A method and system based on oblique photography and webGIS platform

Abstract

This invention relates to a method and system based on oblique photogrammetry and a webGIS platform, comprising: planning an oblique photogrammetry flight path for a drone; determining the drone aerial photography parameters based on the distribution of buildings on site and setting up ground control points (GCPs); taking photos of the project site using a drone; performing aerial triangulation calculations by combining the POS information contained in the photos with the POS information of the GCPs; generating a point cloud and densifying it into a dense point cloud to form a triangular mesh model; and finally generating a real-world 3D model by combining the pixel information in the oblique image. The advantages of this invention are: it allows for oblique photogrammetry flight and modeling of the entire project at the beginning of the project; marking work points on a web platform and connecting the marked work points on the real-world model with the construction drawings provides a clear and intuitive view of the entire project; and it eliminates the need for additional image acquisition hardware and network information transmission hardware during construction, resulting in lower costs.

Description

Technical Field

[0001] This invention relates to the field of construction oblique photogrammetry technology, and more specifically, to a method and system based on oblique photogrammetry and a webGIS platform. Background Technology

[0002] The construction industry is a typical labor-intensive, extensive production industry. Schedule control during construction relies primarily on manual labor. For road repair and urban facade renovation projects, the short construction cycles, long and discontinuous construction routes, and the high degree of real-time coordination present significant challenges to schedule control. On-site construction personnel often need to remotely report specific problems at specific locations to coordinators, but the rushed arrival time often leads to inaccuracies in describing these locations. Project leadership also finds it difficult to intuitively grasp the on-site construction progress and adjust the schedule plan in a timely manner.

[0003] Patent document CN 114119897 B proposes a smart construction site management method and system based on the Internet of Things (IoT). The method includes the following steps: planning drone flight paths based on the construction site area and collecting aerial survey data using oblique photography of the drone; obtaining video data of the construction site using a portable camera and / or a ground-based data collection vehicle; constructing a three-dimensional real-scene model by combining the aerial survey data and the video data; collecting multi-dimensional data of the construction site area; analyzing and processing the multi-dimensional data and sending it to a real-scene control platform via the IoT; and labeling the multi-dimensional data in the three-dimensional real-scene model according to the tags of the multi-dimensional data to control and display the construction site.

[0004] Patent document CN 111006646 B provides a method for monitoring construction progress based on UAV oblique photogrammetry technology, including the following steps: S1: Confirm the construction task; S2: Design a flight path based on the construction task in step S1; S3: After the flight path design in step S2 is completed, determine whether the airspace application is approved. If not approved, return to step S1; if approved, proceed to step S4; S4: Deploy target points on the factory ground; S5: Based on the target point deployment in step S4, acquire factory area images using UAV oblique photogrammetry; S6: Perform aerial triangulation; S7: Generate a true 3D model; S8: After the true 3D model is constructed, compare the actual construction progress with the planned construction progress to reflect the progress deviation; S9: Predict the later progress trend of the project. This invention realistically reflects the spatial form of the building and facilitates the comparison of construction progress deviations.

[0005] While the aforementioned patents all apply oblique photography to construction project progress control, they suffer from the following three shortcomings. First, these patents require substantial hardware and complex software systems for progress control. Whether it's monitoring cameras, equipment, network modules, target setups, or complex data transmission and image comparison systems, all require significant human, material, and financial resources. This makes their application in small to medium-sized projects virtually impossible. Second, these patents heavily rely on automatically collected image data from monitoring cameras or drones for project progress control. However, the quality of this automatically collected image data is highly dependent on weather conditions, making information recognition difficult in practical applications. Third, these patents focus on displaying real-world models and image data, lacking dynamic adjustments and deployments for visualizing the construction area and progress.

[0006] Based on the aforementioned problems with using UAV oblique photography for project control, and considering that the cost of the schedule control system, the ease of use and practicality of the schedule control method, and the dynamic adjustment of the construction schedule are key aspects of schedule control, it is necessary to propose a method and system that is low-cost, easy to use, highly practical, and allows for intuitive and dynamic adjustment of the schedule. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the prior art and to propose a method and system based on oblique photogrammetry and a webGIS platform.

