CN117971995A - Spatial data processing and demonstrating method for traffic homeland planning compliance analysis - Google Patents

Abstract

The invention discloses a space data processing and demonstrating method for traffic homeland planning compliance analysis, which belongs to the technical field of data processing and comprises the following steps: carrying out space buffer analysis on traffic planning data and homeland planning data to obtain buffer data; performing space element intersection analysis on the buffer zone data and the homeland planning data to obtain coincidence analysis data; eliminating element data smaller than a rough difference threshold value; carrying out statistical analysis on the coincidence analysis data through data fusion and data statistics; displaying space data, coincidence analysis data, statistical charts and reports of the traffic homeland planning in map layouts of different levels, and configuring a multi-level association coincidence analysis display model; by clicking on different elements in the map layout, different levels of compliance analysis data and statistics are presented. The data processing method can be applied to space conformity analysis of traffic planning and homeland planning, and provides scientific basis for planning, compiling and adjusting.

Description

Spatial data processing and demonstrating method for traffic homeland planning compliance analysis

Technical Field

The disclosure belongs to the technical field of data processing, and particularly relates to a spatial data processing and demonstrating method for traffic homeland planning compliance analysis.

Background

The homeland space planning is a national space development guide and a sustainable development space blueprint, and is a basic basis for various development, protection and construction activities. The territorial space planning requires each special planning to be coordinated with the territorial space planning, and the traffic planning is taken as an important component of the territorial space planning system, so that transformation and upgrading of the planning and programming technical method are imperative.

The digital traffic development planning schema requires to construct a decision-making and planning system of big data support, promotes multi-source data fusion among departments and enterprises, and improves the traffic decision analysis level. The outline of the planning environmental impact evaluation method and the planning environmental impact evaluation technology requires to develop planning coordination analysis, and the compliance analysis of the planning space layout and related planning such as homeland space planning, natural protection land planning, "three lines one single, important ecological sensitive targets and the like is analyzed.

The space coincidence analysis is essentially space superposition analysis, wherein the space superposition analysis is to superpose two or more element data of the same region and the same scale to generate a new data layer, and each element of the new data layer has multiple attributes of each superimposed element or statistical characteristics of each superimposed element attribute. The overlay analysis includes not only comparison of spatial data relationships, but also comparison of attribute data relationships.

The existing space superposition analysis model and tool have the problems of various data source types, complex operation, weak industry pertinence and the like, can not well solve the application problem in the actual business field, and particularly the space coincidence analysis related to traffic planning research is still blank and is not enough to support the traffic planning research work in the national space planning background.

The variety of the geographic data visualization forms in the existing data visualization class library design is less, and the rule of the data is revealed when the graph type cannot meet the data requirement or cannot fully display the characteristics of the data aiming at complex geographic data. In some visualization platforms and tools, the cost of obtaining the map data is problematic, or a limited number of visualization templates are provided, which cannot meet the expression requirements of diversified geographic data. At present, no visual expression tool capable of realizing space superposition analysis exists in the visual tools, and the problem of poor interactive capability and associated display of space elements is solved.

Disclosure of Invention

Aiming at the defects of the prior art, the purpose of the present disclosure is to provide a data processing method for traffic homeland planning compliance analysis, which solves the problems that in the prior art, no visual expression tool capable of realizing space superposition analysis exists in visual tools, and the correlation display and interaction capability of space elements have gaps.

Aiming at the problems of the prior art.

The purpose of the disclosure can be achieved by the following technical scheme:

A spatial data processing method for traffic homeland planning compliance analysis, the method comprising the steps of:

step 1: pretreatment of traffic homeland planning space data:

The traffic homeland planning space data sources in the step comprise vector data, raster data and picture data which are obtained from planning schemes such as traffic planning, homeland planning and the like, the three types of data are data contents input by the method, and standardized traffic homeland planning space analysis data are output through data preprocessing. The treatment process comprises the following steps: (1) Grid data vectorization preprocessing, picture data space registration and vectorization preprocessing; (2) Carrying out space information standardization pretreatment on the treated vectorized data and the original vector format data, wherein the pretreatment comprises coordinate conversion, unified conversion into a CGCS2000 coordinate system and data space topology structure examination, such as road network connectivity treatment, overhang point treatment and the like; (3) Carrying out standardized preprocessing on attribute data structures of the space standardized data, wherein the traffic planning space data attribute data structures comprise fields including data types, planning ranges, planning waters flat year, traffic element names, technical grades, construction states, planning mileage or planning areas and the like, and the homeland space planning data structures comprise fields including data types, land codes, sitting units, pattern areas and the like; (4) And finally outputting standardized traffic homeland planning space analysis data.

