A high-altitude area large-scale DLG production method and system

Abstract

The application discloses a high-altitude high-region large-scale DLG production method and system, and mainly relates to the field of surveying and mapping science and technology. The production method mainly comprises an image data acquisition step, an overlapping degree design step, a DLG plane element acquisition step and a DLG elevation element acquisition step. The production system is used for realizing the production method and mainly comprises an image data acquisition module, a data processing and element acquisition module, an overlapping degree design unit, a plane element acquisition unit and an elevation element acquisition unit. The application has the beneficial effect of improving the all-time period and all-space height layer aerial image data acquisition and processing capability of the industry.

Description

Technical Field

[0001] This invention relates to the field of surveying and mapping science and technology, specifically a method and system for rapidly acquiring high-resolution aerial imagery data in high-altitude and high-requirement areas and producing large-scale DLG. Background Technology

[0002] Large-scale DLG production relies on high-resolution aerial imagery data that is highly up-to-date. For the production of large-scale DLGs in high-altitude, high-requirement areas, the acquisition of high-resolution aerial imagery data traditionally involves large aerial cameras or drones. However, this approach presents the following problems in practical applications: 1. Conventional large aerial cameras often fly at low altitudes when acquiring high-resolution images. For operational areas with high altitude requirements, such as the airspace above civil airports, the flight altitude cannot meet the requirements. 2. When using a fleet of unmanned aerial vehicles (UAVs) to perform high-resolution image acquisition tasks over civil aviation airports, the limited operation time is affected by airport flights, resulting in short operation time, low average operation efficiency, and lack of image data quality and accuracy. 3. There are difficulties in acquiring high-resolution aerial images in high-altitude and high-requirement areas, as well as in mapping and DLG production.

[0003] Therefore, there is an urgent need for a method and system for producing large-scale DLGs in high-altitude and high-area regions to solve the above problems. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for producing large-scale DLG images in high-altitude areas, which improves the industry's ability to acquire and process aerial imagery data at all times and in all airspace.

[0005] To achieve the above objectives, the present invention employs the following technical solution: On the one hand, the present invention provides a method for producing large-scale DLGs in high-altitude areas, comprising the following steps: Step S1, Image Data Acquisition Step: Using an ultra-long telephoto aerial camera, fly in the operation area that meets the preset high altitude requirements to acquire high-resolution aerial image data of the area. The image data has a very small base-to-height ratio. Step S2, Overlap Design Step: For image data with extremely small base-to-height ratio, based on the photogrammetric model, analyze the relationship between base-to-height ratio and measurement accuracy, and determine a forward and lateral overlap design strategy that takes into account both data applicability and production efficiency; organize the acquired raw image data according to the overlap design strategy. Step S3, DLG planar feature acquisition steps: Based on the image data organized by the overlap design strategy, perform aerial triangulation processing to generate aerial triangulation densification results; using the aerial triangulation densification results, perform indoor stereo data acquisition under the stereo model, and combine field mapping and data editing to complete the production of large-scale DLG planar feature data; Step S4, DLG elevation feature acquisition step: Based on the original image data that has not been thinned according to the strategy in step S2, a three-dimensional model is constructed to generate a three-dimensional model containing high-precision terrain information; elevation point information is obtained by naked-eye acquisition based on the three-dimensional model, and combined with field verification and data editing, the production of large-scale DLG elevation feature data is completed.

[0006] Preferably, in step S1, the focal length of the super telephoto lens is 300mm and the pixel count is not less than 150 million; the preset high flight altitude requirement is a flight altitude between 3000 meters and 3600 meters; and the minimum base-to-altitude ratio is 0.03.

[0007] Preferably, in step S2, the overlap design strategy is specifically as follows: Set the lateral overlap to 40% and the heading overlap to 80%. For images used in stereo mapping, the image data with a forward overlap of 80% is thinned down to 60% for use.

