Gis-based multi-source surveying and mapping data fusion processing information system

Abstract

The application discloses a GIS-based multi-source surveying and mapping data fusion processing information system, and belongs to the field of fusion processing information systems, and comprises a desktop processing subsystem, a mobile terminal acquisition subsystem and a server for realizing data synchronization of the two; the desktop processing subsystem is used for newly establishing and managing surveying and mapping projects, and comprises setting a project geographic area, assigning tasks and permissions; the application introduces an intelligent registration error correction model, the system can automatically detect and correct local residual errors after multi-source data fusion, the fusion accuracy is improved from the traditional manual adjustment of the decimeter level to the centimeter or even the millimeter level, and a solid foundation is laid for realizing a high-precision spatial digital baseplate; a data quality evaluation and import optimization module serves as a front gate, ensures the quality of input data, reduces the interference of poor data on subsequent intelligent registration, and guarantees data consistency from the source to the final fusion process, so that the problems of insufficient data fusion accuracy and intelligent degree are effectively solved.

Description

Technical Field

[0001] This invention belongs to the field of fusion processing information systems, specifically, it relates to a GIS-based multi-source surveying and mapping data fusion processing information system. Background Technology

[0002] With the deepening of smart city construction, urban planning, construction, and management units (such as urban construction groups) are facing increasingly complex geospatial data processing needs. Traditional surveying and geographic information system (GIS) working models typically have the following limitations: First, the fusion processing of multi-source heterogeneous data (such as CAD drawings, point clouds, oblique photogrammetry models, and BIM) heavily relies on manual experience, resulting in low coordinate matching accuracy and efficiency. Furthermore, the lack of automated methods for correcting residuals after fusion leads to severe "data silos," making it difficult to form a consistent, high-precision spatial base. Second, there is a disconnect between field data collection and office processing. After the layout points designed on the desktop are sent to mobile devices, on-site operations lack intelligent navigation and path planning, resulting in low efficiency. Moreover, errors discovered on-site cannot be systematically fed back and corrected in the original design, leading to error accumulation. Finally, existing systems are weak in multi-person collaboration, data quality process control, and adaptability to complex field environments, making it difficult to support large-scale, high-concurrency collaborative surveying project management.

[0003] Based on the above background, existing technologies mainly suffer from problems at the following three levels: 1. Insufficient accuracy and intelligence in data fusion: The problem of local spatial inconsistency after multi-source data fusion is prominent, and there is a lack of automated intelligent registration and error correction mechanisms, which affects the analysis accuracy of all subsequent applications.

[0004] 2. Disruption of the closed-loop collaboration between internal and external operations: The workflow from design to layout and then to correction has not formed an intelligent closed loop, and on-site information cannot be effectively used for design optimization, resulting in efficiency bottlenecks and the risk of error propagation.

[0005] 3. Weak system collaboration and adaptability: Conflicts are prone to occur when multiple people are collaborating on editing, the quality of imported data is inconsistent, and the mobile terminal cannot adaptively adjust the collection strategy according to the complex and ever-changing on-site environment, which affects the overall work quality and reliability.

[0006] To address this, a GIS-based multi-source surveying and mapping data fusion and processing information system is proposed. Summary of the Invention

[0007] To address the aforementioned problems and technical deficiencies, this invention adopts the following technical solution: a GIS-based multi-source surveying and mapping data fusion processing information system, comprising: a desktop processing subsystem, a mobile acquisition subsystem, and a server for synchronizing data between the two; the desktop processing subsystem is used for: Create and manage surveying projects, including setting up project geographic areas, assigning tasks and permissions; Import and integrate multi-source heterogeneous geospatial data, which includes at least CAD data, point cloud LAS data, oblique photogrammetry OSGB data, and BIM model data; The imported multi-source heterogeneous geospatial data is subjected to coordinate matching and unification, including coordinate system import, projection transformation, coordinate inversion and data registration; Perform map surveying and data plotting, and generate stakeout coordinate data; The layout coordinate data is sent to the mobile acquisition subsystem, and the real-time location information of the mobile acquisition subsystem is received and displayed. It also includes the mobile terminal acquisition subsystem, used for: Load the project data and GIS base map synchronized by the desktop processing subsystem; Real-time positioning information is obtained through a high-precision GNSS receiver module; Receive and visualize the stakeout coordinate data sent by the desktop processing subsystem; It provides on-site data plotting and measurement functions, and synchronizes the collected on-site data back to the desktop processing subsystem; The server is used to coordinate the bidirectional synchronization of project data, layout data, real-time location and on-site data between the desktop processing subsystem and the mobile acquisition subsystem.

