A data automatic auditing and analyzing system for real estate surveying and mapping

Abstract

This invention relates to the field of data analysis technology, specifically to an automated data review and analysis system for real estate surveying. In this invention, a multi-dimensional information parsing module receives and parses real estate surveying data, extracting spatial geometric elements and ownership logical attribute elements; a feature fusion base module constructs a boundary relationship aggregation map based on this; a spatial geometric traction module extracts deformation tension attenuation field features and then applies spatial geometric traction processing based on non-rigid displacement features; a rights impedance inference module retrieves node linkage data, performs dynamic rights impedance inference calculations based on common elements, and outputs the redistribution results of the area recalculation ledger; finally, a ownership boundary steady-state reshaping module confirms the final boundary coordinate set and performs a reverse physical force field freezing operation, generating automated data review and analysis results. This process effectively integrates microscopic deformation and impedance inference, achieving a reasonable redistribution of adjacent border areas and steady-state reshaping of ownership boundaries.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, specifically to an automated data review and analysis system for real estate surveying. Background Technology

[0002] With the continuous advancement of urbanization and the in-depth implementation of the unified real estate registration system, the multidimensionality and complexity of real estate surveying and mapping data are showing a rapid growth trend. In the routine review, analysis, and evaluation of real estate surveying and mapping data, it is usually necessary to comprehensively consider the spatial geometric morphological characteristics of surface attachments and their underlying ownership logic.

[0003] However, existing data processing workflows primarily focus on static geometric topological checks of the base map structure and basic form attribute verification, making it difficult to deeply analyze the dynamic correlation and coupling relationship between spatial boundary changes and the properties of multiple rights. In actual surveying scenarios, the boundary ranges of adjacent plots often exhibit irreconcilable topological overlaps, minor gaps, or logical contradictions due to various objective factors such as differences in spatial surveying benchmarks, historical errors, or actual displacement of land features, thereby triggering potential ownership boundary conflicts.

[0004] When faced with disputes involving related rights caused by spatial deformation, the existing review mechanism lacks a dynamic reasoning and calculation method that can integrate macroscopic physical spatial deformation with abstract rights loss and resistance. This makes it difficult to balance the rigor of the geometric topology system and the rationality of the rights allocation in adjacent areas during boundary line correction and area reassessment, thus limiting the scientificity and objectivity of the review and analysis results of real estate surveying data. Summary of the Invention

[0005] The purpose of this invention is to provide an automated data review and analysis system for real estate surveying and mapping to solve the problems mentioned in the background art. Specific technical problems include how to construct a boundary relationship aggregation map based on extracted spatial geometric elements and ownership logical attribute elements, and how to perform non-rigid displacement traction and dynamic rights and interests impedance inference calculations by combining the deformation tension attenuation field characteristics of spatial geometric features. This solves the technical problem that, in the existing real estate surveying and mapping data review and analysis process, the lack of a dynamic fusion inference mechanism for spatial deformation and rights and interests impedance makes it difficult to achieve steady-state reshaping of ownership boundaries and reasonable redistribution of area under complex adjacent conditions.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an automated data review and analysis system for real estate surveying, comprising a multi-dimensional information parsing module, a feature fusion base module, a spatial geometry traction module, a rights resistance reasoning module, and a ownership boundary steady-state reshaping module, wherein: The multidimensional information parsing module receives and parses real estate surveying and mapping data, extracts spatial geometric elements representing the outlines of land features, and extracts the corresponding ownership logical attribute elements; specifically including: The system receives and parses real estate surveying and mapping data through a preset data interaction interface. It then uses a spatial vectorization extraction algorithm to separate the boundary coordinate set containing point, line, and surface topological relationships from the real estate surveying and mapping data. Finally, it performs closed aggregation processing on the boundary coordinate set to extract the spatial geometric elements that characterize the outline of the land features. Based on the storage link index of the boundary coordinate set within the real estate surveying and mapping data, the corresponding semantic attribute registration table is located and read. Using a semantic recognition model, the ownership status and right nature classification labels of the owner are extracted from the semantic attribute registration table. The extracted ownership status and right nature classification labels are then extracted as ownership logical attribute elements corresponding to spatial geometric elements.

[0007] The multidimensional information analysis module receives and analyzes real estate surveying and mapping data, and comprehensively extracts spatial geometric elements that characterize the outline of land features and corresponding ownership logical attribute elements. This provides key basic data support for the system's underlying map construction and deformation reasoning, and initially establishes a bridge between the macro-physical spatial architecture and the underlying ownership semantic classification, thus consolidating the data foundation for solving data verification and ownership division problems under complex adjacent conditions.

