CN115964123A - Method and device for processing traffic planning space data based on homeland space elements - Google Patents

Abstract

The invention provides a method and a device for processing traffic planning space data based on territorial 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 statistical data and traffic unstructured data; fusing the data to obtain homeland space and comprehensive traffic planning thematic data, and further constructing an integrated virtual cluster of the comprehensive traffic planning space data and service thematic application data; performing visualization processing on the integrated virtual cluster based on an extended development request of a user to obtain a thematic data layer to be issued; and issuing and managing the service suitable for multiple roles to the thematic data map layer through a GIS service platform. The traffic planning space data and the attribute data are associated with each other in a service and topology, effective data support is provided for traffic planning analysis, and a foundation is provided for interconnection and sharing of traffic planning data.

Description

Method and device for processing traffic planning space data based on homeland space elements

Technical Field

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

Background

The rapid promotion of the reform of the homeland space planning is more remarkable in the guiding and constraining effect on the traffic planning space resources, and a traffic planning space data processing technology based on homeland space elements becomes a key for meeting the control requirement of the homeland space planning. The traffic planning space data based on the territorial space elements has complex sources, the service range covers the territorial space basic data, various traffic transportation mode data, traffic planning service index data, social and economic data and the like, and the data types comprise space topological data, statistical data, unstructured data and the like. In view of the brand-new technical requirement of 'one map' fusion of the depth of the homeland space planning and traffic planning service, and particularly the high requirements on processing, calculation and release of spatial multi-source data, the conventional single-machine batch and shunt process processing and offline independent analysis and calculation are mainly adopted in the current comprehensive traffic planning, and finally the collective data of the homeland space planning and the traffic planning are subjected to spatial superposition.

Disclosure of Invention

The invention aims to provide a method and a device for processing traffic planning space data based on homeland space elements, which are used for realizing service association and topological association of the traffic planning space data and attribute data, providing visual and convenient reference data for traffic planning, providing effective data support for traffic planning analysis and providing a foundation for interconnection and sharing of the traffic planning data.

In a first aspect, the present invention provides a method for processing traffic planning space data based on homeland space elements, including: acquiring homeland space element data, comprehensive traffic basic space data, traffic analysis and calculation data, traffic statistical data and traffic unstructured data; fusing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic transportation statistical data and the traffic transportation unstructured data to obtain homeland space and comprehensive traffic planning thematic data; constructing an integrated virtual cluster of comprehensive traffic planning space data and service subject application data based on the territorial space and the comprehensive traffic planning subject data; performing visualization processing on the integrated virtual cluster based on an extended development request of a user to obtain a thematic data layer to be issued; and issuing and managing the service suitable for the multi-role by the special data map layer through a GIS service platform.

In an optional embodiment, the integrating the homeland space element data, the integrated traffic basic space data, the traffic analysis calculation data, the traffic statistical 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 statistical 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 topological graphic elements and the attribute indexes based on the relational two-dimensional table set; carrying out space geographic information standardization processing on the associated view to obtain a comprehensive traffic planning geographic information map; modifying the comprehensive traffic planning geographic information map based on a preset traffic planning service rule to obtain a modified comprehensive traffic planning geographic information map; and updating spatial 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 optional embodiment, the processing the homeland space element data, the integrated traffic basic space data, the traffic analysis calculation data, the traffic statistics data and the traffic unstructured data into a corresponding relational two-dimensional table includes: converting the transportation unstructured data into transportation structured data; performing data quality verification on the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistical data and the traffic structured data to obtain a verification result; under the condition that the verification result is determined to be passed, carrying out data cleaning and dimension reduction on the data passed through 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 statistical data and target traffic structured data; converting the target multi-source data into a corresponding initial relational two-dimensional table; and under the condition that the initial relational two-dimensional table is determined to meet the preset data quality requirement, taking the initial relational two-dimensional table as the relational two-dimensional table.

In an optional embodiment, constructing an associated view of the topological primitive associated with the attribute index based on the relational two-dimensional table set includes: establishing a business attribute relation rule, a spatial topological relation rule and an index calculation association rule of data based on the relational two-dimensional table set; performing association fusion on the characteristic index data in the relational two-dimensional table set based on the service attribute relation rule to obtain traffic planning basic index data based on multi-service 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 performing 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 associated view.

In an optional embodiment, constructing an integrated virtual cluster of integrated traffic planning space data and service topic application data based on the homeland space and the integrated traffic planning topic data includes: classifying the territorial space and the comprehensive traffic planning thematic data to obtain comprehensive traffic planning space data and service thematic application data; respectively storing the comprehensive traffic planning space data and the service special topic application data in a warehouse in batches to obtain a comprehensive traffic planning space data entity cluster and a service special topic application data entity cluster; performing virtualization processing on the comprehensive traffic planning space data entity cluster and the service special topic application data entity cluster by using a plurality of servers to obtain corresponding virtualized entity clusters; and performing centralized scheduling and load balancing processing on all the virtualized entity clusters to obtain the integrated virtual cluster.

