Batch generation method of mass spatial element superposition position relationship

Abstract

The application discloses a batch generation method of mass spatial element superposition position relationship, comprising the following steps: 1) establishing a target table of spatial element superposition position relationship; 2) selecting multiple spatial element classes to be involved in superposition analysis, and determining the pairwise relationship of each element in a spatial element set to be analyzed; 3) judging whether the spatial element set to be analyzed is recorded in the target table in whole or in part, if yes, reading the intersection proportion of the spatial element classes from the target table, and removing the read spatial element classes from the spatial element set to be analyzed; 4) if the updated spatial element set to be analyzed is empty, entering step 6), otherwise, entering step 5); 5) calculating the intersection proportion of different spatial element classes in the updated spatial element set to be analyzed by using an iterative superposition analysis model, and determining the overlapping relationship of the different spatial element classes; and 6) updating the target table.

Description

Technical Field

[0001] This invention relates to the field of Geographic Information Systems (GIS), specifically a method for batch generation of location relationships of massive spatial elements overlaid. Background Technology

[0002] With the acceleration of urbanization and the development of information technology, various types of spatial data (such as land use status data, planning data, and building data) are showing a surge in quantity and dispersed sources. When it is necessary to establish large-scale and automated business relationships by overlaying massive spatial data, the need for real-time spatial calculations affects the efficiency of establishing business relationships, and consequently affects the large-scale retrieval of business relationships, such as in decision support systems and dashboards. Therefore, there is an urgent need for an efficient, automated, and configurable method for batch generation of overlaying spatial relationships of massive spatial elements to solve the above problems. Summary of the Invention

[0003] The purpose of this invention is to provide a method for batch generation of the positional relationships of massive spatial elements, comprising the following steps:

[0004] 1) Establish a target table for the spatial element overlay positional relationships; the target table is initially empty;

[0005] 2) Select multiple spatial feature classes to be included in the overlay analysis, denoted as the set of spatial feature classes to be analyzed, and determine the pairwise relationships of the feature classes in the set of spatial feature classes to be analyzed that need to have their overlay position relationships calculated. Record the configured relationships in the data table of the spatial database.

[0006] 3) Traverse each relationship record in the configuration table in step 2), obtain two feature classes each time, and proceed to step 4);

[0007] 4) Calculate the intersection area and intersection ratio between all pairs of features in the two feature classes passed in step 3) using the overlay position analysis model;

[0008] 5) Store the element identifiers with intersection area greater than 0 from step 4) along with the intersection area, intersection ratio, business number, and other information into the target table, and return to step 3) to continue traversing until the traversal is complete;

[0009] 6) Based on the overlapping relationships of different spatial element classes, establish the correlation between business data to achieve cross-business data fusion.

[0010] Further, in step 1), the target table is used to record the names of the spatial feature classes of the two overlay analyses, the unique numbers of the two spatial features with intersecting relationships, the areas of the two spatial features with intersecting relationships, the intersecting area, the proportion of the intersecting area to the area of ​​the smaller spatial feature among the two spatial features, and the business number attribute of the two spatial features with intersecting relationships.

[0011] The business number attributes include the project application number, the construction land planning permit number, the land registration real estate unit number, the house registration real estate unit number, the new construction land approval number, and the land transfer contract number.

[0012] Furthermore, the spatial elements are used to describe the spatial characteristics of geographic entities.

[0013] Furthermore, the spatial elements include surface elements;

[0014] Surface elements represent two-dimensional closed regions;

[0015] Furthermore, in step 2), the configuration information of multiple spatial feature classes to be included in the overlay analysis is recorded in the data table of the spatial database;

[0016] The configuration information includes the name of the unique number field, the name of the area field, and the name of the business number field.

[0017] Furthermore, in step 5), the iterative overlay analysis model is constructed using GIS software;

[0018] The input to the iterative overlay analysis model includes two spatial feature classes and the name of the business number attribute field. The output is the intersection area, intersection ratio, and business number of the two spatial features.