[0008] Preferably, the desktop processing subsystem introduces an intelligent registration error correction model based on feature points of overlapping areas of multi-source data during the coordinate matching and unification process; Suppose there are k different types of data sources involved in the fusion. For any two data sources i and j that overlap spatially, extract the common feature point set. ; Define coordinate correction vector It is obtained by minimizing the following objective function F:

[0009] in, and Let i and j be the initial coordinate transformation functions for data sources i and j, respectively. The regularization term is used to prevent overfitting. The regularization coefficient is used. Optimal calculations yielded Then, the coordinates of data source j in the overlapping region are translated and corrected. This is used to improve the overall spatial consistency of multi-source data fusion.

[0010] Preferably, the mobile acquisition subsystem executes a dynamic optimization method for the layout path during assisted layout. Let the current location of the mobile device be... The current target survey point is The historical movement trajectory point set is Then the estimated cost function C(L) for reaching path L is:

[0011] in, Slope(L) is the straight-line distance between the current point and the target point, and Slope(L) is the terrain slope factor of path L (calculated based on loaded oblique photography or point cloud data). As a measure of the stability of historical trajectories; These are dynamic weighting coefficients that are adaptively adjusted based on the on-site operating environment (such as the degree of building obstruction and GNSS signal quality). The system calculates and suggests the direction and path of movement that minimizes C(L) in real time, helping operators to reach the layout point efficiently and accurately.

[0012] Preferably, the system implements collaborative stakeout closed-loop correction between the desktop and mobile terminals; when the mobile terminal's data acquisition subsystem reports completion of the stakeout point... The actual location was determined and its actual position was measured. Then, the deviation vector Return to the desktop processing subsystem; The desktop processing subsystem is based on this deviation vector Using spatial interpolation algorithms to perform... The set of all points to be staked out within a certain area centered on the center The original design coordinates are pre-corrected to generate a new set of lofting coordinates. Its correction formula is:

[0013] in, Distance from the point to be corrected A weight function that is inversely proportional to the distance d; Updated lofting coordinate set It will be automatically synchronized to the mobile terminal acquisition subsystem for subsequent layout operations, thus forming a closed loop of "measurement-feedback-correction-relayout" and systematically reducing cumulative errors.

[0014] Preferably, when the desktop processing subsystem imports a PDF file, it executes a semi-automatic redrawing and data import method: Convert PDF pages into raster images and align them with their corresponding geographic locations in a GIS scene for display; It provides a dual-screen comparison interface, allowing operators to manually draw corresponding vector graphic elements on the GIS base map by referring to the raster image; The drawn vector graphic features and their attribute information, extracted from PDFs or manually entered, are synchronously stored in the geospatial database of the current project.

[0015] Preferably, when the mobile terminal acquisition subsystem loads BIM model data, it supports automatically switching the display detail level and visible components of the model according to the current position and posture of the mobile terminal; Let the angle between the viewpoint and the normal to the surface of a component of the model be . If the distance is d, then the display priority of this component is calculated by the following formula:

[0016] Among them, ImportanceFactor is the pre-set structural or functional importance coefficient of the component in the BIM model. Based on the calculated Priority, the system dynamically decides whether to render the detailed model, the simplified model, or only display its bounding box of the component, so as to prioritize the smooth visualization of key information under the limited computing power of mobile devices.

[0017] Preferably, it also includes a multi-source data quality assessment and import optimization module, used for pre-checking and optimization when performing data import on the desktop; For any data source D to be imported, this module automatically calculates its data quality score. The calculation formula is as follows:

[0018] Among them, Completeness is a measure of data integrity, PositionalAccuracy is an assessment of location accuracy based on metadata or comparison with control points, and FileSizeComplexity is a normalized value of file size and structural complexity. Weighting coefficients are preset based on data type; based on The system automatically matches and recommends the optimal import parameter configuration scheme based on the range (high, medium, low), including texture compression level, LOD level, whether to pre-generate spatial index, and prompts the user for potential compatibility risks.

