Spatial data one-key lightweight treatment method

Abstract

The invention relates to a one-key lightweight treatment method for spatial data. The method is suitable for the technical field of data management. The technical problem to be solved by the invention is to provide a one-key lightweight treatment method for spatial data. According to the technical scheme, the one-key lightweight treatment method for the spatial data is characterized by comprising the steps that the spatial data are read from BIM and GIS data of various sources and formats, and spatial graphic data and model attribute data are separated from the spatial data; respectively carrying out standardization processing on the spatial graphic data and the model attribute data, and carrying out lightweight processing on the spatial graphic data subjected to standardization processing; generating a three-dimensional model with corresponding precision based on the lightweight spatial graphic data and the lightweight grading precision selected by the user; correcting the coordinates of the three-dimensional model; and based on the three-dimensional model subjected to the coordinate correction processing and the corresponding model attribute data, outputting according to a preset data format and publishing into a corresponding service.

Description

Technical Field

[0001] The present invention relates to a one-key lightweight spatial data management method, which is applicable to the field of data management. Background Art

[0002] At present, BIM / CIM data governance mainly relies on manual processing, which has problems such as cumbersome processes, repeated modifications, and uncontrollable quality. The main problems include the following:

[0003] 1. More than ten tools are required to process various types of 3D data. The processing chain is long, with an average of 4 to 6 links. The process is cumbersome and repetitive, and the efficiency is low.

[0004] 2. Governance data is not compatible with the spatial data platform and the high-rendering visualization platform. Different platforms need to be processed separately, which leads to a lot of repetitive work and inconsistent model information.

[0005] 3. The processing process is heavily dependent on the personal experience of data engineers. The data quality of results processed by different personnel is unstable and the results are uncontrollable. Summary of the invention

[0006] The technical problem to be solved by the present invention is: to provide a one-click lightweight management method for spatial data in response to the above-mentioned problems.

[0007] The technical solution adopted by the present invention is: a one-key lightweight management method for spatial data, characterized by comprising:

[0008] Read spatial data from BIM and GIS data of various sources and formats, and separate spatial graphic data and model attribute data from spatial data;

[0009] Standardize the spatial graphic data and the model attribute data respectively, and perform lightweight processing on the standardized spatial graphic data;

[0010] Generate a 3D model with corresponding precision based on the lightweight processed spatial graphic data and the lightweight graded precision selected by the user;

[0011] Correct the coordinates of the three-dimensional model;

[0012] Based on the coordinate-corrected 3D model and corresponding model attribute data, it is output in a preset data format and published as a corresponding service.

[0013] The method of reading spatial data from BIM and GIS data of various sources and formats and separating spatial graphic data and model attribute data from the spatial data includes:

[0014] Read spatial data from BIM and GIS data in various sources and formats;

[0015] Separate spatial graphic data and model attribute data from spatial data;

[0016] Assign unique codes to all spatial graphic data of components, store model attribute data in json format, and map and match the unique codes of spatial graphic data with json files;

[0017] The model attribute data is stored in the database, and the spatial graphic data is uniformly converted into fbx format data.

[0018] The standardization of the spatial graphic data and the model attribute data respectively includes:

[0019] Read metadata of spatial graphic data;

[0020] Use regular rule matching verification to intelligently identify anomalies in spatial graphic data and model attribute data, and automatically repair errors.

[0021] The lightweight processing of the standardized spatial graphic data includes:

[0022] Merge model components according to the needs of application scenarios;

[0023] Based on the intelligent identification of redundant vertices algorithm, the quality criteria standard is adopted to ensure the model topology and surface smoothness;

[0024] Convert similar components into the same instance and perform deduplication optimization.

[0025] The correction process for the coordinates of the three-dimensional model includes:

[0026] Use FME templates to automatically project 3D geospatial data into the CGCS2000 coordinate system;

[0027] Use FME template to translate 3D data to corresponding coordinate positions;

[0028] Automatically rotate 3D data to match the orientation based on the 3D model’s azimuth;

[0029] Automatically scale the model size based on the four corner coordinates of the 3D model to achieve the best model matching.

[0030] Also includes:

[0031] Based on the output and published corresponding services, the results of data governance are visualized.

[0032] The corresponding services based on output and publication provide a visual display of the results of data governance, including:

[0033] Use FME to publish the resulting data into the 3dtiles format used by Cesium and the datasmith format used by Unreal Engine.