[0019] The intersection ratio is calculated by dividing the intersection area of ​​two elements by the area of ​​the smaller of the two elements.

[0020] Furthermore, in step 5), the step of calculating the intersection ratio of different spatial feature classes using the iterative overlay analysis model includes:

[0021] 5.1) Traverse each record in the relation table, reading two spatial feature classes from each record in the relation table;

[0022] 5.2) Perform overlay analysis on the two spatial feature classes read, and calculate the intersection ratio of the two spatial feature classes;

[0023] 5.3) Repeat steps 5.1)-5.2) to calculate the intersection ratio of any two spatial feature classes among the multiple spatial feature classes to be included in the overlay analysis;

[0024] 5.4) Based on the configuration information, write the feature class name, unique number of the feature, area of ​​the feature, intersection area, percentage of the intersection area to the area of ​​the smaller of the two features, and business number attribute of the feature into the target table.

[0025] Furthermore, in step 5), if the intersection ratio is 100%, the two spatial feature classes are either inclusive or completely overlapping.

[0026] If the intersection ratio is greater than 0 and less than 100%, the two spatial feature classes are considered to be intersecting.

[0027] Furthermore, in step 6), the steps for establishing relationships between business data include:

[0028] 6.1) Set the intersection ratio correlation threshold according to business needs;

[0029] 6.2) Based on business needs, associate the business number attribute of records that are greater than or less than the intersection ratio association threshold with the corresponding business system data table, establish the association relationship between business data, perform cross-business data fusion, and generate cross-business monitoring indicators.

[0030] The technical effects of this invention are undeniable, and its beneficial effects are as follows:

[0031] 1) It enables the batch generation of relationships between the superimposed positions of massive spatial elements.

[0032] 2) Automatically update the relationships between the superimposed positions of massive spatial elements to ensure the timeliness of the data.

[0033] 3) It can establish large-scale relationships between various business operations with spatial element data.

[0034] 4) The flexibility of establishing business relationships in different application scenarios can be achieved by setting a threshold for the proportion of intersecting areas of elements.

[0035] 5) Cross-business data fusion can be performed without real-time spatial computation, significantly improving the efficiency of data fusion and indicator generation.

[0036] In summary, this invention proposes an innovative method for batch generation of the positional relationships of massive spatial elements. By iteratively analyzing the spatial element overlay and recording the positional relationships between spatial elements on a large scale and achieving automatic updates, it significantly improves the efficiency of cross-business data fusion and indicator generation, providing strong support for decision-making in related fields. Attached Figure Description

[0037] Figure 1 This is a flowchart of the method. Detailed Implementation

[0038] The present invention will be further described below with reference to embodiments, but it should not be construed that the scope of the present invention is limited to the following embodiments. Various substitutions and modifications made based on ordinary technical knowledge and common practices in the art without departing from the above-described technical concept of the present invention should be included within the scope of protection of the present invention.

[0039] Example 1:

[0040] See Figure 1 A method for batch generation of the positional relationships of massive spatial elements includes the following steps:

[0041] 1) Establish a target table for the spatial element overlay positional relationships; the target table is initially empty, and the calculation results are stored in the target table after the calculation is completed. The target table must be cleared before each recalculation of distance relationships.

[0042] 2) Select multiple spatial feature classes to be included in the overlay analysis, denoted as the set of spatial feature classes to be analyzed, and determine the pairwise relationships of the feature classes in the set of spatial feature classes to be analyzed that need to have their overlay position relationships calculated. Record the configured relationships in the data table of the spatial database.

[0043] In a spatial feature class set, it is not necessary to calculate the overlay position relationship between any two feature classes. For example, if the feature class set contains feature classes A to F, where AB, AC, AF, BC, BD, CE, CF, and DF need to calculate the overlay position relationship, then the pairwise relationships between these feature classes are recorded in the configuration table. The feature classes AD, AE, BE, BF, CD, DE, and EF do not need to calculate the overlay position relationship, so they do not need to be recorded.