In an optional embodiment, the visualization processing of the integrated virtual cluster based on the extension development request of the user includes: performing data resource extraction on the integrated virtual cluster 5 based on an extended development request of a user to obtain service data and space data; the business class data is processed

Visualization form configuration, namely symbolization configuration is carried out on the space type data to obtain a target rendering strategy; and determining the thematic data layer to be issued based on the target rendering strategy and the integrated virtual cluster.

In an optional embodiment, before issuing and managing a service applicable to 0 multi-role to the thematic data layer through a GIS service platform, the method further includes: obtain in GIS service level

The station carries out role configuration information of service release; and performing role-based configuration on the thematic data image layer to be issued based on the role configuration information.

In a second aspect, the present invention provides a traffic planning space data processing apparatus based on homeland space elements, including: the first acquisition module is used for acquiring homeland space element data, comprehensive traffic foundation 5 space data, traffic analysis calculation data, traffic transportation statistical data and traffic transportation unstructured data; the fusion module is used for fusing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic transportation statistical data and the traffic transportation unstructured data to obtain homeland space and comprehensive traffic planning thematic data; building blocks of

Constructing an integrated virtual cluster of comprehensive traffic planning space data and 0 service thematic application data based on the homeland space and the comprehensive traffic planning thematic data; the visualization processing module is used for performing visualization processing on the integrated virtual cluster based on an extended development request of a user to obtain a thematic data layer to be issued; and the issuing and management module is used for issuing and managing the service suitable for multiple roles to the thematic data map layer through a GIS service platform.

In a third aspect, the present invention provides an electronic device, which includes a memory and a processor, wherein the memory 5 stores thereon a computer program operable on the processor, and the processor executes the computer program to implement the steps of the method for processing traffic planning space data based on territorial space elements according to any one of the foregoing embodiments.

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

According to the traffic planning space data processing method based on the territorial space elements, provided by the invention, a series of processing and operations such as fusion, visualization, service release and the like are carried out on data according to data characteristics and business requirements by acquiring multi-source and heterogeneous territorial space element data, comprehensive traffic basic space data, traffic analysis calculation data, traffic transportation statistical data and traffic transportation unstructured data, so that business association and topological association of the traffic planning space data and attribute data are realized, 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 and 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 used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.

Fig. 1 is a flowchart of a traffic planning space data processing method based on homeland space elements according to an embodiment of the present invention;

fig. 2 is a flowchart for fusing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic statistical data, and the traffic unstructured data according to the embodiment of the present invention;

fig. 3 is a functional block diagram of a traffic planning space data processing apparatus based on territorial space elements 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

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of 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 present invention, 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 derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

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

In order to solve the problem of multi-source heterogeneous traffic planning space data processing combined with homeland space elements, thereby enriching traffic planning decision information and further improving the scientificity and the strictness of traffic planning based on the homeland space elements, the embodiment of the invention provides a traffic planning space data processing method and device based on the homeland space elements.

Example one

Fig. 1 is a flowchart of a traffic planning space data processing method based on territorial spatial elements according to an embodiment of the present invention, and as shown in fig. 1, the method specifically includes the following steps:

and S102, acquiring homeland 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 territorial 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 acquiring planning related information through multiple data sources, detecting in real time, intelligently identifying, uploading manually and the like, so that data support is provided for traffic analysis and planning. Generally, the data is distributed in each existing database, so that the data can be obtained by performing resource interface matching with each related database. The matching of the resource interfaces refers to classifying and summarizing data resources which are originated from various acquisition modes and distributed in various systems, and establishing a unified data resource center and an exchange interface with internal and external data by taking the originality and uniqueness of data sources as the principle, wherein the matching of the resource interfaces comprises the following steps: setting and adapting of resource acquisition channels such as database connection parameter setting, data service address configuration, sensing data interface protocol configuration and the like.

In the embodiment of the present invention, the homeland space element data includes: the territorial space basic geographic information data, the territorial space planning geographic information data and the ecological protection area information data are as follows, for example: administrative division geographic information data, various protection area geographic information data, and the like; infrastructure planning data such as a road network, a port and the like which need to be subjected to traffic planning evaluation; natural environment data; environmental quality data; ecological sensitive data; rare species data. Wherein, the natural environment data, such as land, water, forest, grassland, river and lake wetlands, cities, farmlands, shorelines, fisheries, tourism, and ecological resource data (geographical position, meteorological conditions, hydrology, silt, geological landforms, etc.), etc. Environmental quality data, such as sea, ecological, water, atmospheric, acoustic, solid waste, etc.; ecological sensitive area data, such as natural conservation area, drinking water source conservation area, marine conservation area, aquatic germplasm resource conservation area, world cultural heritage, scenic tourism area, forest park, geological park, wetland park, fishery and culture area; rare species data, such as national primary protected animals, secondary protected animals, precious wild animals, plant communities, and the like.