[0019] Preferably, the system implements a task flow-based multi-user collaborative editing and conflict resolution mechanism: When a project task is assigned to multiple users, the system maintains an edit lock state and operation log for each editable layer or data object; When user A attempts to edit an object that has been locked by user B, the system displays a real-time preview of user B's actions and provides three collaboration options: (1) Waiting for the lock to be released; (2) Send an editing request and annotation to user B; (3) Perform parallel editing on copies of the object, and the system automatically records the editing differences in the background. ; After a task node is completed, the system automatically or semi-automatically merges the difference sets according to preset conflict resolution rules. The final consistent version is generated, and the merged results are synchronized to the desktop and mobile devices of all relevant users.

[0020] Preferably, the mobile acquisition subsystem further includes a field anomaly detection and adaptive data acquisition module: this module analyzes the quality of the GNSS signal acquired in real time by the mobile terminal. Ambient light intensity and equipment attitude stability Calculate the credibility of the current data collection environment. :

[0021] Where k and L0 are empirical constants; according to The system automatically adjusts its data acquisition strategy based on the numerical values. when Below the threshold When the user is not in a good environment for data collection, the system automatically switches to a high-precision verification mode, requiring multiple measurements of the same feature point and taking the statistically optimal value. Above the threshold When needed, the fast acquisition mode is automatically activated to improve the efficiency of plotting and attribute entry while ensuring accuracy.

[0022] A GIS-based multi-source data collaborative mapping method includes the following steps: S1. Integrate multi-source geospatial data on the desktop and perform high-precision fusion and coordinate unification; S2. Generate design layout coordinates based on the fused data and synchronize them to the mobile device; S3. On the mobile device, real-time positioning and path optimization are combined to guide on-site layout and record the measured location. S4. The deviation between the measured position and the design position is sent back to the desktop terminal. The desktop terminal predicts and updates the subsequent layout coordinates based on the deviation and synchronizes it to the mobile terminal to guide subsequent operations. S6. The mobile terminal synchronizes the data collected on-site back to the desktop terminal, forming a closed-loop surveying and mapping result.

[0023] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This GIS-based multi-source surveying and mapping data fusion processing information system, by introducing an intelligent registration error correction model, can automatically detect and correct local residuals after multi-source data fusion, improving the fusion accuracy from the decimeter level of traditional manual adjustments to the centimeter or even millimeter level, laying a solid foundation for realizing a high-precision spatial digital base. The data quality assessment and import optimization module, as a front-end checkpoint, ensures the quality of input data and reduces the interference of poor-quality data on subsequent intelligent registration. The two work together to ensure data consistency from the source to the final fusion process, effectively solving the problems of insufficient data fusion accuracy and intelligence.

[0024] 2. This GIS-based multi-source surveying data fusion processing information system, by constructing a complete work chain of dynamic optimization of the stakeout path and collaborative stakeout closed-loop correction, achieves intelligent navigation from indoor design to on-site execution, and provides real-time, intelligent feedback of measured deviations to correct the original design. This completely changes the traditional unidirectional, open-loop operation mode, forming an intelligent closed loop of design-execution-feedback-optimization, significantly improving stakeout efficiency and first-time success rate, and systematically suppressing error propagation. The on-site anomaly perception module ensures the reliability of the "feedback" link (i.e., measured data) in the closed loop, avoiding erroneous deviation inputs caused by poor on-site data collection environment, thereby ensuring the effectiveness and robustness of the entire closed-loop correction mechanism and effectively solving the problem of broken closed-loop collaboration between indoor and outdoor work.

[0025] 3. This GIS-based multi-source surveying and mapping data fusion processing information system supports concurrent and orderly editing of the same spatial data by multiple users based on a task flow-based multi-user collaborative editing and conflict resolution mechanism. Through editing locks, operation logs, and various resolution strategies, it effectively avoids data conflicts and overwriting loss, greatly improving the efficiency and security of team collaborative work.