[0008] Firstly, a method based on oblique photogrammetry and a webGIS platform is provided, including:

[0009] S1. Confirm the construction tasks and conduct a site survey;

[0010] S2. Plan the drone oblique photography route, determine the drone aerial photography parameters based on the distribution of buildings on site, and set up image control points;

[0011] S3. Take pictures of the project site by drone, combine the POS information contained in the pictures with the POS information of the control point to perform aerial triangulation calculation, generate point cloud and encrypt it into dense point cloud, form a triangular mesh model, and finally combine the pixel information in the oblique image to generate a real scene 3D model.

[0012] S4. Import the real-scene 3D model into the webGIS platform;

[0013] S5. Mark potential construction points on the real-world 3D model and name the construction points;

[0014] S6. Upload the PDF construction drawings for each construction site and link them to the construction site.

[0015] S7. Observe the real scene model and the PDF drawings of each construction point on the real scene model, plan the construction area for each time period on the real scene model, and formulate a construction schedule plan.

[0016] S8. Take photos of the construction site during the construction process and upload them to the web platform, while indicating the specific construction points and dates;

[0017] S9. Drag the timeline on the real-world model to check whether the actual construction progress reflected in the on-site construction photos of each work site at each time point matches the planned construction progress.

[0018] S10. Adjust the planned construction schedule based on the actual intensity of continuous construction and the current actual construction progress.

[0019] As a preferred option, in S2, the parameters for drone aerial photography include flight altitude, flight speed, forward overlap rate, and lateral overlap rate.

[0020] Preferably, S2 includes:

[0021] S201. Take orthophotos of the entire project by using a drone at a preset altitude.

[0022] S202. Convert the orthophoto of the project into a grayscale image. At this time, the plan view of the project becomes an m*n matrix. Each point on the matrix corresponds to a grayscale value on the grayscale image. The grayscale value ranges from 0 to 255. Perform a two-dimensional Fourier transform on the grayscale image matrix, and then shift the spectrum obtained after the Fourier transform to move the center of the transformed image spectrum from the corner point of the matrix to the center point of the matrix.

[0023] S203. Filter the image in the frequency domain;

[0024] S204. Perform a two-dimensional inverse Fourier transform on the matrix to restore the planar image from the frequency domain to the spatial domain. The resulting grayscale image retains only the outline of the building.

[0025] S205. Let the grayscale value of each pixel in the grayscale image be F(i,j), where i takes values ​​between [0,m] and j takes values ​​between [0,n]. By traversing the grayscale values ​​of each row and column of pixels, find the coordinates (i,j) of consecutive F(i,j) greater than the grayscale threshold, and then use (i,j) to find the corresponding coordinates. max ,j max ), (i min ,j max ), (i max ,j min ), (i min ,j min Four points define the boundaries of each contiguous housing area;

[0026] S206. Perform oblique photography flight for each continuous housing area and road, set the flight altitude, heading and lateral overlap rate, and set image control points at ((imax+imin) / 2,(jmax+jmin) / 2,) that is, at the center of each area.

[0027] Preferably, in S203, the coordinates of each frequency point in the frequency domain are (u,v). For an image of size M*N, the distance between the frequency point (u,v) and the center of the frequency domain is D(u,v), and its expression is:

[0028] D(u,v)=[(uM / 2) 2 +(vN / 2) 2 ] 1 / 2

[0029] Multiply each frequency point (u,v) by a filter coefficient H1(u,v) to filter out high-frequency signals in the image. The expression for the filter coefficient H1(u,v) is:

[0030] H1(u,v)=1 / (1+[D(u,v) / D 01 ] 2n )

[0031] Where D 01 The cutoff frequency is given by n, and the filter order is given by n. Then, each frequency point (u, v) is multiplied by a filter coefficient.

[0032] H2(u,v) filters out low-frequency signals in the image. The expression for H2(u,v) is: H2(u,v)=1 / (1+[D 02 / D(u,v)] 2n )

[0033] Where D 02 The cutoff frequency is D 02 <D 01 , where n is the order of the filter, and H2(u,v) = 0 when D(u,v) is 0.

[0034] Preferably, in S4, the webGIS platform includes a marking work point module for marking construction locations and annotating names on the real-world model, a drawing module for uploading PDF drawings and linking them to work points, a construction photo module for uploading construction photos and annotating construction time and location, a construction area planning module for planning construction areas and annotating planned time periods on the real-world model, and a time axis module for changing time variables.