[0044] 3) Traverse each relationship record in the configuration table in step 2), obtain two feature classes each time, and proceed to step 4);

[0045] 4) Calculate the intersection area and intersection ratio between all pairs of features in the two feature classes passed in step 3) using the overlay position analysis model;

[0046] 5) Store the element identifiers with intersection area greater than 0 from step 4) along with the intersection area, intersection ratio, business number, and other information into the target table, and return to step 3) to continue traversing until the traversal is complete;

[0047] 6) Based on the overlapping relationships of different spatial element classes, establish the correlation between business data to achieve cross-business data fusion.

[0048] In step 1), the target table is used to record the names of the spatial feature classes for the two overlay analyses, the unique identifiers of the two spatial features with an intersection relationship, the areas of the two spatial features with an intersection relationship, the intersection area, the ratio of the intersection area to the area of the smaller one of the two spatial features, and the business number attributes of the two spatial features with an intersection relationship;

[0049] The business number attributes include the construction project application number, the document number of the construction land planning permit, the land registration real estate unit number, the housing registration real estate unit number, the approval number of newly added construction land, and the land transfer contract number.

[0050] The spatial features are used to describe the spatial characteristics of geographical entities.

[0051] The spatial features include surface features;

[0052] Surface features represent two-dimensional closed areas;

[0053] In step 2), the configuration information of multiple spatial feature classes to be involved in the overlay analysis is also recorded in a data table of the spatial database;

[0054] The configuration information includes the unique identifier field name, the area field name, and the business number field name. [[ID=二十]]

[0055] In step 5), the iterative overlay analysis model is constructed through GIS software;

[0056] The inputs of the iterative overlay analysis model include two spatial feature classes and the business number attribute field name, and the outputs are the intersection area, the intersection ratio, and the business number of the two spatial features;

[0057] Among them, the intersection ratio is obtained by dividing the intersection area of the two features by the area of the smaller one of the two features. Example: Let a be the area of feature A, b be the area of feature B, and c be the intersection area of features AB, then the intersection ratio d = c / min(a, b). When d is 0, it means that A and B do not intersect. When 0 < d < 1, it means that A and B partially intersect. When d = 1, it means that A and B completely coincide, or A completely contains B, or B completely contains A.

[0058] In step 5), the steps of using the iterative overlay analysis model to calculate the intersection ratio of different spatial feature classes include:

[0059] 5.1) Traverse each record in the relationship table and read the two spatial feature classes in the relationship table record each time;

[0060] 5.2) Perform an overlay analysis on the two read spatial feature classes and calculate the intersection ratio of the current two spatial feature classes;

[0061] 5.3) Repeat steps 5.1)-5.2) to calculate the intersection ratio of any two spatial feature classes among the multiple spatial feature classes to be included in the overlay analysis;

[0062] 5.4) Based on the configuration information, write the feature class name, unique number of the feature, area of ​​the feature, intersection area, percentage of the intersection area to the area of ​​the smaller of the two features, and business number attribute of the feature into the target table.

[0063] In step 5), if the intersection ratio is 100%, the two spatial feature classes are either inclusive or completely overlapping.

[0064] If the intersection ratio is greater than 0 and less than 100%, the two spatial feature classes are considered to be intersecting.

[0065] Step 6) involves establishing relationships between business data, including:

[0066] 6.1) Set an intersection ratio threshold according to business needs; for example, some element classes may have spatial errors due to production scale or coordinate system transformation. Two adjacent elements that do not have an intersection relationship in spatial location may have slight contact at the edges when calculating the spatial relationship, with an extremely small intersection ratio. An intersection ratio threshold can be set to exclude such intersection relationships; when automatically classifying the districts and counties to which some spatial elements cross districts and counties, the intersection ratio threshold between the element and the district / county boundary can be set to 0.5. Only elements with an intersection ratio greater than 0.5 with a certain district or county will be included in that district or county.