[0008] Preferably, in step S3, the aerial triangulation processing includes: Data preparation and project setup, connection point matching, control point measurement and regional network adjustment calculation, quality assessment; The indoor three-dimensional data acquisition includes: directional modeling based on the results of aerial triangulation, and element acquisition and question marking under the three-dimensional model.

[0009] Preferably, in the tie point matching step, tie points are automatically extracted and adjusted by setting the matching algorithm, matching density, and GNSS / IMU parameter weights; The automatic extraction and adjustment calculation of the connection points are specifically as follows: in the aerial triangulation software, a feature point matching algorithm is selected, the density value of the extracted connection points is set, and corresponding weight values ​​are assigned in the adjustment model based on the measured GNSS positioning accuracy and IMU attitude accuracy data of the airborne POS system.

[0010] The quality assessment includes: determining the mean square error of the horizontal position and elevation of the connection point relative to the nearest field control point, and determining whether the mean square error between the basic orientation point and the assessment point meets the preset specification requirements.

[0011] Preferably, in step S4, the construction of the three-dimensional model includes: Aerial triangulation encryption is applied to the image data; Digital Surface Model (DSM) is generated using a dense matching algorithm; Based on aerial triangulation results, original images, and DSM, a white model is constructed and texture mapping is performed to generate an initial 3D model; The initial 3D model is modified, including correcting anomalies in surface suspended matter, building cavities, water surfaces, ground surfaces, mountains, and vegetation areas.

[0012] On the other hand, the present invention also provides a large-scale DLG production system for high-altitude areas, used to implement the above-described method for producing large-scale DLGs for high-altitude areas, including: The image data acquisition module is used to acquire high-resolution aerial image data with a very small base-to-height ratio in areas that meet the high requirements of high-altitude aerial photography by using a large aerial camera equipped with a modified ultra-telephoto lens. A data processing and feature acquisition module, connected to the image data acquisition module, includes: The overlap design unit is used to formulate the optimal overlap strategy for image data with minimal basal-to-height ratio based on a preset photogrammetric model, and to organize the original image data. The planar feature acquisition unit is used to perform aerial triangulation and stereo mapping processes based on the organized image data, and to complete the acquisition and production of DLG planar feature data. The elevation feature acquisition unit is used to execute the 3D model construction process based on the original image data, and to complete the acquisition and production of DLG elevation feature data through naked-eye acquisition based on the generated 3D model.

[0013] Preferably, the planar feature acquisition unit includes: The aerial triangulation subunit is used to perform tie point matching, control point measurement and regional network adjustment calculation, and output aerial triangulation densification results; The stereo mapping subunit is used to import the aerial triangulation results, restore the stereo model, collect indoor elements, and manage the field mapping and data editing process.

[0014] Preferably, the elevation element acquisition unit includes: The 3D modeling subunit is used to perform image dense matching to generate a DSM, and to construct and refine a 3D model based on the DSM and the original image. The elevation acquisition subunit is used to provide a naked-eye acquisition interface to acquire and update elevation point information based on the three-dimensional model.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention utilizes existing large aerial cameras equipped with ultra-long telephoto camera lenses to achieve large-area rapid acquisition of high-resolution aerial image data in areas with special flight altitude requirements; 2. This invention utilizes the acquired aerial imagery data with extremely low base-to-height ratio to achieve the production and updating of DLGs in high-altitude and high-requirement areas through a combination of stereo mapping and 3D model elevation mapping; 3. This invention fills the technological gap in mapping using image data with extremely small base-to-height ratios, and improves the industry's ability to acquire and process aerial image data at all altitude levels throughout the day and in all airspace. Attached Figure Description

[0016] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a flowchart of the aerial triangulation encryption process of the present invention; Figure 3 This is a flowchart of the DLG planar feature acquisition process of the present invention; Figure 4 This is a flowchart of the three-dimensional model construction process of the present invention; Figure 5 This is a flowchart of the DLG elevation element acquisition process of the present invention; Figure 6 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0017] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined in this application.