[0026] 4. This GIS-based multi-source surveying and mapping data fusion processing information system, with its on-site anomaly detection and adaptive data acquisition modules, enables mobile devices to possess intelligent environmental perception and dynamic strategy adjustment capabilities. It can adopt the optimal acquisition mode under different signal and lighting conditions, significantly enhancing the adaptability and robustness of the field system in complex real-world environments. The multi-user collaboration mechanism ensures data order when multiple roles and tasks are carried out in parallel from desktop to mobile devices; while the adaptive acquisition capability ensures that each mobile device can output reliable data in various challenging environments. Together, these two aspects make large-scale, high-concurrency, and cross-complex environment collaborative surveying and mapping projects possible, revolutionizing the overall system's collaboration and adaptability. Attached Figure Description

[0027] In the attached diagram: Figure 1This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. Generally, the components of the embodiments of the present invention described and shown in the accompanying drawings can be arranged and designed in various different configurations.

[0029] Example: A GIS-based multi-source surveying and mapping data fusion processing information system, comprising: a desktop processing subsystem, a mobile acquisition subsystem, and a server for synchronizing data between the two; the desktop processing subsystem is used for: Create and manage surveying projects, including setting up project geographic areas, assigning tasks and permissions; Import and integrate multi-source heterogeneous geospatial data, which includes at least CAD data, point cloud LAS data, oblique photogrammetry OSGB data, and BIM model data; The imported multi-source heterogeneous geospatial data is subjected to coordinate matching and unification, including coordinate system import, projection transformation, coordinate inversion and data registration; Perform map surveying and data plotting, and generate stakeout coordinate data; The layout coordinate data is sent to the mobile acquisition subsystem, and the real-time location information of the mobile acquisition subsystem is received and displayed. It also includes the mobile terminal acquisition subsystem, used for: Load the project data and GIS base map synchronized by the desktop processing subsystem; Real-time positioning information is obtained through a high-precision GNSS receiver module; Receive and visualize the stakeout coordinate data sent by the desktop processing subsystem; It provides on-site data plotting and measurement functions, and synchronizes the collected on-site data back to the desktop processing subsystem; The server is used to coordinate the bidirectional synchronization of project data, layout data, real-time location and on-site data between the desktop processing subsystem and the mobile acquisition subsystem.

[0030] Preferably, the desktop processing subsystem introduces an intelligent registration error correction model based on feature points of overlapping areas of multi-source data during the coordinate matching and unification process; Suppose there are k different types of data sources involved in the fusion. For any two data sources i and j that overlap spatially, extract the common feature point set. ; Define coordinate correction vector It is obtained by minimizing the following objective function F:

[0031] in, and Let i and j be the initial coordinate transformation functions for data sources i and j, respectively. The regularization term is used to prevent overfitting. The regularization coefficient is used. Optimal calculations yielded Then, the coordinates of data source j in the overlapping region are translated and corrected. This is used to improve the overall spatial consistency of multi-source data fusion.

[0032] Preferably, the mobile acquisition subsystem executes a dynamic optimization method for the layout path during assisted layout. Let the current location of the mobile device be... The current target survey point is The historical movement trajectory point set is Then the estimated cost function C(L) for reaching path L is:

[0033] in, Slope(L) is the straight-line distance between the current point and the target point, and Slope(L) is the terrain slope factor of path L (calculated based on loaded oblique photography or point cloud data). As a measure of the stability of historical trajectories; These are dynamic weighting coefficients that are adaptively adjusted based on the on-site operating environment (such as the degree of building obstruction and GNSS signal quality). The system calculates and suggests the direction and path of movement that minimizes C(L) in real time, helping operators to reach the layout point efficiently and accurately.

[0034] Preferably, the system implements collaborative stakeout closed-loop correction between the desktop and mobile terminals; when the mobile terminal's data acquisition subsystem reports completion of the stakeout point... The actual location was determined and its actual position was measured. Then, the deviation vector Return to the desktop processing subsystem; The desktop processing subsystem is based on this deviation vector Using spatial interpolation algorithms to perform... The set of all points to be staked out within a certain area centered on the center The original design coordinates are pre-corrected to generate a new set of lofting coordinates. Its correction formula is:

[0035] in, Distance from the point to be corrected A weight function that is inversely proportional to the distance d; Updated lofting coordinate set It will be automatically synchronized to the mobile terminal acquisition subsystem for subsequent layout operations, thus forming a closed loop of "measurement-feedback-correction-relayout" and systematically reducing cumulative errors.