[0067] 6.2) Based on business needs, associate the business number attribute of records that are greater than or less than the intersection ratio association threshold with the corresponding business system data table, establish the association relationship between business data, perform cross-business data fusion, and generate cross-business monitoring indicators.

[0068] Example 2:

[0069] A method for batch generation of the positional relationships of massive spatial elements includes the following steps:

[0070] 1) Establish a target table for the spatial element overlay positional relationships; the target table is initially empty;

[0071] 2) Select multiple spatial feature classes to be included in the overlay analysis, denoted as the set of spatial feature classes to be analyzed, and determine the pairwise relationships of the feature classes in the set of spatial feature classes to be analyzed that need to have their overlay position relationships calculated. Record the configured relationships in the data table of the spatial database.

[0072] 3) Traverse each relationship record in the configuration table in step 2), obtain two feature classes each time, and proceed to step 4);

[0073] 4) Calculate the intersection area and intersection ratio between all pairs of features in the two feature classes passed in step 3) using the overlay position analysis model;

[0074] 5) Store the element identifiers with intersection area greater than 0 from step 4) along with the intersection area, intersection ratio, business number, and other information into the target table, and return to step 3) to continue traversing until the traversal is complete;

[0075] 6) Based on the overlapping relationships of different spatial element classes, establish the correlation between business data to achieve cross-business data fusion.

[0076] Example 3:

[0077] A method for batch generation of the positional relationship of massive spatial elements is the same as in Embodiment 2. Further, in step 1), the target table is used to record the class name of the two spatial elements in the overlay analysis, the unique number of the two spatial elements with an intersection relationship, the area of ​​the two spatial elements with an intersection relationship, the intersection area, the proportion of the intersection area to the area of ​​the smaller spatial element among the two spatial elements, and the business number attribute of the two spatial elements with an intersection relationship.

[0078] The business number attributes include the project application number, the construction land planning permit number, the land registration real estate unit number, the house registration real estate unit number, the new construction land approval number, and the land transfer contract number.

[0079] Example 4:

[0080] A method for batch generation of the positional relationship of massive spatial elements, the technical content of which is the same as any one of embodiments 2-3, further wherein the spatial elements are used to describe the spatial characteristics of geographic entities.

[0081] Example 5:

[0082] A method for batch generation of the positional relationship of superimposed massive spatial elements, the technical content of which is the same as any one of embodiments 2-4, further wherein the spatial elements include surface elements;

[0083] Surface elements represent two-dimensional closed regions;

[0084] Example 6:

[0085] A method for batch generation of the positional relationship of superimposed massive spatial elements, the technical content of which is the same as any one of embodiments 2-5, further wherein, in step 2), the configuration information of multiple spatial element classes to be included in the superimposed analysis is also recorded in the data table of the spatial database.

[0086] The configuration information includes the name of the unique number field, the name of the area field, and the name of the business number field.

[0087] Example 7:

[0088] A method for batch generation of the positional relationship of massive spatial elements, the technical content of which is the same as any one of embodiments 2-6, further wherein, in step 5), the iterative overlay analysis model is constructed by GIS software;

[0089] The input to the iterative overlay analysis model includes two spatial feature classes and the name of the business number attribute field. The output is the intersection area, intersection ratio, and business number of the two spatial features.

[0090] The intersection ratio is calculated by dividing the intersection area of ​​two elements by the area of ​​the smaller of the two elements.

[0091] Example 8:

[0092] A method for batch generation of positional relationships of massive spatial elements, with technical content identical to any one of embodiments 2-7, further comprising, in step 5), the step of calculating the intersection ratio of different spatial element classes using an iterative overlay analysis model, including:

[0093] 5.1) Traverse each record in the relation table, reading two spatial feature classes from each record in the relation table;

[0094] 5.2) Perform overlay analysis on the two spatial feature classes read, and calculate the intersection ratio of the two spatial feature classes;

[0095] 5.3) Repeat steps 5.1)-5.2) to calculate the intersection ratio of any two spatial feature classes among the multiple spatial feature classes to be included in the overlay analysis;

[0096] 5.4) Based on the configuration information, write the feature class name, unique number of the feature, area of ​​the feature, intersection area, percentage of the intersection area to the area of ​​the smaller of the two features, and business number attribute of the feature into the target table.