[0008] The feature fusion base module constructs a boundary relationship aggregation map based on spatial geometric elements and ownership logical attribute elements, specifically including: The extracted spatial geometric elements are instantiated as geometric feature nodes in the graph topology network, and the extracted ownership logical attribute elements are encoded as attribute feature vectors and deeply embedded into their corresponding geometric feature nodes to form a fusion node state. The spatial adjacency state between nodes with different geometric features is calculated to generate associated constraint edges that characterize the boundary adjacency restrictions of adjacent locations. A graph neural information transmission node update rule is introduced into the network graph structure composed of geometric feature nodes and associated constraint edges. By setting the graph neural information transmission node update rule, the spatial features and attribute features of geometric feature nodes and their neighboring adjacent nodes are forced to be synchronously aggregated to construct a boundary relationship aggregation graph.

[0009] The feature fusion base module introduces the graph neural network information transmission node update rule, which initially realizes the core concept of how to construct a boundary relationship aggregation graph based on the extracted spatial geometric elements and ownership logical attribute elements. It performs deep mapping and forced synchronous aggregation of geometric feature nodes and attribute feature vectors to generate a spatial network topology architecture that can represent the confluence restriction of adjacent boundaries. This provides a structured data carrier base for subsequent high-order fusion operations of spatial deformation and rights resistance.

[0010] The deformation tension attenuation field feature extraction unit in the spatial geometry traction module extracts the deformation tension attenuation field features of corresponding spatial geometric elements based on the boundary relationship aggregation map, specifically including: Read the spatial gradient difference mapping matrix of each node in the boundary relationship aggregation map, call the preset elastic tension distribution kernel function to perform spatial domain calculus differentiation on the spatial gradient difference mapping matrix, and use this as the force boundary condition to extract the deformation tension attenuation field characteristics of the corresponding spatial geometric elements.

[0011] The deformation tension attenuation field feature extraction unit accurately obtains the deformation tension attenuation field features of corresponding spatial geometric elements by calling the preset elastic mechanical tension distribution kernel function and performing calculus differentiation in the spatial domain. This provides quantitative boundary force condition constraints for subsequent characterization of the non-rigid force evolution trend of ground feature boundaries. It is a key preliminary physical parameter extraction step for supporting the system to calculate the real displacement deformation state under adjacent boundary compression or stretching scenarios.

[0012] The traction processing unit in the spatial geometry traction module applies non-rigid body displacement characteristics to spatial geometric elements using deformation tension attenuation field features, specifically including: The calculated deformation tension attenuation field characteristics are analytically transformed into a continuously distributed local deformation displacement vector field. By activating the finite element mesh rearrangement algorithm, the local deformation displacement vector field is controlled to drive all boundary nodes of the spatial geometric elements to undergo elastic coordinate transformations that deviate from the initial fixed relative distance constraints. This completes the spatial geometric traction processing that applies non-rigid displacement characteristics to the spatial geometric elements using the deformation tension attenuation field characteristics.

[0013] The traction processing unit performs non-rigid displacement traction processing by combining the deformation tension attenuation field characteristics of spatial geometric features. This drives the relevant spatial geometric elements to undergo elastic coordinate transformations that deviate from the initial fixed relative distance constraints. This effectively simulates the dynamic deformation behavior caused by boundary cross-changes, providing a deduction environment for the system to capture the topological boundary displacement trajectory sequence. It fills the gap in conventional static accounting methods that cannot measure the associated effects of spatial dynamic deformation.

[0014] The rights and interests impedance inference module retrieves node linkage data triggered by spatial geometric traction processing, specifically including: The topological boundary displacement trajectory sequence recorded in the node linkage data is extracted and formatted and input into the boundary relationship aggregation map. The pre-configured ownership relationship conflict penalty function is used, and the coefficient of the ownership relationship conflict penalty function is combined to calculate the available area loss reaction force caused by the boundary displacement contraction and expansion of adjacent land features. The available area loss reaction force is then converted into a resistance mapping scalar.

[0015] The equity resistance inference module performs dynamic equity resistance inference calculations based on common elements according to the boundary relationship aggregation map, and outputs the redistribution results of the area recalculation ledger, specifically including: Based on the boundary relationship aggregation map, dynamic interest resistance reasoning calculation based on the same source elements is performed. Through multiple rounds of iterative optimization, the equilibrium and coordination state condition in which adjacent border parts in the whole system achieve equal global resistance force is obtained. The updated boundary coordinate set corresponding to the equilibrium and coordination state is captured and the closed plot polygon integral area calculation is performed. Finally, the redistribution result of the area recalculation ledger is output based on the updated parcel area value obtained from the integral area calculation.