[0035] As a preferred option, in S8, additional construction sites are added during the project implementation process.

[0036] As a preferred option, in S5, the construction area at different time periods is visualized on the real-world model.

[0037] As a preferred option, in S6, the construction drawings of each construction point are reflected in their respective real-world model locations.

[0038] As a preferred option, in S9, the planned construction area and on-site construction photos of each work site at each time point can be reflected by dragging the timeline on the real-world model.

[0039] In a second aspect, a system based on oblique photogrammetry and a webGIS platform is provided for executing the method based on oblique photogrammetry and a webGIS platform as described in any of the first aspects, including:

[0040] The confirmation module is used to confirm the construction tasks and conduct on-site surveys.

[0041] The planning module is used to plan the drone's oblique photography flight path, determine the drone's aerial photography parameters based on the distribution of buildings on site, and set up image control points.

[0042] The generation module is used to take pictures of the project site by drone, combine the POS information contained in the pictures with the POS information of the ground control point to perform aerial triangulation calculation, generate point cloud and encrypt it into dense point cloud, form a triangular mesh model, and finally combine the pixel information in the oblique image to generate a real scene 3D model.

[0043] The import module is used to import real-world 3D models into the webGIS platform;

[0044] The marking module is used to mark potential construction points on the real-world 3D model and name the construction points;

[0045] The upload module is used to upload PDF construction drawings for each construction site and link them to the construction site.

[0046] The module is used to observe the real-world model and the PDF drawings of each construction point on the real-world model, plan the construction area for each time period on the real-world model, and formulate a construction schedule.

[0047] The second upload module is used to take photos of the construction site during the construction process and upload them to the web platform, while indicating the specific construction point and date;

[0048] The inspection module is used to drag the timeline on the real-world model to check whether the actual construction progress reflected in the on-site construction photos of each work site at each time point matches the planned construction progress.

[0049] The adjustment module is used to adjust the planned construction schedule based on the actual intensity of the continuous construction and the current actual construction progress.

[0050] The beneficial effects of this invention are:

[0051] 1. This invention performs oblique photogrammetry and modeling of the entire project at the beginning of the project. By marking work points on the web platform and linking the marked work points on the real-world model with the construction drawings, the overall picture of the project can be reflected intuitively and clearly.

[0052] 2. This invention does not require the addition of extra image information acquisition hardware or network information transmission hardware during construction, nor does it require the repeated creation of physical models or the construction of complex and large software systems as support, thereby reducing costs.

[0053] 3. In the process of oblique photography, the present invention converts the project plan into a grayscale image and performs Fourier transform, filtering and inverse Fourier transform on the grayscale image in sequence. This can filter out most of the details and noise of the buildings and retain only the outline of the buildings, which makes it easier to determine the center of the area and the control points. The resulting real scene model has high accuracy. Attached Figure Description

[0054] Figure 1 A flowchart of a method based on oblique photogrammetry and a webGIS platform;

[0055] Figure 2 This is a schematic diagram of a real-world project model within a web platform.

[0056] Figure 3 This is a schematic diagram showing the locations of the construction sites with marked prices.

[0057] Figure 4 This is a schematic diagram showing the connection between the PDF drawings and the construction sites;

[0058] Figure 5 A schematic diagram for planning the construction area and developing a schedule;

[0059] Figure 6 This is an illustration for uploading on-site construction photos;

[0060] Figure 7 A diagram showing the comparison between the planned construction area and the on-site photos at specific time points. Detailed Implementation

[0061] The present invention will be further described below with reference to embodiments. The description of the embodiments below is only for the purpose of helping to understand the present invention. It should be noted that those skilled in the art can make several modifications to the present invention without departing from the principle of the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

[0062] Example 1:

[0063] Taking a city renovation project as an example, this paper illustrates a method based on oblique photogrammetry and a webGIS platform provided in this application. Figure 1 As shown, this invention employs a low-cost method to conveniently and intuitively achieve visualized control of construction progress. This invention only performs oblique photogrammetry and modeling of the entire project at the very beginning of the project. By marking work points on a web platform and displaying PDF drawings of each work point on the real-world model, the overall project view is intuitively and clearly reflected. Furthermore, personnel in different positions can accurately communicate about specific issues occurring at each work point using the marked work points. This method includes:

[0064] S1. Confirm the construction task and conduct a site survey.

