Three-dimensional model rapid construction method and system based on remote sensing data

Abstract

The invention relates to the technical field of model construction, and discloses a rapid three-dimensional model construction method and system based on remote sensing data, and the system comprises an acquisition module which is configured to obtain optimized RPC parameters; the model construction module is configured to construct a digital photogrammetry stereoscopic model based on the optimized RPC parameters and perform homonymy point matching; the identification module is configured to perform DEM sleeving precision inspection and determine a topographic change area in the to-be-monitored area based on an inspection result; the editing and modifying module is configured to perform repair and test updating on the DEM of the topographic change area according to a first precision standard to obtain repair and test updated DEM data; and the result detection module is configured to perform inspection and acceptance on the repair, test and update DEM data and the optimized DSM data, and if the inspection result is qualified, the repair, test and update DEM data and the optimized DSM data are output as final three-dimensional model construction results. According to the method, the efficiency and the precision of three-dimensional model construction are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of model construction, and in particular to a method and system for quickly constructing a three-dimensional model based on remote sensing data. Background Art

[0002] With the continuous development and advancement of remote sensing technology, the ability to use remote sensing data to construct 3D models has become a crucial technical tool. However, in practical applications, traditional 3D model construction methods often face a series of challenges and problems. These methods often require long construction cycles and struggle to achieve satisfactory model accuracy. Consequently, they often fail to meet modern society's demand for fast, efficient, and high-precision 3D model construction.

[0003] Therefore, it is necessary to design a method and system for quickly constructing a three-dimensional model based on remote sensing data to solve the problems existing in current technology. Summary of the Invention

[0004] In view of this, the present invention proposes a method and system for quickly constructing three-dimensional models based on remote sensing data, aiming to solve the problems in current technologies such as long construction cycle and low precision in three-dimensional model construction methods, which make it difficult to meet the needs of fast, efficient and high-precision three-dimensional model construction.

[0005] In one aspect, the present invention provides a system for rapidly constructing a three-dimensional model based on remote sensing data, comprising:

[0006] an acquisition module configured to acquire satellite remote sensing image data, satellite parameter data, and image control point result information of the area to be monitored, and perform aerial triangulation using an RPC model based on the satellite remote sensing image data, satellite parameter data, and image control point result information, and obtain optimized RPC parameters;

[0007] The model building module is configured to build a digital photogrammetric stereo model based on the optimized RPC parameters and perform homonymous point matching; collect DSM data after homonymous point matching is completed, and record it as homonymous point DSM data;

[0008] an identification module configured to convert the DEM result data into a format and obtain standard DEM result data, import the standard DEM result data into the digital photogrammetry stereo model, perform a DEM fitting accuracy check, and determine the terrain change area in the area to be monitored based on the check result;

[0009] The editing and modification module is configured to revise and update the DEM of the terrain change area according to a first accuracy standard, and perform edge processing on adjacent DEM sheets of the terrain change area to obtain revised and updated DEM data; it is also configured to perform elevation anomaly inspection on the DSM data of the same-name points according to a second accuracy standard, obtain elevation-exceeding areas of the area to be monitored, and edit, modify and mosaic-cut the DSM sheets of the elevation-exceeding areas to obtain optimized DSM data;

[0010] The result detection module is configured to inspect and accept the revised and updated DEM data and the optimized DSM data. If the inspection result is qualified, the revised and updated DEM data and the optimized DSM data are output as the final three-dimensional model construction result.

[0011] Furthermore, when the acquisition module performs aerial triangulation based on the satellite remote sensing image data, satellite parameter data and image control point result information using the RPC model and obtains optimized RPC parameters, it includes:

[0012] Using satellite parameter data, converting the satellite remote sensing image data into a ground geometric coordinate system;

[0013] Analyzing the satellite remote sensing image data to obtain a forward-looking image and a downward-looking image;

[0014] Analyzing the image control point result information to extract the measurement control points;

[0015] Combining the forward-view image and the downward-view image into a stereo pair, and measuring the measurement control point in the stereo pair;

[0016] Performing aerial triangulation and adjustment calculation based on the measurement control points;

[0017] The adjusted three-dimensional model is aligned with the ground truth coordinate system to generate the optimized RPC parameters.

[0018] Furthermore, when the model building module builds a digital photogrammetry stereo model based on the optimized RPC parameters and performs matching of homonymous points, it includes:

[0019] When the digital photogrammetry stereo model is used for observation, if the stereo image pair consisting of the forward-looking image and the downward-looking image is tilted with respect to the ground, the stereo image pair is replaced with the stereo image pair consisting of the forward-looking image and the rearward-looking image.

