers to obtain a corresponding virtualized entity cluster.

And carrying out centralized scheduling and load balancing processing on all the virtualized entity clusters to obtain an integrated virtual cluster.

Optionally, the visualization processing module 40 is specifically configured to:

and extracting data resources of the integrated virtual cluster based on the expansion development request of the user to obtain service class data and space class data.

And carrying out visual form configuration on the service class data, and carrying out symbolization configuration on the space class data to obtain a target rendering strategy.

And determining a thematic data layer to be published based on the target rendering strategy and the integrated virtual cluster.

Optionally, the apparatus further comprises:

And the second acquisition module is used for acquiring the role configuration information for service release on the GIS service platform.

The configuration module is used for carrying out the role configuration on the thematic data image layer to be released based on the role configuration information.

Example III

Referring to fig. 4, an embodiment of the present invention provides an electronic device, including: a processor 60, a memory 61, a bus 62 and a communication interface 63, the processor 60, the communication interface 63 and the memory 61 being connected by the bus 62; the processor 60 is arranged to execute executable modules, such as computer programs, stored in the memory 61.

The memory 61 may include a high-speed random access memory (RAM, random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. The communication connection between the system network element and at least one other network element is achieved via at least one communication interface 63 (which may be wired or wireless), and may use the internet, a wide area network, a local network, a metropolitan area network, etc.

Bus 62 may be an ISA bus, a PCI bus, an EISA bus, or the like. The buses may be classified as address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 4, but not only one bus or type of bus.

The memory 61 is configured to store a program, and the processor 60 executes the program after receiving an execution instruction, and the method executed by the apparatus for defining a process disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 60 or implemented by the processor 60.

The processor 60 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software in the processor 60. The processor 60 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but may also be a digital signal processor (Digital Signal Processing, DSP for short), application specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA for short), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory 61 and the processor 60 reads the information in the memory 61 and in combination with its hardware performs the steps of the method described above.

The embodiment of the invention provides a traffic planning space data processing method and device based on a homeland space element, and a computer program product of the method and device comprises a computer readable storage medium storing non-volatile program codes executable by a processor, wherein the instructions included in the program codes can be used for executing the method described in the method embodiment, and specific implementation can be seen in the method embodiment and is not repeated herein.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.

In the description of the present invention, it should be noted that, directions or positional relationships indicated by terms such as "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., are directions or positional relationships based on those shown in the drawings, or are directions or positional relationships conventionally put in use of the inventive product, are merely for convenience of describing the present invention and simplifying the description, and are not indicative or implying that the apparatus or element to be referred to must have a specific direction, be constructed and operated in a specific direction, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and should not be construed as indicating or implying relative importance.

Furthermore, the terms "horizontal," "vertical," "overhang," and the like do not denote a requirement that the component be absolutely horizontal or overhang, but rather may be slightly inclined. As "horizontal" merely means that its direction is more horizontal than "vertical", and does not mean that the structure must be perfectly horizontal, but may be slightly inclined.

In the description of the present invention, it should also be noted that, unless explicitly specified and limited otherwise, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.

Claims

1. The traffic planning space data processing method based on the homeland space elements is characterized by comprising the following steps of:

Acquiring homeland space element data, comprehensive traffic basic space data, traffic analysis and calculation data, traffic statistics data and traffic unstructured data;

the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic unstructured data are fused to obtain homeland space and comprehensive traffic planning thematic data;

constructing an integrated virtual cluster of comprehensive traffic planning space data and business thematic application data based on the homeland space and the comprehensive traffic planning thematic data;

performing visualization processing on the integrated virtual cluster based on an expansion development request of a user to obtain a thematic data layer to be published;

performing multi-role applicable service release and management on the thematic data layer through a GIS service platform;

the method for fusing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic unstructured data comprises the following steps:

processing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic unstructured data into corresponding relational two-dimensional tables to obtain a relational two-dimensional table set;

Constructing an associated view of the topology primitive and the attribute index based on the relation type two-dimensional table set;

carrying out space geographic information standardization processing on the associated view to obtain a comprehensive traffic planning geographic information diagram;

modifying the comprehensive traffic planning geographic information map based on a preset traffic planning business rule to obtain a modified comprehensive traffic planning geographic information map;

updating space topology and attribute data based on the modified comprehensive traffic planning geographic information map to obtain homeland space and comprehensive traffic planning thematic data;

the processing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic unstructured data into corresponding relation type two-dimensional tables comprises the following steps:

converting the traffic unstructured data into traffic structured data;

performing data quality check on the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic structural data to obtain a check result;