[0034] Send 3dtiles and datasmith format data to CesiumLab engine and Unreal Engine respectively, and use dual engines to load and publish services respectively;

[0035] Automatically check the number of models in the result service and the number of original data recognitions, extract the model data that failed to be processed, and output them in the form of a list.

[0036] A one-click lightweight spatial data management device, characterized by comprising:

[0037] Data reading module, used to read spatial data from BIM and GIS data of various sources and formats, and separate spatial graphic data and model attribute data from spatial data;

[0038] A data processing module, used to perform standardization processing on the spatial graphic data and the model attribute data respectively, and to perform lightweight processing on the standardized spatial graphic data;

[0039] A model generation module, used to generate a three-dimensional model of corresponding accuracy based on the lightweight processed spatial graphic data and the lightweight graded accuracy selected by the user;

[0040] A coordinate correction module, used for correcting the coordinates of the three-dimensional model;

[0041] The data publishing module is used to output the coordinate-corrected three-dimensional model and corresponding model attribute data in a preset data format and publish them into corresponding services.

[0042] A storage medium stores a computer program that can be executed by a processor, characterized in that when the computer program is executed, the steps of the one-click lightweight management method of spatial data are implemented.

[0043] A one-click lightweight management device for spatial data comprises a memory and a processor, wherein the memory stores a computer program that can be executed by the processor, and wherein the computer program implements the steps of the one-click lightweight management method for spatial data when executed.

[0044] The beneficial effect of the present invention is as follows: after the spatial graphic data and model attribute data in the spatial data are standardized, the present invention performs lightweight processing on the spatial graphic data, and then generates a three-dimensional model of corresponding accuracy based on the lightweight graded accuracy selected by the user, and publishes it as a corresponding service after coordinate correction, thereby solving the key and difficult points in the field of digital twin cities, namely, lightweighting and integration of massive BIM and GIS data, solving the last mile of publishing spatial data to GIS engines and high rendering engines, improving the work efficiency of the data governance link, reducing the cost caused by relying on manpower to optimize data, and improving the efficiency and controllability of data governance. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 Schematic diagram of the method flow of an embodiment.

[0046] Figure 2 A schematic diagram is written for the model of spatial data standardization processing in the embodiment.

[0047] Figure 3 Schematic diagram of the PIXYZ lightweight BIM model in the embodiment.

[0048] Figure 4 A schematic diagram of the model for automatic correction of spatial data coordinates in the embodiment is written.

[0049] Figure 5 A schematic diagram is written for the model of automatic publishing of spatial data in the embodiment.

[0050] Figure 6 This is a schematic diagram of generating and optimizing Datasmith format data in an embodiment. DETAILED DESCRIPTION

[0051] Example 1: Figure 1 As shown, this embodiment is a one-key lightweight management method for spatial data, which specifically includes the following steps:

[0052] S1. Read spatial data from BIM and GIS data of various sources and formats, and separate spatial graphic data and model attribute data from spatial data.

[0053] S11. Use PIXYZ to extract 3D data such as BIM models (rvt, ifc, dgn, etc.), manual models (3dm, skp, fbx, etc.), oblique photography, etc., and use FME to extract 3D GIS formats such as ArcGIS GDB and SuperMap UDB;

[0054] S12, digital-model separation. During the original spatial data analysis process, all spatial graphic data of components are assigned unique codes (UNIQUE_ID), model attribute data is stored in json format, and the UNIQUE_ID of spatial graphic data is mapped and matched with the json file;

[0055] S13, data storage, storing the model attribute data generated in step S12 into the database, converting the spatial graphic data into fbx format data, and transferring to step S2 for processing.

[0056] S2. Standardize the spatial graphic data and the model attribute data respectively, and perform lightweight processing on the standardized spatial graphic data.

[0057] In this embodiment, an FME data processing model is established to standardize the data, separate the spatial graphic data from the attribute fields, and perform field integrity and feature name correctness verification and intelligent repair respectively. The overall process and results of the data processing model establishment are shown in the figure. Figure 2 shown.

[0058] S21. Parsing of graphic metadata: supports parsing of structured data, supports reading metadata, and supports reading geometric data types such as points, lines, and surfaces.

[0059] S22. Automated data verification and repair: Use regular rule matching verification to support intelligent identification of abnormalities in spatial graphic data and model attribute data of BIM model data, and automatically repair errors.

[0060] In this example, PIXYZ is used to lightweight the BIM model. Cleanup tools include cleaning invalid materials, simplifying complex polygons, removing redundancy, optimizing textures and rendering effects, etc. Figure 3 shown.