[0020] Furthermore, when the model building module builds a digital photogrammetry stereo model based on the optimized RPC parameters and performs matching of homonymous points, it further includes:

[0021] Perform pixel-by-pixel matching on the forward-looking image, the downward-looking image, and / or the rearward-looking image to collect the same-name points;

[0022] Image processing software is used to delete the same-name points that do not meet the second accuracy standard, and retain the same-name points that meet the second accuracy standard.

[0023] Furthermore, the recognition module imports the standard DEM result data into the digital photogrammetry stereo model and performs a DEM fitting accuracy check. When determining the terrain change area in the area to be monitored based on the check result, the following steps are included:

[0024] Check the fit between the DEM grid point elevation and the ground surface elevation, and obtain the fit accuracy;

[0025] Collect and analyze actual terrain data to obtain actual terrain changes;

[0026] Determine the terrain change area in the area to be monitored based on the fitting accuracy and the actual terrain change situation;

[0027] If the fitting accuracy exceeds the fitting accuracy limit, and the actual terrain change situation shows that the real-time terrain has changed and the area is greater than 10,000 square meters, the corresponding area will be determined as the terrain change area in the area to be monitored.

[0028] Furthermore, when the editing and modifying module updates the DEM of the terrain change area according to the first accuracy standard, it includes:

[0029] The DEM of the area with terrain changes is updated by using the characteristic point line difference method or directly editing the DEM grid point elevation;

[0030] The first accuracy standard is that when the terrain information is flat, the elevation error is determined to be 0.7 meters; when the terrain information is hilly, the elevation error is determined to be 1.7 meters; when the terrain information is mountainous, the elevation error is determined to be 3.3 meters.

[0031] Furthermore, the editing and modification module performs edge processing on adjacent DEM sheets in the terrain change area to obtain the revised and updated DEM data, including:

[0032] Conduct overlap analysis on the boundary areas of adjacent DEM sheets to determine the overlapping areas;

[0033] In the overlapping area, smooth transition processing is performed on adjacent map sheets based on the revised and updated DEM data, and quality inspection is performed on the processed adjacent DEM map sheets;

[0034] If the quality inspection is qualified, the adjacent DEM sheets after revision and update will be integrated and output as revised and updated DEM data.

[0035] Furthermore, the editing and modification module performs an elevation anomaly check on the DSM data of the same-name points according to the second accuracy standard, and when obtaining the elevation exceeding limit area of ​​the area to be monitored, includes:

[0036] Using the elevation anomaly detection algorithm to perform elevation anomaly inspection on the DSM data of the same-name points, and identifying elevation anomaly points;

[0037] Based on the distribution of the elevation anomaly points, determining the elevation exceeding limit area in the area to be monitored;

[0038] The second accuracy standard is a threshold for determining elevation anomaly points. When the elevation anomaly value exceeds the threshold, the corresponding area is determined as an elevation exceeding limit area.

[0039] The second accuracy standard is that when the terrain information is flat, the elevation error is determined to be 1.5 meters; when the terrain information is hilly, the elevation error is determined to be 2.5 meters; when the terrain information is mountainous, the elevation error is determined to be 4.0 meters.

[0040] Furthermore, the editing and modification module edits, modifies and mosaics the DSM map sheets of the elevation-exceeding-limit area to obtain optimized DSM data, including:

[0041] Import the DSM data into the DSM editing software, perform splicing according to the scope of the area to be monitored, and correct the errors at the edges of the maps;

[0042] Use the automatic cropping tool to crop the map based on the 1:10,000 scale plus an extrapolation of 10 meters to generate a standardized tiled DSM.

[0043] Conduct quality inspection on the cut DSM;

[0044] If the quality inspection is qualified, the edited, modified and mosaicked DSM data will be integrated and output as optimized DSM data.

[0045] Compared with existing technologies, the present invention offers the following advantages: The remote sensing data-based rapid 3D model construction system provided by the present invention significantly improves the efficiency and accuracy of 3D model construction through a highly integrated module design and refined data processing workflow. Specifically, the system automatically collects and analyzes satellite remote sensing image data, combines satellite parameters and image control point information, and optimizes RPC parameters through aerial triangulation, providing a solid foundation for subsequent digital photogrammetry stereo model construction. The model construction module utilizes the optimized RPC parameters to efficiently match synonyms and collect DSM data, providing an accurate data source for subsequent terrain change identification and DEM revision and update. The identification module accurately identifies areas of terrain change through DEM fit accuracy checks, providing clear guidance for subsequent editing and modification. The editing and modification module updates and edits DEM and DSM data according to strict accuracy standards, ensuring that the final 3D model output is both accurate and meets practical application requirements. The result detection module conducts comprehensive inspection and acceptance of the updated DEM and optimized DSM data to ensure the quality and reliability of the output data. In general, the system and method for rapid construction of three-dimensional models based on remote sensing data proposed in the present invention show significant advantages in improving the efficiency, accuracy and practicality of three-dimensional model construction, and have broad application prospects.