[0016] The equity impedance reasoning module performs dynamic equity impedance reasoning calculations based on the boundary relationship aggregation map and common elements. It transforms the available area loss reaction force into a resistance mapping scalar, and finds the global equilibrium coordination state through multiple rounds of iteration optimization. It outputs the redistribution results of the area recalculation ledger, effectively making up for the lack of a dynamic fusion reasoning mechanism for spatial deformation and equity impedance. It provides a scientific impedance evolution and area back calculation mechanism for solving the technical problem of difficult to achieve reasonable redistribution of area under complex adjacent conditions.

[0017] The ownership boundary steady-state reshaping module uses the redistribution results to confirm the final boundary coordinate set, and performs a reverse physical force field freezing operation on the deformation tension attenuation field characteristics based on the final boundary coordinate set, generating automated data review and analysis results of the corresponding real estate surveying and mapping data, specifically including: Read the updated boundary coordinate set that is in a state of force balance and coordination from the redistribution results, input the updated boundary coordinate set into the preset topology constraint verification container to perform gap closure and overlap elimination calculations to confirm the final boundary coordinate set; Calculate the normal compensating drag and tangential damping parameters required to maintain the current spatial geometry at the final boundary coordinate set, construct and apply reaction constraint tensors of opposite direction and equal magnitude to the node network until the mesh deformation evolution trend returns to a completely static state; Based on the final boundary coordinate set, a reverse physical force field freezing operation is performed on the deformation tension attenuation field characteristics. The area recalculation ledger that presents a unique static property rights analysis matching attribute in the force field freezing stagnation environment, as well as the vector closed parcel full-view features without any topological penetration conflicts, are captured, packaged together with automatically added verification compliance marks, converted and exported, generating the corresponding real estate surveying and mapping data collection data automated review and analysis results.

[0018] The ownership boundary steady-state reshaping module, based on topological constraint verification and compensation injection of reaction constraint tensors, confirms the final boundary coordinate set and performs a reverse physical force field freezing operation on the deformation tension attenuation field characteristics, bringing the grid deformation evolution trend to a standstill and ultimately generating rigorous automated data review and analysis results. This module integrates the aforementioned dynamic reasoning results, fundamentally overcoming the technical obstacles that make it difficult to achieve ownership boundary steady-state reshaping under complex adjacent conditions in the existing real estate surveying and mapping data review and analysis process, and improving the coordination and anti-penetration topological compliance of the accounting ledger output.

[0019] Compared with the prior art, the beneficial effects of the present invention are: This invention proposes an automated data review and analysis system for real estate surveying. A multi-dimensional information parsing module receives and parses real estate surveying data, extracting spatial geometric elements and ownership logical attribute elements. A feature fusion base module then constructs a boundary relationship aggregation map based on these two types of elements. On this basis, a spatial geometric traction module, combined with the extracted deformation tension attenuation field characteristics, applies spatial geometric traction processing with non-rigid displacement characteristics to the spatial geometric elements. Finally, a rights and interests impedance inference module retrieves node linkage data and performs dynamic rights and interests impedance inference calculations based on elements from the same source, outputting an area recalculation ledger. The redistribution results are ultimately confirmed by the ownership boundary steady-state reshaping module, which then performs a reverse physical force field freezing operation on the deformation tension attenuation field characteristics to generate automated data review and analysis results. This system effectively compensates for the shortcomings of the existing real estate surveying and mapping data review and analysis process caused by the lack of a dynamic fusion reasoning mechanism for spatial deformation and rights resistance. Under complex adjacent conditions, it can fuse and deduce the evolution of physical stress deformation and the reaction force of available area loss, thereby scientifically and effectively realizing the steady-state reshaping of ownership boundaries and reasonable redistribution of area, and improving the objectivity and topological compliance of surveying and mapping review and analysis results. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the overall modules of the present invention; Figure 2 This is a schematic diagram of the spatial geometry traction module unit of the present invention; Figure 3 This is a schematic diagram illustrating the core process of the application of the boundary relationship aggregation map of the present invention; Figure 4 This is the impedance calculation convergence diagram of the present invention.

[0021] In the diagram: 100, Multidimensional Information Analysis Module; 200, Feature Fusion Base Module; 300, Spatial Geometric Traction Module; 301, Deformation Tension Attenuation Field Feature Extraction Unit; 302, Traction Processing Unit; 400, Rights Impedance Inference Module; 500, Ownership Boundary Steady-State Reshaping Module. Detailed Implementation

[0022] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Next, please refer to Figure 1 The present invention provides a technical solution: an automated data review and analysis system for real estate surveying, including a multi-dimensional information parsing module 100, a feature fusion base module 200, a spatial geometry traction module 300, a rights resistance reasoning module 400, and a ownership boundary steady-state reshaping module 500.