Step 2: traffic homeland planning compliance analysis:

The input data of the step is mainly the preprocessed traffic and territorial planning space analysis data obtained in the step 1, the traffic planning space analysis data (which does not contain territorial planning space analysis data) preprocessed in the step 1 is subjected to data classification according to a planning index and buffer distance comparison relation model, so that whether the data are subjected to data buffering and data buffering distance is determined, and then the traffic planning space analysis data subjected to buffering analysis and the territorial planning space data subjected to preprocessing are subjected to space element intersection analysis, so that the coincidence analysis data are obtained. The treatment process comprises the following steps: (1) According to the data types of the space data points, the lines and the planes, and combining the planning types of the traffic planning, a comparison relation model of planning indexes and the buffer distances is established, namely, the traffic planning analysis data establishes a comparison relation with the planning buffer distances according to the planning types and the planning technical levels of the two planning indexes; (2) Judging that the data type of the traffic planning space analysis data preprocessed in the step 1 is point and line element data, performing space buffer analysis according to a comparison relation model of planning indexes and buffer distances, buffering the line data elements into rectangular surface elements, buffering the point data elements into circular surface elements, adding buffer distance fields (buffdist) into the data, and assigning values to the fields by using buffer distance values corresponding to the data elements of different planning indexes; (3) Then, carrying out space element intersection analysis on the traffic planning space analysis data after buffer analysis processing and the territorial planning space data after preprocessing, solving the intersection of the geometric figures of the two planning elements, and only reserving the intersection part of the two planning geometric figures as the geometric figure of the output data; and correlating the input traffic planning space analysis data with the homeland planning space data, and transmitting the correlated traffic planning space analysis data and the homeland planning space data to output data as an attribute table of the output data, so as to obtain the compliance analysis data.

Step 3: compliance analysis data governance:

The step mainly carries out result data treatment on the coincidence analysis data obtained in the step 2, screens out data gross errors caused by data vectorization and space buffer analysis, and eliminates element data smaller than a data gross error threshold. The treatment process comprises the following steps:

(1) The element area and length are calculated.

Calculating the geometric area (area) of the element of the coincidence analysis surface obtained in the step 2, and adding an area (area) field into the data attribute table; if the data type is a line element, for example, the planning type is highway planning, the buffer distance (buffdist) in step 2 is also used to calculate the length (length) of the line element, and a length field is added to the data attribute table, where the length formula is length=area/buffdist.

(2) A coarse threshold is calculated. And establishing a connection between data management and user use, checking the coincidence analysis data of which the length and the area are calculated by the user through man-machine interaction investigation, measuring the length and the area of the elements in real time if obvious intersecting gross errors are found in the areas such as road network intersection sections, hub port surface boundaries and the like, and taking the measured value as a gross error threshold value.

(3) The spatial data is filtered using the coarse threshold. And screening the coincidence analysis data elements smaller than the coarse difference threshold value in the length and area fields by using the coarse difference threshold value of the user error as an input condition, and then performing secondary human-computer interaction error detection to remove non-coarse difference data elements in the screening result.

(4) And eliminating the screened data coarse difference elements. And deleting the data elements of the compliance analysis data elements with the screened rough differences, and finally obtaining the compliance analysis data after data treatment.

Step 4: the statistical analysis method of the coincidence analysis data comprises the following steps:

And (3) carrying out data fusion according to the traffic planning index field and the homeland planning index field by utilizing the coincidence analysis data obtained in the step (3) to obtain the coincidence analysis data after fusion, obtaining a coincidence analysis data statistics chart according to the planning coincidence data statistics dimension, and obtaining a coincidence analysis data statistics report according to a data statistics report template. The treatment process comprises the following steps: (1) Selecting a traffic planning index field and a homeland planning index field from the data-treated compliance analysis data, wherein the field selection range is a field standardized by the pretreatment data structure in the step 1, and comprises a traffic planning selectable planning type, a planning range, planning water flat year, a traffic element name, a technical grade and a construction state, and the homeland space planning field is selectable in a type, a land coding, a sitting unit, a pattern area and the like;

(2) Carrying out data fusion analysis according to the selection index field, taking the planning coincidence data field selected in the step (1) as a data fusion characteristic field, carrying out space primitive fusion, namely fusing primitives with the same value in the selected field, carrying out attribute data fusion, namely merging data with the same value in the selected field in an attribute data structure table, taking a unique value if the data type is character type, carrying out statistics on the maximum value, the minimum value, the average value or the summation if the data type is numerical value type, carrying out summation statistics on the length and the area field calculated in the step (3), and deleting other fields of non-selected fields in the data attribute table;

(3) Extracting the data attribute table after data fusion as a planning compliance data statistical table;

(4) Drawing a data statistics chart by using a data statistics table, wherein the statistics chart is generally selected as a two-dimensional histogram, the abscissa of the chart is an index field selected in the step (1), and the ordinate is the length or the area of data fusion statistics in the step (2); (5) And (3) making a coincidence analysis data statistics report by using the data statistics table, further summarizing the conflict crossing length or occupied area of the traffic planning and the homeland space planning according to the space coincidence analysis data statistics table, and screening key information needed in the statistics report from the input data of the step (2) to obtain a text report.