[0046] In another aspect, the present invention also proposes a method for rapidly constructing a three-dimensional model based on remote sensing data, comprising the following steps:

[0047] S100: collecting satellite remote sensing image data, satellite parameter data and image control point result information of the area to be monitored, and performing aerial triangulation using an RPC model based on the satellite remote sensing image data, satellite parameter data and image control point result information, and obtaining optimized RPC parameters;

[0048] S200: constructing a digital photogrammetric stereo model based on the optimized RPC parameters and performing homonymous point matching; collecting DSM data after homonymous point matching is completed, and recording it as homonymous point DSM data;

[0049] S300: converting the DEM result data into a format and obtaining standard DEM result data, importing the standard DEM result data into the digital photogrammetry stereo model, performing a DEM fitting accuracy check, and determining the terrain change area in the area to be monitored based on the check result;

[0050] S400: The DEM of the terrain change area is revised and updated according to a first accuracy standard, and adjacent DEM sheets of the terrain change area are edge-joined to obtain revised and updated DEM data; the method is further configured to perform an elevation anomaly check on the DSM data of the same-name points according to a second accuracy standard, obtain elevation-exceeding areas of the area to be monitored, and edit, modify, and mosaic-cut the DSM sheets of the elevation-exceeding areas to obtain optimized DSM data;

[0051] S500: Check and accept the revised and updated DEM data and the optimized DSM data. If the inspection result is qualified, output the revised and updated DEM data and the optimized DSM data as the final three-dimensional model construction result.

[0052] It is understandable that the above-mentioned method and system for rapidly constructing a three-dimensional model based on remote sensing data have the same beneficial effects, and will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0054] Figure 1 A structural block diagram of a system for rapidly constructing a three-dimensional model based on remote sensing data provided by an embodiment of the present invention;

[0055] Figure 2 This is a flowchart of a method for rapidly constructing a three-dimensional model based on remote sensing data provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0057] See Figure 1 As shown, in some embodiments of the present application, this embodiment provides a system for rapidly constructing a three-dimensional model based on remote sensing data, including:

[0058] an acquisition module configured to acquire satellite remote sensing image data, satellite parameter data, and image control point result information of the area to be monitored, and perform aerial triangulation using an RPC model based on the satellite remote sensing image data, satellite parameter data, and image control point result information, and obtain optimized RPC parameters;

[0059] The model building module is configured to build a digital photogrammetric stereo model based on the optimized RPC parameters and perform homonymous point matching; collect DSM data after homonymous point matching is completed, and record it as homonymous point DSM data;

[0060] an identification module configured to convert the DEM result data into a format and obtain standard DEM result data, import the standard DEM result data into the digital photogrammetry stereo model, perform a DEM fitting accuracy check, and determine the terrain change area in the area to be monitored based on the check result;

[0061] The editing and modification module is configured to revise and update the DEM of the terrain change area according to a first accuracy standard, and perform edge processing on adjacent DEM sheets of the terrain change area to obtain revised and updated DEM data; it is also configured to perform elevation anomaly inspection on the DSM data of the same-name points according to a second accuracy standard, obtain elevation-exceeding areas of the area to be monitored, and edit, modify and mosaic-cut the DSM sheets of the elevation-exceeding areas to obtain optimized DSM data;

[0062] The result detection module is configured to inspect and accept the revised and updated DEM data and the optimized DSM data. If the inspection result is qualified, the revised and updated DEM data and the optimized DSM data are output as the final three-dimensional model construction result.