[0018] In this invention, terms such as "upper," "lower," "left," "right," "front," "back," "vertical," "horizontal," "side," and "bottom" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used only to facilitate the description of the structural relationships of the various components or elements of this invention and do not specifically refer to any component or element in this invention. They should not be construed as limiting the invention.

[0019] Example: This embodiment first modifies an existing large aerial camera: to meet the altitude requirements of photogrammetry in special areas such as over civil aviation airports, the lens of the existing aerial camera is replaced with a super telephoto lens to acquire high-resolution aerial image data at high altitudes. In this embodiment, the above modification specifically involves: Utilizing the SWDC (All-in-one) aerial camera technology from Beijing Siwei Vision Information Technology Co., Ltd., the Phase (Phase) super telephoto lens was selected for upgrade and modification. Based on the airspace operation altitude requirements of the airport control area (generally 3000 meters to 3600 meters), a Phase super telephoto lens with a 300mm focal length and 150 million pixels (10625*14204) was selected to complete the upgrade and modification of the super telephoto aerial camera. Using the modified ultra-long telephoto aerial camera, large-area, high-resolution aerial image data can be quickly acquired in high-altitude, high-requirement areas such as over civil aviation airports.

[0020] like Figure 1 As shown in the figure, this embodiment provides a method for producing large-scale DLG images in high-altitude areas, including image data acquisition steps, overlap design steps, DLG planar feature acquisition steps, and DLG elevation feature acquisition steps.

[0021] Step S1, Image Data Acquisition: Using an ultra-long telephoto aerial camera, fly over the operating area that meets the preset high altitude requirements to acquire high-resolution aerial image data of the area. The image data has a preset minimum base-to-height ratio (approximately 0.03).

[0022] Step S2, Overlap Design: Based on existing imagery data with extremely low basalt ratios, and by setting different overlap design strategies, a method for utilizing imagery data that meets accuracy requirements is obtained; specifically: The greater the overlap of the photographs, the shorter the baseline, and the smaller the base-to-height ratio. In the stereo model, a smaller base-to-height ratio leads to a smaller intersection angle of corresponding ground features, which reduces the stereo observation effect and directly affects the measurement accuracy. Under the premise of ensuring three-degree overlap, the base-to-height ratio can be increased by reducing the overlap of the photographs or aligning the long side of the CCD array with the photographic flight path, thereby further improving the accuracy of photogrammetry. Stereoscopic mapping using minimum basal ratio orthophoto data can obtain planar position information that meets accuracy requirements, but the elevation information has a large error. When constructing a 3D model using minimum basal ratio orthophoto data, the model's elevation and topographic information meet accuracy requirements, but the planar information accuracy is poor. Therefore, this embodiment determines the optimal overlap design strategy for acquiring image data that takes into account both applicability and production efficiency, based on relevant specifications: setting the lateral overlap to 40% and the forward overlap to 80% (for 3D modeling), and selecting forward image data thinning for use (for stereoscopic mapping).