[0065] S2. Plan the drone oblique photography route, determine the drone aerial photography parameters based on the distribution of buildings on site, and set up image control points.

[0066] In S2, the parameters for drone aerial photography include flight altitude, flight speed, forward overlap rate, and lateral overlap rate.

[0067] Specifically, S2 includes:

[0068] S201. Orthophotos of the entire project are obtained by taking orthophotos of the project from a predetermined altitude using a drone.

[0069] S202. Convert the orthophoto of the project into a grayscale image. At this point, the project's plan view becomes an m*n matrix, where each point in the matrix corresponds to a grayscale value in the grayscale image, with the grayscale value ranging from 0 to 255. Perform a two-dimensional Fourier transform on the grayscale image matrix, and then shift the spectrum obtained after the Fourier transform, moving the center of the transformed image spectrum from the corner point to the center point of the matrix. Through the above operations, the project's plan view is transformed from the spatial domain to the frequency domain.

[0070] S203. Filter the image in the frequency domain; the coordinates of each frequency point in the frequency domain are (u,v). For an image of size M*N, the distance between the frequency point (u,v) and the center of the frequency domain is D(u,v), and its expression is:

[0071] D(u,v)=[(uM / 2) 2 +(vN / 2) 2 ] 1 / 2

[0072] Multiply each frequency point (u,v) by a filter coefficient H1(u,v) to filter out high-frequency signals in the image. The expression for the filter coefficient H1(u,v) is:

[0073] H1(u,v)=1 / (1+[D(u,v) / D 01 ] 2n )

[0074] Where D 01 With the cutoff frequency set to 50 and the filter order n set to 2, most of the building details and noise are filtered out in the frequency domain. Then, each frequency point (u,v) is multiplied by a filter coefficient H2(u,v) to filter out low-frequency signals in the image. The expression for H2(u,v) is: H2(u,v) = 1 / (1+[D 02 / D(u,v)] 2n )

[0075] Where D 02 With the cutoff frequency set to 30 and the filter order n set to 2, H1(u,v) = 0 when D(u,v) is 0. In this case, only frequency information between 30 and 50 is retained in the frequency domain plot.

[0076] S204. Perform a two-dimensional inverse Fourier transform on the matrix to restore the planar image from the frequency domain to the spatial domain. The resulting grayscale image retains only the outline of the building.

[0077] S205. Let the grayscale value of each pixel in the grayscale image be F(i,j), where i takes values ​​between [0,m] and j takes values ​​between [0,n]. By iterating through the grayscale values ​​of each row and column of pixels, and setting the grayscale threshold to 150, find the coordinates of (i,j) where F(i,j) > 150. max ,j max ), (i min ,j max ), (i max ,j min ), (i min ,j min Four points define the boundaries of each contiguous housing area;

[0078] S206. Perform oblique photogrammetry flight for each continuous housing area and road, with the flight altitude taken as 1.2 times the maximum building height in each area, and the forward and lateral overlap rates taken as 70%. max+ i min ) / 2,(j max+ j min ) / 2,) that is, a control point is set at the center of each area.

[0079] S3. Take pictures of the project site using drones, combine the POS information contained in the pictures with the POS information of the control points to perform aerial triangulation calculations, generate point clouds and encrypt them into dense point clouds to form a triangular mesh model, and finally combine the pixel information in the oblique images to generate a real-world 3D model.

[0080] S4. Import the real-world 3D model into the webGIS platform, such as... Figure 2 As shown.

[0081] In S4, the webGIS platform includes a work site marking module, a drawing module (including a drawing upload sub-module and a drawing display sub-module), a construction photo module (including a photo upload sub-module and a photo display sub-module), a construction area planning module, a timeline module, and a communication module.

[0082] The work site marking module is used to mark potential construction sites and display the priced sites in the model space. It enables interactive site control on the front end and simultaneously publishes site change information to the backend server for data and resource storage.