The comprehensive traffic basic spatial data is the traffic basic current situation data, the national comprehensive three-dimensional traffic network data, the geographic spatial basic data and the environmental protection target data which are 4 categories, and 132 items of data are subjected to spatial topological data standardization, wherein the traffic basic current situation data comprises the following steps: railway line data, highway line data, port data, channel data, airport data, and the like.

The traffic analysis calculation data is calculated, processed and structurally expressed from time and space dimensions according to a calculation rule of the attribute of the traffic and transportation service characteristic index, wherein the traffic and transportation service characteristic index comprises traffic flow, ship flow, passenger and cargo transportation quantity, OD index and hour travel time.

The traffic statistics data comprises: the system comprises structured data such as traffic survey data, passenger transport and freight related data, control and overload data, port planning data, traffic and transportation statistical report data, highway maintenance statistical data, port container throughput statistical data, railway freight volume data, airport throughput data, environment evaluation and monitoring data and the like.

The transportation unstructured data refer to data attachments and derivative data attached to the data in the process of collecting and cleaning the data, and the data attachments and the derivative data comprise: and unstructured transportation industry data such as pictures, video monitoring, three-dimensional models, real scene data, texts and the like are surveyed.

And step S104, fusing the territorial space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic transportation statistical data and the traffic transportation unstructured data to obtain the territorial space and comprehensive traffic planning thematic data.

In view of the fact that the data acquired in step S102 has the characteristics of multiple sources and heterogeneity, after the multiple data are acquired, the service association and the topology association of the traffic planning space data and the attribute data should be further implemented, which specifically includes: and associating the spatial data with the service data, and associating the attribute indexes of different data characteristics of the service. The association of the spatial data and the service data comprises the following steps: according to the topological association relation of the spatial data, establishing attribute index association corresponding rules of geographic point positions, line positions and position positions, corresponding the geographic attributes of the traffic planning service data to the associations, and simultaneously producing the geographic attribute information of the unstructured service data and associating the geographic attribute information with the unstructured service data.

The attribute index association of different data characteristics of the service comprises the following steps: and performing correlation calculation from time and space dimensions according to the traffic attribute relation rule and aiming at the traffic attributes of the key traffic transportation service characteristic indexes to form the traffic planning characteristic indexes based on the multi-service source data.

The embodiment of the invention analyzes and calculates the association relation of the spatial topological relation, the service attribute relation and the index of all the data, and fuses according to the association rule and the method of the planning service to obtain the homeland space and the comprehensive traffic planning thematic data.

And S106, constructing an integrated virtual cluster of the comprehensive traffic planning space data and the service 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 a standard integrated virtual cluster of the comprehensive traffic planning space data and the service thematic application data by operations of standardized library building, data cluster scheduling, load balancing and the like.

And S108, 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 issued.

And step S110, issuing and managing the service suitable for the multiple roles to the thematic data map layer through the GIS service platform.

Specifically, in order to provide visual and convenient reference data for traffic planning, the sharing application of the data processing result is realized. After the integrated virtual cluster is obtained, the integrated virtual cluster is further subjected to visualization processing according to an extended development request of a user to obtain a thematic data layer, wherein the visualization processing comprises data rendering scheme configuration and data symbolization configuration, and the thematic data layer of the service application is generated.

After the thematic data layer configured by visual rendering is obtained, the embodiment of the invention utilizes a general GIS service platform to issue and manage multi-role applicable services to the thematic data layer, realizes exporting and issuing of data visual results in various forms such as pictures, documents, data services and the like, and supports management and sharing of data services. Management, namely background management, comprises: operation response and temporary data processing.

According to the traffic planning space data processing method based on the homeland space elements, provided by the invention, a series of processing and operations such as fusion, visualization, service release and the like are carried out on data according to data characteristics and service requirements by acquiring multi-source and heterogeneous homeland space element data, comprehensive traffic basic space data, traffic analysis calculation data, traffic transportation statistical data and traffic transportation unstructured data, so that the service association and topological association of the traffic planning space data and attribute data are realized, 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 and sharing of traffic planning data.

