Batch generation method for superposition position relation of massive space elements

Abstract

The invention discloses a mass space element superposition position relation batch generation method. The method comprises the following steps: 1) establishing a target table of space element superposition position relations; 2) selecting a plurality of spatial element classes to participate in overlay analysis, and determining a pairwise relationship of each element in the spatial element set to be analyzed; 3) judging whether the to-be-analyzed space element set is completely or partially recorded in the target table, if so, reading the intersection proportion of the space element classes from the target table, and removing the read space element classes from the to-be-analyzed space element set; 4) if the updated to-be-analyzed space element set is empty, entering a step 6), otherwise, entering a step 5); 5) calculating an intersection proportion of different space element classes in the updated to-be-analyzed space element set by using an iterative overlay analysis model, and determining an overlapping relation of the different space element classes; according to the method, the position relation between the large-scale recorded space elements is analyzed through iteration space element overlay, and automatic updating is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of geographic information system (GIS), and particularly relates to a batch generation method of massive spatial element superposition position relationship. BACKGROUND

[0002] With the acceleration of urbanization process and the development of information technology, various types of spatial data (such as land use status data, planning data, building data, etc.) show the characteristics of explosive growth in quantity and dispersion in source. When the correlation relationship of related businesses must be established on a large scale and automatically through the superposition position relationship of massive spatial data, the efficiency of establishing the correlation relationship of businesses is affected due to the need for instant spatial operation, and then the large-scale calling of the correlation relationship of businesses is affected, such as decision support system, cockpit, etc. Therefore, an efficient, automatic and configurable batch generation method of massive spatial element superposition position relationship is urgently needed to solve the above problems. SUMMARY

[0003] The purpose of the present application is to provide a batch generation method of massive spatial element superposition position relationship, comprising the following steps:

[0004] 1) establishing a target table of spatial element superposition position relationship; the initial state of the target table is empty;

[0005] 2) selecting a plurality of spatial element classes to be involved in superposition analysis, denoted as a set of to-be-analyzed spatial element classes, and determining the pairwise relationship of the element classes in the set of to-be-analyzed spatial element classes that need to calculate the superposition position relationship, and recording the configured relationship in the data table of the spatial database;

[0006] 3) traversing each relationship record in the configuration table in step 2), obtaining two element classes each time, and entering step 4);

[0007] 4) calculating the intersection area and intersection ratio between all elements in the two element classes transmitted in step 3) by using a superposition position analysis model;

[0008] 5) storing the element identification and intersection area, intersection ratio, business number and other information of the element with an intersection area greater than 0 in step 4) into the target table, and returning to step 3) for continuous traversal until the traversal is completed;

[0009] 6) establishing the correlation relationship between business data based on the overlapping relationship of different spatial element classes, and realizing the data fusion across businesses.

[0010] Further, in step 1), the target table is used to record the spatial feature class names of two superimposed analyses, the unique numbers of the two spatial features with intersection relationship, the areas of the two spatial features with intersection relationship, the intersection area, the proportion of the intersection area to the area of the smaller one of the two spatial features, and the business number attribute of the two spatial features with intersection relationship.

[0011] The business number attribute includes the construction project reporting number, the construction land planning license number, the land registration real estate unit number, the housing registration real estate unit number, the newly added construction land license number, and the land transfer contract number.

[0012] Further, the spatial feature is used to describe the spatial characteristics of a geographic entity.

[0013] Further, the spatial feature includes a surface feature.

[0014] The surface feature represents a two-dimensional closed area.

[0015] Further, in step 2), the configuration information of the multiple spatial feature classes to be involved in the superimposed analysis is also recorded in the data table of the spatial database.

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

[0017] Further, in step 5), the iterative superimposed analysis model is constructed by GIS software.

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

[0019] The intersection proportion is the intersection area of the two features divided by the area of the smaller one of the two features.

[0020] Further, in step 5), the step of calculating the intersection proportion of different spatial feature classes using the iterative superimposed analysis model includes:

[0021] 5.1) Traverse each record in the relationship table, and read two spatial feature classes in the relationship table record each time;

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

[0023] 5.3) Repeat steps 5.1) to 5.2) to calculate the intersection proportion of any two spatial feature classes in the multiple spatial feature classes to be involved in the superimposed analysis.

[0024] 5.4) According to the configuration information, the element class name of superposition analysis, the unique number of the element, the area of the element, the intersection area, the proportion of the intersection area to the area of the smaller one of the two elements, and the business number attribute of the element are written into the target table.

[0025] Further, in step 5), if the intersection ratio is 100%, the two spatial element classes are in a containing relationship or completely coincide.