[0063] It is understood that the remote sensing data-based rapid 3D model construction system provided in this embodiment significantly improves the efficiency and accuracy of 3D model construction through its highly integrated module design and refined data processing process. Specifically, the system automatically collects and analyzes satellite remote sensing image data, combines satellite parameters and image control point information, and optimizes RPC parameters through aerial triangulation, providing a solid foundation for subsequent digital photogrammetry stereo model construction. The model construction module utilizes the optimized RPC parameters to efficiently match synonyms and collect DSM data, providing an accurate data source for subsequent terrain change identification and DEM revision and update. The identification module accurately identifies areas of terrain change through DEM fit accuracy checks, providing clear guidance for subsequent editing and modification. The editing and modification module performs revision, update, and editing of DEM and DSM data according to strict accuracy standards, ensuring that the final output 3D model data is both accurate and meets practical application requirements. The result detection module conducts comprehensive inspection and acceptance of the revised, updated DEM data and optimized DSM data to ensure the quality and reliability of the output data. In general, the system and method for rapidly constructing a three-dimensional model based on remote sensing data proposed in this embodiment show significant advantages in improving the efficiency, accuracy and practicality of three-dimensional model construction, and have broad application prospects.

[0064] Specifically, the acquisition module performs aerial triangulation based on the satellite remote sensing image data, satellite parameter data, and image control point result information using the RPC model, and obtains optimized RPC parameters, including:

[0065] Using satellite parameter data, converting the satellite remote sensing image data into a ground geometric coordinate system;

[0066] Analyzing the satellite remote sensing image data to obtain a forward-looking image and a downward-looking image;

[0067] Analyzing the image control point result information to extract the measurement control points;

[0068] Combining the forward-view image and the downward-view image into a stereo pair, and measuring the measurement control point in the stereo pair;

[0069] Performing aerial triangulation and adjustment calculation based on the measurement control points;

[0070] The adjusted three-dimensional model is aligned with the ground truth coordinate system to generate the optimized RPC parameters.

[0071] It's clear that during aerial triangulation, the RPC model accurately analyzes satellite remote sensing imagery data, effectively improving its geometric accuracy. By measuring control points within stereo pairs of forward- and downward-looking images, the geometric consistency between the image data is further enhanced. Adjustment calculations further eliminate errors in the image data, ensuring perfect alignment of the resulting 3D model with the ground truth coordinate system. This optimized RPC parameter acquisition process provides highly accurate foundational data for subsequent digital photogrammetry stereo model construction, ensuring the accuracy and reliability of the entire rapid 3D model construction system.

[0072] Specifically, the model building module builds a digital photogrammetry stereo model based on the optimized RPC parameters and performs matching of homonymous points, including:

[0073] When the digital photogrammetry stereo model is used for observation, if the stereo image pair consisting of the forward-looking image and the downward-looking image is tilted with respect to the ground, the stereo image pair is replaced with the stereo image pair consisting of the forward-looking image and the rearward-looking image.

[0074] It is understandable that, in the process of constructing a digital photogrammetric stereo model, ground tilt may cause geometric inconsistencies between stereo pairs, thereby affecting subsequent matching of homonymous points and DSM data acquisition. Therefore, the model construction module of this embodiment can intelligently identify and handle such ground tilt during observation. When it is found that the stereo pair consisting of the forward-looking image and the downward-looking image has ground tilt, the module will automatically replace it with a stereo pair consisting of the forward-looking image and the rearward-looking image. This flexible stereo pair selection strategy ensures the accuracy and stability of the digital photogrammetric stereo model construction, and provides a more reliable data basis for subsequent terrain change identification and DEM revision and update.

[0075] Specifically, when the model building module builds a digital photogrammetry stereo model based on the optimized RPC parameters and performs matching of homonymous points, it also includes:

[0076] Perform pixel-by-pixel matching on the forward-looking image, the downward-looking image, and / or the rearward-looking image to collect the same-name points;

[0077] Image processing software is used to delete the same-name points that do not meet the second accuracy standard, and retain the same-name points that meet the second accuracy standard.

[0078] It is understood that during the matching of homonymous points, the pixel-by-pixel matching strategy between images ensures the accurate collection of homonymous points, while the use of image processing software for precision screening further enhances the reliability and accuracy of homonymous points. This is crucial for subsequent terrain change identification and DEM revision and update, as only accurate and reliable homonymous point data can effectively support these processing steps. Overall, the model construction module of this embodiment significantly improves the quality and efficiency of digital photogrammetry stereo model construction through intelligent stereo image pair selection and refined homonymous point matching strategies, providing a solid foundation for the subsequent rapid construction of three-dimensional models.