[0024] The multi-dimensional information parsing module 100 receives and parses real estate surveying and mapping data. First, it performs temporal and spatial benchmark alignment of the multi-source data, extracts spatial geometric elements representing the contours of land features, and extracts the corresponding ownership logical attribute elements, specifically including: The system receives and parses real estate surveying and mapping data with timestamp alignment (ensuring consistent measurement times) through a pre-defined data interaction interface. It then uses a spatial vectorization extraction algorithm to separate boundary coordinate sets containing point, line, and surface topological relationships from the data. Finally, it performs closed aggregation processing on these boundary coordinate sets to extract spatial geometric elements representing the contours of land features. ,in A globally unique identifier representing a feature. This represents the index of the discrete coordinate points that constitute the feature. Indicates the first Total number of coordinate points for each feature Represents the discrete coordinate point variables that constitute the boundary coordinate set, and extracts... The technical objective is to transform an unordered set of boundary coordinates into a solid spatial outline with a definite topological closed shape. Simultaneously, based on the storage link index of the boundary coordinate set within the real estate surveying and mapping data, the corresponding semantic attribute registration table is located and read. A semantic recognition model is then used to extract ownership status and rights nature classification labels from the semantic attribute registration table. ,in This represents a string representing the semantic attribute registration table content located using a storage link index. Represents the feature extraction mapping function. This represents the logical attribute elements of ownership. The extracted ownership status and right nature classification labels are used as the logical attribute elements of ownership corresponding to spatial geometric elements for precise extraction. The technical purpose is to give spatial entities legitimate identity characteristics.

[0025] The execution flow of the spatial vectorization extraction algorithm in the multidimensional information parsing module 100 is as follows: First, the original pixel or discrete point coordinates in the real estate surveying and mapping data are scanned column by column and row by row to extract boundary feature points with abrupt changes in grayscale or abnormal elevation differences. Then, the relative distance and azimuth between each feature point are calculated, and the feature points with the closest distance and continuous azimuth are directly connected in sequence to form the initial discrete line segments. Finally, a fixed distance tolerance threshold is set (the range is usually set to 0.05 meters to 0.15 meters, determined according to the comprehensive system error calibration of the actual surveying instrument). The endpoints of all line segments are traversed. When the straight-line distance between the endpoints of two independent line segments is less than the set tolerance threshold, the arithmetic mean of the horizontal and vertical coordinates of the two endpoints is automatically calculated as the new common connection part. The separated endpoints are forcibly moved to the common connection part, thereby completely closing the disordered data and separating and extracting the boundary coordinate set that represents the outline of a clearly closed land feature.

[0026] The training process and execution flow of the semantic recognition model in the multidimensional information parsing module 100 are as follows: Collect the content strings of the historically approved semantic attribute registration form. As input samples, the ownership status and rights classification labels of historical archiving standards are used as ground truth labels. Supervised gradient descent training is performed using the cross-entropy loss function to construct a feature extraction mapping function. ; During inference execution analysis, the semantic attribute registration table content string located using the storage link index is received. Subsequently, the sequence is parsed to output a comprehensive numerical score matrix for each item, corresponding to the owner's ownership status and the nature of the rights. Finally, a multi-dimensional joint judgment is used instead of a single extreme value. The two highest-valued items in the comprehensive numerical score matrix are selected, and if their difference is greater than or equal to a set confidence interval threshold (range 0.2-0.4, set based on historical classification boundary ambiguity), the status and nature classification label represented by the highest-valued item is extracted and used as the logical attribute element of ownership. Perform precise extraction; if the difference is less than the set confidence interval threshold, output a system anomaly review flag to reject one-sided and extreme judgments.

[0027] The feature fusion base module 200 constructs a boundary relationship aggregation map based on spatial geometric elements and ownership logical attribute elements, specifically including: The extracted spatial geometric elements are instantiated as geometric feature nodes in the graph topology network, and the extracted ownership logical attribute elements are encoded as attribute feature vectors and deeply embedded into their corresponding geometric feature nodes to form fused node states. , build The technical objective is to achieve the underlying numerical binding between spatial contours and legitimate identity features; Subsequently, the spatial adjacency states between nodes with different geometric features are calculated to generate associated constraint edges that characterize the boundary adjacency restrictions between adjacent nodes. ,in Indicates the relationship with the first The neighboring feature numbers of each feature. Represents the topological intersection discriminant function, generating The technical objective is to construct a topological network foundation that represents neighborhood constraint relationships; based on this, a graph neural information transmission node update rule is introduced into the network graph structure composed of geometric feature nodes and associated constraint edges. ,in This represents the iterative depth level of graph neural information. Indicates the first The hidden layer vector of node features in the next iteration Indicates the spatial neighborhood adjacency node at the th Hidden layer vector in the next iteration Represents the set of spatially adjacent nodes. This represents the globally shared learnable weight matrix. This represents a nonlinear activation function. By setting a rule for updating graph neural information transmission nodes, it forces the synchronous aggregation of spatial features and attribute features of geometric feature nodes and their neighboring nodes. Based on spatial geometric elements and ownership logical attribute elements, it constructs a boundary relationship aggregation graph. The technical purpose of setting this update rule is to achieve deep coupling of elements and global information connectivity within the entire graph space.