[0097] Example 9:

[0098] A method for batch generation of the positional relationship of superimposed massive spatial elements, the technical content of which is the same as any one of embodiments 2-8, further wherein, in step 5), if the intersection ratio is 100%, the two spatial element classes are in an inclusive relationship or completely overlap.

[0099] If the intersection ratio is greater than 0 and less than 100%, the two spatial feature classes are considered to be intersecting.

[0100] Example 10:

[0101] A method for batch generation of the positional relationships of massive spatial elements, with technical content identical to any one of embodiments 2-9, further comprising, in step 6), establishing the association relationships between business data, including:

[0102] 6.1) Set the intersection ratio correlation threshold according to business needs;

[0103] 6.2) Based on business needs, associate the business number attribute of records that are greater than or less than the intersection ratio association threshold with the corresponding business system data table, establish the association relationship between business data, perform cross-business data fusion, and generate cross-business monitoring indicators.

[0104] Example 11:

[0105] A method for batch generation of the positional relationships of massive spatial elements, comprising the following steps:

[0106] 1. Establish a target table for the superimposed positional relationships of spatial elements.

[0107] Establish a target table in the spatial database to record the spatial element overlay positional relationships, which records the element class names of two overlay analyses, the unique numbers of the two elements with intersecting relationships, the areas of the two elements with intersecting relationships, the intersecting area, the proportion of the intersecting area to the area of ​​the smaller of the two elements, and the business number attribute of the two elements with intersecting relationships.

[0108] 2. Select the feature classes to be included in the overlay analysis.

[0109] Select the multiple feature classes that need to participate in the overlay analysis, determine the pairwise relationships between the feature classes that need to be overlayed, record the relationships in the data table of the spatial database, and record the configuration information such as the unique number field name, area field name, and business number field name of the feature classes.

[0110] 3. Construct an iterative overlay analysis model

[0111] Constructing an iterative overlay analysis model using GIS software:

[0112] Construct an iterative model for table records. Traverse each record in the relation table, reading two feature classes from each record.

[0113] Perform overlay analysis. Perform overlay analysis on the two feature classes read.

[0114] Calculate the feature area of ​​the feature class in the overlay analysis results.

[0115] Construct an iterative model for the elements, traverse each element in the element class of the overlay analysis results, and write information such as the element class name, unique number of the element, area of ​​the element, intersection area, percentage of the intersection area of ​​the element with the smaller area of ​​the two elements, and business number attribute of the element into the target table according to the configuration information.

[0116] 4. Establish a regular update mechanism

[0117] The superposition and iterative analysis model is executed on a scheduled basis through a task scheduling system.

[0118] 5. Application Scenarios and Application Methods

[0119] For different business and application scenarios, by setting a threshold for the intersection ratio between elements, the intersection or containment relationship between two spatial elements can be obtained. For example, an intersection ratio of 100% indicates that the two spatial elements are contained or completely overlap; an intersection ratio greater than 50% indicates that the two spatial elements have a high degree of overlap. According to business needs, the business IDs of the records with intersection ratios greater than or less than the threshold are associated with the corresponding business system data tables. This allows for the establishment of large-scale relationships between business data, enabling cross-business data fusion, generating cross-business monitoring indicators, and providing data support for decision support systems and dashboards.