Step 5: multistage association compliance analysis display model:

The method comprises the steps of configuring a data visual display model of the coincidence analysis data, configuring preprocessed traffic homeland space data, space coincidence analysis data after data treatment, coincidence analysis statistical charts and reports, displaying traffic homeland space coincidence analysis data results through data association link configuration, establishing a multi-level association coincidence analysis display model, and improving the result visual level.

The specific configuration steps are as follows:

(1) Inputting the traffic and homeland planning space analysis data preprocessed in the step 1 into a map layout, and configuring a map style according to planning symbols of traffic and homeland by a GIS symbolization tool to serve as first-level planning space data to display a map, wherein the homeland planning space data serve as a base map to be displayed, such as road network planning space layout data;

(2) The method comprises the steps of inputting the coincidence analysis data after the data treatment in the step 3 into a map layout of the two-level coincidence analysis data by associating and linking space graphic elements and attribute data elements of a first-level planning space data display map, wherein the two-level coincidence analysis data is used as display content of the two-level coincidence analysis data;

(3) And (3) linking the statistical chart and the statistical report of the step (4) to a map layout of the secondary coincidence analysis data as the display content of the three-level coincidence analysis statistical data, wherein each secondary coincidence analysis data of the step can be linked with a plurality of statistical charts and statistical reports, such as the statistical charts and the statistical reports of non-coincidence pattern areas of different highway routes and basic farmland protection areas in highway network planning and basic farmland protection area coincidence analysis data.

(4) And completing the configuration of the multi-stage association compliance analysis display model, and outputting the display model.

Step 6: visual demonstration of traffic homeland planning compliance analysis data:

And (5) carrying out visual demonstration on the multi-stage association coincidence analysis display model output in the step (5). The specific display steps are as follows:

(1) Firstly, opening a model, and displaying a map by a first map layout page according to traffic planning space data configured in the step 5- (1);

(2) Displaying the map catalogue of the compliance analysis data configured in all the steps 5- (2) on a second map layout page by clicking the element of the traffic planning space data associated with the compliance analysis data in the step 5- (2);

(3) And displaying any one of the two-level coincidence analysis data display maps in the map catalog through the coincidence analysis data, entering a third map layout page, displaying the amplified coincidence analysis data display map, and synchronously displaying the three-level coincidence analysis statistical data configured in the step 5- (3).

The beneficial effects of the present disclosure are:

according to the invention, the space buffer analysis is carried out on the traffic planning data by using the comparison relation model of the planning index and the buffer distance, the point and line elements are expanded into the face elements, the space influence range of the traffic planning and the control requirement of the homeland space planning are considered, and the rationality and the reliability of the coincidence analysis are improved.

Drawings

In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the following description will make a brief description of the drawings that are required to be used in the embodiments or the description of the prior art, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.

FIG. 1 is a flow chart of a method for analyzing data processing and demonstrating achievements of traffic homeland planning compliance in the embodiment;

FIG. 2 is a flow chart of the standardized pretreatment of the traffic homeland planning space data in the embodiment;

FIG. 3 is a flow chart of the traffic homeland planning compliance analysis of the present embodiment;

FIG. 4 is a flow chart of the compliance analysis data governance of the present embodiment;

FIG. 5 is a flow chart of the statistical analysis of the compliance analysis data according to the present embodiment;

FIG. 6 is a flow chart of a multi-level correlation compliance analysis presentation model configuration of the present embodiment;

FIG. 7 is a flow chart of a visual demonstration of traffic homeland planning compliance analysis data in the present embodiment;

FIG. 8 is a diagram showing a road and soil space planning compliance analysis in line element data type according to the present embodiment;

Fig. 9 is a diagram showing the analysis of the conformance of the regional land space plan of the transportation junction according to the type of the point and face element data in the present embodiment.

Detailed Description

The following description of the embodiments of the present disclosure will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present disclosure. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments in this disclosure without inventive faculty, are intended to fall within the scope of this disclosure.

Example 1: as shown in FIG. 1, the spatial data processing method for traffic homeland planning compliance analysis comprises the following steps of

Step 1: pretreatment of traffic homeland planning space data:

the planning compliance analysis refers to the analysis of the spatial position relation between the traffic special planning and the upper space constraint planning (here referred to as homeland space planning), and the result data of the compliance analysis can be used to obtain whether the spatial layout of the traffic special planning meets the spatial control requirement of the upper planning, and the specific contradictory or conflicting spatial position data is defined.

Aiming at the input data requirements of two types of planning space compliance analysis, the traffic homeland planning compliance analysis data mainly comprises data obtained from planning schemes such as traffic planning, homeland planning and the like, and is specifically divided into planning vector data, planning grid data and planning picture data, wherein the three types of data are data contents input by the method, and the step contents are mainly characterized in that the input vector data, grid data and picture data of the traffic homeland planning are output as standardized traffic homeland planning space analysis data through data preprocessing.

As shown in fig. 2, the data processing steps are:

(1.1) raster data vectorization preprocessing, picture data spatial registration and vectorization preprocessing. Converting raster data representing planning element information by raster units into vector data representing planning element information by points, lines and planes according to an algorithm of raster angular point coordinates by using a GIS software raster vector inter-conversion tool, selecting picture graphic feature points for spatial registration by using a GIS software spatial registration tool, and drawing the vector data representing the planning element information by using a point, line and plane editing tool.