[0083] In addition, the marking of construction points module includes adding, deleting, modifying, and querying potential construction points. Specifically, adding a construction point is done by triggering a mouse click event, obtaining the coordinates of the view camera position and the mouse position in the world coordinate system, creating a ray from these two coordinate points, and finding the intersection of the ray and the real-world model. This intersection point is the location of the new construction point in the world coordinate system. Then, annotation information for the construction point is input using a Vue reactive component. Further, the world coordinate position of the construction point and the annotation information are packaged and sent to the Cesium API to create a blue sphere entity to display the construction point location, with the annotation information displayed above it. After confirmation and saving on the browser side, the world coordinate position of the construction point and the annotation information are packaged in JSON format and sent to the backend Django server. The server receives the data, stores it in the construction point database, and returns all updated construction point information to the browser. The browser updates the construction point list based on the received construction point information. Deleting a construction point is achieved by triggering a click event on the blue ball representing that point. This retrieves the point's index in the construction point list. After the browser confirms the deletion, the Cesium API removes the blue ball representing the point and its corresponding annotation, and sends the point's ID from the backend construction point database to the Django server. Upon receiving the ID, the backend server removes the point from the database and returns the updated construction point information to the browser. The browser then updates its construction point list based on this information. Modifying construction point annotations involves inputting updated annotations using a Vue reactive component. After the browser confirms and saves the changes, it updates the annotations in the Cesium model space and packages the construction point's ID and the updated information into a JSON file, sending it to the backend Django server. The server receives the data, updates the data based on the ID, and returns the updated information to the browser. The browser then updates its construction point list based on this information. This process enables interactive and dynamic control of construction points on the browser side.

[0084] The drawing upload and photo upload submodules are used to upload construction drawings and on-site construction photos to the corresponding folders in the backend and link the construction drawings and on-site construction photos with the construction locations. Specifically, the shooting time of the construction photos is automatically captured. Then, the location information of the construction drawings and photos, including the shooting time, is stored in the backend database and dynamically controlled.

[0085] The drawing display submodule and the photo display submodule are used to display drawings and photos above construction points, and dynamically follow, scale, show, and hide them as the model moves and rotates. The photo display submodule is also used to dynamically control the hiding and showing of photos as the timeline changes.

[0086] The construction area planning module allows for interactive planning of construction areas at different time periods on a real-world model, enabling visualized planning of construction schedules. Furthermore, during construction, the construction area can be dynamically adjusted for specific time periods based on actual conditions.

[0087] The timeline module is used to control the time parameters in the platform, thereby controlling the display and hiding of construction areas and on-site construction photos.

[0088] The communication module is used for communication between the front-end server and the back-end server, including sending requests for data, models, images and other resources, as well as sending data generated during the front-end browsing and interaction process and the resources obtained to the back-end server.

[0089] S5. Mark potential construction points on the realistic 3D model and name the construction points, such as... Figure 3 As shown, potential construction sites include: No. 126-144 Kangtai Road, No. 131-135 Kangtai Road, etc.

[0090] In S5, construction areas at different time periods can be visualized on a real-world model.

[0091] S6. Upload the PDF construction drawings for each construction site and link them to the construction site.

[0092] In S6, such as Figure 4 As shown, the construction drawings for each construction point are reflected in their respective real-world model locations. Clicking on a construction drawing will display its detailed drawings.

[0093] S7. Observe the real-world model and the PDF drawings of each construction point on the real-world model. Plan the construction area for each time period on the real-world model and formulate a construction schedule, such as... Figure 5 As shown.

[0094] S8. On-site construction personnel shall take photos of the construction site daily and upload them to the web platform, clearly indicating the specific construction location and date. Figure 6 As shown, it includes construction photos of different construction sites on the same date (such as construction photo 1 and construction photo 2), as well as construction photos of the same construction site on different dates (such as construction photo 2 and construction photo 3).

[0095] In S8, newly added construction sites are added during the project implementation process.

[0096] S9. Drag the timeline on the real-world model to check whether the actual construction progress reflected in the on-site construction photos of each work site at each time point matches the planned construction progress. Figure 7As shown, clicking on the construction area will display photos of the on-site construction.

[0097] In S9, the planned construction area and on-site construction photos of each work site can be viewed by dragging the timeline on the real-world model.

[0098] S10. Adjust the planned construction schedule based on the actual intensity of continuous construction and the current actual construction progress.