[0036] Preferably, when the desktop processing subsystem imports a PDF file, it executes a semi-automatic redrawing and data import method: Convert PDF pages into raster images and align them with their corresponding geographic locations in a GIS scene for display; It provides a dual-screen comparison interface, allowing operators to manually draw corresponding vector graphic elements on the GIS base map by referring to the raster image; The drawn vector graphic features and their attribute information, extracted from PDFs or manually entered, are synchronously stored in the geospatial database of the current project.

[0037] Preferably, when the mobile terminal acquisition subsystem loads BIM model data, it supports automatically switching the display detail level and visible components of the model according to the current position and posture of the mobile terminal; Let the angle between the viewpoint and the normal to the surface of a component of the model be . If the distance is d, then the display priority of this component is calculated by the following formula:

[0038] Among them, ImportanceFactor is the pre-set structural or functional importance coefficient of the component in the BIM model. Based on the calculated Priority, the system dynamically decides whether to render the detailed model, the simplified model, or only display its bounding box of the component, so as to prioritize the smooth visualization of key information under the limited computing power of mobile devices.

[0039] Preferably, it also includes a multi-source data quality assessment and import optimization module, used for pre-checking and optimization when performing data import on the desktop; For any data source D to be imported, this module automatically calculates its data quality score. The calculation formula is as follows:

[0040] Among them, Completeness is a measure of data integrity, PositionalAccuracy is an assessment of location accuracy based on metadata or comparison with control points, and FileSizeComplexity is a normalized value of file size and structural complexity. Weighting coefficients are preset based on data type; based on The system automatically matches and recommends the optimal import parameter configuration scheme based on the range (high, medium, low), including texture compression level, LOD level, whether to pre-generate spatial index, and prompts the user for potential compatibility risks.

[0041] Preferably, the system implements a task flow-based multi-user collaborative editing and conflict resolution mechanism: When a project task is assigned to multiple users, the system maintains an edit lock state and operation log for each editable layer or data object; When user A attempts to edit an object that has been locked by user B, the system displays a real-time preview of user B's actions and provides three collaboration options: (1) Waiting for the lock to be released; (2) Send an editing request and annotation to user B; (3) Perform parallel editing on copies of the object, and the system automatically records the editing differences in the background. ; After a task node is completed, the system automatically or semi-automatically merges the difference sets according to preset conflict resolution rules. The final consistent version is generated, and the merged results are synchronized to the desktop and mobile devices of all relevant users.

[0042] Preferably, the mobile acquisition subsystem further includes a field anomaly detection and adaptive data acquisition module: this module analyzes the quality of the GNSS signal acquired in real time by the mobile terminal. Ambient light intensity and equipment attitude stability Calculate the credibility of the current data collection environment. :

[0043] Where k and L0 are empirical constants; according to The system automatically adjusts its data acquisition strategy based on the numerical values. when Below the threshold When the user is not in a good environment for data collection, the system automatically switches to a high-precision verification mode, requiring multiple measurements of the same feature point and taking the statistically optimal value. Above the threshold When needed, the fast acquisition mode is automatically activated to improve the efficiency of plotting and attribute entry while ensuring accuracy.

[0044] A GIS-based multi-source data collaborative mapping method includes the following steps: S1. Integrate multi-source geospatial data on the desktop and perform high-precision fusion and coordinate unification; S2. Generate design layout coordinates based on the fused data and synchronize them to the mobile device; S3. On the mobile device, real-time positioning and path optimization are combined to guide on-site layout and record the measured location. S4. The deviation between the measured position and the design position is sent back to the desktop terminal. The desktop terminal predicts and updates the subsequent layout coordinates based on the deviation and synchronizes it to the mobile terminal to guide subsequent operations. S6. The mobile terminal synchronizes the data collected on-site back to the desktop terminal, forming a closed-loop surveying and mapping result.