The method comprises the steps of (1.2) carrying out space information standardization pretreatment on the treated vectorization data together with original vector format data, namely, the process of unifying multi-source space data, specifically comprising coordinate conversion, such as unifying conversion into a CGCS2000 coordinate system, unifying space reference standard through the coordinate conversion, wherein the vector data has the same space reference standard as required by the data treatment of space compliance analysis, namely, the plane coordinate system and the projection coordinate system are required to be kept consistent as required by the data participating in the compliance analysis; the data space topology structure inspection, such as road network connectivity processing and overhang point processing, is necessary for the road section connectivity of traffic planning road network data and the overhang point inspection and correction of nodes, and the data vectorization error is further eliminated through the space topology structure inspection.

And (1.3) carrying out standardized preprocessing on the attribute data structure of the space standardized data, wherein the attribute data structure of the traffic planning space data comprises a field including a planning type, a planning range, a planning water flat year, a traffic element name, a technical grade, a construction state, a planning mileage (area) and the like, and the territorial space planning data structure comprises a field useful type, a land code, a sitting unit, a map spot area and the like. For data management, data statistics analysis and standardization management of data warehouse entry after subsequent space compliance analysis, data structure standardization processing is further required to be performed on fields of space data, and a data structure of standardized input data is constructed through standardization preprocessing.

And (1.4) finally outputting standardized traffic and homeland planning space analysis data.

Step two: space superposition analysis of planning compliance analysis:

The road network planning, the hub planning and the port planning are taken as typical representatives, the planning compliance analysis requirements are combed, the buffer distance design rules of different types of traffic elements are researched based on the space constraint characteristics of different space elements of the traffic special planning and the national space planning, the space superposition analysis algorithm research is carried out by using the point, line and surface space data types, the intersection relation among the elements is identified, and the traffic national space compliance analysis data is obtained.

As shown in fig. 3, the data consistency analysis steps are:

And (2.1) establishing a relation model of the planning index and the buffer distance. And according to the data types of the space data points, the lines and the planes, combining two planning indexes of the planning type and the planning technical grade of the traffic planning, and establishing a planning index and planning buffer distance comparison relation model.

Because of the macroscopic attribute of traffic planning, the specific route selection and address selection of planning elements cannot be deepened, the planning road network has certain line swing in the actual line planning stage and the line engineering research stage, and the planning hub can further evaluate and refine the land and sea in the detailed planning stage. Therefore, in the planning analysis stage, in the process of analyzing the coincidence of traffic planning such as planning road network and junction and national space planning, a certain swing research is needed for the network and junction point positions, and the road network line and junction point positions are expanded to the traffic land, namely, the space line and point element layers are expanded to the space plane element layers.

TABLE 1 comparison relationship sample table of traffic planning index and buffer distance

And (2.2) judging that the data type of the traffic planning space analysis data preprocessed in the step (2.1) is point and line element data, and performing space buffer analysis according to a comparison relation model of planning indexes and buffer distances. Road network planning, channel layout planning and shoreline utilization planning are typical line element type traffic special planning, and line data elements are buffered into rectangular surface elements; the layout planning of ports, passenger-cargo hubs and airports is a typical point element type traffic special plan, and the point data elements are buffered into circular surface elements; the port overall planning is a typical traffic special planning of the microscopic scale of the surface elements, the space position is relatively accurate, and buffer analysis is not needed; and adding a buffer distance field (buffdist) in the buffer analysis data table, and assigning values to the field by using buffer distance values corresponding to the data elements of different planning indexes.

(2.3) Carrying out space element intersection analysis on the traffic planning space analysis data after buffer analysis processing and the homeland planning space data after preprocessing, and solving intersection of geometric figures of two planning elements according to a face element and face element intersection method, wherein only intersection parts of the two planning geometric figures are reserved as geometric figures of output data; and correlating the input traffic planning space analysis data with the homeland planning space data, and transmitting the correlated traffic planning space analysis data and the homeland planning space data to output data as an attribute table of the output data, so as to obtain the compliance analysis data.

Step three: compliance analysis data governance:

the type of the traffic homeland compliance analysis data is a face element, the compliance analysis data errors of the data are generated by factors such as the coordinate vectorization precision of planning element primitives, the buffer analysis setting of traffic planning space data and the like, in order to eliminate rough compliance analysis results caused by the factors, filtering conditions are set by calculating a threshold value based on area or length, and the plaque or road section lower than the threshold value in the superposition results is filtered, so that the compliance analysis data after data management is obtained.

As shown in fig. 4, the specific data management steps are:

(3.1) calculating the element area and length.

And calculating the geometric area (area) of the element of the coincidence analysis surface, adding an area (area) field into a data attribute table, and specifically carrying out trapezoidal projection calculation on the element of the space polygon surface of the coincidence analysis result through a GIS tool according to the polygon area of the known vertex coordinates.