In an alternative embodiment, as shown in fig. 2, the step S104 of fusing the homeland space element data, the integrated traffic basic space data, the traffic analysis calculation data, the traffic transportation statistical data, and the traffic transportation unstructured data specifically includes the following steps:

and S1041, processing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic transportation statistical data and the traffic transportation unstructured data into corresponding relational two-dimensional tables to obtain a relational two-dimensional table set.

Since the territorial and local space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic statistics data and the traffic unstructured data which are respectively acquired from various data sources are data with different unprocessed formats, and abnormal data, redundant data and the like may exist, 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 source data which are relevant to the territorial space and the comprehensive traffic planning and meet the specifications.

Step S1042, constructing an associated view of the topological graph elements and the attribute indexes based on the relational two-dimensional table set.

After obtaining the relational two-dimensional table corresponding to each data, the data included in the five relational two-dimensional tables are associated, and the association operation has been described in detail above, and is not described herein again. In order to further deepen the association relationship of the data, the embodiment of the invention further 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 extracted by the comprehensive space topological relationship, and finally extracts through the comprehensive space topological relationship to form an association view of the topological primitives associated with the attribute indexes. Wherein the associated view is initialized data assets of a homeland space and a comprehensive traffic planning space.

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

After the associated view is obtained, the associated view needs to be subjected to spatial geographic information standardization processing to form a "map", that is, a comprehensive traffic planning geographic information map. The display form of the comprehensive traffic planning geographic information map comprises the following steps: upper plot placement, thermal map, expected line graph, statistical chart, and the like.

And S1044, modifying the comprehensive traffic planning geographic information map based on a preset traffic planning service rule to obtain the modified comprehensive traffic planning geographic information map.

Further, the visual comprehensive traffic planning geographic information map is interactively adjusted and modified according to preset traffic planning service rules to obtain a modified comprehensive traffic planning geographic information map. The preset traffic planning service rule is a rule formulated according to service requirements of a series of traffic planning scheme compilation, current state analysis, optimization adjustment, tracking evaluation and the like. For example: 1) Mileage proportion of each transportation mode; 2) The high-iron mileage accounts for the eastern midwest; 3) The development of the east midwest; 4) The number of lanes on the highway (4/6/8 and above) is in proportion to the number of second-level roads on national roads; 5) Covering the number, population and GDP of county administrative districts in percentage of the whole country; 6) The number of the established/long-term planning lines covering the land-level administrative districts/population/GDP account for the percentage of the whole country; 7) The transport strength of the passenger and freight transport; 8) And the capacity utilization rate of each transportation mode.

And step S1045, updating the spatial 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 optional embodiment, in the step S1041, the processing of the territorial space element data, the integrated traffic basic space data, the traffic analysis calculation data, the traffic statistics data, and the traffic unstructured data into the corresponding relational two-dimensional table specifically includes the following steps:

and step S10411, converting the transportation unstructured data into transportation structured data.

As it is known that the homeland space element data, the comprehensive traffic basic space data, the traffic analysis calculation data and the traffic statistical data all belong to structured data, in order to process all the data by the same technical means, the traffic unstructured data should be first converted into traffic structured data. If the acquired unstructured transportation data is not electronic data, the unstructured transportation data should be processed electronically first and then structured.

And step S10412, performing data quality verification on the homeland space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic transportation statistical data and the traffic transportation structured data to obtain a verification result.

In the embodiment of the present invention, the data quality verification includes: and (4) universal checking and arithmetic checking. The normalization, the integrity, the accuracy and the consistency of the data can be ensured through 5 data quality checks. In particular, general

The adaptive check means: and verifying the data according to the data exchange standard. Since traffic routes are typically linear spatial elements, arithmetic checking refers to: the map length (space shape proportion length) of the route is compared with the distance value (actual mileage length) in the field record table, and whether the automatically calculated result is consistent with the filling value is checked.

0, that is, based on the characteristics of the data, develop the related data quality audit rule program to audit the data

And performing universality verification, wherein the universality verification comprises the following steps: null, duplicate, format exception, value domain exception, spatial reference exception, etc. For example: and (3) checking the type of the data field, wherein the exchange standard specifies the text type and cannot contain numbers, such as: ten thousand cannot be represented by 10000 arabic numerals, and likewise, if the field is used

The type is a number, and likewise, text cannot be filled in. In addition, after the field type check is passed, the field content is 5 blank, or there are two duplicate records in a table, the field content, for example: the type of pavement is only

And (4) verifying the value range if the cement and the asphalt cannot have other types and the like. And (4) format exception: if the data format agreed in the exchange data standard is the shapefile format, the data can not be found to be in the coverage format after the resource interface (data pipeline) is successfully matched. The arithmetic check is for example: and judging whether the coefficient of variation is too high.