[0045] System Overall Architecture Implementation: This system adopts a hybrid architecture combining C / S and M / S architectures. The desktop processing subsystem is deployed on professional workstations in the project center, based on the Supermap iDesktop platform for secondary development, and undertakes core data processing, analysis, and design tasks. The mobile acquisition subsystem is a dedicated APP developed based on the Android system, installed on ruggedized tablets or handheld devices that support high-precision GNSS modules. The server side can use an enterprise-grade server to deploy data synchronization services, user management, and project management databases. All three are connected via the enterprise intranet or a secure mobile communication network to achieve bidirectional real-time data synchronization.

[0046] Multi-source data integration and intelligent registration: During implementation, users select data files such as CAD, point cloud, oblique photogrammetry, and BIM through the "Data Import" module on the desktop. The system calls the data quality assessment and import optimization module described in claim 7 to perform a rapid pre-check on each file. For example, when importing a BIM model, the system automatically analyzes its component completeness. If a large number of components are found to be missing (such as doors and windows), a quality score is given. The warning is relatively low, and users are advised to check the source file or import it using the "geometric reduction" mode to improve performance.

[0047] After data import, the system enters the intelligent registration stage. Assume that the CAD topographic map (data source i), which has undergone preliminary projection transformation, and the oblique photogrammetry model (data source j) have an average positional deviation of 5 cm at building corners. The system automatically extracts 10 clearly identifiable roof corner points from both as a common feature point set. Subsequently, the system runs the minimization objective function in the background. The regularization term R is set to the L2 norm of the correction vector to prevent model distortion caused by over-correction. The optimal correction vector is then calculated. After a few meters, the system automatically applies this translation correction to the coordinates of the oblique photography model in that area, thereby aligning it with the CAD topographic map with sub-decimeter accuracy.

[0048] In one implementation, the lofting design and closed-loop collaborative workflow involves: In the merged 3D scene, the interior designers use a "data plotting" tool to set up a series of design lofting points. At that time, the dynamic optimization function for the layout path is activated. The mobile device obtains its own location in real time. The system calculates the slope factor of the path from the current location to the target point by combining the loaded oblique photogrammetric terrain data. Simultaneously, the system assesses that the GNSS signal is stable in the initial stage and the historical trajectory variance is small; therefore, it automatically sets the weighting coefficients in the cost function C(L). Higher (heavy distance) and If the slope is low, the screen map will immediately display an optimal suggested route to bypass the steep slope ahead, guiding the operator forward.

[0049] After arriving at the target area, the operator guides the workers to complete the stake point calibration based on precise distances and angles, and records the measured coordinates. At this point, the system detected... and There is a 2 cm northward deviation. The deviation and environmental confidence information are automatically transmitted back to the desktop; among them, environmental confidence... Calculated by the following formula And this collection The value is high, and the data is reliable.

[0050] The collaborative lofting closed-loop correction module on the desktop was triggered, and the system... Centered on the target area, and based on a predetermined influence radius of 200 meters, the subsequent 10 sampling points to be surveyed were... Perform anti-distance formaldehyde (IDW) pre-correction. For example, for distance... 50 meters Its weight w(50) is relatively large, therefore its new coordinates A significant northward adjustment (e.g., 0.016 meters) will be obtained. All updated coordinates are automatically synchronized to the mobile device for subsequent stakeout. This process smoothly distributes the random deviation of the first point to subsequent points, effectively suppressing the linear accumulation of errors.

[0051] In another sub-project, Engineer A and Surveyor B were assigned to jointly edit the same pipeline layer. Engineer A first locked a section of pipeline on the desktop and edited its attributes (such as changing the pipe diameter). At this time, Surveyor B attempted to modify the location coordinates of the same pipeline on the mobile device. The system immediately popped up a notification: "This object is being edited by user A on the desktop," and displayed a preview of the attribute field that A was modifying. Surveyor B selected "Send Edit Request," attaching a site photo and the note "Ground subsidence here; it is recommended to lower the pipeline elevation by 0.5 meters." This request was pushed to Engineer A's desktop in real time. After reviewing it, A agreed to the modification and directly adjusted the pipeline elevation on the desktop. The system automatically released the editing lock on the object. Throughout the process, the operation log was fully recorded. After review by the project manager, a unified version was generated and synchronized, ensuring data consistency and traceability.