[0023] Step S3, DLG planar feature acquisition: Considering the impact of the datum-to-height ratio on stereo mapping (the datum-to-height ratio is positively correlated with the planar accuracy of stereo mapping), and to ensure the requirement of three-dimensional overlap of the flight path images, the 80% overlap image data was thinned to 60% before stereo mapping was performed, completing the production of DLG planar feature data. Based on the completed aerial triangulation results, a method combining fully digital aerial photogrammetry and full field data acquisition was adopted, specifically including: (1) Aerial triangulation: The main process of aerial triangulation densification includes data preparation, project setup, parameter setting, tie point matching, control point addition, area network adjustment calculation, and output of aerial triangulation results. Specific technical procedures are as follows: Figure 2 As shown; The construction project includes: The construction of a new aerial triangulation project involves setting the internal orientation parameters of the aerial camera, such as focal length, image size, and pixel size. Collect the calculated external orientation parameters such as POS; The route is divided into several flight strips using POS parameters; Collect control point coordinates, and set connection points and control point residuals; The measurement interface checks whether the image arrangement is correct. Once confirmed to be correct, proceed to the next step. Connection point matching includes: Set the tie point matching algorithm and matching density, set GNSS and IMU parameters and weights, perform automatic tie point extraction, adjustment calculation and successive iteration to obtain the matched tie point results, enter the measurement interface to determine whether the connection strength of the entire survey area meets the requirements, whether there are any aerial photos not connected to the network, delete the wrong tie points, until all the required aerial photos of the entire survey area are connected to the network. Image control measurement and adjustment calculations include: Measure control points and decision points, perform regional network adjustment calculations, output aerial triangulation reports, perform residual analysis on control points and decision points, determine whether points with large errors are due to errors in indoor or outdoor measurements, correct the problems, and re-adjust; Quality assessment includes: Determine the measurement accuracy of the added control points to ensure the correctness of the control point addition; Determine whether the horizontal position and elevation error of the connection point relative to the nearest field control point meet the specifications. Determine whether the horizontal position and elevation error of the basic orientation point and the judgment point (redundant control point) meet the design requirements; Determine the data format for submitting the aerial triangulation encryption results to ensure that it meets the requirements of the fully digital photogrammetry system for different sections; (2) Acquisition of planar elements in stereoscopic mapping: Data foundation: Aerial triangulation results, raw image data; Main steps: indoor 3D data collection, field mapping, data editing, quality assessment, etc. Technical processes such as Figure 3 As shown, it specifically includes: Oriented modeling: Based on aerial triangulation, an automatic modeling method is adopted. By importing the aerial triangulation results, the stereo model of the image is automatically restored. Then, the orientation accuracy of the model is checked manually, the work area is set, and the boundary line of the single model is delineated. Modeling quality control: Check the absolute orientation accuracy of the model. If the orientation points of the model are within the error range, refer to the stereo model and make appropriate adjustments. After ensuring that the orientation accuracy meets the requirements, proceed to the next step of stereo data acquisition. 3D acquisition: Based on the results of orientation modeling, the image positioning and mapping are carried out under the stereo model, and the difficult-to-confirm elements are marked; the DLG data collected in the office and its question marks are simply edited and output to the mapping base map with orthophoto as the background. Field survey: Before conducting field surveys (verification and correction), the data from the indoor surveys are analyzed and then carried out on a digital orthophoto map overlaid with the indoor pre-judgment digital line map. Verify, correct, and characterize the topographic map elements predicted in the office; adjust and redraw attribute information (such as geographical names) that was missed or could not be obtained in the office; and conduct full field digital surveys in areas obscured by images. Data Editor: Using field survey maps and office editing and modification of data, large-scale DLG planar feature data production is completed through surface mapping, attribute editing, and topological relationship construction. Topographic map edge matching: After data collection and editing are completed, adjacent data blocks are joined to ensure correct positioning, reasonable form, and consistent attributes.

[0024] Step S4, DLG elevation element acquisition: To meet the requirements of 3D model elevation mapping, 3D model is generated using unthinned orthophoto data (80% overlap). Elevation points are collected based on this data to produce DLG elevation element data. (1) Three-dimensional model construction: First, the image data is aerially triangulated for encryption. Then, dense matching is performed to obtain a high-precision DSM (Digital Model Scheme). Next, a white model is constructed and texture mapping is performed to output the 3D model result. The technical flowchart is as follows: Figure 4 As shown, specifically: 1) Aerial triangulation encryption includes: data preprocessing, data import, link point extraction, manual conversion of control points, adjustment calculation, and other procedures; 2) DSM dense matching, including: image format conversion, importing the adjusted POS results for re-adjustment, pixel-by-pixel matching to obtain dense point cloud data, interpolation to obtain DSM matching results; filtering out erroneous values ​​in the matched DSM, filling holes, etc., and outputting the final DSM results. 3) Automated model creation: using aerial triangulation results, original images, and DSM results to construct white models and map textures to generate 3D models; 4) Output and format conversion of process results: Convert the 3D model format and perform coordinate offset to obtain the final geographic scene result; 5) Model Refinement: During the aerial triangulation process, some weak texture areas (such as large water surfaces, vegetation, etc.) may have elevation anomalies due to incorrect connection points, resulting in voids, undulations, spikes, etc. in the 3D model. In addition, there may be suspended objects, etc. The model results need to be refined. The refinement content includes: removing suspended objects under the ground surface, removing voids in buildings, and refining water surfaces, ground, mountains, and vegetation. (2) DLG elevation point acquisition: Data foundation: High-resolution 3D model; The steps include: naked-eye internal judgment data collection, field investigation and verification, data editing, and edge integration; The technical approach to completing large-scale DLG elevation element data acquisition is as follows: Figure 5 As shown, this step of the data acquisition stage uses naked-eye acquisition of ground point elevation information based on a 3D model to complete the production of large-scale DLG essential elevation element data.