[0026] If the intersection ratio is greater than 0 and less than 100%, the two spatial element classes are in an intersection relationship.

[0027] Further, in step 6), the step of establishing the association relationship between the business data includes:

[0028] 6.1) According to the business requirements, set the intersection ratio association threshold value;

[0029] 6.2) According to the business requirements, associate the business number attribute recorded greater or less than the intersection ratio association threshold value with the corresponding business system data table, establish the association relationship between the business data, perform cross-business data fusion, and generate cross-business monitoring indicators.

[0030] The technical effects of the present application are self-evident, and the beneficial effects of the present application are as follows:

[0031] 1) Batch generation of the relationship of the position of a large number of spatial elements is achieved.

[0032] 2) The relationship of the position of a large number of spatial elements is automatically updated, ensuring the timeliness of the data.

[0033] 3) The association relationship between multiple types of businesses with spatial element data can be established on a large scale.

[0034] 4) The flexibility of establishing the association relationship between businesses in different application scenarios can be achieved by setting the element intersection area ratio threshold value.

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

[0036] In summary, the present application proposes an innovative batch generation method of the position relationship of a large number of spatial elements, which iteratively analyzes the spatial element superposition to record the position relationship between spatial elements on a large scale and achieve automatic updating, significantly improving the efficiency of cross-business data fusion and indicator generation, and providing strong support for decision-making in related fields. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 The method flowchart. DETAILED DESCRIPTION

[0038] The application will be further described in connection with the following examples, which should not be construed as limiting the above-mentioned subject matter of the application to the following examples. Various replacements and modifications can be made according to ordinary technical knowledge and conventional means in the art without departing from the above-mentioned technical idea of the application, and all of them should be included in the protection scope of the application.

[0039] Example 1

[0040] Referring to Figure 1 A batch generation method of mass spatial element superposition position relationship includes the following steps:

[0041] 1) Establish a target table of spatial element superposition position relationship; the initial state of the target table is empty, and the calculation result is stored in the target table after the calculation is completed. Each time the distance relationship is recalculated, the target table needs to be emptied first.

[0042] 2) Select a plurality of spatial element classes to be involved in superposition analysis, denoted as a set of spatial element classes to be analyzed, and determine the two-way relationship of the element classes in the set of spatial element classes to be analyzed which need to calculate the superposition position relationship, and record the configured relationship in the data table of the spatial database;

[0043] In the set of spatial element classes, not all two element classes need to calculate the superposition position relationship, for example, the set of element classes contains element class A~element class F, wherein AB, AC, AF, BC, BD, CE, CF, and DF need to calculate the superposition position relationship, and then these two element classes are recorded in the configuration table. AD, AE, BE, BF, CD, DE, and EF element classes do not need to calculate the superposition position relationship, and do not need to be recorded.

[0044] 3) Traverse each relationship record in the configuration table in step 2), and enter step 4) each time two element classes are obtained;

[0045] 4) Calculate the intersection area and intersection ratio between all elements in the two element classes transmitted in step 3) by using the superposition position analysis model;

[0046] 5) Store the element identification and intersection area, intersection ratio, business number and other information in the target table in step 4) where the intersection area is greater than 0, and return to step 3) to continue traversal until the traversal is completed;

[0047] 6) Based on the overlapping relationship of different spatial element classes, the association relationship between business data is established to realize cross-business data fusion.

[0048] In step 1), the target table is used to record the spatial feature class names of two superimposed analyses, the unique numbers of the two spatial features with intersection relationship, the areas of the two spatial features with intersection relationship, the intersection area, the proportion of the intersection area to the area of the smaller one of the two spatial features, and the business number attribute of the two spatial features with intersection relationship.

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

[0050] The spatial feature is used to describe the spatial characteristics of a geographic entity.

[0051] The spatial feature includes a surface feature.

[0052] The surface feature represents a two-dimensional closed area.

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

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

[0055] In step 5), the iterative superimposed analysis model is constructed by GIS software.

[0056] The input of the iterative superimposed analysis model includes two spatial feature classes and the business number attribute field name, and the output is the intersection area, the intersection proportion, and the business number of the two spatial features.

[0057] The intersection proportion is the intersection area of the two features divided by the area of the smaller one of the two features. For example, let a be the area of feature A, b be the area of feature B, and c be the intersection area of features A and B. Then the intersection proportion 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 overlap, or A completely contains B, or B completely contains A.

[0058] In step 5), the step of calculating the intersection proportion of different spatial feature classes using the iterative superimposed analysis model includes:

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

[0060] 5.2) Perform superimposed analysis on the two spatial feature classes read, and calculate the intersection proportion of the current two spatial feature classes.