If the data type is a line element, if the planning type is highway planning, a buffer distance (buffdist) field value in the space buffer analysis is also required, the length (length) of the line element is calculated, and a length (length) field is added in the data attribute table, and the length (length) calculation formula is length=area/buffdist.

(3.2) Calculating a coarse threshold. And establishing a connection between data management and user use, checking the coincidence analysis data of which the length and the area are calculated by the user through man-machine interaction investigation, measuring the length and the area of the elements in real time if the obvious data elements with the intersection rough differences are found in the areas such as road network intersection sections, hub port surface boundaries and the like, and taking the measured value as a rough difference threshold value.

(3.3) Screening the spatial data using the coarse threshold. And screening the coincidence analysis data elements with the length and area fields smaller than the gross error threshold value in the data attribute table by using the gross error threshold value of the user investigation as an input condition, synchronously checking the corresponding geometric figure, and then performing secondary man-machine interaction investigation to remove non-gross error data elements in the screening result.

And (3.4) eliminating the screened data coarse difference elements. And deleting the data elements of the compliance analysis data elements with the screened rough differences, and finally obtaining the compliance analysis data after data treatment.

Step four: compliance analysis data statistical analysis model:

according to the coincidence analysis data and the space coincidence analysis business scene requirement, calculating a multi-dimensional coincidence analysis statistical index, and successively carrying out data fusion processing, data statistical analysis, statistical chart and report making, and supporting the visual tool configuration of planning analysis and subsequent result data.

As shown in fig. 5, the specific processing procedure is as follows:

(4.1) selecting a data fusion field. Selecting a traffic planning index field and a homeland planning index field from the data-treated consistency analysis data, wherein the field selection range is a field standardized by a pretreatment data structure, and comprises a traffic planning selectable planning type, a planning range, planning water flat year, a traffic element name, a technical grade, a construction state, a homeland space planning field selectable land type, land coding, a sitting unit, a map spot area and the like;

(4.2) performing data fusion analysis according to the selection field. Combining two or more primitive elements with the same value in the selected field into one primitive element, fusing the space primitive elements, synchronously combining two or more attribute data corresponding to the primitive fusion, taking a unique value if the selected field data type is character type, and counting the maximum value, the minimum value, the average value or the summation if the selected field data type is numerical value type, wherein the length and area fields calculated in the third step are summed and counted, and deleting other fields of non-selected fields in the data attribute table;

(4.3) extracting the data attribute table after data fusion as a planning compliance data statistical table;

In the road homeland space planning compliance analysis, firstly, managing and controlling areas in homeland space planning, which have layout conflicts with each traffic planning project, and the related length or area are counted one by one according to the dimension of the traffic planning project; secondly, the dimensions of the control area are planned according to the homeland space, traffic planning projects with layout conflicts with the control area in the homeland space planning and the related length or area are counted one by one, so that a planning compliance data statistical table is obtained, and generation of a statistical chart and a report is supported.

Table 2 plan compliance analysis statistics samples Table 1 (dimension according to traffic plan project)

Table 3 planning compliance analysis statistical samples Table 2 (control zone dimension according to the territory space plan)

(4.4) Drawing a data statistics chart by utilizing a data statistics table, wherein the statistics chart is generally selected as a two-dimensional histogram, and the abscissa of the chart is a selected index field, specifically two dimensions of the data statistics table, namely a dimension according to a traffic planning project, mainly a route code or a route name, and a dimension according to a homeland space planning management and control area, mainly a management and control area name or a functional partition; the ordinate of the statistical chart is the length or area of the data fusion statistic.

(4.5) Making a compliance analysis data statistics report using the data statistics table.

And (3) further summarizing the crossing length or occupied area of the conflict area between the traffic planning and the national space planning according to the space consistency analysis data statistics table, and screening key information needed in the statistics report from the input data of the step two to obtain a text report. Providing two statistical report templates according to the planning type, wherein one statistical report template is a line element data type statistical template, such as highway and homeland space compliance analysis, and the main statistical index is related mileage; and secondly, a statistical template of the point and surface element data types, such as the analysis of the coincidence of the national soil space of a junction and a port, is adopted, and the main statistical index is the occupied area.

Taking the highway and homeland space planning compliance analysis of line element data type as an example, a text report is shown in fig. 8.

Taking the analysis of the national space planning compliance of the transportation hub with the point and face element data type as an example, a text report is shown in fig. 9.

Step five: multistage association compliance analysis presentation model configuration:

and configuring the preprocessed traffic homeland space data, the space coincidence analysis data after data treatment, the coincidence analysis statistical chart and the report through a data association model, displaying traffic homeland space coincidence analysis data results, establishing a multi-level association coincidence analysis display model, and improving the result visualization level.

