Land ownership spatial information construction method based on cadastral survey data

Abstract

The application discloses a land ownership space information construction method based on cadastral survey data, relates to the technical field of data processing, and comprises the following steps: adopting cadastral elements and ownership identification in cadastral survey results to perform coordinate unification, geometry repair, reference relationship calibration and ownership relationship calibration, and generating a cadastral space object sequence; performing Hilbert curve coding sorting on parcel space objects in the cadastral space object sequence, and dividing data sections according to cadastral sub-areas and continuous coding intervals, to generate a cadastral segmented directory; constructing a Hilbert global directory, an R-star tree local space index and a B-plus tree ownership attribute index through the cadastral segmented directory, and generating an ownership space construction index table. Through vectorized R-tree space connection, the application can perform batch judgment on the spatial relationship among parcel surfaces, boundary lines and boundary points, and can generate segmented ownership space results in combination with ownership attribute matching, so that the spatial relationship calculation efficiency and the ownership corresponding accuracy in a big data processing scene can be improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method for constructing spatial information on land ownership based on cadastral survey data. Background Technology

[0002] With the development of unified real estate registration, digitization of cadastral survey results, and refined land space governance, cadastral survey data is gradually shifting from traditional map data to spatial database management. Existing cadastral spatial information is typically constructed based on parcel land area, boundary lines, boundary points, parcel codes, real estate unit numbers, and ownership registration information. Through methods such as coordinate unification, geometric object organization, spatial index construction, and attribute table association, cadastral data that can be used for parcel querying, ownership registration, boundary management, and spatial analysis is formed.

[0003] In large-scale cadastral survey data processing scenarios, existing technologies often employ fixed sheet divisions, ordinary spatial indexes, or attribute table connections to organize parcel spatial information. Spatial geometric objects, ownership identifiers, and version records are typically stored in a dispersed manner, making it difficult to maintain consistency between boundary line sharing relationships, boundary point reference relationships, and ownership source records when parcels are distributed across data segments. Especially when there are a large number of parcels, frequent survey version updates, and significant reuse of boundaries between adjacent parcels, relying solely on spatial overlay or table field matching can easily lead to a disconnect between spatial index results and ownership relationship verification, affecting the accuracy and traceability of the cadastral ownership spatial information database. Summary of the Invention

[0004] Given the aforementioned existing problems, namely that the existing methods of constructing cadastral spatial information are difficult to maintain the spatial topological consistency, ownership identification consistency, and traceability of measurement version sources among parcels, boundary lines, and boundary points under the same data organization framework during large-scale cadastral survey data processing, especially when parcels are distributed across data segments, adjacent parcel boundaries are reused, and measurement results are frequently updated, problems such as the spatial index results being disconnected from ownership relationship verification, mismatched boundary reference relationships, and broken ownership source records are likely to occur.

[0005] Therefore, this invention provides a method for constructing spatial information of land ownership based on cadastral survey data, which solves the problem that it is difficult to construct spatial topology and ownership relationship in a consistent manner in large-scale cadastral survey data.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: This invention provides a method for constructing spatial information on land ownership based on cadastral survey data, including: Using cadastral elements and ownership identifiers from cadastral survey results, coordinate unification, geometric repair, reference relationship calibration, and ownership relationship calibration are performed to generate a sequence of cadastral spatial objects; The parcel spatial objects in the cadastral spatial object sequence are sorted by Hilbert curve encoding, and the data segments are divided according to cadastral sub-regions and continuous encoding intervals to generate a cadastral segment catalog. Hilbert global directory, R-star tree local spatial index and B-tree ownership attribute index are constructed by cadastral segmentation directory to generate ownership space construction index table; The ownership space is used to construct an index table to locate the land parcel, boundary line, boundary point and ownership identifier, and vectorized R-tree spatial connection and ownership attribute matching are performed to generate segmented ownership space results; The segmented ownership spatial results are constructed into a subgraph integrated R-tree topology graph, and cross-segment land parcel reorganization and ownership version sorting are carried out by tree tracking and ownership chain pruning, generating a cadastral ownership spatial information database.

[0007] As a preferred embodiment of the land ownership spatial information construction method based on cadastral survey data according to the present invention, the step of generating a cadastral spatial object sequence specifically includes: Extract parcel land area, boundary lines, boundary points, parcel codes, and ownership identifiers from cadastral survey results to generate an initial cadastral object set; The initial cadastral object set is transformed to a unified coordinate system, and self-intersection, boundary breaks, and surface ring orientation anomalies of the parcels are repaired to generate a standard cadastral geometric object set. Based on the parcel code, boundary line number, and boundary point number in the standard cadastral geometric object set, spatial reference chains are arranged, and the corresponding relationship of real estate unit number, ownership source document number, and registration status in the ownership identifier is combined to generate a cadastral spatial object sequence.

[0008] As a preferred embodiment of the land ownership spatial information construction method based on cadastral survey data according to the present invention, the step of performing Hilbert curve encoding and sorting on the parcel spatial objects in the cadastral spatial object sequence specifically includes: Extract parcel spatial objects from the cadastral spatial object sequence, calculate the center point of the bounding rectangle of the parcel spatial object and map it to the Hilbert curve coding space to generate parcel Hilbert coding sequence. The Hilbert code sequence of land parcels is rearranged according to the cadastral area code, cadastral sub-area code, parcel Hilbert code, and parcel code to generate a coded and sorted parcel sequence.

[0009] As a preferred embodiment of the land ownership spatial information construction method based on cadastral survey data described in this invention, the step of dividing the data segments according to cadastral sub-regions and continuous coding intervals specifically includes: The land parcel sequence is divided and coded according to the cadastral sub-region code, and the continuous interval of Hilbert curve coding is identified along the divided land parcel sequence to generate sub-region coded data segments. The cadastral sub-region codes, continuous coding intervals, parcel codes, and measurement version numbers in the sub-region coding data segments are compiled into catalog records to generate a cadastral segment catalog.

[0010] As a preferred embodiment of the land ownership spatial information construction method based on cadastral survey data described in this invention, the construction of the Hilbert global catalog specifically includes: Extract cadastral sub-region codes, consecutive coding intervals, and data segment numbers from the cadastral segmentation directory to generate a global directory key; The global directory key is mapped to the storage location, parcel code range, and measurement version number of the sub-area coded data segment, and the retrieval boundary of the sub-area coded data segment is defined by the mapping relationship, generating the Hilbert global directory and global retrieval boundary set.

[0011] As a preferred embodiment of the land ownership spatial information construction method based on cadastral survey data described in this invention, the construction of the R-star tree local spatial index specifically includes: The sub-region coded data segment is determined by globally retrieving the boundary set, and the minimum bounding rectangle of the standard cadastral geometric objects within the sub-region coded data segment is extracted to generate a set of bounding rectangles for local spatial objects. The smallest bounding rectangle in the set of bounding rectangles of local spatial objects is combined with the parcel code, boundary line number and boundary point number to form the R-star tree spatial leaf entry, and then merged into the R-star tree spatial leaf node set according to spatial overlap relationship and coverage range. An R-star tree spatial non-leaf node set is formed along the spatial coverage of the R-star tree spatial leaf node set. The node number, minimum bounding rectangle, and corresponding parcel code, boundary line number, and boundary point number are marked by the R-star tree spatial leaf node set and the R-star tree spatial non-leaf node set to generate the R-star tree local spatial index.

[0012] As a preferred embodiment of the land ownership spatial information construction method based on cadastral survey data described in this invention, the generation of the ownership spatial construction index table specifically includes: Extract the real estate unit number, parcel code, ownership identifier, ownership source document number, and measurement version number from the cadastral spatial object sequence to generate an ownership attribute key sequence; Arrange the internal nodes of the B-tree attribute according to the ownership attribute key sequence, and record the ownership identifier position in the leaf node of the B-tree attribute to generate the B-tree ownership attribute index. The Hilbert global directory, R-star tree local spatial index, and B-tree ownership attribute index are aligned according to cadastral sub-region codes, continuous coding intervals, and parcel codes to generate an ownership spatial construction index table.