[0079] Specifically, the recognition module imports the standard DEM result data into the digital photogrammetry stereo model and performs a DEM fitting accuracy check. When determining the terrain change area in the area to be monitored based on the check result, the following steps are included:

[0080] Check the fit between the DEM grid point elevation and the ground surface elevation, and obtain the fit accuracy;

[0081] Collect and analyze actual terrain data to obtain actual terrain changes;

[0082] Determine the terrain change area in the area to be monitored based on the fitting accuracy and the actual terrain change situation;

[0083] If the fitting accuracy exceeds the fitting accuracy limit, and the actual terrain change situation shows that the real-time terrain has changed and the area is greater than 10,000 square meters, the corresponding area will be determined as the terrain change area in the area to be monitored.

[0084] It is understandable that, in the DEM fitting accuracy check process, by comparing the fitting of the DEM grid point elevation and the ground surface elevation, the degree of consistency between the DEM data and the real terrain can be intuitively reflected. At the same time, by collecting the actual terrain data for analysis, more detailed and accurate actual terrain changes can be obtained. Combining the fitting accuracy with the actual terrain changes, the terrain change areas in the area to be monitored can be determined more accurately. Especially when the fitting accuracy exceeds the limit and the actual terrain changes over a large area, the system can automatically mark these areas as terrain change areas, providing clear guidance for subsequent processing steps. This not only improves the accuracy and efficiency of terrain change identification, but also ensures the pertinence and effectiveness of subsequent DEM revision and update and DSM data editing and modification. Overall, the recognition module of the present embodiment provides reliable terrain data support for the rapid construction of a three-dimensional model through refined DEM fitting accuracy inspection and intelligent terrain change area determination strategy.

[0085] Specifically, when the editing and modification module updates the DEM of the terrain change area according to the first accuracy standard, it includes:

[0086] The DEM of the area with terrain changes is updated by using the characteristic point line difference method or directly editing the DEM grid point elevation;

[0087] The first accuracy standard is that when the terrain information is flat, the elevation error is determined to be 0.7 meters; when the terrain information is hilly, the elevation error is determined to be 1.7 meters; when the terrain information is mountainous, the elevation error is determined to be 3.3 meters.

[0088] It is understandable that during the DEM revision and update process, the characteristic point line difference method or the method of directly editing the DEM grid point elevation can make precise adjustments for different terrain features. The characteristic point line difference method makes fine corrections to the DEM data by analyzing the differences between terrain feature points and feature lines to ensure the accuracy and continuity of terrain features. Directly editing the DEM grid point elevation is suitable for situations where local terrain changes are small or rapid corrections are required. At the same time, the setting of the first accuracy standard fully considers the different requirements of different terrain information for elevation accuracy. Flat land, hills and mountains correspond to different elevation error limits. This differentiated accuracy control strategy not only ensures the accuracy and reliability of DEM revision and update, but also avoids unnecessary waste of accuracy, thereby improving the efficiency and practicality of the entire three-dimensional model rapid construction system.

[0089] Specifically, the editing and modification module performs edge processing on adjacent DEM sheets in the terrain change area to obtain the revised and updated DEM data, including:

[0090] Conduct overlap analysis on the boundary areas of adjacent DEM sheets to determine the overlapping areas;

[0091] In the overlapping area, smooth transition processing is performed on adjacent map sheets based on the revised and updated DEM data, and quality inspection is performed on the processed adjacent DEM map sheets;

[0092] If the quality inspection is qualified, the adjacent DEM sheets after revision and update will be integrated and output as revised and updated DEM data.

[0093] Understandably, during the DEM sheet edge-joining process, the boundary areas between adjacent DEM sheets often exhibit a certain degree of inconsistency. Overlap analysis of these boundary areas identifies the overlapping regions requiring attention. Within these overlapping regions, smooth transitions are performed between adjacent sheets based on the updated DEM data to ensure continuity and consistency of topographic features between the adjacent sheets. This smooth transition typically involves interpolation or weighted averaging of the DEM data within the overlapping region to reduce or eliminate errors introduced during data acquisition and processing. The processed adjacent DEM sheets undergo quality checks to ensure they meet accuracy requirements and practical application needs. This quality check may include checking elevation accuracy and topographic consistency. Only after passing these quality checks can the updated adjacent DEM sheets be combined and output as the final updated DEM data. This edge-joining process not only improves the continuity and consistency of the DEM data but also ensures the accuracy and reliability of data integration within the entire rapid 3D model construction system.

[0094] Specifically, the editing and modification module performs an elevation anomaly check on the DSM data of the same-name points according to the second accuracy standard, and when obtaining the elevation exceeding limit area of ​​the area to be monitored, includes:

[0095] Using the elevation anomaly detection algorithm to perform elevation anomaly inspection on the DSM data of the same-name points, and identifying elevation anomaly points;

[0096] Based on the distribution of the elevation anomaly points, determining the elevation exceeding limit area in the area to be monitored;

[0097] The second accuracy standard is a threshold for determining elevation anomaly points. When the elevation anomaly value exceeds the threshold, the corresponding area is determined as an elevation exceeding limit area.