As shown in fig. 6, the specific model configuration method is as follows:

And (3) carrying out space-time data visual display on the coincidence analysis data, overlapping the traffic and homeland planning space analysis data preprocessed in the first step on a map, displaying the coincidence analysis data treated by the third data in the third step from space dimension, displaying the condition that the traffic planning space layout data is coincident and does not accord with the homeland space planning data from the traffic homeland coincidence analysis service angle, and finally hanging the statistical chart and the statistical report obtained in the fourth step on the map, effectively displaying the data analysis statistical condition, wherein the three-level visual map layout can be subjected to associated interactive click viewing. The method comprises the following specific steps:

Inputting the traffic and homeland planning space analysis data preprocessed in the step one into a map layout, and configuring a map style according to planning symbols of traffic and homeland by a GIS symbolization tool to serve as first-level planning space data to display a map, wherein the homeland planning space data serve as a base map to be displayed, such as road network planning space layout data;

(5.2) associating the step three data after treatment with space graphic elements and attribute data elements linked to a first-level planning space data display map, inputting the space graphic elements and attribute data elements into a second-level compliance analysis data map layout, and using the space graphic elements and the attribute data elements as second-level compliance analysis data display contents, wherein the step can associate a plurality of compliance analysis data after the step one, the step two and the step three, such as compliance analysis data of a highway network planning and a basic farmland protection area, compliance analysis data of a highway network planning and an ecological red line, compliance analysis data of the highway network planning and a town protection area, and associating and linking the compliance analysis data to one or more graphic elements and attribute elements in a highway network planning layout;

And (5.3) linking the statistical chart and the statistical report of the step four to a map layout of the secondary compliance analysis data as the display content of the three-level compliance analysis statistical data, wherein each secondary compliance analysis data of the step can be linked with a plurality of statistical charts and statistical reports, such as the statistical charts and the statistical reports of non-compliance pattern areas of different highway routes and basic farmland protection areas in highway network planning and basic farmland protection area compliance analysis data.

And (5.4) completing the configuration of the multi-stage association compliance analysis display model, and outputting the display model.

Step six: visualization of traffic homeland planning compliance analysis data:

and 5, visually displaying the multi-level association coincidence analysis display model output in the step 5 and the model configured in the step one-step three. The visual model can be used for three-level display linkage relation description:

the first-stage display traffic planning research area level, when a certain space element geometric figure is selected, automatically calculating related geometric elements with space topological relation with the space figure, and entering a second-stage area level;

The second-level display is to conduct layered stripping display on relevant space elements of the selected area according to the layers to form a map catalog, and fully display data superposition association relations;

And the third-level display is to dynamically display the data such as the full planning range, the planning elements or small areas one by one, the statistical analysis chart and the like by calling the layered data of the second-level area.

The specific display steps are as follows:

Opening a model, wherein a first map layout page displays a traffic planning space data display map configured in the first step, clicking on traffic planning space data primitive elements in the traffic planning space data display map, a second map layout page displays all coincidence analysis data display map catalogues configured in the second step, clicking one of two-stage coincidence analysis data display maps, and a third map layout page displays an amplified coincidence analysis data display map, and synchronously displays three-stage coincidence analysis statistical data configured in the third step, wherein a specific flow chart is shown in fig. 7.

Example 2: as shown in fig. 1, the invention relates to a data processing method for traffic homeland planning compliance analysis, and the specific implementation mode is as follows:

S1: carrying out space buffer analysis on traffic planning data and homeland planning data through a comparison relation model of planning indexes and buffer distances to obtain buffer zone data;

The comparison relation model of the planning index and the buffer distance is established according to the control requirement of the national space planning and the space influence range of the traffic planning index, for example, for highway planning, different buffer distances are respectively set according to the technical grade and the construction state of the highway planning. The space buffer analysis is to expand the point and line elements in the traffic planning data into surface elements according to the corresponding buffer distance by using a space analysis tool of GIS software to obtain buffer area data.

S2: performing space element intersection analysis on the buffer zone data and the homeland planning data to obtain coincidence analysis data;

the space element intersection analysis is to use a space analysis tool of GIS software to perform space superposition operation on buffer data and homeland planning data, and calculate an intersection part of the two data to be used as coincidence analysis data. The attribute table of the compliance analysis data contains relevant fields of traffic planning data and homeland planning data, such as planning type, planning range, planning water flat year, traffic element name, technical grade, construction state, land type, land code, seating unit, spot area and the like.

S3: performing data treatment on the coincidence analysis data through man-machine interaction error investigation, and removing element data smaller than a rough difference threshold value;

The data management is to eliminate errors of the coincidence analysis data caused by factors such as data vectorization precision, buffer distance setting and the like, and filter conditions are set by calculating a threshold value based on area or length, so that plaques or road sections lower than the threshold value in the superposition result are filtered out, and the coincidence analysis data after the data management is obtained. The data management process comprises the following steps:

s31: calculating the area or length of the coincidence analysis data, and adding corresponding fields in an attribute table;

S32: checking coincidence analysis data through man-machine interaction error, measuring the area or length of obvious error elements, and taking the maximum value as a rough difference threshold;

S33: and screening the coincidence analysis data by using the rough threshold value, and eliminating the element data smaller than the threshold value.

