High-precision digital twinning scene construction method and system

Abstract

The invention relates to the technical field of geographic scene construction, and discloses a high-precision digital twin scene construction method and system, and the method comprises the following steps: obtaining a digital elevation model (DEM) and satellite image data from a geographic data platform, and carrying out the projection conversion and cutting processing; model generation and coordinate registration: converting the cut DEM data into a three-dimensional grid model, and setting the longitude and latitude of an original point of the model in three-dimensional software; geographical registration is carried out through a Gerecircumference plug-in of an unreal engine, and scene coordinate deviation is corrected in combination with error compensation parameters; dynamic data integration: accessing an external data source through a real-time data interface, and analyzing and dynamically updating a POI point location position in a scene; scene optimization and output: packaging the processed virtual texture and the corrected coordinate parameters into a configuration file, and generating a high-precision digital twinning scene; according to the method, the problems of low precision and poor efficiency in traditional digital twinning scene construction are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of geographic scene construction, and in particular to a high-precision digital twin scene construction method and system. Background Art

[0002] The integration of Geographic Information Systems (GIS) and digital twin technology has become a crucial technology in areas such as smart cities, environmental monitoring, and disaster response. By mapping real-world geographic data into virtual three-dimensional scenes, digital twin systems enable dynamic simulation of the physical environment and support decision-making. However, existing GIS and three-dimensional engine integration solutions still face significant technical bottlenecks, limiting their practicality and scalability in complex scenarios. Currently, the construction of digital twin scenarios still faces the following challenges: The multi-software collaboration process is inefficient and has a high error rate. GIS data and models are prone to misalignment and lack standardized configuration. This paper proposes a set of standardized operation processes that integrate GIS data collection, GIS data clipping, GIS model export, and digital twin scene import to improve efficiency and reduce operational errors. The scene accuracy is insufficient. When traditional GIS data (such as elevation maps and satellite images) are imported into a 3D engine, simplified coordinate system conversion methods (such as direct scaling of the Mercator projection) are usually used, resulting in scene offset errors generally exceeding 5 meters. This invention uses a latitude and longitude coordinate system conversion plug-in and uses error compensation parameter configuration to reduce the scene conversion error to ≤ 0.5 meters. The dynamic data fusion capability is missing, the real-time data interface is not integrated, and the CSV file needs to be imported in advance. It cannot be updated in real time, and the scene element updates are delayed. The present invention uses a plug-in to access the background data interface in real time, which can update the GIS coordinate position every frame; Therefore, a new digital twin scene construction method is urgently needed to solve the problems of low accuracy and poor efficiency in traditional digital twin scene construction. Summary of the Invention

[0003] The present invention provides a high-precision digital twin scene construction method and system to solve the problems of low precision and poor efficiency in traditional digital twin scene construction.

[0004] In order to achieve the above object, the present invention is implemented through the following technical solutions: In a first aspect, the present invention provides a method for constructing a high-precision digital twin scene, comprising the following steps: (1) Data acquisition and processing: Obtain digital elevation model (DEM) and satellite image data from the geographic data platform, and perform projection conversion and cropping; (2) Model generation and coordinate registration: Convert the cropped DEM data into a 3D mesh model and set the latitude and longitude of the model origin in the 3D software; perform georeferencing using the Unreal Engine's Georeferencing plug-in and correct the scene coordinate deviation in combination with error compensation parameters; (3) Dynamic data integration: access external data sources through real-time data interfaces to analyze and dynamically update the locations of POIs in the scene; (4) Scene optimization and output: Encapsulate the processed virtual texture and the corrected coordinate parameters into a configuration file to generate a high-precision digital twin scene.

[0005] Optionally, in step (1): The projection is converted to the CGCS 2000 3 Degree GK Zone 37 coordinate system (EPSG:4525); The clipping process is based on a preset Shp range file and clips the DEM and satellite image data by using a mask extraction tool; The satellite image data is divided into power-of-two resolution images using UDIM technology and mapped to UV space to generate virtual textures.

[0006] Optionally, in step (2): The georeferencing includes setting the latitude and longitude of the scene origin, selecting the Transverse Mercator projection type, and configuring the central meridian, false easting value, and geographic CRS parameters; The error compensation is performed by selecting multiple control points to construct an error equation and adjusting the curvature coefficient or origin offset so that the scene coordinate deviation is ≤0.5 meters.

[0007] Optionally, the curvature coefficient adjustment range of the error compensation is ±0.01, and the origin latitude and longitude offset adjustment amount is ±0.0001°.

[0008] Optionally, in step (3): The real-time data interface is connected to HTTP API, database or local file through Varest plug-in; The POI location is updated once per second, and the data fields are associated with POI attributes through a preset mapping relationship; When the POI position deviation exceeds the threshold, the error compensation algorithm is triggered and the scene configuration file is updated.

[0009] Optionally, the error compensation algorithm includes the following steps: (a) Record the latitude and longitude and engine coordinates of the abnormal point; (b) Call the curvature compensation formula to recalculate the correction amount; (c) Update the scene configuration file and synchronize it to all modules.