[0013] As a preferred embodiment of the land ownership spatial information construction method based on cadastral survey data described in this invention, the generation of segmented ownership spatial results specifically includes: The index table is constructed using the ownership space to determine the target sub-region coded data segment, and the minimum bounding rectangle of the standard cadastral geometric object is extracted from the R-star tree local spatial index to generate a set of candidate spatial object rectangles. Arrange the candidate spatial object rectangle set into a contiguous memory array, and batch determine the spatial connection relationship between the land parcel and the boundary line, the boundary line and the boundary point, and the adjacent land parcels to generate a candidate spatial connection relationship set; The candidate spatial connection relationship set is used to perform geometrically accurate verification of standard cadastral geometric objects, and the parcel code, real estate unit number, boundary line number and boundary point number are extracted from the verification results to generate a segmented spatial reference relationship set; By triggering the key-order traversal of the B-tree ownership attribute index through the segmented spatial reference relationship set, a segmented ownership identifier set is generated, and ownership attribute matching is completed according to the parcel code, real estate unit number, registration status and measurement version number to generate segmented ownership matching results. The segmented ownership matching results, parcel division, shared boundary lines, and boundary point references are grouped into the same segmented record according to the parcel code to generate segmented ownership spatial results.

[0014] As a preferred embodiment of the land ownership spatial information construction method based on cadastral survey data described in this invention, the step of constructing the segmented ownership spatial results into a subgraph integrated R-tree topology graph specifically includes: Extract the parcel division, shared boundary lines, boundary point reference relationships, and segment ownership matching results from the segmented ownership spatial results to generate a segmented topology object set; The segmented topology object set is transformed into parcel block nodes, boundary line nodes, boundary point nodes, real estate unit number nodes, and ownership source document number nodes, and the reference relationship between nodes is transformed into topology graph edges to generate cadastral ownership topology sub-graph. Embed the spatial index nodes and minimum bounding rectangles in the R-star tree local spatial index into the cadastral ownership topology subgraph to generate an index-embedded topology subgraph. The spatial index path embedded in the index subgraph is combined with the cadastral topology path in the cadastral ownership topology subgraph to generate a subgraph integrated R-tree topology graph.

[0015] As a preferred embodiment of the land ownership spatial information construction method based on cadastral survey data described in this invention, the step of generating a cadastral ownership spatial information database specifically includes: The original parcel code in the subgraph integrated R-tree topology graph is used to start the tree tracing connection, and the parcel block nodes, boundary line nodes, boundary point nodes, real estate unit number nodes and ownership source file number nodes are traversed to generate ownership chain candidate paths. The integrity of the link between land parcel blocks, boundary lines, boundary points, real estate unit numbers and ownership source document numbers is verified using the ownership chain candidate path to generate ownership chain verification paths; When a broken chain occurs in the ownership chain verification path, the candidate result corresponding to the broken chain is removed from the cross-segment reorganization object, and a complete ownership chain and broken chain verification table are generated. The original parcel codes in the complete ownership chain are used to merge the parcel blocks across data segments, the clipping boundaries formed by the segments are deleted, and the cross-segment parcel topology is arranged by combining standard cadastral geometric objects and shared boundary line nodes to generate the cross-segment parcel reorganization result. The ownership records of the same parcel are arranged according to the parcel code, ownership source document number, registration status and measurement version number in the cross-parcel reorganization results, and an ownership version chain is generated. The results of cross-segment land reorganization, ownership version chain, subgraph integrated R-tree topology, and chain break verification table are encapsulated into a cadastral ownership spatial information database.

[0016] The beneficial effects of this invention are as follows: By unifying the arrangement of land parcels, boundary lines, boundary points, ownership identifiers, and measurement version numbers into a cadastral spatial object sequence, compared to the existing method of storing spatial geometric objects, ownership registration information, and version records in a scattered manner, a synchronous verification basis for spatial reference relationships and ownership correspondence can be formed at the data entry stage, reducing mismatches between subsequent land parcel codes, real estate unit numbers, and ownership source files; By using Hilbert curve coding and sorting and generating a cadastral segmented directory according to cadastral sub-regions and continuous coding intervals, compared with the existing fixed-area or simple administrative division segmentation methods, adjacent spatial land parcels can maintain continuity in storage and retrieval order, reducing cross-segment jumps and discrete accesses during large-scale cadastral data retrieval; By grouping the Hilbert global directory, R-tree local spatial index, and B-tree ownership attribute index according to cadastral sub-region codes, continuous coding intervals, and land parcel codes, compared to the existing method of separately constructing spatial indexes and then linking attribute tables, this approach achieves a more efficient and consistent result. This approach enables parcel spatial positioning, boundary relationship retrieval, and ownership attribute querying to be completed around the same index record, improving the consistency between spatial retrieval results and ownership verification results. By using vectorized R-tree spatial connections to batch determine the connection relationships between parcels, boundary lines, boundary points, and adjacent parcels, and combining this with B-tree ownership attribute matching to generate segmented ownership spatial results, compared with existing object-by-object spatial overlay and manual field comparison, it can improve the efficiency of spatial relationship calculation and reduce misjudgments of shared boundary lines and boundary point reference relationships. Constructing a subgraph to integrate the R-tree topology graph, and completing cross-segment parcel reorganization and ownership version sorting through tree tracking and connection ownership chain pruning, compared with existing methods of directly merging cross-segment parcels or only merging historical records by field, it can identify broken chain paths and remove abnormal candidate results before entering the database, reducing the risk of cross-segment merging errors, duplicate boundary generation, and incorrect entry of invalid historical ownership records, thereby improving the accuracy of cadastral ownership spatial information database construction, topological integrity, and ownership traceability. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating a method for constructing spatial information on land ownership based on cadastral survey data; Figure 2 A schematic diagram of Hilbert coding sorting and segmented directory generation for land parcels; Figure 3 A schematic diagram illustrating the same-origin homing structure for constructing an index table in the ownership space; Figure 4A schematic diagram of subgraph integration R-tree topology and cross-segment parcel reorganization. Detailed Implementation

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0020] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0021] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0022] Example, refer to Figures 1-4 This is one embodiment of the present invention, which provides a method for constructing spatial information on land ownership based on cadastral survey data, including the following steps: S1. Using cadastral elements and ownership identifiers from cadastral survey results, coordinate unification, geometric repair, reference relationship calibration, and ownership relationship calibration are performed to generate a cadastral spatial object sequence.

[0023] S1.1. Cadastral survey results are obtained by checking the format, registering the coordinate system, and checking the uniqueness of the parcel code of field cadastral survey data, parcel graphic data, and ownership registration data before storing them in the cadastral results database. Cadastral survey results include parcel surface area, boundary line, boundary point, parcel code, cadastral area code, cadastral sub-area code, survey version number, and ownership identifier.

[0024] Among them, the parcel surface is the planar geometric object formed by the closed boundary of the parcel, the boundary line is the linear geometric object of the parcel boundary formed by connecting adjacent boundary points, the boundary point is the coordinate point corresponding to the endpoint and turning point of the parcel boundary, the parcel code is the unique number of the parcel in the cadastral results database, and the ownership identifier includes the real estate unit number, the ownership source document number and the registration status.

[0025] Extract parcel land area, boundary line, boundary point, parcel code, and ownership identifier from the cadastral survey results database. Assign parcel land area to the corresponding parcel record according to parcel code, boundary line to the corresponding parcel boundary record according to boundary line number, boundary point to the corresponding boundary line endpoint record according to boundary point number, and ownership identifier to the corresponding parcel code to generate an initial cadastral object set.

[0026] The parcels, boundary lines, and boundary points in the initial cadastral object set are uniformly transformed to a unified coordinate system. The unified coordinate system adopts the legal plane coordinate system registered when the cadastral survey results are entered into the database. When there are multiple coordinate systems in the cadastral survey results, the original coordinate system name and transformation parameters are retained, and the parcels, boundary lines, and boundary points are transformed to the same coordinate datum according to the coordinate transformation relationship registered when the cadastral survey results are entered into the database, thereby generating a unified coordinate object set.