[0099] On-site personnel are indispensable in construction projects. Most existing technologies neglect the initiative of on-site construction workers, instead relying heavily on data acquisition hardware and intelligent recognition systems to obtain actual construction progress, which undoubtedly increases the cost of reflecting actual construction progress significantly. As can be seen from the specific implementation, this invention achieves accurate and real-time reflection of actual construction progress by combining an initial real-world model of the project with on-site construction photos taken daily by on-site personnel, along with a timeline. This method not only avoids increasing the project's hardware and software costs but also does not add extra workload to on-site personnel, thus achieving low-cost and easy-to-operate reflection of actual construction progress. Simultaneously, this invention enables the visualization of project schedules on the real-world model through a construction area planning module. By dragging the timeline, the planned construction area at a specific time point can be easily compared with on-site construction photos, allowing for timely adjustments to the planned construction schedule based on actual conditions. This invention achieves visualized display of actual construction progress and dynamic adjustment of the schedule in a low-cost manner, making it applicable not only to large-scale projects but also to small and medium-sized projects, especially road reconstruction and urban facade renovation projects with long routes and short cycles.

[0100] Example 2:

[0101] A system based on oblique photogrammetry and a webGIS platform includes:

[0102] The confirmation module is used to confirm the construction tasks and conduct on-site surveys.

[0103] The planning module is used to plan the drone's oblique photography flight path, determine the drone's aerial photography parameters based on the distribution of buildings on site, and set up image control points.

[0104] The generation module is used to take pictures of the project site by drone, combine the POS information contained in the pictures with the POS information of the ground control point to perform aerial triangulation calculation, generate point cloud and encrypt it into dense point cloud, form a triangular mesh model, and finally combine the pixel information in the oblique image to generate a real scene 3D model.

[0105] The import module is used to import real-world 3D models into the webGIS platform;

[0106] The marking module is used to mark potential construction points on the real-world 3D model and name the construction points;

[0107] The upload module is used to upload PDF construction drawings for each construction site and link them to the construction site.

[0108] The module is used to observe the real-world model and the PDF drawings of each construction point on the real-world model, plan the construction area for each time period on the real-world model, and formulate a construction schedule.

[0109] The second upload module is used to take photos of the construction site during the construction process and upload them to the web platform, while indicating the specific construction point and date;

[0110] The inspection module is used to drag the timeline on the real-world model to check whether the actual construction progress reflected in the on-site construction photos of each work site at each time point matches the planned construction progress.

[0111] The adjustment module is used to adjust the planned construction schedule based on the actual intensity of the continuous construction and the current actual construction progress.

Claims

1. A method based on oblique photogrammetry and a webGIS platform, characterized in that, include: S1. Confirm the construction tasks and conduct a site survey; S2. Plan the drone oblique photography route, determine the drone aerial photography parameters based on the distribution of buildings on site, and set up image control points; S2 includes: S201. Take orthophotos of the entire project by using a drone at a preset altitude. S202. Convert the orthophoto of the project into a grayscale image. At this time, the plan view of the project becomes an m*n matrix. Each point on the matrix corresponds to a grayscale value on the grayscale image. The grayscale value ranges from 0 to 255. Perform a two-dimensional Fourier transform on the grayscale image matrix, and then shift the spectrum obtained after the Fourier transform to move the center of the transformed image spectrum from the corner point of the matrix to the center point of the matrix. S203. Filter the image in the frequency domain; S204. Perform a two-dimensional inverse Fourier transform on the matrix to restore the planar image from the frequency domain to the spatial domain. The resulting grayscale image retains only the outline of the building. S205. Let the grayscale value of each pixel in the grayscale image be F(i,j), where i takes values ​​between [0,m] and j takes values ​​between [0,n]. By traversing the grayscale values ​​of each row and column of pixels, find the coordinates (i,j) of consecutive F(i,j) greater than the grayscale threshold, and then use (i,j) to find the corresponding coordinates. max , j max ), (i min , j max ), (i max , j min ), (i min , j min Four points define the boundaries of each contiguous housing area; S206. Perform oblique photogrammetry flight for each continuous housing area and road, setting the flight altitude, flight speed, heading, and lateral overlap rate, and in ((i max + i min ) / 2, (j max + j min That is, a control point is set at the center of each area; S3. Take pictures of the project site by drone, combine the POS information contained in the pictures with the POS information of the control point to perform aerial triangulation calculation, generate point cloud and encrypt it into dense point cloud, form a triangular mesh model, and finally combine the pixel information in the oblique image to generate a real scene 3D model. S4. Import the real-scene 3D model into the webGIS platform; S5. Mark potential construction points on the real-world 3D model and name the construction points; S6. Upload the PDF construction drawings for each construction site and link them to the construction site. S7. Observe the real scene model and the PDF drawings of each construction point on the real scene model, plan the construction area for each time period on the real scene model, and formulate a construction schedule plan. S8. Take photos of the construction site during the construction process and upload them to the web platform, while indicating the specific construction points and dates; S9. Drag the timeline on the real-world model to check whether the actual construction progress reflected in the on-site construction photos of each work site at each time point matches the planned construction progress. S10. Adjust the planned construction schedule based on the actual intensity of continuous construction and the current actual construction progress.