[0010] In a second aspect, an embodiment of the present application provides a high-precision digital twin scene construction system, including: Data acquisition module: used to obtain DEM and satellite image data from the geographic data platform; Data processing module: used to perform projection conversion, cropping and UDIM image segmentation; Coordinate registration module: integrates the Unreal Engine Georeferencing plug-in to achieve geographic coordinate conversion and error compensation; Dynamic update module: access real-time data through the Varest plug-in to dynamically generate and update POI points; Scene generation module: encapsulates virtual textures and correction parameters, and outputs high-precision digital twin scenes.

[0011] Optionally, the coordinate registration module further includes an error detection unit, configured to calculate deviations based on control points and automatically adjust the curvature coefficient or origin coordinates.

[0012] Optionally, the dynamic update module supports multiple data source types and is configured with abnormal point warning and automatic correction functions.

[0013] Optionally, the configuration file output by the scene generation module includes texture scaling parameters, projection parameters and curvature coefficients, and is in JSON or XML format.

[0014] Beneficial effects: The high-precision digital twin scene construction method provided by the present invention integrates multi-source geographic data and optimizes standardized processing procedures. It shortens the time required for traditional manual operation processes across multiple software from 40 hours per square kilometer to an automated processing mode, significantly reducing the need for human intervention and the error rate of operation, meeting the needs for rapid construction of large-scale digital twin scenes. It also uses a latitude and longitude coordinate system conversion plug-in and an error compensation algorithm to effectively solve the scene offset problem caused by coordinate system conversion in traditional solutions, reducing the conversion error between geographic data and three-dimensional scenes from ≥3 meters in the existing technology to ≤0.5 meters, meeting the high-precision application requirements of digital twins. By integrating the Varest plug-in and real-time data interface, it supports dynamic updates of POI points once per second, and can respond to data changes of IoT sensors, external APIs or databases in real time. It solves the update lag problem caused by the existing technology relying on static data tables, significantly improves the dynamic simulation capability of the scene, and by encapsulating virtual textures, coordinate parameters and projection configurations into standardized files, it realizes the rapid reuse and migration of scene configurations, reduces the workload of repeated development, and provides technical support for the rapid deployment of multi-scenario digital twin applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a flowchart of a high-precision digital twin scene construction method according to a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0016] The following is a clear and complete description of the technical solutions of the present invention. It should be understood that the embodiments described are only a portion of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are intended to fall within the scope of protection of the present invention.

[0017] Unless otherwise defined, the technical or scientific terms used in the present invention shall have the usual meanings understood by persons of ordinary skill in the field to which the present invention belongs. The words "first", "second" and similar terms used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. Similarly, words such as "one" or "a" do not indicate a quantity limitation, but rather indicate the existence of at least one. Words such as "connected" or "connected" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship also changes accordingly.

[0018] See Figure 1 , an embodiment of the present application provides a high-precision digital twin scene construction method, comprising the following steps: (1) Data acquisition and processing: Obtain digital elevation model (DEM) and satellite image data from the geographic data platform, and perform projection conversion and cropping; (2) Model generation and coordinate registration: Convert the cropped DEM data into a 3D mesh model and set the latitude and longitude of the model origin in the 3D software; perform georeferencing using the Unreal Engine's Georeferencing plug-in and correct the scene coordinate deviation in combination with error compensation parameters; (3) Dynamic data integration: access external data sources through real-time data interfaces to analyze and dynamically update the locations of POIs in the scene; (4) Scene optimization and output: Encapsulate the processed virtual texture and the corrected coordinate parameters into a configuration file to generate a high-precision digital twin scene.

[0019] Optionally, in step (1): The projection is converted to the CGCS 2000 3 Degree GK Zone 37 coordinate system (EPSG:4525); The clipping process is based on a preset Shp range file and clips the DEM and satellite image data by using a mask extraction tool; The satellite image data is divided into power-of-two resolution images using UDIM technology and mapped to UV space to generate virtual textures.

[0020] Optionally, in step (2): The georeferencing includes setting the latitude and longitude of the scene origin, selecting the Transverse Mercator projection type, and configuring the central meridian, false easting value, and geographic CRS parameters; The error compensation is performed by selecting multiple control points to construct an error equation and adjusting the curvature coefficient or origin offset so that the scene coordinate deviation is ≤0.5 meters.

[0021] Optionally, the curvature coefficient adjustment range of the error compensation is ±0.01, and the origin latitude and longitude offset adjustment amount is ±0.0001°.

[0022] Optionally, in step (3): The real-time data interface is connected to HTTP API, database or local file through Varest plug-in; The POI location is updated once per second, and the data fields are associated with POI attributes through a preset mapping relationship; When the POI position deviation exceeds the threshold, the error compensation algorithm is triggered and the scene configuration file is updated.

[0023] Optionally, the error compensation algorithm includes the following steps: (a) Record the latitude and longitude and engine coordinates of the abnormal point; (b) Call the curvature compensation formula to recalculate the correction amount; (c) Update the scene configuration file and synchronize it to all modules.