[0027] S1.2. Perform geometric legality repair on the parcels in the coordinate unified object set. Geometric legality repair includes eliminating self-intersections of parcels, connecting the endpoints of broken boundaries, correcting the direction of surface loops, and completing closed boundaries to generate repaired parcel boundaries. Compare the starting and ending boundary point numbers of the boundary lines sequentially along the closed direction of the repaired parcel boundaries. When the ending boundary point number of the previous boundary line is consistent with the starting boundary point number of the next boundary line, and the ending boundary point number of the last boundary line is consistent with the starting boundary point number of the first boundary line, confirm that the sequence of the starting and ending points of the boundary lines is consistent with the repaired parcel boundaries. When the direction of the boundary lines is opposite to the direction of the repaired parcel boundaries, swap the starting and ending boundary point numbers of the boundary lines and re-compare. When the boundary lines cannot form a closed sequence with the repaired parcel boundaries, retain the boundary line anomaly markers.

[0028] The boundary point numbers are matched with the starting and ending boundary point numbers of the boundary line, and the coordinates of the matched boundary points are compared with the coordinates of the boundary line endpoints. When the boundary point coordinates match the boundary line endpoint coordinates, the boundary point coordinates are confirmed to be valid. When the boundary point coordinates do not match the boundary line endpoint coordinates, the boundary line endpoint coordinates are corrected with the boundary point coordinates corresponding to the boundary point number, and the coordinate verification mark is retained. After completing the boundary line start and end point sequence verification and boundary point coordinate verification, a standard cadastral geometric object set is generated.

[0029] S1.3. Arrange spatial reference chains based on the parcel codes, boundary line numbers, and boundary point numbers in the standard cadastral geometric object set. The spatial reference chains sequentially record the relationship between the boundary lines corresponding to the parcels, the boundary points corresponding to the boundary lines, and the shared boundary lines of adjacent parcels, thereby generating a spatial reference object set.

[0030] The method involves verifying the correspondence between the land parcel code in the spatial reference object set and the real estate unit number in the ownership identifier. Specifically, the code field of the corresponding land parcel in the real estate unit number is compared with the land parcel code in the spatial reference object set, and the real estate unit number that matches the comparison is used as the ownership identifier corresponding to the land parcel code.

[0031] The validity of ownership records under the same land parcel code is verified using the ownership source document number and registration status. Specifically, it is checked whether the ownership source document number corresponds to the registration record to which the real estate unit number belongs, and whether the registration status is registered and not cancelled, revoked, or replaced by subsequent change registration. When the real estate unit number corresponding to the same land parcel code is consistent, the ownership source document number points to the same registration record, the registration status is registered and not cancelled, revoked, or replaced by subsequent change registration, and there are no conflicting registered valid ownership records under the same land parcel code, it is confirmed that there is a consistent correspondence between the land parcel code, real estate unit number, ownership source document number, and registration status. The land parcels, boundary lines, boundary points, and ownership identifiers with consistent correspondence are arranged into the same cadastral spatial object, generating a cadastral spatial object sequence.

[0032] S2. Perform Hilbert curve coding sorting on the parcel spatial objects in the cadastral spatial object sequence, and divide the data into segments according to cadastral sub-regions and continuous coding intervals to generate a cadastral segment catalog.

[0033] S2.1. Extract parcel spatial objects from the cadastral spatial object sequence. Each parcel spatial object includes the parcel surface area, parcel code, cadastral area code, cadastral sub-area code, and survey version number. Determine the circumscribed rectangle of the parcel spatial object according to the coordinate range of the parcel surface area in a unified coordinate system. The circumscribed rectangle is defined by the minimum and maximum abscissa, minimum and maximum ordinate of the parcel surface area coordinates. Calculate the center point of the circumscribed rectangle using the formula for the midpoint of the diagonal vertex of a rectangle in plane analytic geometry. The expression is: ; in, Represents the index of a land parcel spatial object. Indicates the first The x-coordinate of the center point of the bounding rectangle of each land parcel spatial object Indicates the first The ordinate of the center point of the bounding rectangle of each land parcel spatial object. Indicates the first The minimum x-coordinate of each land parcel spatial object Indicates the first The maximum x-coordinate of each parcel spatial object Indicates the first The minimum ordinate of each land parcel spatial object Indicates the first The maximum ordinate of each spatial object.

[0034] The x-coordinate of the center point of each circumscribed rectangle, the y-coordinate of the center point of the circumscribed rectangle, and the parcel code, cadastral zone code, cadastral sub-zone code, and measurement version number of the same parcel spatial object are arranged as parcel center point records. All parcel center point records are arranged in the order of the parcel codes to generate a parcel center point sequence.

[0035] like Figure 2 The left-hand cadastral sub-zone spatial diagram shows that parcels within the same cadastral sub-zone can be represented as parcel A, parcel B, parcel C, parcel D, parcel E, parcel F, parcel G, and parcel H. The outer boundary of each parcel is formed by boundary lines. The ends and turning points of the boundary lines correspond to boundary points. The center point of the circumscribed rectangle of each parcel is located inside or near the geometric center of the corresponding parcel. When generating the parcel center point sequence, the center points of the circumscribed rectangles from parcel A to parcel H are extracted to form A( The parcel center point records corresponding to x_A, y_A), B(x_B, y_B), C(x_C, y_C), D(x_D, y_D), E(x_E, y_E), F(x_F, y_F), G(x_G, y_G), and H(x_H, y_H) enable subsequent Hilbert coding to use the parcel center points as the spatial sorting objects, rather than directly using all points of the parcel boundary as the coding objects, thereby avoiding the instability of coding sorting caused by complex parcel boundary morphology.

[0036] S2.2. Map the parcel center point sequence to the Hilbert curve coding space. Specifically, use the minimum abscissa and minimum ordinate of the parcel center point sequence within the same cadastral sub-region as the coding origin, and use the coordinate precision unit registered when the cadastral survey results are entered into the database as the grid unit to convert the parcel center point coordinates into integer grid coordinates. The expression is: ; in, Indicates the first The horizontal integer grid coordinates of each parcel spatial object in the Hilbert curve encoding space. Indicates the first The vertical integer grid coordinates of each parcel spatial object in the Hilbert curve encoding space. The minimum x-coordinate representing the sequence of parcel center points within the same cadastral sub-region. The smallest ordinate representing the sequence of parcel center points within the same cadastral sub-region. This indicates the unit of coordinate precision used when cadastral survey results are entered into the database. This indicates rounding to the nearest integer.

[0037] The horizontal integer grid coordinates and vertical integer grid coordinates are combined with the parcel code, cadastral area code, cadastral sub-area code and measurement version number in the parcel center point record to form a parcel coded grid point record. All parcel coded grid point records are then arranged according to the order of the parcel center point sequence to generate a parcel coded grid point sequence.

[0038] like Figure 2 The Hilbert curve coding grid in the middle section is illustrated. After projecting the sequence of parcel center points onto the discrete coding grid, each parcel center point falls into a corresponding grid cell. The grid cells are assigned coding numbers according to the spatial filling order of the Hilbert curve. For parcels A to H falling within the same cadastral sub-region, the corresponding Hilbert curve positions are determined based on their integer grid coordinates, and the coding value of that position is written into the parcel coding grid point record. This process ensures that spatially adjacent parcels remain as adjacent as possible in the coding sequence, thus providing a spatial continuity basis for subsequent data segmentation according to continuous coding intervals.

[0039] S2.3. According to the existing recursive quadrant traversal rules of Hilbert space filling curves, encode the integer grid coordinates in the parcel coding grid point sequence to obtain the parcel Hilbert code corresponding to each parcel spatial object; when different parcel spatial objects are mapped to the same integer grid coordinates, retain the same parcel Hilbert code, and continue to retain the corresponding parcel code, cadastral area code, cadastral sub-area code and measurement version number to generate a parcel Hilbert code sequence.