[0028] Please see Figure 2-3 The deformation tension attenuation field feature extraction unit 301 in the spatial geometry traction module 300 extracts the deformation tension attenuation field features of the corresponding spatial geometric elements based on the boundary relationship aggregation map, specifically including: Read the spatial gradient difference mapping matrix of each node in the boundary relationship aggregation graph. The system invokes a preset elasticity tension distribution kernel function to perform spatial domain calculus differentiation on the spatial gradient difference mapping matrix, using this as the force boundary condition to accurately extract the deformation tension attenuation field characteristics of the corresponding spatial geometric elements. ,in This represents the calculated tension characteristic result. Indicates spatial correlation distance The elastic mechanical tension distribution kernel function is extracted. The technical objective is to quantitatively describe the distribution of internal stress caused by the compression and deformation of ground features under the constraints of their surroundings.

[0029] The traction processing unit 302 in the spatial geometry traction module 300 applies non-rigid displacement characteristics of spatial geometry elements to spatial geometry elements using deformation tension attenuation field characteristics, specifically including: The calculated deformation tension attenuation field characteristics are analytically transformed into a continuously distributed local deformation displacement vector field. ,in For the set of vector field distributions, This represents the analytical transformation operator for deformation, and the transformation... The technical objective is to determine the direction and magnitude of the spatial migration trend of each ground feature node after it is subjected to force. By activating the finite element mesh rearrangement algorithm, the local deformation displacement vector field is controlled to drive all boundary nodes of the spatial geometric elements to undergo elastic coordinate transformations that deviate from the initial fixed relative distance constraint. ,in The new coordinate system represents the result of the driving offset, and completes the spatial geometric traction process by applying non-rigid displacement characteristics to spatial geometric elements using the deformation tension attenuation field characteristics, to obtain... The technical objective is to obtain a temporary stable pre-arrangement state of geometric nodes that can absorb deformation pressure.

[0030] The execution flow of the finite element mesh rearrangement algorithm in the traction processing unit 302 is as follows: First, using the outline points and internal discrete points of the ground features as vertices, the original spatial geometric elements are divided into a network skeleton composed of multiple adjacent and non-overlapping triangles; then, the calculated local deformation displacement vector field is... The displacement directions and magnitudes of each parameter are directly superimposed onto the initial coordinate components of the corresponding boundary vertices of the mesh triangles. During the superposition process, the proportion of the change in the side length of the triangle after being subjected to force is calculated simultaneously. For internal mesh vertices with extremely compressed or stretched side lengths, the coordinates are adjusted in amortized manner according to the average offset of all neighboring nodes connected to that vertex. Finally, after item-by-item offsetting and amortized attenuation correction of all nodes in the global domain, a new coordinate system representing the effect of the driving offset is obtained. This completes the elastic coordinate transformation.

[0031] The rights and interests impedance inference module 400 retrieves node linkage data triggered by spatial geometric traction processing, performs dynamic rights and interests impedance inference calculations based on common elements according to the boundary relationship aggregation map, and outputs the redistribution results of the area recalculation ledger, specifically including: Retrieve node linkage data triggered by spatial geometric traction processing, and extract the topological boundary displacement trajectory sequence recorded in the node linkage data. The formatted input is entered into the boundary relationship aggregation map. Using the pre-configured ownership conflict penalty function and the coefficients of the ownership conflict penalty function, the available area loss reaction force caused by the contraction and expansion of adjacent land features due to boundary displacement is calculated. ,in Indicates the first Local serial numbers of the boundary coordinates of adjacent features This represents the sequence of topological boundary displacement trajectories corresponding to adjacent land features. This represents the analytical operator for calculating the loss of overlapping area. The coefficient of the ownership conflict penalty function (set in the interval [1.0, 3.0], dynamically adjusted according to the local land dispute tolerance policy) transforms the available area loss reaction force into a resistance mapping scalar. ,in Given the impedance scalarization transformation mapping function, calculate The technical objective is to quantify the abstract conflict of mutual encroachment on property rights into a physical resistance index that can be rigorously compared numerically. Then, based on the boundary relationship aggregation map, dynamic interest resistance reasoning calculation based on common elements is performed. Through multiple rounds of iterative optimization, the equilibrium coordination condition in which adjacent junctions across the entire system achieve equal global resistance forces is obtained. ,in Indicates the relationship between adjacent features and the first The technical purpose of calculating the scalar mapping of the reverse resistance generated by each feature and the equilibrium coordination state condition is to find the critical point of interest balance with the minimum loss in the global ownership area game. Subsequently, the updated boundary coordinate set corresponding to the equilibrium and coordinated state is captured, and the integral operation of the closed plot polygon is performed. ,in and Indicates extraction from The absolute components of the horizontal and vertical coordinates in a two-dimensional orthogonal coordinate system. and These represent the coordinates of the next-to-the-th boundary in the sequence of updated boundary coordinates that constitute the three-dimensional feature outline. The next neighboring node of the discrete coordinate point (i.e., the first) The two-dimensional plane horizontal and vertical coordinate components of each point are calculated; finally, the updated land parcel area value is obtained by integral calculation. Output the redistribution results of the area recalculation ledger, and calculate... The technical objective is to generate an accurate area recalculation ledger after adjustment for equity impedance correction.