S4: carrying out statistical analysis on the coincidence analysis data through data fusion and data statistics to obtain a coincidence analysis data statistical table, a statistical chart and a statistical report;

the data statistics are used for reflecting the space coincidence condition of traffic planning and homeland planning, and carrying out data fusion and data statistics on the coincidence analysis data according to different statistical dimensions and statistical indexes to obtain a coincidence analysis data statistical table, a statistical chart and a statistical report. The data statistics process comprises the following steps:

S41: selecting data fusion fields such as traffic planning type, planning range, planning water flat year, traffic element name, technical grade, construction state, land type, land code, seating unit and the like;

S42: carrying out data fusion analysis according to the selected fields, combining elements with the same field value into one element, and simultaneously carrying out summation statistics on the area or length fields to obtain data after data fusion;

s43: extracting the data attribute table after data fusion as a coincidence analysis data statistical table;

S44: drawing a data statistics chart, such as a histogram, a pie chart and the like, by using the data statistics table, and displaying the distribution condition of the coincidence analysis data of different dimensions;

S45: and (3) utilizing the data statistics table to manufacture a coincidence analysis data statistics report, summarizing the space conflict situation of traffic planning and homeland planning, and providing corresponding suggestions and measures.

S5: displaying the traffic homeland planning space data, the coincidence analysis data, the statistical chart and the report in map layouts of different levels through data association links, and configuring a multi-level association coincidence analysis display model;

The data association link is used for dynamically displaying traffic homeland planning compliance analysis data, and by setting data association rules, displaying traffic homeland planning space data, compliance analysis data, statistical charts and reports in map layouts of different levels according to different data levels and data types to form a multi-level association compliance analysis display model. The process of data association linking comprises the following steps:

S51: setting a data association rule, for example, performing data association according to fields such as a planning type, a planning range, planning water flat year, a traffic element name, a technical grade, a construction state, a land type, a land code, a seating unit and the like;

S52: displaying space data, coincidence analysis data, statistical charts and reports of the traffic homeland planning in map layouts of different levels, such as national level, provincial level, urban level, county level and the like according to different data levels and data types to form a multi-level association coincidence analysis display model;

S53: and triggering a data association rule by clicking different elements in the map layout, and displaying the coincidence analysis data and the statistical data of different levels related to the elements, so as to realize the dynamic display of the coincidence analysis data of the traffic homeland planning.

The data processing method can be applied to space conformity analysis of traffic planning and homeland planning, improves analysis efficiency and accuracy, and provides scientific basis for planning, compiling and adjusting.

In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims.

Claims (10)

1. The data processing method for traffic homeland planning compliance analysis is characterized by comprising the following steps of:

S1: carrying out spatial information standardization and attribute data structure standardization on vector data, raster data and picture data acquired in planning schemes such as traffic planning, homeland planning and the like, and outputting standardized traffic homeland planning spatial analysis data;

S2: carrying out data classification and space buffer analysis on the traffic planning space analysis data according to a planning index and buffer distance comparison relation model, and carrying out space element intersection analysis on the traffic planning space analysis data processed by the buffer analysis and the homeland planning space data to obtain coincidence analysis data;

S3: carrying out result data management on the coincidence analysis data, screening out data gross errors caused by data vectorization and space buffer analysis, and eliminating element data smaller than a data gross error threshold;

S4: carrying out data fusion according to the traffic planning index field and the territorial planning index field by utilizing the screened coincidence analysis data to obtain the coincidence analysis data after fusion, obtaining a coincidence analysis data statistics chart according to the planning coincidence data statistics dimension, and obtaining a coincidence analysis data statistics report according to a data statistics report template;

S5: and configuring a data visualization display model of the coincidence analysis data, configuring preprocessed traffic homeland space data, space coincidence analysis data after data treatment, a coincidence analysis statistical chart and a report, displaying traffic homeland space coincidence analysis data results through configuration of data association links, and establishing a multi-level association coincidence analysis display model.

2. The data processing method for traffic homeland planning compliance analysis according to claim 1, further comprising visually demonstrating the outputted multi-stage association compliance analysis presentation model.

3. The data processing method for traffic homeland planning compliance analysis according to claim 1, wherein the specific steps of S1 are as follows:

converting the raster data into vector data according to an algorithm of raster angular point coordinates by GIS software, performing spatial registration on the picture data, and drawing the vector data;

carrying out space information standardization pretreatment on the vectorization data and the original vector data, wherein the pretreatment comprises coordinate conversion and data space topology structure inspection;

performing attribute data structure standardization preprocessing on the data subjected to spatial standardization to construct a data structure of standardized input data;

And outputting standardized traffic and homeland planning space analysis data.

4. The data processing method for traffic homeland planning compliance analysis according to claim 1, wherein the specific steps of S2 are as follows;

according to the data types of the space data points, the lines and the planes, combining two planning indexes of the planning type and the planning technical grade of the traffic planning, and establishing a comparison relation model of the planning indexes and the buffer distance;

Performing space buffer analysis on the point and line element data according to a comparison relation model of planning indexes and buffer distances, buffering the line data elements into rectangular surface elements, buffering the point data elements into circular surface elements, and adding a buffer distance field;

and carrying out space element intersection analysis on the traffic planning space data after the buffer analysis and the homeland planning space data, solving the intersection of the geometric figures of the two planning elements, and reserving the intersection part as the geometric figure and the attribute table of the output data to obtain the coincidence analysis data.