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

[0062] 5.4) According to the configuration information, write the feature class name of the overlay analysis, the unique number of the feature, the area of the feature, the intersection area, the intersection area accounting for the area of the smaller one of the two features, and the 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 in a containment relationship or completely overlap.

[0064] If the intersection ratio is greater than 0 and less than 100%, the two spatial feature classes are in an intersection relationship.

[0065] In step 6), the step of establishing the association relationship between the business data includes:

[0066] 6.1) According to the business requirements, set the intersection ratio association threshold value; for example, due to production degree or coordinate system conversion, some feature classes will have spatial errors, and two adjacent features that have no intersection relationship in spatial position may have slight contact at the edge of the feature when calculating the spatial position relationship, and the intersection ratio is very small. The threshold value of the intersection ratio can be set to exclude such intersection relationship; when automatically dividing the district of a spatial feature that crosses the county, the intersection ratio threshold value of the feature and the county boundary can be set to 0.5, and the feature and the county whose intersection ratio is greater than 0.5 are included in the county.

[0067] 6.2) According to the business requirements, associate the business number attribute recorded greater or less than the intersection ratio association threshold value with the corresponding business system data table, establish the association relationship between the business data, perform cross-business data fusion, and generate cross-business monitoring indicators.

[0068] Embodiment 2:

[0069] A batch generation method of massive spatial feature overlay position relationship includes the following steps:

[0070] 1) Establish a target table of spatial feature overlay position relationship; the initial state of the target table is empty;

[0071] 2) Select multiple spatial feature classes to be involved in the overlay analysis, denoted as a set of spatial feature classes to be analyzed, and determine the pairwise relationship of the feature classes in the set of spatial feature classes to be analyzed that need to calculate the overlay position relationship, and record the configured relationship 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 enter step 4);

[0073] 4) calculating the intersection area and the intersection proportion between each two of all the elements in the two element classes transmitted in step 3) by using the superimposed position analysis model;

[0074] 5) storing the elements with the intersection area greater than 0 in step 4) in a target table, and returning to step 3) to continue traversing until the traversing is completed;

[0075] 6) establishing the association relationship between the business data based on the overlapping relationship of different spatial element classes, and realizing the data fusion across the business.

[0076] Embodiment 3:

[0077] A batch generation method of the superimposed position relationship of mass spatial elements, the technical content is same as that of embodiment 2, further, in step 1), the target table is used for recording the names of two spatial element classes for superimposed analysis, the unique numbers of the two spatial elements with the intersection relationship, the areas of the two spatial elements with the intersection relationship, the intersection area, the proportion of the intersection area to the area of the smaller one of the two spatial elements, and the business number attributes of the two spatial elements with the intersection relationship;

[0078] The business number attributes include the construction project reporting number, the construction land planning license number, the land registration real estate unit number, the housing registration real estate unit number, the newly added construction land approval number, and the land transfer contract number.

[0079] Embodiment 4:

[0080] A batch generation method of the superimposed position relationship of mass spatial elements, the technical content is same as that of any one of embodiments 2-3, further, the spatial elements are used for describing the spatial characteristics of geographical entities.

[0081] Embodiment 5:

[0082] A batch generation method of the superimposed position relationship of mass spatial elements, the technical content is same as that of any one of embodiments 2-4, further, the spatial elements include surface elements.

[0083] The surface elements represent two-dimensional closed areas.

[0084] Embodiment 6:

[0085] A batch generation method of the superimposed position relationship of mass spatial elements, the technical content is same as that of any one of embodiments 2-5, further, in step 2), the configuration information of the multiple spatial element classes to be involved in the superimposed analysis is also recorded in the data table of the spatial database;

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

[0087] Embodiment 7:

[0088] The batch generation method of the position relationship of the mass spatial element superposition, the technical content is same as any one of embodiments 2-6, further, in step 5), the iterative superposition analysis model is obtained by constructing through the GIS software;

[0089] The input of the iterative superposition analysis model includes two spatial element classes, the business number attribute field name, and the output is the intersection area of two spatial elements, the intersection ratio and the business number;

[0090] The intersection ratio is the intersection area of two elements divided by the area of the smaller one of the two elements.