Under the condition that the verification result is determined to be passing, carrying out data cleaning and dimension reduction on the data passing the verification to obtain target multi-source data; wherein the target multi-source data comprises: target homeland space element data, target comprehensive traffic basic space data, target traffic analysis and calculation data, target traffic statistics data and target traffic structural data;

converting the target multisource data into a corresponding initial relation type two-dimensional table;

under the condition that the initial relation type two-dimensional table meets the preset data quality requirement, the initial relation type two-dimensional table is used as the relation type two-dimensional table;

the construction of the association view of the topology primitive and the attribute index based on the relation type two-dimensional table set comprises the following steps:

establishing a business attribute relation rule, a space topology relation rule and an index calculation association rule of data based on the relation type two-dimensional table set;

carrying out association fusion on the characteristic index data in the relational two-dimensional table set based on the business attribute relation rule to obtain basic index data of traffic planning based on multi-business source data;

performing multi-index calculation on the traffic planning basic index data based on the index calculation association rule to obtain planning characteristic index data;

And carrying out comprehensive space topological relation extraction on the traffic planning basic index data, the planning characteristic index data and the relational two-dimensional table set based on the space topological relation rule to obtain the association view.

2. The traffic planning spatial data processing method based on the homeland spatial elements according to claim 1, wherein constructing an integrated virtual cluster of comprehensive traffic planning spatial data and business topic application data based on the homeland spatial and comprehensive traffic planning topic data comprises:

classifying the territorial space and the comprehensive traffic planning thematic data to obtain comprehensive traffic planning space data and business thematic application data;

respectively carrying out batch warehousing on the comprehensive traffic planning space data and the business thematic application data to obtain a comprehensive traffic planning space data entity cluster and a business thematic application data entity cluster;

carrying out virtualization processing on the comprehensive traffic planning space data entity cluster and the business thematic application data entity cluster by utilizing a plurality of servers to obtain a corresponding virtualized entity cluster;

and carrying out centralized scheduling and load balancing processing on all the virtualized entity clusters to obtain the integrated virtual cluster.

3. The traffic planning space data processing method based on the homeland space element according to claim 1, wherein the visualizing process of the integrated virtual cluster based on the extended development request of the user comprises:

extracting data resources of the integrated virtual cluster based on an expansion development request of a user to obtain service class data and space class data;

performing visual form configuration on the service class data, and performing symbolization configuration on the space class data to obtain a target rendering strategy;

and determining the thematic data layer to be published based on the target rendering strategy and the integrated virtual cluster.

4. The traffic planning spatial data processing method based on homeland space elements according to claim 3, wherein before performing multi-personally applicable service distribution and management on the thematic data map layer through a GIS service platform, the method further comprises:

acquiring role configuration information for service release in a GIS service platform;

and performing character configuration on the thematic data image layer to be distributed based on the character configuration information.

5. A traffic planning spatial data processing device based on homeland space elements, comprising:

The first acquisition module is used for acquiring homeland space element data, comprehensive traffic basic space data, traffic analysis and calculation data, traffic statistics data and traffic unstructured data;

the fusion module is used for fusing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistics data and the traffic unstructured data to obtain homeland space and comprehensive traffic planning thematic data;

the construction module is used for constructing an integrated virtual cluster of comprehensive traffic planning space data and business thematic application data based on the homeland space and the comprehensive traffic planning thematic data;

the visualization processing module is used for carrying out visualization processing on the integrated virtual cluster based on the expansion development request of the user to obtain a thematic data layer to be issued;

the publishing and management module is used for publishing and managing the multi-role applicable service of the thematic data image layer through the GIS service platform;

wherein, the fusion module includes:

the processing unit is used for processing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic statistics data and the traffic unstructured data into corresponding relation type two-dimensional tables to obtain a relation type two-dimensional table set;

The construction unit is used for constructing an association view of the topology graphic element and the attribute index based on the relation type two-dimensional table set;

the normalization unit is used for carrying out space geographic information normalization processing on the associated view to obtain a comprehensive traffic planning geographic information diagram;

the modification unit is used for modifying the comprehensive traffic planning geographic information map based on a preset traffic planning business rule to obtain a modified comprehensive traffic planning geographic information map;

the updating unit is used for updating the space topology and attribute data based on the modified comprehensive traffic planning geographic information map to obtain the homeland space and comprehensive traffic planning thematic data;

wherein, the processing unit is specifically configured to:

converting the traffic unstructured data into traffic structured data;

wherein, the construction unit is specifically used for:

6. An electronic device comprising a memory, a processor, the memory having stored thereon a computer program executable on the processor, characterized in that the processor, when executing the computer program, implements the steps of the method for processing traffic planning spatial data based on homeland space elements as claimed in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions, which when executed by a processor, implement the traffic planning spatial data processing method based on the homeland spatial elements of any one of claims 1 to 4.