[0061] S23, automatic merging model: For components that do not need to be called individually, they can be quickly merged according to the needs of the application scenario, such as merging by type, specialty, floor, or area;

[0062] S24, Vertex Compression: Built-in intelligent redundant vertex identification algorithm, using quality criteria to ensure model topology and surface smoothness;

[0063] S25, automatic UV generation: UV generation algorithm based on BIM / CAD data, supporting parametric creation of UV;

[0064] S26, instantiation operator: similar components are converted into the same instance and deduplication optimization is performed to reduce the number of triangles and reduce the computing resource usage of the GPU.

[0065] S3. Based on the lightweight processed spatial graphic data and the lightweight graded accuracy selected by the user, a three-dimensional model of corresponding accuracy is generated and output as an fbx file.

[0066] According to the classification goals set by the user, the 3D BIM and GIS data are exported in a unified fbx format with the accuracy of CIM1-CIM7.

[0067] S4. Establish an FME data processing model to automatically correct the coordinates of the 3D model. The overall process and results of coordinate correction are as follows: Figure 4 shown.

[0068] S41. Use FME templates to automatically project various 3D geospatial data into the CGCS2000 coordinate system.

[0069] S42. Use the FME template to translate the 3D data (including oblique photography, BIM model, etc.) to the corresponding coordinate position;

[0070] S43, automatically rotating the three-dimensional data to match the direction according to the azimuth of the three-dimensional model;

[0071] S44. Automatically scale the model size according to the coordinates of the four corners of the three-dimensional model to achieve optimal model matching.

[0072] In this embodiment, the east / west, north / south, elevation, and angle value to the true north of the BIM model project base point are obtained. Check whether the unit of the project base point is meter, otherwise it needs to be scaled and adjusted to meters; check whether the plane coordinates and elevation of the project base point have been reset to zero, otherwise it needs to be translated to zero. First rotate the model according to the angle value to the true north, and then translate it on the X, Y, and Z axes according to the values ​​of east / west, north / south, and elevation, and finally match it to the plane coordinates of CGCS2000. Set the UE project origin coordinates (longitude, latitude, elevation), use CGCS2000 geographic coordinates, and then perform Gaussian calculation to convert the geographic coordinates into CGCS plane projection coordinates (x, y, z). The model is translated from the GIS coordinates by -x, -y, and -z along the X, Y, and Z axes respectively, and then enlarged 100 times, and the unit is converted to centimeters. The model automatically reaches the coordinates of the Unreal Engine.

[0073] S5. Based on the coordinate-corrected three-dimensional model and corresponding model attribute data, the data is output in a preset data format and published as a corresponding service.

[0074] In this embodiment, an FME data processing model is established to output spatial data in three data formats: UE engine, Cesium engine, and ArcGIS, and publish them into corresponding services. The overall process and results of automatic data publishing are as follows: Figure 5 shown.

[0075] S51. Model conversion to standard format. BIM models, manual models, and 3D GIS models are uniformly converted into an intermediate format to facilitate conversion into files of different formats.

[0076] S52. Output in UDATASMITH format. Determine the output type. If it is in UDATASMITH format, reorganize the geometry and name, enter the UDATASMITH scene name and layer name, set the Actor name to From GeometryName, the Mesh name to From Geometry Name, set the coordinate system to not move to the local coordinate system, and finally output the UDATASMITH file.

[0077] S52, output 3DTILES format. Determine the output type. If the output format is 3DTILES, first set the maximum number of triangles that can be contained in each tile, then set the output map format and whether to create a texture atlas, then set the file name coordinate system, and finally output the 3dtiles file.

[0078] S6. Based on the corresponding services output and published in step S5, the results of data governance are visualized.

[0079] S61. Use FME to publish the result data into 3dtiles format for use by Cesize and Datasmith format for use by Unreal Engine.

[0080] S62. Send the 3dtiles and Datasmith format data to the CesiumLab engine and the Unreal Engine respectively, and use the dual engines to load and publish services respectively;

[0081] S63. Automatically check the number of models in the result service and the number of original data recognitions, extract the model data that failed to be processed, and output them in the form of a list.

[0082] Figure 6 This is a schematic diagram of using FME to run a script to optimize the datasmith format data supported by the UE engine in the embodiment.