Claims

1. A method for batch generation of the positional relationships of superimposed massive spatial elements, characterized in that, Includes the following steps: Step 1) Establish a target table for the spatial element overlay positional relationships; the target table is initially empty. Step 2) Select multiple spatial feature classes to be included in the overlay analysis, denoted as the set of spatial feature classes to be analyzed, and determine the pairwise relationships of the feature classes in the set of spatial feature classes to be analyzed that need to have their overlay position relationships calculated. Record the configured relationships in the data table of the spatial database. Step 3) Iterate through each relationship record in the data table from Step 2), obtaining two feature classes each time, and proceed to Step 4). Step 4) Calculate the intersection area and intersection ratio between all pairs of features in the two feature classes passed in Step 3) using the overlay location analysis model; Step 5) Store the element identifiers with intersection area greater than 0, along with their intersection area, intersection ratio, and business number information from Step 4) into the target table, and return to Step 3) to continue traversing until the traversal is complete; Step 6) Based on the overlapping relationships of different spatial element classes, establish the correlation between business data to achieve cross-business data fusion.

2. The method for batch generation of the positional relationship of massive spatial elements according to claim 1, characterized in that, In step 1), the target table is used to record the names of the spatial feature classes of the two overlay analyses, the unique numbers of the two spatial features with an intersection relationship, the areas of the two spatial features with an intersection relationship, the intersection area, the proportion of the intersection area to the area of ​​the smaller spatial feature among the two spatial features, and the business number attribute of the two spatial features with an intersection relationship. The business number attributes include the project application number, the construction land planning permit number, the land registration real estate unit number, the house registration real estate unit number, the new construction land approval number, and the land transfer contract number.

3. The method for batch generation of the positional relationship of massive spatial elements according to claim 2, characterized in that, The spatial elements are used to describe the spatial characteristics of geographic entities.

4. The method for batch generation of the positional relationship of massive spatial elements according to claim 2, characterized in that, The spatial elements include surface elements; A surface element represents a two-dimensional closed region.

5. The method for batch generation of the positional relationship of massive spatial elements according to claim 1, characterized in that, In step 2), the configuration information of multiple spatial feature classes to be included in the overlay analysis is also recorded in the data table of the spatial database; The configuration information includes the name of the unique number field, the name of the area field, and the name of the business number field.

6. The method for batch generation of the positional relationship of massive spatial elements according to claim 1, characterized in that, In step 4), the overlay location analysis model is constructed using GIS software; The input to the overlay location analysis model includes two spatial feature classes and the name of the business number attribute field. The output is the intersection area, intersection ratio, and business number of the two spatial features. The intersection ratio is calculated by dividing the intersection area of ​​two elements by the area of ​​the smaller of the two elements.

7. The method for batch generation of the positional relationship of massive spatial elements according to claim 1, characterized in that, Step 4), which involves calculating the intersection ratio of different spatial feature classes using the overlay location analysis model, includes: Step 4.1) Traverse each record in the data table, reading two spatial feature classes from the relation record each time; Step 4.2) Perform overlay analysis on the two spatial feature classes read, and calculate the intersection ratio of the two spatial feature classes; Step 4.3) Repeat steps 4.1)-4.2) to calculate the intersection ratio of any two spatial feature classes among the multiple spatial feature classes to be included in the overlay analysis; Step 4.4) Write the feature class name, unique number of the feature, area of ​​the feature, intersection area, percentage of the intersection area of ​​the smaller of the two features, and business number attribute of the feature into the target table according to the configuration information.

8. The method for batch generation of the positional relationship of massive spatial elements according to claim 1, characterized in that, In step 5), if the intersection ratio is 100%, the two spatial feature classes are either inclusive or completely overlapping. If the intersection ratio is greater than 0 and less than 100%, the two spatial feature classes are considered to be intersecting.

9. The method for batch generation of the positional relationship of massive spatial elements according to claim 1, characterized in that, Step 6) involves establishing relationships between business data, including: Step 6.1) Set the intersection ratio association threshold according to business needs; Step 6.2) Based on business needs, associate the business number attribute of records that are greater than or less than the intersection ratio association threshold with the corresponding business system data table, establish the association relationship between business data, perform cross-business data fusion, and generate cross-business monitoring indicators.

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