[0091] Embodiment 8:

[0092] The batch generation method of the position relationship of the mass spatial element superposition, the technical content is same as any one of embodiments 2-7, further, in step 5), the step of calculating the intersection ratio of different spatial element classes by using the iterative superposition analysis model includes:

[0093] 5.1) traversing each record in the relationship table, reading two spatial element classes in the relationship table record each time;

[0094] 5.2) performing superposition analysis on the read two spatial element classes, and calculating the intersection ratio of the current two spatial element classes;

[0095] 5.3) repeating step 5.1)-step 5.2), and calculating the intersection ratio of any two spatial element classes in the multiple spatial element classes to be involved in the superposition analysis;

[0096] 5.4) according to the configuration information, writing the element class name of the superposition analysis, the unique number of the element, the area of the element, the intersection area, the area ratio of the intersection area to the area of the smaller one of the two elements, and the business number attribute of the element into the target table.

[0097] Embodiment 9:

[0098] The batch generation method of the position relationship of the mass spatial element superposition, the technical content is same as any one of embodiments 2-8, further, in step 5), if the intersection ratio is 100%, the two spatial element classes are in a containing relationship or completely coincide;

[0099] If the intersection ratio is greater than 0 and less than 100%, the two spatial element classes are in an intersection relationship.

[0100] Embodiment 10:

[0101] A batch generation method of mass spatial element superposition position relationship, the technical content is the same as any one of embodiments 2-9, further, in step 6), the step of establishing the association relationship between the business data includes:

[0102] 6.1) Set the intersection proportion association threshold according to the business demand;

[0103] 6.2) According to the business demand, associate the business number attribute of the record greater or less than the intersection proportion association threshold with the corresponding business system data table, establish the association relationship between the business data, perform cross-business data fusion, and generate cross-business monitoring indicators.

[0104] Embodiment 11:

[0105] A batch generation method of mass spatial element superposition position relationship, the steps include:

[0106] 1. Establish a target table of spatial element superposition position relationship

[0107] A target table of spatial element superposition position relationship is established in a spatial database, which is used to record the names of two superposition analysis element classes, the unique numbers of two elements with intersection relationship, the areas of two elements with intersection relationship, the intersection area, the proportion of the intersection area to the area of the smaller one of the two elements, and the business number attribute of the two elements with intersection relationship.

[0108] 2. Select the element classes participating in superposition analysis

[0109] Select multiple element classes participating in superposition analysis, determine the two-by-two relationship of the element classes that need to be analyzed, record the relationship in the data table of the spatial database, and record the unique number field name, area field name, and business number field name of the element class and other configuration information.

[0110] 3. Build an iterative superposition analysis model

[0111] Build an iterative superposition analysis model using GIS software:

[0112] Build a table record iterative model. Traverse each record in the relationship table, and read two element classes in the relationship table record each time.

[0113] Perform superposition analysis. Perform superposition analysis on the two element classes read.

[0114] Calculate the element area of the superposition analysis result element class.

[0115] The construction element iteration model traverses each element in the superimposed analysis result element class, and writes the superimposed analysis element class name, the unique number of the element, the area of the element, the intersection area, the proportion of the intersection area to the area of the smaller one of the two elements, the business number attribute of the element and other information into the target table according to the configuration information.

[0116] 4. Establish a timing update mechanism

[0117] The superimposed iteration superimposed analysis model is executed by the task scheduling system.

[0118] 5. Application scenarios and application methods

[0119] For different businesses and application scenarios, the intersection ratio between elements is set as a threshold value, and the intersection or inclusion relationship between two spatial elements can be obtained, such as an intersection ratio of 100%, which indicates that the two spatial elements are in an inclusion relationship or completely coincide; an intersection ratio greater than 50% indicates that the two spatial elements have a high degree of coincidence. According to business requirements, the business number of the record of the element intersection ratio greater than or less than the threshold value is associated with the corresponding business system data table, and the association relationship between the business data can be established on a large scale, the data fusion across businesses can be performed, and the monitoring indicators across businesses can be generated to provide data support for the decision support system and the cockpit.

Claims

1. A method for batch generation of the positional relationships of superimposed massive spatial elements, characterized in that, Includes the following steps: 1) Establish a target table for the spatial element overlay positional relationships; the target table is initially empty. 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. 3) Traverse each relationship record in the configuration table in step 2), obtain two feature classes each time, and proceed to step 4); 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; 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; 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 5), the iterative overlay analysis model is constructed using GIS software; 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. 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 5), which involves using an iterative overlay analysis model to calculate the intersection ratio of different spatial feature classes, includes: 5.1) Traverse each record in the relation table, reading two spatial feature classes from each record in the relation table; 5.2) Perform overlay analysis on the two spatial feature classes read, and calculate the intersection ratio of the two spatial feature classes; 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; 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.

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: 6.1) Set the intersection ratio correlation threshold according to business needs; 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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