[0032] Analysis operators in the equity impedance inference module 400 The operation process involves processing the displacement trajectory sequence of adjacent ground features across topological boundaries. and The intersection determination of the new geometric contour formed after the movement is performed, and the specific steps are as follows: Extract all constituent edges of two adjacent contours, find all intersection points by solving a system of two linear equations in two variables for each pair of line segments, and connect the intersection points to the vertices contained within each other's contours to form a polygonal contour block extracted from the overlapping areas of the two contours. Then, use the formula for the cumulative summation of polygonal trapezoidal surfaces in the coordinate plane to perform a basic algebraic product on the coordinate point set of this polygonal contour block to obtain the absolute overlapping area value. Finally, the ownership conflict penalty function uses the set ownership conflict penalty function coefficients. By directly multiplying and amplifying the overlapping area value, the purely geometric cross-sectional encroachment area is transformed into a usable area loss reaction force that characterizes the intensity of the struggle for rights. .

[0033] The ownership boundary steady-state reshaping module 500 uses the redistribution results to confirm the final boundary coordinate set, and performs a reverse physical force field freezing operation on the deformation tension attenuation field characteristics based on the final boundary coordinate set, generating the corresponding automated data review and analysis results of the real estate surveying and mapping data, specifically including: Read the updated boundary coordinate set that is in a state of force equilibrium and coordination from the redistribution results, and input the updated boundary coordinate set into a preset topology constraint verification container to perform gap closure and overlap removal calculations, i.e. ,in This represents the final boundary coordinate set after the computational constraints have been applied. This represents the morphological gap closure and overlap removal functions, which are used to determine the final boundary coordinate set using the redistribution results, and then extract... The technical objective is to generate the baseline of an absolutely seamless overlapping rights-establishing contour map. Subsequently, the normal compensating drag and tangential damping parameters required to maintain the current spatial geometry at the final boundary coordinate set are calculated, and reaction constraint tensors of opposite direction and equal magnitude are constructed and applied to the node network. ,in This represents the set of constraint tensors constructed to maintain the spatial layout. Indicates normal compensating resistance, Indicates the tangential damping parameter. and These are the resistance constant allocation coefficients for the corresponding directional compensation domains, used to neutralize the residual deformation potential energy throughout the entire network space until the mesh deformation evolution trend returns to a completely static state, thus constructing... The technical objective is to completely counteract the coordinate inertial shift caused by the internal calculations of the model by applying a negative virtual tensile force within the artificial system. Furthermore, based on the final boundary coordinate set, an inverse physical force field freezing operation is performed on the deformation tension attenuation field characteristics to ensure that the network is completely static. ,in The time step span value of the physical process of grid deformation evolution is used. The technical purpose of implementing this mathematical condition is to permanently solidify the optimal steady-state shape of the land parcel boundary achieved through iterative game allocation. Finally, the area recalculation ledger that presents a unique static property rights analysis matching attribute in the force field freezing and stagnation environment, as well as the vector closed parcel full-view feature without any topological penetration conflict, are captured, packaged together with automatically added verification compliance marks, converted and exported to generate the corresponding automated data review and analysis results of real estate surveying and mapping data.