[0052] In one implementation, adaptive data acquisition is performed on-site: During a mapping operation inside an underground parking garage, after the mobile device enters the garage, the GNSS signal strength is monitored. A sharp drop, ambient light Darkening. Environmental confidence level calculated by the on-site anomaly detection module. Instantly below the threshold The system then: (1) issues a warning of "weak signal, dark environment" in a prominent position on the interface; (2) automatically switches to "high-precision verification mode". When the operator marks a fire hydrant location, the system requires continuous measurement 5 times, and after automatically removing gross errors, takes the median coordinate as the final result; (3) suggests turning on the equipment's LED supplementary light to improve the lighting. These adaptive strategies ensure the reliability of data collection in harsh environments.

[0053] The embodiments described above are merely preferred embodiments of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications, improvements, and substitutions without departing from the concept of the present invention, and these all fall within the protection scope of the present invention.

Claims

1. A GIS-based multi-source surveying and mapping data fusion processing information system, characterized in that, It includes a desktop processing subsystem, a mobile acquisition subsystem, and a server for synchronizing data between the two; the desktop processing subsystem is used for: Create and manage surveying projects, including setting up project geographic areas, assigning tasks and permissions; Import and integrate multi-source heterogeneous geospatial data, which includes at least CAD data, point cloud LAS data, oblique photogrammetry OSGB data, and BIM model data; The imported multi-source heterogeneous geospatial data is subjected to coordinate matching and unification, including coordinate system import, projection transformation, coordinate inversion and data registration; Perform map surveying and data plotting, and generate stakeout coordinate data; The layout coordinate data is sent to the mobile acquisition subsystem, and the real-time location information of the mobile acquisition subsystem is received and displayed. It also includes the mobile terminal acquisition subsystem, used for: Load the project data and GIS base map synchronized by the desktop processing subsystem; Real-time positioning information is obtained through a high-precision GNSS receiver module; Receive and visualize the stakeout coordinate data sent by the desktop processing subsystem; It provides on-site data plotting and measurement functions, and synchronizes the collected on-site data back to the desktop processing subsystem; The server is used to coordinate the bidirectional synchronization of project data, layout data, real-time location and on-site data between the desktop processing subsystem and the mobile acquisition subsystem.

2. The GIS-based multi-source surveying and mapping data fusion processing information system according to claim 1, characterized in that, In the process of coordinate matching and unification, the desktop processing subsystem introduces an intelligent registration error correction model based on feature points of overlapping areas of multi-source data. Suppose there are k different types of data sources involved in the fusion. For any two data sources i and j that overlap spatially, extract the common feature point set. ; Define coordinate correction vector It is obtained by minimizing the following objective function F: in, and Let i and j be the initial coordinate transformation functions for data sources i and j, respectively. The regularization term is used to prevent overfitting. The regularization coefficient is used. Optimal calculations yielded Then, the coordinates of data source j in the overlapping region are translated and corrected. This is used to improve the overall spatial consistency of multi-source data fusion.

3. The GIS-based multi-source surveying and mapping data fusion processing information system according to claim 1, characterized in that, The mobile terminal acquisition subsystem executes a dynamic optimization method for the layout path during assisted layout. Let the current location of the mobile device be... The current target survey point is The historical movement trajectory point set is Then the estimated cost function C(L) for reaching path L is: in, The current point is the straight-line distance between the current point and the target point, and Slope(L) is the terrain slope factor of path L. As a measure of the stability of historical trajectories; These are dynamic weighting coefficients that adaptively adjust based on the on-site working environment. The system calculates and suggests the direction and path of movement that minimizes C(L) in real time.

4. The GIS-based multi-source surveying and mapping data fusion processing information system according to claim 1 or 3, characterized in that, The system enables collaborative stakeout closed-loop correction between desktop and mobile terminals; when the mobile terminal's data acquisition subsystem reports completion of the stakeout point... The actual location was determined and its actual position was measured. Then, the deviation vector Return to the desktop processing subsystem; The desktop processing subsystem is based on this deviation vector Using spatial interpolation algorithms to perform... The set of all points to be staked out within a certain area centered on the center The original design coordinates are pre-corrected to generate a new set of lofting coordinates. Its correction formula is: in, Distance from the point to be corrected A weight function that is inversely proportional to the distance d; Updated lofting coordinate set Automatically synchronize to the mobile data collection subsystem.