0 if the check result is no, the page shows specific problems, such as: the format of a certain table is E00 format, and does not conform to the agreed shapefile format in the exchange standard; and the type of a certain field is character type, the field does not conform to specific non-compliant contents such as text type requirements in an exchange standard and the like, the data acquisition is terminated, error information is recorded in a log, and at the moment, a user can correct the items which fail to pass the verification through a man-machine interaction page, so that all data can pass the verification finally.

5, S10413, if the verification result is determined to be passed, the data which is passed is processed

And performing line data cleaning and dimension reduction to obtain target multi-source data.

Furthermore, in order to eliminate the technical problems of inconsistent formats, scattered positions and large caliber difference of basic data resources, a standardized guarantee is provided for data service and application. After the data check is passed, data cleaning is required to be performed next, the embodiment of the invention does not specifically limit the rule of data cleaning, and a user can set according to actual requirements, for example, data format conversion is performed, and the shape format is converted into the GDB format; cleaning a suspension point: the linear data of the road network is intersected with other lines at the starting point or the end point of one line unless the linear data of the road network is ended at the broken end of the road or the end of the road, and the suspected abnormal communication condition of the road network data is found out through the data cleaning rule; topology logic cleaning: i.e. the points are not on-line, as: the transfer station is originally on the route and can be absent on the route; and (3) cleaning attribute codes: data are cleaned through attribute coding of administrative regions and lines, and the data are used for distinguishing data of different administrative levels such as provinces, cities, counties and villages, and data granularity is unified.

After the data is cleaned, the embodiment of the invention further performs data dimension reduction, constructs a global and local dimension reduction method according to the data characteristics, and performs heterogeneous dimension reduction processing on the data. Specifically, a Principal Component Analysis (PCA) method is used for processing data, combining repeated information and deleting invalid information. After the series of processing, target multi-source data can be obtained, wherein the target multi-source data comprises: the system comprises target homeland space element data, target comprehensive traffic basic space data, target traffic analysis and calculation data, target traffic transportation statistical data and target traffic transportation structured data. The target territorial space element data represents data obtained after data quality verification, data cleaning and data dimension reduction are carried out on the territorial space element data, the target comprehensive traffic basic space data represents data obtained after data quality verification, data cleaning and data dimension reduction are carried out on the comprehensive traffic basic space data, and the like.

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

After obtaining the target multi-source data, the embodiment of the present invention further converts the target multi-source data into a corresponding initial relational two-dimensional table, and the "conversion" operation may also be understood as a data structuring process, specifically, a business indexing structure process is performed on data, and data with various sources and expression modes are digitized and tabulated to meet the data content of the base table structure rule, such as: the statistical form in the paper statistical yearbook is identified into an electronic form through computer OCR, and the statistical form is manually processed into a single-row and single-column data format.

And step S10415, taking the initial relational two-dimensional table as a relational two-dimensional table under the condition that the initial relational two-dimensional table is determined to meet the preset data quality requirement.

And step S10414, obtaining five initial relational two-dimensional tables, further performing secondary data quality verification on all the initial relational two-dimensional tables in order to determine whether the data quality of the initial relational two-dimensional tables meets the basic business logic rules and the warehousing standards, and if the verification is passed, indicating that the data quality meets the preset data quality requirement, so that the initial relational two-dimensional tables can be used as the relational two-dimensional tables used in the subsequent operation steps. And if the verification fails, the steps of data cleaning, dimension reduction and structuring are required to be carried out again, and finally the source data which is in line with the standard and related to the territorial space and the comprehensive traffic planning is obtained.

In an optional implementation manner, in the step S1042, an association view of the topology primitive and the attribute index is constructed based on the relational two-dimensional table set, which 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 relational 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, a traffic planning basic index processing and mapping relation based on a certain (or multiple) expression dimension is established to form a business attribute relation rule; for example: and (2) calculating bidirectional average natural vehicle flow of a section K300+000 to K345+000 of G101 national road at 10 months and 10 days in 2022, at 17 hours, and performing mapping processing such as sample expansion, vehicle type proportion estimation, track data playback and the like by adopting cross-section cross-dispatching flow data, GPS data of two passengers and one danger, mobile phone signaling data and truck overload overrun data to obtain an average natural vehicle flow value of the section at the moment.

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

And according to the data which can be calculated, predicted or derived from the 5 types of data and accords with the requirements of optimization, evaluation and analysis of the comprehensive traffic planning, establishing a planning characteristic index calculation generation relation for optimization, evaluation and analysis, and forming an index calculation association rule. For example, highway traffic volume = highway traffic volume number + traffic mileage number.

And step S10422, performing association fusion on the feature index data in the relational two-dimensional table set based on the service attribute relation rule to obtain traffic planning basic index data based on the multi-service source data.