[0083] In this example, the XML library is used to read the udatasmith file and parse the XMLdom tree. Locate the . / / UEPbrMateri al tag. All Constant3Vector tags are rewritten as Col or tags. <Constant3Vector R={r va lue},G={g va l ue},B={b va l ue}><Co l or Name="{name}"constant="(R={r val ue},G={g va l ue},B={b va l ue})" / > To adapt to the reading method of UE, rewrite the Name attribute of the Expressions tag to Name = 'Texture'.

Claims

1. A one-click lightweight management method for spatial data, characterized in that: include: Read spatial data from BIM and GIS data of various sources and formats, and separate spatial graphic data and model attribute data from spatial data; Standardize the spatial graphic data and the model attribute data respectively, and perform lightweight processing on the standardized spatial graphic data; Generate a 3D model with corresponding precision based on the lightweight processed spatial graphic data and the lightweight graded precision selected by the user; Correct the coordinates of the three-dimensional model; Based on the coordinate-corrected 3D model and corresponding model attribute data, it is output in a preset data format and published as a corresponding service.

2. The one-key lightweight management method for spatial data according to claim 1 is characterized in that: The method of reading spatial data from BIM and GIS data of various sources and formats and separating spatial graphic data and model attribute data from the spatial data includes: Read spatial data from BIM and GIS data in various sources and formats; Separate spatial graphic data and model attribute data from spatial data; Assign unique codes to all spatial graphic data of components, store model attribute data in json format, and map and match the unique codes of spatial graphic data with json files; The model attribute data is stored in the database, and the spatial graphic data is uniformly converted into fbx format data.

3. The one-key lightweight management method for spatial data according to claim 1 is characterized in that: The standardization of the spatial graphic data and the model attribute data respectively includes: Read the metadata of spatial graphic data; Use regular rule matching verification to intelligently identify anomalies in spatial graphic data and model attribute data, and automatically repair errors.

4. The one-key lightweight management method for spatial data according to claim 1 is characterized in that: The lightweight processing of the standardized spatial graphic data includes: Merge model components according to the needs of application scenarios; Based on the intelligent identification of redundant vertices algorithm, the quality criteria standard is adopted to ensure the model topology and surface smoothness; Convert similar components into the same instance and perform deduplication optimization.

5. The one-key lightweight management method for spatial data according to claim 1 is characterized in that: The correction process for the coordinates of the three-dimensional model includes: Use FME templates to automatically project 3D geospatial data into the CGCS2000 coordinate system; Use FME template to translate 3D data to corresponding coordinate positions; Automatically rotate 3D data to match the orientation based on the 3D model’s azimuth; Automatically scale the model size based on the four corner coordinates of the 3D model to achieve the best model matching.

6. The one-key lightweight management method for spatial data according to claim 1 is characterized in that: Also includes: Based on the output and published corresponding services, the results of data governance are visualized.

7. The one-key lightweight management method for spatial data according to claim 6 is characterized in that: The corresponding services based on output and publication provide a visual display of the results of data governance, including: Use FME to publish the resulting data into 3dtiles format for Cesium and Datasmith format for Unreal Engine. Send 3dtiles and datasmith format data to CesiumLab engine and Unreal Engine respectively, and use dual engines to load and publish services respectively; Automatically check the number of models in the result service and the number of original data recognitions, extract the model data that failed to be processed, and output them in the form of a list.

8. A one-click lightweight spatial data management device, characterized in that: include: Data reading module, used to read spatial data from BIM and GIS data of various sources and formats, and separate spatial graphic data and model attribute data from spatial data; A data processing module, used to perform standardization processing on the spatial graphic data and the model attribute data respectively, and to perform lightweight processing on the standardized spatial graphic data; A model generation module, used to generate a three-dimensional model of corresponding accuracy based on the lightweight processed spatial graphic data and the lightweight graded accuracy selected by the user; A coordinate correction module, used for correcting the coordinates of the three-dimensional model; The data publishing module is used to output the coordinate-corrected three-dimensional model and corresponding model attribute data in a preset data format and publish them into corresponding services.

9. A storage medium having stored thereon a computer program executable by a processor, characterized in that: When the computer program is executed, the steps of the one-click lightweight management method for spatial data described in any one of claims 1 to 7 are implemented.

10. A one-click lightweight spatial data management device, comprising a memory and a processor, wherein the memory stores a computer program executable by the processor, characterized in that: When the computer program is executed, the steps of the one-click lightweight management method for spatial data described in any one of claims 1 to 7 are implemented.

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