[0024] The present application also provides a high-precision digital twin scene construction system, including: Data acquisition module: used to obtain DEM and satellite image data from the geographic data platform; Data processing module: used to perform projection conversion, cropping and UDIM image segmentation; Coordinate registration module: integrates the Unreal Engine Georeferencing plug-in to achieve geographic coordinate conversion and error compensation; Dynamic update module: access real-time data through the Varest plug-in to dynamically generate and update POI points; Scene generation module: encapsulates virtual textures and correction parameters, and outputs high-precision digital twin scenes.

[0025] Optionally, the coordinate registration module further includes an error detection unit, configured to calculate deviations based on control points and automatically adjust the curvature coefficient or origin coordinates.

[0026] Optionally, the dynamic update module supports multiple data source types and is configured with abnormal point warning and automatic correction functions.

[0027] Optionally, the configuration file output by the scene generation module includes texture scaling parameters, projection parameters and curvature coefficients, and is in JSON or XML format.

[0028] The above describes in detail the preferred embodiments of the present invention. It should be understood that those skilled in the art can make numerous modifications and variations based on the concepts of the present invention without inventive effort. Therefore, any technical solutions that can be derived by those skilled in the art through logical analysis, reasoning, or limited experimentation based on the concepts of the present invention and the prior art should be within the scope of protection defined by the claims.

Claims

1. A high-precision digital twin scene construction method, characterized in that: The following steps are involved: (1) Data acquisition and processing: Obtain digital elevation model and satellite image data from the geographic data platform, and perform projection conversion and cropping on the digital elevation model and satellite image data to obtain DEM data; (2) Model generation and coordinate registration: Convert the cropped DEM data into a 3D mesh model, set the latitude and longitude of the model origin in the 3D software, perform georeferencing through the Georeferencing plug-in of the Unreal Engine, and correct the scene coordinate deviation in combination with the error compensation parameters; (3) Dynamic data integration: access external data sources through real-time data interfaces to analyze and dynamically update the locations of POIs in the scene; (4) Scene optimization and output: Encapsulate the processed virtual texture and the corrected coordinate parameters into a configuration file to generate a high-precision digital twin scene.

2. The high-precision digital twin scene construction method according to claim 1 is characterized in that: In step (1): The projection is converted to the CGCS 2000 3 Degree GK Zone 37 coordinate system; The clipping process is based on a preset Shp range file and clips the DEM and satellite image data by using a mask extraction tool; The satellite image data is divided into power-of-two resolution images using UDIM technology and mapped to UV space to generate virtual textures.

3. The high-precision digital twin scene construction method according to claim 1 is characterized in that: In step (2): The georeferencing includes setting the latitude and longitude of the scene origin, selecting the Transverse Mercator projection type, and configuring the central meridian, false easting value, and geographic CRS parameters; The error compensation is performed by selecting multiple control points to construct an error equation and adjusting the curvature coefficient or origin offset so that the scene coordinate deviation is ≤0.5 meters.

4. The high-precision digital twin scene construction method according to claim 3 is characterized in that: The curvature coefficient adjustment range of the error compensation is ±0.01, and the origin latitude and longitude offset adjustment amount is ±0.0001°.

5. The high-precision digital twin scene construction method according to claim 1 is characterized in that: In step (3): The real-time data interface is connected to HTTP API, database or local file through Varest plug-in; The POI location is updated once per second, and the data fields are associated with POI attributes through a preset mapping relationship; When the POI position deviation exceeds the threshold, the error compensation algorithm is triggered and the scene configuration file is updated.

6. The high-precision digital twin scene construction method according to claim 5 is characterized in that: The error compensation algorithm comprises the following steps: (a) Record the latitude and longitude and engine coordinates of the abnormal point; (b) Call the curvature compensation formula to recalculate the correction amount; (c) Update the scene configuration file and synchronize it to all modules.

7. A high-precision digital twin scene construction system, characterized by: include: Data acquisition module: used to obtain DEM and satellite image data from the geographic data platform; Data processing module: used to perform projection conversion, cropping and UDIM image segmentation; Coordinate registration module: integrates the Unreal Engine Georeferencing plug-in to achieve geographic coordinate conversion and error compensation; Dynamic update module: access real-time data through the Varest plug-in to dynamically generate and update POI points; Scene generation module: encapsulates virtual textures and correction parameters, and outputs high-precision digital twin scenes.

8. The high-precision digital twin scene construction system according to claim 7, characterized in that: The coordinate registration module further includes an error detection unit for calculating deviations based on control points and automatically adjusting curvature coefficients or origin coordinates.

9. The high-precision digital twin scene construction system according to claim 7, characterized in that: The dynamic update module supports multiple data source types and is configured with abnormal point warning and automatic correction functions.

10. The high-precision digital twin scene construction system according to claim 7, characterized in that: The configuration file output by the scene generation module includes texture scaling parameters, projection parameters and curvature coefficients, and is in JSON or XML format.

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