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

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

After the basic index data of the traffic planning is obtained, multi-index calculation is further performed according to the index calculation association rule and the traffic planning deep-level demand and traffic index mutual expression relation, so that planning characteristic index data for planning analysis, evaluation and tracking evaluation are generated.

And S10424, performing 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.

After obtaining the traffic planning basic index data, the planning characteristic index data and the relational two-dimensional table set 7-class data, the comprehensive space topological relation extraction can be carried out. Specifically, for the service type attribute data without the topological structure, an association relationship between multiple attribute data table items is established, then a space index field is established by encoding, and finally the space index field is associated with the data of the existing topological structure to form an associated view of the topological primitive associated with the attribute index, so that the initialized data assets of the homeland space and the comprehensive traffic planning space are formed.

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

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

In the process of building the integrated virtual cluster, firstly, extracting and dividing the homeland space and the comprehensive traffic planning thematic data, and specifically, extracting and dividing the homeland space and the comprehensive traffic planning thematic application data according to different scenes of traffic planning service requirements: and integrating two types of traffic planning space data and business topic application data. Wherein the basic and common traffic planning service demand data is 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; the traffic planning service requirement class data with strong thematic planning application scene is service thematic application data, for example: comprehensive traffic three-dimensional network evaluation, comprehensive junction evaluation and the like.

And step S1062, respectively storing the comprehensive traffic planning space data and the service special topic application data in a warehouse in batches to obtain a comprehensive traffic planning space data entity cluster and a service special topic application data entity cluster.

And then, the comprehensive traffic planning space data is put in storage in batches according to the planning space attribute as the main and the service attribute as the auxiliary to form a comprehensive traffic planning space data entity cluster, and the service thematic application data is put in storage in batches according to the planning service attribute as the main and the time and space attribute as the auxiliary to form a service thematic application data entity cluster. Entity cluster refers to a cluster of physical machines, which mainly provides hardware resources, such as: IBM servers, data stores, etc.

And step S1063, performing virtualization processing on the comprehensive traffic planning space data entity cluster and the service special topic application data entity cluster by using a plurality of servers to obtain corresponding virtualized entity clusters.

Then, the existing two entity clusters are virtualized by using a plurality of servers to obtain corresponding virtualized entity clusters. One part of the virtual machine servers are used for installing the database, the other most of the virtual machine servers are used for dynamically distributing the computing power of computing analysis, and the other virtual machine server is used for storing, analyzing and managing 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 cluster is subjected to centralized scheduling and load balancing, the data exchange node supports application system cluster deployment and load balancing deployment, large-data-volume and large-concurrency transmission requirements can be supported, fault transfer is carried out under the condition of network faults or server faults, and high reliability of the system is supported. And finally, an integrated virtual cluster of comprehensive traffic planning space data and service special application data is formed, and unified management and scheduling are realized.

In an optional embodiment, in the step S108, performing visualization processing on the integrated virtual cluster based on the extension development request of the user specifically includes the following steps:

step S1081, data resources of the integrated virtual cluster are extracted based on the user' S extended development request, and service data and space data are obtained.

For performing visualization processing on the integrated virtual cluster, firstly, according to the secondary extension development requirement of a third-party external user, data resources are extracted and screened from two dimensions of a business class and a space class of the integrated virtual cluster according to user permission, extension development permission conditions, a technical environment and the like, so as to obtain business class data and space class data.

And step S1082, performing visualization configuration on the service class data, and performing symbolization configuration on the space class data to obtain a 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 visualization form of the service class data is configured, such as a category (a line graph, a bar graph, a pie graph, a radar chart, a waterfall graph, and the like), a color, a font, and the like of an analysis chart. And symbolizing and configuring the extracted and screened spatial data, wherein similar to the hundred-degree map, the symbolic signs of gas stations, identification signs of shopping malls and the like, road linear signs and the like can be seen, and the railway, the road, the channel, the port, the airport and the traffic infrastructure in the planning are all expressed by specific signs.

And step S1083, determining a thematic data layer to be issued 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 data resources in the integrated virtual cluster, so that a thematic data layer to be issued can be generated, and remote visualization and spatial integrated display and calling of data are realized.

In an optional embodiment, before performing step S110, performing multi-role applicable service publishing and management on the thematic data map layer through the GIS service platform, the method of the present invention further includes the following steps:

step S1091, role configuration information for service publishing on the GIS service platform is obtained.

Step S1092, based on the role configuration information, the thematic data layer to be issued is configured in a role-based manner.

Specifically, in order to perform role-based configuration on three dimensions of a user, a role and an authority on a published thematic data layer according to different user identities, before service publishing is performed on the thematic data layer, role configuration information for performing service publishing on a GIS service platform needs to be acquired, so that role-based configuration is performed on the thematic data layer to be published by using the role configuration information. After configuration and service release through a GIS service platform, a user belongs to a certain role, and different roles have different operation authorities to system functions and data. For example: the system administrator can maintain the system cluster data, and the ordinary users can only maintain the data and the services uploaded by the ordinary users.