[0098] The second accuracy standard is that when the terrain information is flat, the elevation error is determined to be 1.5 meters; when the terrain information is hilly, the elevation error is determined to be 2.5 meters; when the terrain information is mountainous, the elevation error is determined to be 4.0 meters.

[0099] It is understandable that the elevation anomaly detection algorithm plays a key role in the elevation anomaly inspection process of DSM data with the same name. The algorithm can comprehensively scan the same name points in the DSM data and accurately identify elevation anomaly points by comparing and analyzing the elevation information of these points. These elevation anomaly points are often a direct reflection of terrain changes or data errors, so their identification is crucial for determining areas with elevation violations. When determining areas with elevation violations, the algorithm further considers the distribution of elevation anomaly points. If elevation anomaly points appear densely in a certain area and their elevation anomaly values ​​exceed the preset threshold, then the area will be determined as an elevation violation area. This judgment process not only relies on the number of elevation anomaly points, but also fully considers their spatial distribution characteristics, thereby ensuring the accuracy and rationality of the determination of elevation violation areas.

[0100] Specifically, the editing and modification module edits, modifies, and mosaics the DSM map sheets of the elevation-exceeding-limit area to obtain optimized DSM data, including:

[0101] Import the DSM data into the DSM editing software, perform splicing according to the scope of the area to be monitored, and correct the errors at the edges of the maps;

[0102] Use the automatic cropping tool to crop the map based on the 1:10,000 scale plus an extrapolation of 10 meters to generate a standardized tiled DSM.

[0103] Conduct quality inspection on the cut DSM;

[0104] If the quality inspection is qualified, the edited, modified and mosaicked DSM data will be integrated and output as optimized DSM data.

[0105] Understandably, ensuring data consistency and accuracy is crucial during the editing, modification, and mosaicking process of DSM tiles. First, DSM data is imported into professional DSM editing software and stitched together according to the actual extent of the monitored area. This allows DSM data from different sources to form a complete dataset. During the stitching process, particular attention is paid to errors at the edges of the tiles, and necessary corrections are made to ensure continuity and consistency of topographic features between adjacent tiles. Next, the stitched DSM data is cropped using an automatic cropping tool. The cropping standard is set to a 1:10,000 tile with a 10-meter expansion. This standard takes into account practical application needs while ensuring data integrity and standardization. The cropped DSM tiles undergo rigorous quality checks, including elevation accuracy and topographic consistency. Only after passing these quality checks can the edited, modified, and mosaicked DSM tiles be integrated for the final optimized DSM output. This processing not only improves the accuracy and reliability of DSM data, but also ensures the standardization and practicality of the data output of the entire 3D model rapid construction system.

[0106] See Figure 2 As shown, in some embodiments of the present application, this embodiment provides a method for quickly constructing a three-dimensional model based on remote sensing data, including the following steps:

[0107] S100: collecting satellite remote sensing image data, satellite parameter data and image control point result information of the area to be monitored, and performing aerial triangulation using an RPC model based on the satellite remote sensing image data, satellite parameter data and image control point result information, and obtaining optimized RPC parameters;

[0108] S200: constructing a digital photogrammetric stereo model based on the optimized RPC parameters and performing homonymous point matching; collecting DSM data after homonymous point matching is completed, and recording it as homonymous point DSM data;

[0109] S300: converting the DEM result data into a format and obtaining standard DEM result data, importing the standard DEM result data into the digital photogrammetry stereo model, performing a DEM fitting accuracy check, and determining the terrain change area in the area to be monitored based on the check result;

[0110] S400: The DEM of the terrain change area is revised and updated according to a first accuracy standard, and adjacent DEM sheets of the terrain change area are edge-joined to obtain revised and updated DEM data; the method is further configured to perform an elevation anomaly check on the DSM data of the same-name points according to a second accuracy standard, obtain elevation-exceeding areas of the area to be monitored, and edit, modify, and mosaic-cut the DSM sheets of the elevation-exceeding areas to obtain optimized DSM data;

[0111] S500: Check and accept the revised and updated DEM data and the optimized DSM data. If the inspection result is qualified, output the revised and updated DEM data and the optimized DSM data as the final three-dimensional model construction result.