[0040] like Figure 2 As shown in the Hilbert coding table and coding sorting parcel sequence on the upper right, parcel spatial objects such as parcel A, parcel B, parcel E, parcel H, parcel C, parcel D, parcel F, and parcel G each have corresponding Hilbert codes. When performing rearrangement, the same processing range is first limited according to the cadastral zone code and cadastral subzone code, and then the spatial traversal order is determined according to the Hilbert code. When the codes are the same or adjacent, the parcel code and measurement version number are retained. Figure 2 The parcel codes and coding values ​​in the database are used to explain the coding and sorting process. In actual implementation, the parcel codes, grid coordinates, and Hilbert coding calculation results in the cadastral results database shall prevail.

[0041] The parcel Hilbert code sequence is rearranged in the order of cadastral area code, cadastral sub-area code, parcel Hilbert code, and parcel code. When the cadastral area code and cadastral sub-area code are the same and the parcel Hilbert code is the same, the corresponding parcel spatial objects are arranged in lexicographical order according to the parcel codes. When there are multiple measurement version numbers for the same parcel code, the record order of the corresponding measurement version number is retained under the parcel code order. After the rearrangement is completed, a coded and sorted parcel sequence is generated.

[0042] S2.4. Divide the land parcels into consecutively arranged cadastral sub-zone codes according to the coded sorted land parcel sequence; when two adjacent land parcel records have the same cadastral sub-zone code, keep the two adjacent land parcel records in the same land parcel sorting segment; when two adjacent land parcel records have different cadastral sub-zone codes, end the current land parcel sorting segment and start the next land parcel sorting segment, until the entire coded sorted land parcel sequence is divided to obtain the land parcel sorting segment of the corresponding cadastral sub-zone.

[0043] Identify continuous Hilbert codes for adjacent parcels along the parcel sorting segments of the corresponding cadastral sub-regions. When adjacent parcels have the same or different Hilbert codes by one, the adjacent parcel spatial objects are included in the current continuous coding interval. When the difference between adjacent parcel Hilbert codes is greater than one, the current continuous coding interval ends and the next continuous coding interval begins. After the continuous coding interval identification is completed, sub-region coding data segments are generated.

[0044] The cadastral sub-area codes, continuous coding intervals, parcel codes, and survey version numbers in the sub-area coding data segments are compiled into a catalog record; among them, the cadastral sub-area codes are the first-level catalog, the continuous coding intervals are the second-level catalog, and the parcel codes and survey version numbers are the third-level catalogs; the catalog record retains the reference relationship between the parcel codes, boundary line numbers, real estate unit numbers, and ownership source document numbers, and generates a cadastral segment catalog.

[0045] like Figure 2 As shown in the cadastral segment directory below, the cadastral segment directory is organized hierarchically according to the following structure: "Cadastral sub-zone code—continuous coding interval—parcel code and measurement version number." For example, when cadastral sub-zone code SUB001 corresponds to the continuous coding interval 0000 to 0101, parcel codes A, B, and E, along with their measurement version number V2024.01, falling within this continuous coding interval, are grouped into the same sub-zone coding data segment. When cadastral sub-zone code SUB002 corresponds to the continuous coding interval 0110 to 1011, parcel codes H, D, and F, along with their measurement version numbers, falling within this continuous coding interval, are grouped into another sub-zone coding data segment. The remaining cadastral sub-zones continue to generate directory records such as SUB00N according to the same rules. Each directory record simultaneously stores the reference relationships between parcel codes, boundary line numbers, real estate unit numbers, and ownership source document numbers, ensuring that a consistent data entry point can be obtained from the same cadastral segment directory when constructing the global directory, local spatial index, and ownership attribute index.

[0046] S3. Construct a Hilbert global directory, an R-tree local spatial index, and a B-tree ownership attribute index through cadastral segmentation directory, and generate an ownership space construction index table.

[0047] S3.1. Extract the cadastral sub-area code, continuous coding interval, parcel code and measurement version number from the cadastral segmentation catalog, and determine the corresponding sub-area coded data segment according to the same cadastral sub-area code and the same continuous coding interval; assign a data segment number to each sub-area coded data segment, and the data segment number, together with the cadastral sub-area code and continuous coding interval, form a global catalog key, and generate a global catalog key sequence.

[0048] Among them, the cadastral sub-zone code in the global directory key is used to limit the administrative management scope, the continuous coding interval is used to limit the Hilbert curve sequence range, and the data segment number is used to distinguish the data segments corresponding to different continuous coding intervals within the same cadastral sub-zone.

[0049] By mapping the global directory keys in the global directory key sequence to the storage location, parcel code range, and measurement version number of the sub-area coded data segment, a Hilbert global directory is generated.

[0050] The storage location of the sub-area coded data segment is the address record of the sub-area coded data segment in the data storage medium; the parcel code range is the sequential range from the first parcel code to the last parcel code within the sub-area coded data segment; and the measurement version number is the cadastral survey result version corresponding to the parcel spatial object within the sub-area coded data segment.

[0051] Extract the global directory key, continuous coding interval, parcel code range and measurement version number from the Hilbert global directory as retrieval boundary records to generate a global retrieval boundary set.

[0052] like Figure 3 As shown in the Hilbert global directory on the left, the Hilbert global directory includes a root directory, a cadastral sub-zone code directory, a continuous coding interval directory, and a data segment directory. Taking the cadastral sub-zone code SUB001 as an example, its directory record contains the continuous coding interval, data segment number D001, storage location storage node A / path / SUB001 / D001, parcel code range, measurement version number V2024.01, and global retrieval boundary. In actual retrieval, the cadastral sub-zone code is first located through the root directory, then the data segment number is located through the continuous coding interval, and the corresponding sub-zone coded data segment is read according to the storage location, thus enabling cadastral spatial objects to be quickly located according to the segmented directory.

[0053] S3.2. Determine the sub-region coded data segments for which the R-Star Tree local spatial index needs to be constructed by using the global retrieval boundary set. Specifically, compare the cadastral sub-region code, continuous coding interval, and measurement version number in the global retrieval boundary set with the directory records in the cadastral segment directory. When the cadastral sub-region code is consistent, the continuous coding interval covers the same sub-region coded data segment, and the measurement version number is consistent, the corresponding sub-region coded data segment is determined as the object for constructing the R-Star Tree local spatial index.

[0054] Extract standard cadastral geometric objects from the defined sub-area coded data segment; the standard cadastral geometric objects include parcel land area, boundary line and boundary point; calculate the minimum bounding rectangle of parcel land area, boundary line and boundary point in a unified coordinate system respectively, and combine the minimum bounding rectangle with the corresponding parcel code, boundary line number and boundary point number to generate a set of bounding rectangles of local spatial objects.

[0055] Among them, the minimum bounding rectangle of the land parcel is defined by the minimum and maximum abscissa, minimum and maximum ordinate of the land parcel boundary coordinates; the minimum bounding rectangle of the boundary line is defined by the coordinate range of the two ends and turning points of the boundary line; and the minimum bounding rectangle of the boundary point is represented by the point-shaped bounding rectangle formed by the coordinates of the boundary point.

[0056] S3.3. Combine each minimum bounding rectangle in the set of bounding rectangles of local spatial objects with the corresponding parcel code, boundary line number and boundary point number to form an R-star tree spatial leaf entry; according to the existing minimum bounding rectangle overlap priority reduction rule and coverage expansion priority reduction rule of R-star tree, merge the R-star tree spatial leaf entries with the closest spatial location into an R-star tree spatial leaf node set.