5. The data processing method for traffic homeland planning compliance analysis according to claim 1, wherein the specific steps of S3 are as follows:

Calculating the area of the element of the coincidence analysis surface and the length of the line element by using a GIS tool, and adding corresponding fields in a data attribute table;

Through man-machine interaction error investigation, a user checks and measures the coincidence analysis data, and if obvious intersecting gross error data elements are found, the measured value is taken as the maximum value and is used as the gross error threshold;

screening space data by using the rough threshold value, removing coincidence analysis data elements with length and area fields smaller than the rough threshold value, and performing secondary human-computer interaction error investigation;

And removing the screened data coarse difference elements to obtain the coincidence analysis data after data treatment.

6. The data processing method for traffic homeland planning compliance analysis according to claim 1, wherein the specific step of S4 is as follows:

selecting a traffic planning index field and a homeland planning index field from the data of the compliance analysis after the data management as a data fusion field;

According to the data fusion field, carrying out space and attribute fusion on the primitive elements and attribute data with the same value, if the field data type is selected to be character type, taking a unique value, if the field data type is numerical type, counting the maximum value, the minimum value, the average value or the summation, and deleting non-selected fields;

extracting the data attribute table after data fusion as a planning compliance data statistical table, and counting the length or area of layout conflict with each traffic planning project or management and control area according to the dimension of the traffic planning project and the dimension of the management and control area planned by the homeland space;

Drawing a data statistics chart by using a data statistics table, wherein the statistics chart is a two-dimensional histogram, the abscissa is a selected index field, and the ordinate is the length or area of data fusion statistics;

and (3) making a coincidence analysis data statistics report by using a data statistics table, summarizing the crossing length or occupied area of the conflict area between the traffic planning and the homeland space planning, and screening key information from the input data of the step two to obtain a text report.

7. The data processing method for traffic homeland planning compliance analysis according to claim 1, wherein the specific step of S5 is as follows:

inputting the preprocessed traffic and territorial planning space data into a map layout, and configuring a map style according to planning symbols to serve as first-level planning space data to display a map;

The data after treatment is correlated to the primitive and attribute data elements of the first-level planning space data display map, and is used as the display content of the second-level coincidence analysis data, and a plurality of coincidence analysis data can be correlated;

Associating the coincidence analysis statistical chart and the statistical report to a second-level coincidence analysis data display map as third-level coincidence analysis statistical data display content, wherein each second-level coincidence analysis data can be associated with a plurality of statistical charts and reports;

and completing the configuration of the multi-stage association compliance analysis display model, and outputting the display model.

8. The data processing method for traffic homeland planning compliance analysis according to claim 2, wherein the specific steps of the visual presentation are as follows:

Opening a multi-level association compliance analysis display model, and displaying the preprocessed traffic and territorial planning space data;

clicking the element of the traffic planning space data graphic element, and displaying the related coincidence analysis data as a map directory;

Clicking one item of coincidence analysis data in the map catalog, displaying the amplified coincidence analysis data, and synchronously displaying a statistical chart and a statistical report;

And outputting a visual result.

9. A storage medium storing a program for executing a data processing method for traffic homeland planning compliance analysis according to any one of claims 1 to 8.

10. A data system for traffic homeland planning compliance analysis, comprising the following modules:

And a data preprocessing module: carrying out spatial information standardization and attribute data structure standardization on vector data, raster data and picture data acquired in planning schemes such as traffic planning, homeland planning and the like, and outputting standardized traffic homeland planning spatial analysis data;

And a compliance analysis module: carrying out data classification and space buffer analysis on the traffic planning space analysis data according to a planning index and buffer distance comparison relation model, and carrying out space element intersection analysis on the traffic planning space analysis data processed by the buffer analysis and the homeland planning space data to obtain coincidence analysis data;

and the data management module is used for: carrying out result data management on the coincidence analysis data, screening out data gross errors caused by data vectorization and space buffer analysis, and eliminating element data smaller than a data gross error threshold;

Carrying out data fusion according to the traffic planning index field and the territorial planning index field by utilizing the screened coincidence analysis data to obtain the coincidence analysis data after fusion, obtaining a coincidence analysis data statistics chart according to the planning coincidence data statistics dimension, and obtaining a coincidence analysis data statistics report according to a data statistics report template;

Multistage association compliance analysis display module: configuring a data visualization display model of the coincidence analysis data, configuring preprocessed traffic homeland space data, space coincidence analysis data after data treatment, a coincidence analysis statistical chart and a report, displaying traffic homeland space coincidence analysis data results through configuration of data association links, and establishing a multi-level association coincidence analysis display model;

And a display module: the visual demonstration method is used for visually demonstrating the output multi-level association compliance analysis demonstration model.