In addition, it should be noted that the databases involved in the method of the present invention are mainly 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 cleaning of ETL data or is used as a data exchange preposed database to be in butt joint with a target database. The basic database is a standardized data resource for cleaning and storing data 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 business requirements, is a database which provides efficient data support and calling for the system and is completed by matching the 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 territorial space elements, which is mainly used for executing the traffic planning space data processing method based on the territorial space elements provided by the embodiment.

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

the first obtaining module 10 is configured to obtain homeland space element data, comprehensive traffic basic space data, traffic analysis calculation data, traffic transportation statistical data, and transportation unstructured data.

And the fusion module 20 is configured to fuse the homeland space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic transportation statistical data, and the traffic transportation unstructured data to obtain homeland space and comprehensive traffic planning topic data.

And the construction module 30 is used for constructing an integrated virtual cluster of the comprehensive traffic planning space data and the service subject application data based on the territorial space and the comprehensive traffic planning subject data.

And the visualization processing module 40 is configured to perform visualization processing on the integrated virtual cluster based on the extended development request of the user to obtain a thematic data map layer to be published.

And the publishing and managing module 50 is used for publishing and managing the multi-role service applicable to the thematic data map layer through the GIS service platform.

The traffic planning space data processing device based on the territorial space elements obtains multisource and heterogeneous territorial space element data, comprehensive traffic basic space data, traffic analysis calculation data, traffic transportation statistical data and traffic transportation unstructured data, and performs a series of processing and operation such as fusion, visualization, service release and the like on the data according to data characteristics and service requirements, so that service association and topological association of the traffic planning space data and attribute data are realized, 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 and sharing of traffic planning data.

Optionally, the fusion module 20 comprises:

and 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 relational two-dimensional tables to obtain a relational two-dimensional table set.

And the construction unit is used for constructing an associated view of the topological graphic primitives and the attribute indexes based on the relational two-dimensional table set.

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

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

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

Optionally, the processing unit is specifically configured to:

and converting the transportation unstructured data into transportation 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 statistical data and the traffic structured data to obtain a verification result.

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

And converting the target multi-source data into a corresponding initial relational two-dimensional table.

And under the condition that the initial relational two-dimensional table is determined to meet the preset data quality requirement, taking the initial relational two-dimensional table as a relational two-dimensional table.

Optionally, the construction unit is specifically configured to:

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

And performing 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 carrying out 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.

And performing 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 a space topological relation rule to obtain an associated view.

Optionally, the building module 30 is specifically configured to:

and classifying the homeland space and the comprehensive traffic planning thematic data to obtain comprehensive traffic planning space data and service thematic application data.

And respectively storing the comprehensive traffic planning space data and the service special topic application data in a warehouse in batches to obtain a comprehensive traffic planning space data entity cluster and a service special topic application data entity cluster.

And performing virtualization processing on the comprehensive traffic planning space data entity cluster and the service special application data entity cluster by using a plurality of servers to obtain corresponding virtualized entity clusters.

And performing 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 performing data resource extraction on the integrated virtual cluster based on the expansion development request of the user to obtain service data and space data.

And carrying out visualization 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 issued 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 role configuration information for service release on the GIS service platform.

And the configuration module is used for carrying out role-based color-based configuration on the thematic data image layer to be issued.

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, wherein the processor 60, the communication interface 63 and the memory 61 are connected through the bus 62; the processor 60 is adapted to execute executable modules, such as computer programs, stored in the memory 61.

The Memory 61 may include a Random Access Memory (RAM) and a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 63 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like may be used.

The bus 62 may be an ISA bus, a PCI bus, an EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 4, but that does not indicate only one bus or one type of bus.

The memory 61 is configured to store a program, and the processor 60 executes the program after receiving an execution instruction, where the method performed by the apparatus defined by the 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 instructions in the form of hardware integrated logic circuits or software in the processor 60. The Processor 60 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed 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 directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is 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 above method.

The computer program product of the traffic planning space data processing method and device based on the territory space elements provided by the embodiment of the invention comprises a computer readable storage medium storing a nonvolatile program code executable by a processor, wherein instructions included in the program code can be used for executing the method in the previous method embodiment, and specific implementation can refer to the method embodiment, and is not described herein again.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into 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 such understanding, the technical solution of the present invention or a part thereof which substantially contributes to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute 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), a magnetic disk or an optical disk, and other various media capable of storing program codes.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.