[0057] For each R-star tree spatial leaf node in the R-star tree spatial leaf node set, calculate the minimum bounding rectangle of the node. The minimum bounding rectangle of the node covers all R-star tree spatial leaf entries within the corresponding R-star tree spatial leaf node. According to the spatial overlap relationship and coverage range between the minimum bounding rectangles of the nodes, merge R-star tree spatial leaf nodes with adjacent spatial coverage ranges into R-star tree spatial non-leaf nodes of the upper layer. Repeat the merging until the root node is formed, generating the R-star tree spatial non-leaf node set. The R-star tree spatial leaf node set stores the spatial leaf entries of standard cadastral geometric objects, and the R-star tree spatial non-leaf node set stores the coverage range of the lower layer nodes. The R-star tree spatial non-leaf node set points to the corresponding R-star tree spatial leaf node set through the node number.

[0058] By marking node numbers, minimum bounding rectangles, parcel codes, boundary line numbers, and boundary point numbers using the leaf node set and non-leaf node set of the R-star tree space, a local spatial index of the R-star tree is generated.

[0059] like Figure 3The R-tree local spatial index in the middle section is shown. The R-tree local spatial index consists of a root node R0, non-leaf nodes R1-1 to R1-n, leaf nodes L1 to Ln, and entries within the leaf nodes. The root node R0 records the spatial coverage of the entire sub-region coded data segment. The non-leaf nodes record the minimum bounding rectangle of their subordinate nodes. The leaf nodes store the minimum bounding rectangle entries corresponding to specific standard cadastral geometric objects. Each leaf entry records at least the minimum bounding rectangle MBRj, parcel code, boundary line number, boundary point number, and corresponding object type, enabling subsequent vectorized R-tree spatial joins to directly read candidate parcels, candidate boundary lines, and candidate boundary points from the leaf nodes.

[0060] S3.4. Extract the real estate unit number, parcel code, ownership identifier, ownership source document number, and measurement version number from the cadastral spatial object sequence to generate an ownership attribute key sequence. Sort the ownership attribute key sequence in ascending order according to the real estate unit number, parcel code, ownership source document number, and measurement version number. Assign the sorted ownership attribute key sequence to the leaf nodes of the B-tree attribute, and record the ownership identifier position and registration status in the leaf nodes of the B-tree attribute. Extract the first ownership attribute key in each leaf node of the B-tree attribute as the upper-level index key, and arrange the internal nodes of the B-tree attribute according to the order of the upper-level index keys to generate a B-tree ownership attribute index.

[0061] Among them, the internal nodes of the B-tree attribute are used to point to the range of the ownership attribute key, the leaf nodes of the B-tree attribute are used to point to the specific ownership identifier record, and the B-tree ownership attribute index is used to locate the ownership identifier, the ownership source file number, and the registration status.

[0062] like Figure 3 As shown in the B-tree ownership attribute index on the right, the B-tree ownership attribute index includes an internal node layer and a leaf node layer. The internal node layer stores ordered key ranges such as K1 to Km and Kp to Kr. The leaf node layer is connected in key order to form a chain of leaf nodes P1 to Pn. Each leaf node records the real estate unit number, parcel code, ownership source document number, measurement version number, registration status, and ownership identifier location. When performing an ownership query, the corresponding leaf node is located through the internal node key range, and then the ownership identifier record that matches the parcel code and real estate unit number is read from the leaf node, thereby realizing the key sequence correspondence between spatial objects and ownership attribute records.

[0063] S3.5. The Hilbert global directory, R-tree local spatial index, and B-tree ownership attribute index are aligned according to cadastral sub-area codes, continuous coding intervals, and parcel codes. Specifically, the global directory key in the Hilbert global directory is used as the entry point for locating sub-area coded data segments; the parcel code, boundary line number, and boundary point number in the R-tree local spatial index are used as the entry point for locating standard cadastral geometric objects; and the real estate unit number, parcel code, ownership source document number, and measurement version number in the B-tree ownership attribute index are used as the entry point for locating ownership identifiers. When the same parcel code exists simultaneously in the Hilbert global directory, R-tree local spatial index, and B-tree ownership attribute index, the corresponding global directory key, R-tree spatial leaf node number, B-tree attribute leaf node position, and measurement version number are arranged into a common-source index record to generate an ownership spatial construction index table.

[0064] like Figure 3 As shown in the ownership spatial construction index table below, same-source index records are merged in the form of "global directory key—R-star tree spatial leaf node number—B-plus-tree attribute leaf node position—parcel code—measurement version number". For example, the global directory key SUB001-00001, R-star tree spatial leaf node number L1, B-plus-tree attribute leaf node position P1, parcel code TD200123, and measurement version number V2024.01 can constitute a merged record. This merged record simultaneously points to the sub-area coded data segment, spatial geometric leaf node, and ownership attribute leaf node, enabling subsequent steps to complete spatial positioning, geometric connection, and ownership matching based on the same parcel code, avoiding inconsistencies in the sources of the global directory, spatial index, and attribute index.

[0065] S4. Use the ownership space to construct an index table to locate the land parcel, boundary line, boundary point and ownership identifier, and perform vectorized R-tree spatial connection and ownership attribute matching to generate segmented ownership space results.

[0066] S4.1. Determine the target sub-area coded data segment according to the cadastral sub-area code, continuous coding interval and data segment number in the ownership spatial construction index table, and obtain the R-star tree local spatial index and B-tree ownership attribute index corresponding to the target sub-area coded data segment; locate the minimum bounding rectangle of the standard cadastral geometric object from the R-star tree spatial leaf node set in the R-star tree local spatial index, and arrange the minimum bounding rectangles corresponding to the parcel land, boundary line and boundary point together with the parcel code, boundary line number and boundary point number to generate a candidate spatial object rectangle set.

[0067] The candidate spatial object rectangle set is split into a column of land parcel rectangles, a column of boundary line rectangles, and a column of boundary point coordinates according to the object type. The minimum x-coordinate, maximum x-coordinate, minimum y-coordinate, and maximum y-coordinate of each minimum bounding rectangle are arranged into a contiguous memory array in the order of the same object. The contiguous memory array retains the corresponding positions of the land parcel code, boundary line number, and boundary point number in the candidate spatial object rectangle set, and generates a vectorized spatial connection array.

[0068] S4.2. Spatial connectivity relationships between land parcels and boundary lines, boundary lines and boundary points, and adjacent land parcels are determined in batches using a vectorized spatial connectivity array. The batch determination uses the planar analytic geometry midline aligned rectangle intersection criterion as the minimum bounding rectangle candidate selection criterion, the expression of which is: ; ; in, This represents the first smallest bounding rectangle in the set of candidate spatial object rectangles. This represents the second smallest bounding rectangle in the set of candidate spatial object rectangles. This represents the minimum x-coordinate of the first minimum bounding rectangle. This represents the maximum x-coordinate of the first minimum bounding rectangle. Let represent the minimum y-coordinate of the first minimum bounding rectangle. This represents the maximum ordinate of the first minimum bounding rectangle. This represents the minimum x-coordinate of the second smallest bounding rectangle. This represents the maximum x-coordinate of the second smallest bounding rectangle. Let represent the minimum y-coordinate of the second smallest bounding rectangle. This represents the maximum ordinate of the second smallest bounding rectangle.

[0069] When the x-coordinate interval and y-coordinate interval intersect, the two smallest bounding rectangles have candidate spatial connection relationships, generating a set of candidate spatial connection relationships.

[0070] S4.3. A candidate spatial connection set is used to perform geometrically accurate verification of standard cadastral geometric objects. For candidate spatial connection relationships between parcels and boundary lines, the boundary line coordinates are compared with the parcel boundary coordinates point by point. When all coordinate points of the boundary line fall on the parcel boundary and the boundary line number exists in the spatial reference chain of the corresponding parcel code, the parcel code and boundary line number are determined as valid parcel reference boundary line relationships. When the boundary line coordinates do not fall on the parcel boundary, the candidate spatial connection relationship is marked as having an abnormal boundary position and is excluded from valid parcel reference boundary line relationships. When the boundary line number does not exist in the spatial reference chain of the corresponding parcel code, the candidate spatial connection relationship is marked as having an abnormal boundary line number and is excluded from valid parcel reference boundary line relationships.