[0025] like Figure 6 As shown, this embodiment also provides a large-scale DLG production system for high-altitude areas, including: The image data acquisition module is used to acquire high-resolution aerial image data with a very small base-to-height ratio in areas that meet the high requirements of high-altitude aerial photography by using a large aerial camera equipped with a modified ultra-telephoto lens. A data processing and feature acquisition module, connected to the image data acquisition module, includes: The overlap design unit is used to formulate the optimal overlap strategy for image data with minimal basal-to-height ratio based on a preset photogrammetric model, and to organize the original image data. The planar feature acquisition unit is used to perform aerial triangulation and stereo mapping processes based on the organized image data, and to complete the acquisition and production of DLG planar feature data. The elevation feature acquisition unit is used to execute the 3D model construction process based on the original image data, and to complete the acquisition and production of DLG elevation feature data through naked-eye acquisition based on the generated 3D model.

[0026] The planar feature acquisition unit includes: The aerial triangulation subunit is used to perform tie point matching, control point measurement and regional network adjustment calculation, and output aerial triangulation densification results; The stereo mapping subunit is used to import the aerial triangulation results, restore the stereo model, collect indoor elements, and manage the field mapping and data editing process.

[0027] The elevation feature acquisition unit includes: The 3D modeling subunit is used to perform image dense matching to generate a DSM, and to construct and refine a 3D model based on the DSM and the original image. The elevation acquisition subunit is used to provide a naked-eye acquisition interface to acquire and update elevation point information based on the three-dimensional model.

[0028] The above is a detailed description of the preferred embodiments of the present invention, but the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention, and these equivalent modifications or substitutions are all included within the scope defined by the claims of this application.

Claims

1. A method for producing large-scale DLG (Digital Light Gauge) in high-altitude areas, characterized in that, Includes the following steps: Step S1, Image Data Acquisition Step: Using an ultra-long telephoto aerial camera, fly in the operation area that meets the preset high altitude requirements to acquire high-resolution aerial image data of the area. The image data has a very small base-to-height ratio. Step S2, Overlap Design Step: For image data with extremely small base-to-height ratio, based on the photogrammetric model, analyze the relationship between base-to-height ratio and measurement accuracy, and determine a forward and lateral overlap design strategy that takes into account both data applicability and production efficiency; organize the acquired raw image data according to the overlap design strategy. Step S3, DLG planar feature acquisition steps: Based on the image data organized by the overlap design strategy, perform aerial triangulation processing to generate aerial triangulation densification results; using the aerial triangulation densification results, perform indoor stereo data acquisition under the stereo model, and combine field mapping and data editing to complete the production of large-scale DLG planar feature data; Step S4, DLG elevation feature acquisition step: Based on the original image data that has not been thinned according to the strategy in step S2, a three-dimensional model is constructed to generate a three-dimensional model containing high-precision terrain information; elevation point information is obtained by naked-eye acquisition based on the three-dimensional model, and combined with field verification and data editing, the production of large-scale DLG elevation feature data is completed.

