Earthwork Measurement Method and Related Devices for Densely Vegetated Areas Based on Laser Point Clouds

Abstract

This invention discloses a method and related apparatus for measuring earthwork in densely vegetated areas based on laser point clouds. The method includes: a flight device carrying an airborne lidar along a preset flight path to collect and process airborne laser point cloud data of a target area in a preset airspace, obtaining airborne laser point cloud data corresponding to the target area; performing ground point cloud extraction processing on the airborne laser point cloud data based on a moving surface fitting method to obtain extracted ground point cloud data; using the extracted ground point cloud data to construct a regular digital elevation model (DEM) based on a minimum difference algorithm, obtaining a regular DEM; and using the regular DEM and the designed regular DEM to measure the fill and excavation volumes of earthwork in the target area, obtaining the fill and excavation volume measurement results for the target area. In this embodiment of the invention, the measurement accuracy in densely vegetated areas is significantly improved while reducing labor costs.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method and related apparatus for measuring earthwork in densely vegetated areas based on laser point clouds. Background Technology

[0002] Earthwork surveying involves measuring elevation data within a specific area and calculating earthwork volume according to engineering surveying needs. It is a crucial step in road, water conservancy, railway, and building construction projects, providing a basis for project pre- and post-construction cost estimates and construction plan development. Traditional methods typically use instruments such as total stations and RTK receivers, employing polar coordinate methods and grid surveying to collect elevation data. While this method yields high accuracy, it is labor-intensive, costly, and inefficient. Especially for large-scale projects, traditional methods can significantly impact project progress. However, with the development of UAV oblique photogrammetry and airborne laser detection and ranging (LiDAR) technologies, the situation has changed dramatically. With the development of RANG technology, more and more scholars and engineers are studying its application in earthwork surveying. Some scholars have also compared the accuracy and efficiency of these two technologies in earthwork surveying. These studies are all aimed at survey areas with bare land or sparse vegetation, where elevation measurement is relatively simple. However, for high and steep mountainous areas with vegetation cover, it is difficult to obtain the original terrain. Airborne LiDAR is used to obtain the original terrain of densely vegetated mountainous areas with its non-contact and high-precision characteristics. Based on the multi-echo characteristics of point clouds, point clouds are classified to distinguish between topographic points and ground points, thereby obtaining ground elevation. However, in actual production operations, the multi-echo characteristics of point clouds are affected by the survey area environment, laser scanner performance, flight altitude, etc., and often only a small part of the point cloud has multiple echoes, which seriously affects the extraction of ground elevation points. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art. This invention provides a method and related device for measuring earthwork in densely vegetated areas based on laser point clouds. It can effectively filter out vegetation points, generate a regular digital elevation model (DEM) based on ground point cloud data, and finally calculate the earthwork volume based on the DEM. This significantly improves the measurement accuracy of densely vegetated areas while reducing labor costs.

[0004] To address the aforementioned technical problems, this invention provides a method for measuring earthwork in densely vegetated areas based on laser point clouds, applicable to a flight device equipped with an airborne lidar. The method includes:

[0005] The flight equipment, equipped with the airborne lidar, performs airborne laser point cloud data acquisition and processing on the target area over a preset airspace along a preset route to obtain airborne laser point cloud data corresponding to the target area, where the target area is a densely vegetated area.

[0006] The airborne laser point cloud data is processed by ground point cloud extraction based on the moving surface fitting method to obtain extracted ground point cloud data.

[0007] Based on the minimum difference algorithm, the extracted ground point cloud data is used to construct a regular digital elevation model to obtain the regular digital elevation model corresponding to the extracted ground point cloud data.

[0008] The regular digital elevation model and the design regular digital elevation model are used to measure the earthwork filling and excavation volume of the target area, and the earthwork filling and excavation volume measurement results of the target area are obtained.

[0009] Optionally, the step of performing ground point cloud extraction processing on the airborne laser point cloud data based on the moving surface fitting method to obtain extracted ground point cloud data includes:

[0010] The airborne laser point cloud data is denoised based on the radius filtering algorithm to obtain the denoised airborne laser point cloud data.

[0011] Ground point cloud extraction is performed on the denoised airborne laser point cloud data using the moving surface fitting method to obtain the extracted ground point cloud data.

[0012] Optionally, the step of performing point cloud denoising processing on the airborne laser point cloud data based on the radius filtering algorithm to obtain denoised airborne laser point cloud data includes:

[0013] Set the filtering radius r of the radius filtering algorithm, form a sphere with any point in the airborne laser point cloud data and the filtering radius r, and search for the number n of neighborhood points in the sphere with the center point as the neighborhood range;

[0014] If a threshold t is set, and the number of neighborhood points n is less than the threshold t, then the center point cloud is determined to be a noise point, and the noise point is removed.