[0071] For candidate spatial connection relationships between boundary lines and boundary points, the boundary point number is compared with the starting and ending boundary point numbers of the boundary line, and the boundary point coordinates are compared with the starting and ending coordinates of the boundary line, respectively. When the boundary point number equals the starting boundary point number and the boundary point coordinates are consistent with the starting coordinates of the boundary line, the boundary point number is determined as the starting boundary point reference relationship. When the boundary point number equals the ending boundary point number and the boundary point coordinates are consistent with the ending coordinates of the boundary line, the boundary point number is determined as the ending boundary point reference relationship. When the boundary point number is neither equal to the starting nor ending boundary point number, the candidate spatial connection relationship is marked as having an abnormal boundary point number and is excluded from the valid boundary line-to-boundary point relationship. When the boundary point numbers are consistent but the boundary point coordinates are inconsistent with the corresponding boundary line endpoint coordinates, the candidate spatial connection relationship is marked as having an abnormal boundary point coordinate and is excluded from the valid boundary line-to-boundary point relationship.

[0072] For candidate spatial connection relationships between adjacent parcels, the boundary line numbers and boundary point numbers corresponding to the two adjacent parcels are extracted respectively. When two adjacent parcels share the same boundary line number, and the starting and ending boundary point numbers of the same boundary line number are in reverse order in the two adjacent parcels, the same boundary line number is determined as a shared boundary line relationship between adjacent parcels. When two adjacent parcels do not share the same boundary line number, the candidate spatial connection relationship is marked as a non-shared boundary line relationship and excluded from the shared boundary line relationship between adjacent parcels. When two adjacent parcels share the same boundary line number but the boundary point numbers are not in reverse order, the candidate spatial connection relationship is marked as an abnormal shared boundary line direction and excluded from the shared boundary line relationship between adjacent parcels.

[0073] The valid parcel reference boundary line relationship, the valid boundary line connecting boundary point relationship, and the adjacent parcel shared boundary line relationship are used as the geometrically accurate verification results. The parcel code, real estate unit number, boundary line number and boundary point number are extracted from the geometrically accurate verification results to generate a segmented spatial reference relationship set.

[0074] S4.4. Trigger key-order traversal of the B-tree ownership attribute index through the segmented spatial reference relationship set. Specifically, locate the internal node of the B-tree attribute according to the land parcel code and real estate unit number in the segmented spatial reference relationship set, obtain the ownership identifier position along the leaf node of the B-tree attribute pointed to by the internal node of the B-tree attribute, obtain the real estate unit number, land parcel code, registration status, ownership source document number and measurement version number corresponding to the ownership identifier position, and generate the segmented ownership identifier set.

[0075] The segmented spatial reference set and the segmented ownership identifier set are matched according to the parcel code and real estate unit number. When the parcel code in the segmented spatial reference set is consistent with the parcel code in the segmented ownership identifier set, and the real estate unit number in the segmented spatial reference set is consistent with the real estate unit number in the segmented ownership identifier set, a parcel ownership candidate record is formed. In the parcel ownership candidate record, ownership identifiers with a registration status of "registered" and "not cancelled, not revoked, and not replaced by subsequent change registration" are retained, and ownership identifiers with a measurement version number consistent with the cadastral survey result version corresponding to the target sub-area code data segment are retained, thus generating the segmented ownership matching result.

[0076] The segmented ownership matching results, parcel blocks, shared boundary lines, and boundary point reference relationships are grouped into the same segmented record according to the parcel code. Among them, the parcel block is the parcel corresponding to the same parcel code within the target sub-area coded data segment, the shared boundary line is the boundary line that has been geometrically verified and confirmed to be jointly referenced by adjacent parcels, and the boundary point reference relationship is the connection relationship between the endpoints of the boundary line and the boundary point number that has been geometrically verified and confirmed. The same segmented record retains the parcel code, real estate unit number, ownership source document number, registration status, and measurement version number to generate segmented ownership spatial results.

[0077] like Figure 4 The segmented ownership space result on the left shows that the result stores the reference relationships between parcel blocks, boundary lines, and boundary points in adjacent data segments. For example, adjacent data segment A stores parcel blocks A-1, A-2, and A-3, and records the reference relationships between boundary lines L1 and boundary points P1 to P2, boundary line L2 and boundary points P2 to P3, and boundary line L3 and boundary points P4 to P5. Adjacent data segment B stores parcel blocks B-2 and B-3, and records the reference relationships between boundary lines L4, L5, and L6 and their corresponding boundary points. This segmented ownership space result serves as the direct input for subsequent construction of the subgraph integrated R-tree topology, enabling cross-segment parcel reorganization to be performed based on verified spatial and ownership relationships.

[0078] S5. Construct the segmented ownership spatial results into a subgraph integrated R-tree topology graph, and perform cross-segment land parcel reorganization and ownership version sorting through tree tracking and ownership chain pruning to generate a cadastral ownership spatial information database.

[0079] S5.1. Extract parcel blocks, shared boundary lines, boundary point reference relationships, and segmented ownership matching results from the segmented ownership spatial results; the segmented ownership matching results include parcel code, real estate unit number, ownership source document number, registration status, and measurement version number; use the parcel code as the original parcel code, and arrange the original parcel code together with the parcel blocks, shared boundary lines, boundary point reference relationships, real estate unit number, and ownership source document number to generate a segmented topology object set.

[0080] The parcel blocks in the segmented topology object set are converted into parcel block nodes, shared boundary lines are converted into boundary line nodes, boundary points in boundary point reference relationships are converted into boundary point nodes, real estate unit numbers are converted into real estate unit number nodes, and ownership source document numbers are converted into ownership source document number nodes. The reference relationships between parcel block nodes and boundary line nodes, the connection relationships between boundary line nodes and boundary point nodes, the correspondence relationships between parcel block nodes and real estate unit number nodes, and the source relationships between parcel block nodes and ownership source document number nodes are converted into topology map edges, generating a cadastral ownership topology sub-map.

[0081] like Figure 4 As shown in the integrated R-tree topology diagram of the central subgraph, parcel block nodes can be represented as nodes such as A-1, A-2, A-3, B-1, B-2, and B-3; boundary line nodes can be represented as L1 to L6; boundary point nodes can be represented as P1 to P8; real estate unit number nodes can be represented as U1 to U6; and ownership source document number nodes can be represented as F_A_01, F_A_02, F_B_01, and F_B_02. When constructing the cadastral ownership topology subgraph, the same parcel block node is connected to the boundary point node through the corresponding boundary line node, and at the same time, it is connected to the real estate unit number node and the ownership source document number node through the corresponding ownership relationship. This forms a ownership topology path that exists in parallel: "parcel block - boundary line - boundary point" and "parcel block - real estate unit number - ownership source document number".

[0082] S5.2. Extract the R-star tree spatial leaf node set, R-star tree spatial non-leaf node set, and minimum bounding rectangle from the R-star tree local spatial index. Transform the R-star tree spatial leaf node set and R-star tree spatial non-leaf node set into spatial index nodes, and use the node number, minimum bounding rectangle, parcel code, boundary line number, and boundary point number as the node attributes of the spatial index nodes. According to the coverage relationship between the R-star tree spatial non-leaf node set and the R-star tree spatial leaf node set, transform the coverage path between spatial index nodes into spatial index edges to generate a spatial index subgraph.

[0083] Embed the spatial index submap into the cadastral ownership topology submap; when the parcel code in the spatial index node matches the original parcel code in the parcel block node, connect the spatial index node to the parcel block node; when the boundary line number in the spatial index node matches the boundary line number in the boundary line node, connect the spatial index node to the boundary line node; when the boundary point number in the spatial index node matches the boundary point number in the boundary point node, connect the spatial index node to the boundary point node; after the connection is completed, generate the index-embedded topology submap.