2. The method based on oblique photogrammetry and a webGIS platform according to claim 1, characterized in that, In S203, the coordinates of each frequency point in the frequency domain are (u,v). For an image of size m*n, the distance between the frequency point (u,v) and the center of the frequency domain is D(u,v), which is expressed as: D(u,v) = [(u- m / 2) 2 +(v-n / 2) 2 ] 1 / 2 Multiply each frequency point (u,v) by a filter coefficient H1(u,v) to filter out high-frequency signals in the image. The expression for the filter coefficient H1(u,v) is: H1(u,v)=1 / (1+[ D(u,v) / D 01 ] 2n ) Where D 01 Let n be the cutoff frequency and n be the filter order. Then, multiply each frequency point (u,v) by a filter coefficient H2(u,v) to filter out low-frequency signals in the image. The expression for H2(u,v) is: H2(u,v)=1 / (1+[ D 02 / D(u,v)] 2n ) Where D 02 The cutoff frequency is D 02 <D 01 n is the order of the filter, and H2(u,v)=0 when D(u,v) is 0.

3. The method based on oblique photogrammetry and a webGIS platform according to claim 2, characterized in that, In S4, the webGIS platform includes a marker module for marking construction locations and annotating names on the real-world model, a drawing module for uploading PDF drawings and linking them to the work points, a construction photo module for uploading construction photos and annotating construction time and location, a construction area planning module for planning construction areas and annotating planned time periods on the real-world model, and a time axis module for changing time variables.

4. The method based on oblique photogrammetry and a webGIS platform according to claim 3, characterized in that, In S8, newly added construction sites are added during the project implementation process.

5. The method based on oblique photogrammetry and a webGIS platform according to claim 4, characterized in that, In S5, construction areas at different time periods can be visualized on a real-world model.

6. The method based on oblique photogrammetry and a webGIS platform according to claim 5, characterized in that, In S6, the construction drawings of each construction site are reflected in their respective real-world model locations.

7. The method based on oblique photogrammetry and a webGIS platform according to claim 6, characterized in that, In S9, the planned construction area and on-site construction photos of each work site can be viewed by dragging the timeline on the real-world model.

8. A system based on oblique photogrammetry and a webGIS platform, characterized in that, The method for performing any one of claims 1 to 7 based on oblique photogrammetry and a webGIS platform includes: The confirmation module is used to confirm the construction tasks and conduct on-site surveys. The planning module is used to plan the drone's oblique photography flight path, determine the drone's aerial photography parameters based on the distribution of buildings on site, and set up image control points. The generation module is used to take pictures of the project site by drone, combine the POS information contained in the pictures with the POS information of the ground control point to perform aerial triangulation calculation, generate point cloud and encrypt it into dense point cloud, form a triangular mesh model, and finally combine the pixel information in the oblique image to generate a real scene 3D model. The import module is used to import real-world 3D models into the webGIS platform; The marking module is used to mark potential construction points on the real-world 3D model and name the construction points; The upload module is used to upload PDF construction drawings for each construction site and link them to the construction site. The module is used to observe the real-world model and the PDF drawings of each construction point on the real-world model, plan the construction area for each time period on the real-world model, and formulate a construction schedule. The second upload module is used to take photos of the construction site during the construction process and upload them to the web platform, while indicating the specific construction point and date; The inspection module is used to drag the timeline on the real-world model to check whether the actual construction progress reflected in the on-site construction photos of each work site at each time point matches the planned construction progress. The adjustment module is used to adjust the planned construction schedule based on the actual intensity of the continuous construction and the current actual construction progress.

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