[0112] It is understandable that the inspection and acceptance of the revised and updated DEM data and the optimized DSM data includes a comprehensive quality assessment of the revised and updated DEM data and the optimized DSM data. The content of the quality assessment includes but is not limited to elevation accuracy, consistency of terrain features, data integrity and other aspects. By comparing the actual terrain data with the revised and updated DEM data and the optimized DSM data, the accuracy and reliability of the data can be intuitively evaluated. At the same time, it is also necessary to check whether errors or inconsistencies have occurred in the data during processing such as splicing and cropping. Only when all quality assessment indicators meet the preset standards can the revised and updated DEM data and the optimized DSM data be considered qualified and can be output as the final three-dimensional model construction result. This process ensures that the data output by the three-dimensional model rapid construction system is both accurate and reliable, providing a solid foundation for subsequent applications.

[0113] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware embodiments. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0114] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0115] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0116] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A system for rapidly constructing three-dimensional models based on remote sensing data, characterized in that: include: an acquisition module configured to acquire satellite remote sensing image data, satellite parameter data, and image control point result information of the area to be monitored, and perform aerial triangulation using an RPC model based on the satellite remote sensing image data, satellite parameter data, and image control point result information, and obtain optimized RPC parameters; The model building module is configured to build a digital photogrammetric stereo model based on the optimized RPC parameters and perform homonymous point matching; collect DSM data after homonymous point matching is completed, and record it as homonymous point DSM data; an identification module configured to convert the DEM result data into a format and obtain standard DEM result data, import the standard DEM result data into the digital photogrammetry stereo model, perform a DEM fitting accuracy check, and determine the terrain change area in the area to be monitored based on the check result; The editing and modification module is configured to revise and update the DEM of the terrain change area according to a first accuracy standard, and perform edge processing on adjacent DEM sheets of the terrain change area to obtain revised and updated DEM data; it is also configured to perform elevation anomaly inspection on the DSM data of the same-name points according to a second accuracy standard, obtain elevation-exceeding areas of the area to be monitored, and edit, modify and mosaic-cut the DSM sheets of the elevation-exceeding areas to obtain optimized DSM data; The result detection module is configured to inspect and accept the revised and updated DEM data and the optimized DSM data. If the inspection result is qualified, the revised and updated DEM data and the optimized DSM data are output as the final three-dimensional model construction result.

2. The system for rapidly constructing a three-dimensional model based on remote sensing data according to claim 1, characterized in that: The acquisition module performs aerial triangulation based on the satellite remote sensing image data, satellite parameter data and image control point result information using the RPC model and obtains optimized RPC parameters, including: Using satellite parameter data, converting the satellite remote sensing image data into a ground geometric coordinate system; Analyzing the satellite remote sensing image data to obtain a forward-looking image and a downward-looking image; Analyzing the image control point result information to extract the measurement control points; Combining the forward-view image and the downward-view image into a stereo pair, and measuring the measurement control point in the stereo pair; Performing aerial triangulation and adjustment calculation based on the measurement control points; The adjusted three-dimensional model is aligned with the ground truth coordinate system to generate the optimized RPC parameters.

3. The system for rapidly constructing a three-dimensional model based on remote sensing data according to claim 2, characterized in that: The model building module builds a digital photogrammetry stereo model based on the optimized RPC parameters and performs matching of homonymous points, including: When the digital photogrammetry stereo model is used for observation, if the stereo image pair consisting of the forward-looking image and the downward-looking image is tilted with respect to the ground, the stereo image pair is replaced with the stereo image pair consisting of the forward-looking image and the rearward-looking image.

4. The system for rapidly constructing a three-dimensional model based on remote sensing data according to claim 3, characterized in that: When the model building module builds a digital photogrammetry stereo model based on the optimized RPC parameters and performs matching of homonymous points, it also includes: Perform pixel-by-pixel matching on the forward-looking image, the downward-looking image, and / or the rearward-looking image to collect the same-name points; Image processing software is used to delete the same-name points that do not meet the second accuracy standard, and retain the same-name points that meet the second accuracy standard.

5. The system for rapidly constructing a three-dimensional model based on remote sensing data according to claim 4, characterized in that: The identification module imports the standard DEM result data into the digital photogrammetry stereo model and performs a DEM fitting accuracy check. When determining the terrain change area in the area to be monitored based on the check result, the following steps are included: Check the fit between the DEM grid point elevation and the ground surface elevation, and obtain the fit accuracy; Collect and analyze actual terrain data to obtain actual terrain changes; Determine the terrain change area in the area to be monitored based on the fitting accuracy and the actual terrain change situation; If the fitting accuracy exceeds the fitting accuracy limit, and the actual terrain change situation shows that the real-time terrain has changed and the area is greater than 10,000 square meters, the corresponding area will be determined as the terrain change area in the area to be monitored.