[0084] The spatial index path embedded in the index in the topology subgraph is combined with the cadastral topology path in the cadastral ownership topology subgraph. The path combination aligns the nodes according to the original parcel code, boundary line number, and boundary point number. The parcel block nodes, spatial index nodes, boundary line nodes, boundary point nodes, real estate unit number nodes, and ownership source document number nodes under the same original parcel code are connected into the same graph path to generate a subgraph integrated R-tree topology graph.

[0085] like Figure 4 As shown in the middle section, the spatial index path is formed by R1, R1-1, R1-2, and their subordinate spatial index nodes, while the cadastral topology path is formed by boundary point nodes, boundary line nodes, parcel block nodes, real estate unit number nodes, and ownership source document number nodes. During path synthesis, the boundary point index nodes corresponding to P1 to P8 in the R-tree spatial index path are connected to the boundary point nodes in the cadastral topology path, and the spatial index nodes corresponding to the parcel blocks are connected to parcel block nodes such as A-1, A-2, and B-1. Through this index embedding process, the subgraph integrates the R-tree topology map while retaining both the spatial retrieval path and the ownership topology path, supporting both rapid spatial location and tracing from parcel blocks to ownership source documents.

[0086] S5.3. Integrate the original parcel codes in the R-tree topology graph along the subgraph to start the tree tracing connection. Traverse the nodes in the order of parcel block nodes, boundary line nodes, boundary point nodes, real estate unit number nodes, and ownership source document number nodes. When there are topology graph edges between adjacent nodes, add the adjacent nodes to the same candidate path. When there are no topology graph edges between adjacent nodes, mark the node relationship corresponding to the missing topology graph edge as a connection failure relationship. After completing the node traversal under the same original parcel code, generate ownership chain candidate paths.

[0087] The integrity of the links between land parcel sub-nodes, boundary line nodes, boundary point nodes, real estate unit number nodes, and ownership source document number nodes is verified using the ownership chain candidate path. When the ownership chain candidate path simultaneously contains topological graph edges from land parcel sub-nodes to boundary line nodes, boundary line nodes to boundary point nodes, land parcel sub-nodes to real estate unit number nodes, and land parcel sub-nodes to ownership source document number nodes, the ownership chain candidate path is marked as a complete link path. When the ownership chain candidate path lacks any topological graph edge, the ownership chain candidate path is marked as a broken link path. The complete link paths and broken link paths are jointly arranged to generate the ownership chain verification path.

[0088] The parcel block nodes, boundary line nodes, boundary point nodes, real estate unit number nodes, ownership source document number nodes, and measurement version number corresponding to the same original parcel code in the ownership chain verification path are arranged into cross-segment reorganization objects; the cross-segment reorganization object represents the set of candidate nodes under the same original parcel code waiting to perform cross-data segment parcel block merging.

[0089] like Figure 4 As shown on the right, the tree tracing connection outputs three types of paths from the subgraph integrated R-tree topology graph: First, a complete ownership chain path, which can trace from the parcel block node through boundary line nodes and boundary point nodes to the real estate unit number node and the ownership source document number node; second, a broken chain path, which is identified as an abnormal path when boundary points, shared boundary lines, or ownership source document numbers are missing; and third, a cross-segment candidate reorganization path, which is used to determine whether parcel blocks in different adjacent data segments belong to the same original parcel code. For Figure 4 If A-2 and B-1, as illustrated in the diagram, have a shareable address line and a consistent ownership chain at the boundary of adjacent data segments, then A-2 and B-1 will be written into the same cross-segment reorganization object.

[0090] S5.4. When there is a broken chain path in the ownership chain verification path, remove the candidate node set corresponding to the broken chain path from the cross-segment reorganization object, generate a valid cross-segment reorganization object, and compile the original parcel code, missing node relationship and corresponding measurement version number in the broken chain path into a broken chain verification table, and take the complete link path as the complete ownership chain.

[0091] The original parcel codes in the valid cross-segment reorganization objects and complete ownership chains are used to merge cross-data segment parcel blocks; for multiple parcel blocks corresponding to the same original parcel code, the clipping boundaries formed by the segmentation are deleted, the real boundary lines and real boundary points in the standard cadastral geometric objects are retained, and the parcel blocks corresponding to adjacent parcels are connected by shared boundary line nodes to generate cross-segment parcel reorganization results.

[0092] The ownership records of the same parcel are collected according to the parcel code in the cross-parcel reorganization results, and arranged according to the ownership source document number, registration status and measurement version number. The arranged ownership records are then matched with the cross-parcel reorganization results to generate an ownership version chain.

[0093] The results of cross-segment land reorganization, ownership version chain, subgraph integrated R-tree topology, and chain break verification table are encapsulated into a cadastral ownership spatial information database.

[0094] like Figure 4As shown on the right and bottom, when A-2 and B-1 are confirmed to belong to the same cross-segment parcel, the temporary clipping boundary caused by data segmentation between them is deleted, and the real boundary lines and real boundary points are retained, forming the cross-segment parcel reorganization result A-2 / B-1. When a boundary point corresponding to a certain boundary line is found to be missing during the tree tracing connection process, for example, if the boundary point P3 of A-2 / B-1 corresponding to L2 is missing, the broken chain path is removed from the valid cross-segment reorganization objects, and the missing node relationship, the parcels involved, and the reason are written into the broken chain verification table. For parcels confirmed by the complete ownership chain, ownership version chains V1, V2, V3 to Vn are formed according to the measurement version number and registration status. Finally, the subgraph is integrated into the R-tree topology, the broken chain verification table, the ownership version chains, and the cross-segment parcel reorganization result and written into the cadastral ownership spatial information database, so that the cadastral ownership spatial information database not only preserves the spatial geometric reorganization result, but also preserves the ownership source, version evolution, and anomaly verification basis.

[0095] In summary, this invention, by unifying the arrangement of land parcels, boundary lines, boundary points, ownership identifiers, and measurement version numbers into a sequence of cadastral spatial objects, compared to the existing method of dispersing spatial geometric objects, ownership registration information, and version records, can establish a synchronous verification basis for spatial reference relationships and ownership correspondence at the data entry stage, reducing mismatches between subsequent land parcel codes, real estate unit numbers, and ownership source files. By employing Hilbert curve coding and sorting and generating a cadastral segmented directory according to cadastral sub-regions and continuous coding intervals, compared to existing fixed-area or simple administrative division segmentation methods, it can maintain the continuity of spatially adjacent land parcels in storage and retrieval order, reducing cross-segment jumps and discrete accesses during large-scale cadastral data retrieval. Furthermore, by grouping the Hilbert global directory, R-tree local spatial index, and B-tree ownership attribute index according to cadastral sub-region codes, continuous coding intervals, and land parcel codes, compared to the existing method of separately constructing spatial indexes and then connecting attribute tables, this approach achieves a more consistent and efficient result. This method enables land parcel spatial positioning, boundary relationship retrieval, and ownership attribute query to be completed around the same index record, improving the consistency between spatial retrieval results and ownership verification results. By using vectorized R-tree spatial connections to batch determine the connection relationships between land parcels, boundary lines, boundary points, and adjacent land parcels, and combining B-tree ownership attribute matching to generate segmented ownership spatial results, compared with existing object-by-object spatial overlay and manual field comparison, it can improve the efficiency of spatial relationship calculation and reduce misjudgments of shared boundary lines and boundary point reference relationships. Constructing a subgraph to integrate the R-tree topology graph, and completing cross-segment land parcel reorganization and ownership version sorting through tree tracking and connection ownership chain pruning, compared with existing methods of directly merging cross-segment land parcels or only merging historical records by field, it can identify broken chain paths and remove abnormal candidate results before entering the database, reducing the risk of cross-segment merging errors, duplicate boundary generation, and incorrect entry of invalid historical ownership records into the database, thereby improving the accuracy of cadastral ownership spatial information database construction, topological integrity, and ownership traceability.