[0034] Morphological gap closure and overlap removal functions in the steady-state reshaping module 500 of ownership boundaries The specific execution process is as follows: First, iterate through the boundary segments of any two adjacent polygons in the updated boundary coordinate set input to the validation container, and calculate their vertical relative shortest distances in turn. When the vertical shortest distance is greater than zero and less than the set micro-interval threshold, directly take the arithmetic mean of the coordinates of the two pairs of vertices corresponding to these two boundary segments, generate a new midline coordinate point sequence to replace the original boundary and fill the gaps. When it is detected that the boundary segments of adjacent polygons intersect and form an overlapping closed loop region, calculate the coordinate compromise midpoint sequence of all vertices in the overlapping region, establish a common boundary line that equally divides the region, and delete the original penetrating independent vertices that exceed the common boundary line. Through point-by-point position comparison and compromise coordinate replacement, eliminate all non-compliant topological states and output the final boundary coordinate set. . Please see Figure 4This diagram visually illustrates the entire convergence game process of the rights and interests resistance inference module 400 in dynamic calculation and its technical effects. By retrieving the linked data of the preceding nodes and combining it with the ownership conflict penalty function, the available area loss reaction force caused by the contraction and expansion of adjacent land features due to boundary displacement is calculated and accurately converted into the resistance mapping scalar in the diagram. Subsequently, dynamic rights and interests resistance inference calculation based on the same source elements is executed. Through multiple rounds of iterative optimization, the resistance scalars of both parties are made to converge. Finally, the equilibrium coordination state condition in which adjacent border parts in the whole system reach the global resistance force is equal is obtained. This physical fusion inference mechanism not only successfully quantifies the abstract ownership squeezing conflict into a strictly comparable physical indicator, but also directly captures the updated boundary coordinate set corresponding to the equilibrium coordination state, performs integral calculation and outputs the redistribution result of the area recalculation ledger. Thus, it scientifically and effectively resolves the spatial deformation and related rights and interests disputes under complex border conditions, and lays a rigorous data review and analysis foundation for the subsequent accurate execution of the ownership boundary steady-state reshaping operation.

[0035] As can be seen from the above description, the automated data review and analysis system for real estate surveying provided in this embodiment has the following technical effects: This embodiment uses a multi-dimensional information parsing module 100 to transform an unordered set of boundary coordinates into a spatial outline of entities with a clear topological closure, and assigns legitimate identity features to the spatial entities. A feature fusion base module 200 achieves underlying numerical binding between the spatial outline and legitimate identity features, constructing a topological network foundation representing neighborhood constraint relationships, realizing deep coupling of elements and global information connectivity across the entire map space. A spatial geometry traction module 300 quantifies the internal stress distribution caused by the deformation of ground features due to surrounding constraints, establishing the direction and magnitude of spatial migration trends, thereby obtaining a temporary stable pre-arrangement state of geometric nodes to absorb deformation pressure. An equity impedance inference module 40... The abstract conflict of property rights encroachment is quantified into a physical resistance index that can be rigorously compared numerically. The critical point of interest balance with minimal loss in the global ownership area game is found, and an accurate area recalculation ledger is generated after adjustment for rights resistance. Finally, the ownership boundary steady-state reshaping module 500 applies a reaction constraint tensor to neutralize the residual deformation potential energy in the entire network space, effectively offsetting the coordinate inertia offset caused by the internal calculation of the model, and steadily solidifying the steady-state shape of the land parcel boundary achieved through iterative game allocation. This avoids non-compliant topological states and generates the bottom line of seamless overlapping ownership contour patches, thereby efficiently outputting the automated review and analysis results of the corresponding real estate surveying and mapping data.

[0036] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. An automated data review and analysis system for real estate surveying, characterized in that, It includes a multi-dimensional information parsing module (100), a feature fusion base module (200), a spatial geometry traction module (300), an equity impedance reasoning module (400), and an ownership boundary steady-state reshaping module (500), wherein: The multidimensional information parsing module (100) receives and parses real estate surveying and mapping data, extracts spatial geometric elements that characterize the outline of land features, and extracts ownership logical attribute elements corresponding to the spatial geometric elements. The feature fusion base module (200) constructs a boundary relationship aggregation map based on the spatial geometric elements and the ownership logical attribute elements; The spatial geometry traction module (300) extracts the deformation tension attenuation field features corresponding to the spatial geometric elements based on the boundary relationship aggregation map, and applies the spatial geometry traction processing of non-rigid displacement features to the spatial geometric elements using the deformation tension attenuation field features. The equity impedance reasoning module (400) retrieves the node linkage data triggered by the spatial geometric traction processing, performs dynamic equity impedance reasoning calculation based on the same source elements based on the boundary relationship aggregation map, and outputs the redistribution result of the area recalculation ledger. The ownership boundary steady-state reshaping module (500) uses the redistribution result to confirm the final boundary coordinate set, and performs a reverse physical force field freezing operation on the deformation tension attenuation field characteristics based on the final boundary coordinate set, generating the data automated review and analysis result corresponding to the real estate surveying and mapping data.

2. The automated data review and analysis system for real estate surveying and mapping according to claim 1, characterized in that, The extraction process of the spatial geometric elements specifically includes: The system receives and parses real estate surveying and mapping data through a preset data interaction interface. It then uses a spatial vectorization extraction algorithm to separate the boundary coordinate set containing point, line, and surface topological relationships from the real estate surveying and mapping data. Finally, it performs closed aggregation processing on the boundary coordinate set to extract the spatial geometric elements that characterize the outline of the land features.