6. The system for rapidly constructing a three-dimensional model based on remote sensing data according to claim 5, characterized in that: When the editing and modifying module updates the DEM of the terrain change area according to the first accuracy standard, it includes: The DEM of the area with terrain changes is updated by using the characteristic point line difference method or directly editing the DEM grid point elevation; The first accuracy standard is that when the terrain information is flat, the elevation error is determined to be 0.7 meters; when the terrain information is hilly, the elevation error is determined to be 1.7 meters; when the terrain information is mountainous, the elevation error is determined to be 3.3 meters.

7. The system for rapidly constructing a three-dimensional model based on remote sensing data according to claim 6, characterized in that: The editing and modification module performs edge processing on adjacent DEM sheets in the terrain change area to obtain the revised and updated DEM data, including: Conduct overlap analysis on the boundary areas of adjacent DEM sheets to determine the overlapping areas; In the overlapping area, smooth transition processing is performed on adjacent map sheets based on the revised and updated DEM data, and quality inspection is performed on the processed adjacent DEM map sheets; If the quality inspection is qualified, the adjacent DEM sheets after revision and update will be integrated and output as revised and updated DEM data.

8. The system for rapidly constructing a three-dimensional model based on remote sensing data according to claim 7, characterized in that: The editing and modification module performs a full-map elevation anomaly check on the DSM data of the same-name points according to the second accuracy standard, and when obtaining an elevation exceeding limit area of ​​the area to be monitored, includes: Using the elevation anomaly detection algorithm to perform elevation anomaly inspection on the DSM data of the same-name points, and identifying elevation anomaly points; Based on the distribution of the elevation anomaly points, determining the elevation exceeding limit area in the area to be monitored; The second accuracy standard is a threshold for determining elevation anomaly points. When the elevation anomaly value exceeds the threshold, the corresponding area is determined as an elevation exceeding limit area. The second accuracy standard is that when the terrain information is flat, the elevation error is determined to be 1.5 meters; when the terrain information is hilly, the elevation error is determined to be 2.5 meters; when the terrain information is mountainous, the elevation error is determined to be 4.0 meters.

9. The system for rapidly constructing a three-dimensional model based on remote sensing data according to claim 8, characterized in that: The editing and modification module edits, modifies and mosaics the DSM map sheets of the elevation-exceeding-limit area to obtain optimized DSM data, including: Import the DSM data into the DSM editing software, perform splicing according to the scope of the area to be monitored, and correct the errors at the edges of the maps; Use the automatic cropping tool to crop the map based on the 1:10,000 scale plus an extrapolation of 10 meters to generate a standardized tiled DSM. Conduct quality inspection on the cut DSM; If the quality inspection is qualified, the edited, modified and mosaicked DSM data will be integrated and output as optimized DSM data.

10. A method for rapidly constructing a three-dimensional model based on remote sensing data, applied to a system for rapidly constructing a three-dimensional model based on remote sensing data as claimed in any one of claims 1 to 9, characterized in that: include: Collect satellite remote sensing image data, satellite parameter data and image control point result information of the area to be monitored, and use the RPC model to perform aerial triangulation based on the satellite remote sensing image data, satellite parameter data and image control point result information to obtain optimized RPC parameters; A digital photogrammetric stereo model is constructed based on the optimized RPC parameters, and homonymous point matching is performed; DSM data after homonymous point matching is completed is collected and recorded as homonymous point DSM data; Converting the DEM result data into a format and obtaining standard DEM result data, importing the standard DEM result data into the digital photogrammetry stereo model, and performing a DEM fitting accuracy check, and determining the terrain change area in the area to be monitored based on the check results; The DEM of the terrain change area is revised and updated according to the first accuracy standard, and adjacent DEM sheets of the terrain change area are edge-joined to obtain revised and updated DEM data; the DSM data of the same-name points are checked for elevation anomalies throughout the entire map according to the second accuracy standard to obtain elevation-exceeding areas of the area to be monitored, and the DSM sheets of the elevation-exceeding areas are edited, modified, and mosaicked to obtain optimized DSM data; The revised and updated DEM data and the optimized DSM data are inspected and accepted. If the inspection result is qualified, the revised and updated DEM data and the optimized DSM data are output as the final three-dimensional model construction result.

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