[0096] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for constructing spatial information on land ownership based on cadastral survey data, characterized in that: include, Using cadastral elements and ownership identifiers from cadastral survey results, coordinate unification, geometric repair, reference relationship calibration, and ownership relationship calibration are performed to generate a sequence of cadastral spatial objects; The parcel spatial objects in the cadastral spatial object sequence are sorted by Hilbert curve encoding, and the data segments are divided according to cadastral sub-regions and continuous encoding intervals to generate a cadastral segment catalog. Hilbert global directory, R-star tree local spatial index and B-tree ownership attribute index are constructed by cadastral segmentation directory to generate ownership space construction index table; The ownership space is used to construct an index table to locate the land parcel, boundary line, boundary point and ownership identifier, and vectorized R-tree spatial connection and ownership attribute matching are performed to generate segmented ownership space results; The segmented ownership spatial results are constructed into a subgraph integrated R-tree topology graph. Cross-segment parcel reorganization and ownership version organization are then performed through tree tracing and ownership chain pruning, generating a cadastral ownership spatial information database. Specifically, this includes: Extract the parcel division, shared boundary lines, boundary point reference relationships, and segment ownership matching results from the segmented ownership spatial results to generate a segmented topology object set; The segmented topology object set is transformed into parcel block nodes, boundary line nodes, boundary point nodes, real estate unit number nodes, and ownership source document number nodes, and the reference relationship between nodes is transformed into topology graph edges to generate cadastral ownership topology sub-graph. Embed the spatial index nodes and minimum bounding rectangles in the R-star tree local spatial index into the cadastral ownership topology subgraph to generate an index-embedded topology subgraph. The spatial index path embedded in the index subgraph is combined with the cadastral topology path in the cadastral ownership topology subgraph to generate a subgraph integrated R-tree topology graph. The original parcel code in the subgraph integrated R-tree topology graph is used to start the tree tracing connection, and the parcel block nodes, boundary line nodes, boundary point nodes, real estate unit number nodes and ownership source file number nodes are traversed to generate ownership chain candidate paths. The integrity of the link between land parcel blocks, boundary lines, boundary points, real estate unit numbers and ownership source document numbers is verified using the ownership chain candidate path to generate ownership chain verification paths; When a broken chain occurs in the ownership chain verification path, the candidate result corresponding to the broken chain is removed from the cross-segment reorganization object, and a complete ownership chain and broken chain verification table are generated. The original parcel codes in the complete ownership chain are used to merge the parcel blocks across data segments, the clipping boundaries formed by the segments are deleted, and the topological relationships of the parcels across segments are arranged by combining standard cadastral geometric objects and shared boundary line nodes to generate the cross-segment parcel reorganization results. The ownership records of the same parcel are arranged according to the parcel code, ownership source document number, registration status and measurement version number in the cross-parcel reorganization results, and an ownership version chain is generated. The results of cross-segment land reorganization, ownership version chain, subgraph integrated R-tree topology, and chain break verification table are encapsulated into a cadastral ownership spatial information database.

2. The method for constructing spatial information on land ownership based on cadastral survey data as described in claim 1, characterized in that: The generation of the cadastral spatial object sequence specifically includes: Extract parcel land area, boundary lines, boundary points, parcel codes, and ownership identifiers from cadastral survey results to generate an initial cadastral object set; The initial cadastral object set is transformed to a unified coordinate system, and self-intersection, boundary breaks, and surface ring orientation anomalies of the parcels are repaired to generate a standard cadastral geometric object set. Based on the parcel code, boundary line number, and boundary point number in the standard cadastral geometric object set, spatial reference chains are arranged, and the corresponding relationship of real estate unit number, ownership source document number, and registration status in the ownership identifier is combined to generate a cadastral spatial object sequence.

3. The method for constructing spatial information on land ownership based on cadastral survey data as described in claim 2, characterized in that: The process of performing Hilbert curve encoding and sorting on parcel spatial objects in the cadastral spatial object sequence specifically includes: Extract parcel spatial objects from the cadastral spatial object sequence, calculate the center point of the bounding rectangle of the parcel spatial object and map it to the Hilbert curve coding space to generate parcel Hilbert coding sequence. The Hilbert code sequence of land parcels is rearranged according to the cadastral area code, cadastral sub-area code, parcel Hilbert code, and parcel code to generate a coded and sorted parcel sequence.

4. The method for constructing spatial information on land ownership based on cadastral survey data as described in claim 3, characterized in that: The division of data segments according to cadastral sub-regions and continuous coding intervals specifically includes: The land parcel sequence is divided and coded according to the cadastral sub-region code, and the continuous interval of Hilbert curve coding is identified along the divided land parcel sequence to generate sub-region coded data segments. The cadastral sub-region codes, continuous coding intervals, parcel codes, and measurement version numbers in the sub-region coding data segments are compiled into catalog records to generate a cadastral segment catalog.

5. The method for constructing spatial information on land ownership based on cadastral survey data as described in claim 4, characterized in that: The construction of the Hilbert global directory specifically includes: Extract cadastral sub-region codes, consecutive coding intervals, and data segment numbers from the cadastral segmentation directory to generate a global directory key; The global directory key is mapped to the storage location, parcel code range, and measurement version number of the sub-area coded data segment, and the retrieval boundary of the sub-area coded data segment is defined by the mapping relationship, generating the Hilbert global directory and global retrieval boundary set.

6. The method for constructing spatial information of land ownership based on cadastral survey data as described in claim 5, characterized in that: The construction of the R-star tree local spatial index specifically includes: The sub-region coded data segment is determined by globally retrieving the boundary set, and the minimum bounding rectangle of the standard cadastral geometric objects within the sub-region coded data segment is extracted to generate a set of bounding rectangles for local spatial objects. The smallest bounding rectangle in the set of bounding rectangles of local spatial objects is combined with the parcel code, boundary line number and boundary point number to form the R-star tree spatial leaf entry, and then merged into the R-star tree spatial leaf node set according to spatial overlap relationship and coverage range. An R-star tree spatial non-leaf node set is formed along the spatial coverage of the R-star tree spatial leaf node set. The node number, minimum bounding rectangle, and corresponding parcel code, boundary line number, and boundary point number are marked by the R-star tree spatial leaf node set and the R-star tree spatial non-leaf node set to generate the R-star tree local spatial index.

7. The method for constructing spatial information on land ownership based on cadastral survey data as described in claim 6, characterized in that: The process of generating the ownership space and constructing the index table specifically includes: Extract the real estate unit number, parcel code, ownership identifier, ownership source document number, and measurement version number from the cadastral spatial object sequence to generate an ownership attribute key sequence; Arrange the internal nodes of the B-tree attribute according to the ownership attribute key sequence, and record the ownership identifier position in the leaf node of the B-tree attribute to generate the B-tree ownership attribute index. The Hilbert global directory, R-star tree local spatial index, and B-tree ownership attribute index are aligned according to cadastral sub-region codes, continuous coding intervals, and parcel codes to generate an ownership spatial construction index table.

8. The method for constructing spatial information on land ownership based on cadastral survey data as described in claim 7, characterized in that: The generation of segmented ownership space results specifically includes: The index table is constructed using the ownership space to determine the target sub-region coded data segment, and the minimum bounding rectangle of the standard cadastral geometric object is extracted from the R-star tree local spatial index to generate a set of candidate spatial object rectangles. Arrange the candidate spatial object rectangle set into a contiguous memory array, and batch determine the spatial connection relationship between the land parcel and the boundary line, the boundary line and the boundary point, and the adjacent land parcels to generate a candidate spatial connection relationship set; The candidate spatial connection relationship set is used to perform geometric precision verification on the standard cadastral geometric objects, and the parcel code, real estate unit number, boundary line number and boundary point number are extracted from the verification results to generate a segmented spatial reference relationship set; By triggering the key-order traversal of the B-tree ownership attribute index through the segmented spatial reference relationship set, a segmented ownership identifier set is generated, and ownership attribute matching is completed according to the parcel code, real estate unit number, registration status and measurement version number to generate segmented ownership matching results. The segmented ownership matching results, parcel division, shared boundary lines, and boundary point references are grouped into the same segmented record according to the parcel code to generate segmented ownership spatial results.

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