In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings or the orientations or positional relationships that the products of the present invention are conventionally placed in use, and are only used for convenience in describing the present invention and simplifying the description, but do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," "third," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.

Furthermore, the terms "horizontal", "vertical", "overhang" and the like do not imply that the components are required to be absolutely horizontal or overhang, but may be slightly inclined. For example, "horizontal" merely means that the 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 otherwise explicitly specified or limited, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly and may, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and these modifications or substitutions do not depart from the spirit of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

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

acquiring homeland space element data, comprehensive traffic basic space data, traffic analysis and calculation data, traffic statistical data and traffic unstructured data;

fusing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic transportation statistical data and the traffic transportation unstructured data to obtain homeland space and comprehensive traffic planning thematic data;

constructing an integrated virtual cluster of comprehensive traffic planning space data and service 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 extended development request of a user to obtain a thematic data layer to be issued;

and issuing and managing the service suitable for multiple roles to the thematic data map layer through a GIS service platform.

2. The method for processing the traffic planning space data based on the territorial space elements according to claim 1, wherein the fusing of the territorial space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic transportation statistical data and the traffic transportation unstructured data comprises:

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

constructing an associated view of the topological graphic elements and the attribute indexes based on the relational two-dimensional table set;

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

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

and updating spatial 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.

3. The method for processing the traffic planning space data based on the territorial space elements of claim 2, wherein the territorial space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistical data and the traffic unstructured data are processed into corresponding relational two-dimensional tables, and the method comprises the following steps:

converting the transportation unstructured data into transportation structured data;

performing data quality verification on the homeland space element data, the comprehensive traffic basic space data, the traffic analysis and calculation data, the traffic statistical data and the traffic structured data to obtain a verification result;

under the condition that the verification result is determined to be passed, 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 transportation statistical data and target traffic transportation structured data;

converting the target multi-source data into a corresponding initial relational two-dimensional table;

and under the condition that the initial relational two-dimensional table is determined to meet the preset data quality requirement, taking the initial relational two-dimensional table as the relational two-dimensional table.

4. The method for processing traffic planning space data based on homeland space elements according to claim 2, wherein constructing an associated view of a topological primitive associated with an attribute index based on the relational two-dimensional table set comprises:

establishing a business attribute relation rule, a spatial topological relation rule and an index calculation association rule of data based on the relational two-dimensional table set;

performing association fusion on the characteristic index data in the relational two-dimensional table set based on the service attribute relation rule to obtain traffic planning basic index data based on multi-service 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 performing 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 associated view.

5. The method for processing traffic planning space data based on homeland space elements according to claim 1, wherein constructing an integrated virtual cluster of integrated traffic planning space data and service topic application data based on the homeland space and integrated traffic planning topic data comprises:

classifying the homeland space and the comprehensive traffic planning thematic data to obtain comprehensive traffic planning space data and service thematic application data;

respectively storing the comprehensive traffic planning space data and the service special topic application data in a warehouse in batches to obtain a comprehensive traffic planning space data entity cluster and a service special topic application data entity cluster;

virtualizing the comprehensive traffic planning space data entity cluster and the service special topic application data entity cluster by using a plurality of servers to obtain corresponding virtualized entity clusters;

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

6. The method for processing traffic planning space data based on territorial space elements according to claim 1, wherein the visualization processing of the integrated virtual cluster based on the user's extended development request comprises:

performing data resource extraction on the integrated virtual cluster based on an extended development request of a user to obtain service data and space data;

carrying out visual configuration on the service data, and carrying out symbolic configuration on the space data to obtain a target rendering strategy;

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

7. The method for processing traffic planning space data based on territorial spatial elements of claim 6, wherein before issuing and managing multi-role applicable services to the thematic data map layer through a GIS service platform, the method further comprises:

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

and performing role-based configuration on the thematic data image layer to be issued based on the role configuration information.

8. A traffic planning space data processing device based on homeland space elements is characterized by comprising:

the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring homeland space element data, comprehensive traffic basic space data, traffic analysis calculation data, traffic transportation statistical data and traffic transportation unstructured data;

the fusion module is used for fusing the homeland space element data, the comprehensive traffic basic space data, the traffic analysis calculation data, the traffic transportation statistical data and the traffic transportation 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 service thematic application data based on the territorial space and the comprehensive traffic planning thematic data;

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

and the issuing and management module is used for issuing and managing the service suitable for multiple roles to the thematic data map layer through a GIS service platform.

9. An electronic device comprising a memory and a processor, wherein the memory stores thereon a computer program operable on the processor, and the processor implements the steps of the method for processing traffic planning space data based on homeland space elements according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions, which when executed by a processor, implement the method for processing territorial space element-based traffic planning space data according to any one of claims 1 to 7.

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