2. The method for producing large-scale DLG in high-altitude areas according to claim 1, characterized in that, In step S1, the focal length of the super telephoto lens is 300mm and the number of pixels is not less than 150 million; the preset high flight altitude requirement is a flight altitude between 3000 meters and 3600 meters; and the minimum base-to-altitude ratio is 0.

03.

3. The method for producing large-scale DLG in high-altitude areas according to claim 1, characterized in that, In step S2, the overlap design strategy is specifically as follows: Set the lateral overlap to 40% and the heading overlap to 80%. For images used in stereo mapping, the image data with a forward overlap of 80% is thinned down to 60% for use.

4. The method for producing large-scale DLG in high-altitude areas according to claim 1, characterized in that, In step S3, the aerial triangulation processing includes: Data preparation and project setup, connection point matching, control point measurement and regional network adjustment calculation, quality assessment; The indoor three-dimensional data acquisition includes: directional modeling based on the results of aerial triangulation, and element acquisition and question marking under the three-dimensional model.

5. A method for producing large-scale DLG in high-altitude areas according to claim 4, characterized in that, In the tie point matching step, tie points are automatically extracted and adjusted by setting the matching algorithm, matching density, and GNSS / IMU parameter weights. The automatic extraction and adjustment calculation of the connection points are specifically as follows: in the aerial triangulation software, a feature point matching algorithm is selected, the density value of the extracted connection points is set, and corresponding weight values ​​are assigned in the adjustment model based on the measured GNSS positioning accuracy and IMU attitude accuracy data of the airborne POS system. The quality assessment includes: determining the mean square error of the horizontal position and elevation of the connection point relative to the nearest field control point, and determining whether the mean square error between the basic orientation point and the assessment point meets the preset specification requirements.

6. A method for producing large-scale DLG in high-altitude areas according to claim 1, characterized in that, In step S4, the construction of the three-dimensional model includes: Aerial triangulation encryption is applied to the image data; Digital Surface Model (DSM) is generated using a dense matching algorithm; Based on aerial triangulation results, original images, and DSM, a white model is constructed and texture mapping is performed to generate an initial 3D model; The initial 3D model is modified, including correcting anomalies in surface suspended matter, building cavities, water surfaces, ground surfaces, mountains, and vegetation areas.

7. A high-altitude, high-area, large-scale DLG production system, used to implement the high-altitude, high-area, large-scale DLG production method as described in any one of claims 1-6, characterized in that, include: The image data acquisition module is used to acquire high-resolution aerial image data with a very small base-to-height ratio in areas that meet the high requirements of high-altitude aerial photography by using a large aerial camera equipped with a modified ultra-telephoto lens. A data processing and feature acquisition module, connected to the image data acquisition module, includes: The overlap design unit is used to formulate the optimal overlap strategy for image data with minimal basal-to-height ratio based on a preset photogrammetric model, and to organize the original image data. The planar feature acquisition unit is used to perform aerial triangulation and stereo mapping processes based on the organized image data, and to complete the acquisition and production of DLG planar feature data. The elevation feature acquisition unit is used to execute the 3D model construction process based on the original image data, and to complete the acquisition and production of DLG elevation feature data through naked-eye acquisition based on the generated 3D model.

8. A large-scale DLG production system for high-altitude areas according to claim 7, characterized in that, The planar feature acquisition unit includes: The aerial triangulation subunit is used to perform tie point matching, control point measurement and regional network adjustment calculation, and output aerial triangulation densification results; The stereo mapping subunit is used to import the aerial triangulation results, restore the stereo model, collect indoor elements, and manage the field mapping and data editing process.

9. A large-scale DLG production system for high-altitude areas according to claim 7, characterized in that, The elevation element acquisition unit includes: The 3D modeling subunit is used to perform image dense matching to generate a DSM, and to construct and refine a 3D model based on the DSM and the original image. The elevation acquisition subunit is used to provide a naked-eye acquisition interface to acquire and update elevation point information based on the three-dimensional model.

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