3. The automated data review and analysis system for real estate surveying and mapping according to claim 2, characterized in that, The extraction process of the ownership logical attribute elements specifically includes: Based on the storage link index of the boundary coordinate set within the real estate surveying and mapping data, the corresponding semantic attribute registration table is located and read. Using a semantic recognition model, the ownership status and right nature classification labels are extracted from the semantic attribute registration table. The extracted ownership status and right nature classification labels are then extracted as ownership logical attribute elements corresponding to spatial geometric elements.

4. The automated data review and analysis system for real estate surveying and mapping according to claim 1, characterized in that, The feature fusion base module (200) instantiates the extracted spatial geometric elements into geometric feature nodes in the graph topology network, and encodes the extracted ownership logical attribute elements into attribute feature vectors and deeply embeds them into their corresponding geometric feature nodes to form a fusion node state.

5. The automated data review and analysis system for real estate surveying and mapping according to claim 4, characterized in that, The construction process of the boundary relationship aggregation map specifically includes: The spatial adjacency state between nodes with different geometric features is calculated to generate associated constraint edges that characterize the boundary adjacency restrictions of adjacent locations. A graph neural information transmission node update rule is introduced into the network graph structure composed of geometric feature nodes and associated constraint edges. By setting the graph neural information transmission node update rule, the spatial features and attribute features of geometric feature nodes and their neighboring adjacent nodes are forced to be synchronously aggregated to construct a boundary relationship aggregation graph.

6. The automated data review and analysis system for real estate surveying and mapping according to claim 1, characterized in that, The spatial geometry traction module (300) includes a deformation tension attenuation field feature extraction unit (301). The deformation tension attenuation field feature extraction unit (301) reads the spatial gradient difference mapping matrix of each node in the boundary relationship aggregation map, calls the preset elastic mechanical tension distribution kernel function to perform spatial domain calculus differentiation operation on the spatial gradient difference mapping matrix, and uses this as the force boundary condition to extract the deformation tension attenuation field features of the corresponding spatial geometric elements.

7. The automated data review and analysis system for real estate surveying and mapping according to claim 6, characterized in that, The spatial geometry traction module (300) includes a traction processing unit (302), which analyzes the calculated deformation tension attenuation field characteristics into a continuously distributed local deformation displacement vector field; by activating the finite element mesh rearrangement algorithm, the local deformation displacement vector field drives all boundary nodes of the spatial geometric elements to undergo elastic coordinate transformations that deviate from the initial fixed relative distance constraint, thereby completing the spatial geometry traction processing that applies non-rigid displacement characteristics to the spatial geometric elements using the deformation tension attenuation field characteristics.

8. The automated data review and analysis system for real estate surveying and mapping according to claim 1, characterized in that, The right-of-ownership impedance reasoning module (400) extracts the topological boundary displacement trajectory sequence recorded in the node linkage data and formats it into the boundary relationship aggregation map. It uses the pre-configured ownership relationship conflict penalty function and combines the ownership relationship conflict penalty function coefficient to calculate the available area loss reaction force caused by the boundary displacement contraction and expansion of adjacent land features, and converts the available area loss reaction force into a resistance mapping scalar.

9. The automated data review and analysis system for real estate surveying and mapping according to claim 8, characterized in that, The calculation process for the redistribution result specifically includes: Based on the boundary relationship aggregation map, dynamic interest resistance reasoning calculation based on the same source elements is performed. Through multiple rounds of iterative optimization, the equilibrium and coordination state condition in which adjacent border parts in the whole system achieve equal global resistance force is obtained. The updated boundary coordinate set corresponding to the equilibrium and coordination state is captured and the closed plot polygon integral area calculation is performed. Finally, the redistribution result of the area recalculation ledger is output based on the updated parcel area value obtained from the integral area calculation.

10. The automated data review and analysis system for real estate surveying and mapping according to claim 1, characterized in that, The process of generating the automated data review and analysis results specifically includes: Read the updated boundary coordinate set that is in a state of force balance and coordination from the redistribution results, input the updated boundary coordinate set into the preset topology constraint verification container to perform gap closure and overlap elimination calculations to confirm the final boundary coordinate set; Calculate the normal compensating drag and tangential damping parameters required to maintain the current spatial geometry at the final boundary coordinate set, construct and apply reaction constraint tensors of opposite direction and equal magnitude to the node network until the mesh deformation evolution trend returns to a completely static state; Based on the final boundary coordinate set, a reverse physical force field freezing operation is performed on the deformation tension attenuation field characteristics. The area recalculation ledger that presents a unique static property rights analysis matching attribute in the force field freezing stagnation environment, as well as the vector closed parcel full-view features without any topological penetration conflicts, are captured, packaged together with automatically added verification compliance marks, converted and exported, generating the corresponding real estate surveying and mapping data collection data automated review and analysis results.

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