5. The GIS-based multi-source surveying and mapping data fusion processing information system according to claim 1, characterized in that, When the desktop processing subsystem imports PDF files, it executes a semi-automatic redrawing and database import method: Convert PDF pages into raster images and align them with their corresponding geographic locations in a GIS scene for display; It provides a dual-screen comparison interface, allowing operators to manually draw corresponding vector graphic elements on the GIS base map by referring to the raster image; The drawn vector graphic features and their attribute information, extracted from PDFs or manually entered, are synchronously stored in the geospatial database of the current project.

6. The GIS-based multi-source surveying and mapping data fusion processing information system according to claim 1, characterized in that, When the mobile terminal acquisition subsystem loads BIM model data, it supports automatically switching the display detail level and visible components of the model according to the current position and posture of the mobile terminal. Let the angle between the viewpoint and the normal to the surface of a component of the model be . If the distance is d, then the display priority of this component is calculated by the following formula: The ImportanceFactor is the pre-defined structural or functional importance coefficient of the component in the BIM model.

7. The GIS-based multi-source surveying and mapping data fusion processing information system according to claim 1, characterized in that, It also includes a multi-source data quality assessment and import optimization module, which is used to perform pre-checks and optimizations when performing data import on the desktop. For any data source D to be imported, this module automatically calculates its data quality score. The calculation formula is as follows: Among them, Completeness is a measure of data integrity, PositionalAccuracy is an assessment of location accuracy based on metadata or comparison with control points, and FileSizeComplexity is a normalized value of file size and structural complexity. The weighting coefficients are preset based on the data type.

8. The GIS-based multi-source surveying and mapping data fusion processing information system according to claim 1, characterized in that, The system implements a task flow-based multi-user collaborative editing and conflict resolution mechanism: When a project task is assigned to multiple users, the system maintains an edit lock state and operation log for each editable layer or data object; When user A attempts to edit an object that has been locked by user B, the system displays a real-time preview of user B's actions and provides three collaboration options: (1). Wait for the lock to be released; (2) Send an editing request and annotation to user B; (3) Perform parallel editing on copies of the object, and the system automatically records the edit differences in the background. ; After a task node is completed, the system automatically or semi-automatically merges the difference sets according to preset conflict resolution rules. The final consistent version is generated, and the merged results are synchronized to the desktop and mobile devices of all relevant users.

9. The GIS-based multi-source surveying and mapping data fusion processing information system according to claim 1, characterized in that, The mobile acquisition subsystem also includes a field anomaly detection and adaptive data acquisition module: this module analyzes the quality of the GNSS signals acquired in real time by the mobile terminal. Ambient light intensity and equipment attitude stability Calculate the credibility of the current data collection environment. : Where k and L 0为 Empirical constants; based on The system automatically adjusts its data acquisition strategy based on the numerical values. when Below the threshold When the user is not in a good environment for data collection, the system automatically switches to a high-precision verification mode, requiring multiple measurements of the same feature point and taking the statistically optimal value. Above the threshold When needed, the fast acquisition mode will be automatically activated.

10. A GIS-based multi-source data collaborative mapping method, employing the GIS-based multi-source mapping data fusion processing information system as described in any one of claims 1-9, characterized in that, Includes the following steps: S1. Integrate multi-source geospatial data on the desktop and perform high-precision fusion and coordinate unification; S2. Generate design layout coordinates based on the fused data and synchronize them to the mobile device; S3. On the mobile device, real-time positioning and path optimization are combined to guide on-site layout and record the measured location. S4. The deviation between the measured position and the design position is sent back to the desktop terminal. The desktop terminal predicts and updates the subsequent layout coordinates based on the deviation and synchronizes it to the mobile terminal to guide subsequent operations. S6. The mobile terminal synchronizes the data collected on-site back to the desktop terminal, forming a closed-loop surveying and mapping result.

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