[0015] The process continues until all points in the airborne laser point cloud data have been traversed, resulting in denoised airborne laser point cloud data.

[0016] Optionally, the step of performing ground point cloud extraction processing on the denoised airborne laser point cloud data based on the moving surface fitting method to obtain extracted ground point cloud data includes:

[0017] An index is built in the denoised airborne laser point cloud data based on the KD tree method;

[0018] Based on the index, the point m with the lowest elevation is selected from the denoised airborne laser point cloud data, and two other points with the lowest elevation within a preset range centered on point m are used to form a ground point set G, and other points within a preset range centered on point m are used as a candidate point set Q.

[0019] The points in the ground point set G are used to perform plane fitting on the plane equation to form a fitting plane;

[0020] Select point c from the candidate point set Q that is closest to the fitted plane, and set the plane coordinates X of point c. c Y c Substitute into the plane equation to calculate the fitted coordinates z c If the fitted coordinate z c Elevation Z of point c c If the threshold is exceeded, point c is considered to be a non-ground point; otherwise, point c is transferred from the candidate point set Q to the ground point set G to form an updated ground point set G. Then, plane fitting is performed using the definite plane equation of the updated ground point set G to form an updated fitting plane.

[0021] Until the number of points in the updated ground point set G equals the preset number, a new quadratic surface point set S is created using the updated ground point set G, and the number of points in the quadratic surface point set S remains unchanged by the preset number; a quadratic surface is constructed using the quadratic surface point set S to fit the terrain surface.

[0022] Select the point f closest to the quadratic surface from the candidate point set Q, and set the plane coordinates X of point f. f Y f Substitute into the equation of the quadratic surface to calculate the fitted coordinates z f ;

[0023] If the fitted coordinate z f Elevation Z of point f f If the threshold is exceeded, point f is considered a non-ground point. Otherwise, point f is transferred from the candidate point set Q to the ground point set G and the quadratic surface point set S. The oldest point is deleted in the quadratic surface point set S. This process continues until all points in the denoised airborne laser point cloud data have been traversed. Finally, the obtained ground point set G is used as the extracted ground point cloud data.

[0024] Optionally, the step of using the extracted ground point cloud data to construct a regular digital elevation model based on the minimum difference algorithm to obtain the regular digital elevation model corresponding to the extracted ground point cloud data includes:

[0025] The two-dimensional plane of the target area is divided into a regular grid according to squares of preset side lengths, and the extracted ground point cloud data is projected into the regular grid according to the planar coordinates of each ground point to form a projected regular grid.

[0026] The elevation value of the ground point with the lowest elevation among all ground points in each grid of the projection rule grid is taken as the elevation value of the corresponding grid.

[0027] If one of the grids does not have a projected ground point, then search all the ground points in the adjacent grids and select the ground point with the lowest elevation in the adjacent grids as the elevation value of the grid that does not have a projected ground point.

[0028] The regular digital elevation model corresponding to the extracted ground point cloud data is formed by the elevation value corresponding to each grid in the regular grid.

[0029] Optionally, the step of using the rule-based digital elevation model and the design rule-based digital elevation model to measure the earthwork filling and excavation volumes of the target area, and obtaining the earthwork filling and excavation volume measurement results of the target area, includes:

[0030] Extract the elevation value of each grid in the regular digital elevation model and extract the elevation value of each grid in the design regular digital elevation model, wherein the area of ​​each grid in the regular digital elevation model and the area of ​​each grid in the design regular digital elevation model are the same;

[0031] The earthwork volume of each grid is calculated based on the area of ​​each grid, the elevation value of each grid in the regular digital elevation model, and the elevation value of each grid in the design regular digital elevation model.

[0032] Based on the earthwork volume of each grid cell, the earthwork volume of the target area is measured, including both fill and cut volumes.

[0033] Optionally, obtaining the measurement results of the fill volume and the cut volume of the target area based on the fill and cut volume of each grid includes:

[0034] Determine whether the earthwork volume of each grid is greater than 0;

[0035] If the earthwork volume of each grid is less than 0, then the earthwork volume of the grid with a volume less than 0 is considered to be the earthwork volume; otherwise, the earthwork volume of the grid with a volume greater than 0 is considered to be the earthwork volume.

[0036] The total earthwork volume of all grids with a value greater than 0 is calculated as the earthwork fill volume measurement result for the target area, and the total earthwork excavation volume of all grids with a value less than 0 is calculated as the earthwork excavation volume measurement result for the target area.

[0037] In addition, this invention also provides a device for measuring earthwork in densely vegetated areas based on laser point clouds, applicable to a flight device equipped with an airborne lidar, the device comprising:

[0038] Data acquisition module: used for the flight equipment to carry the airborne lidar along a preset route in a preset airspace to collect and process airborne lidar point cloud data of the target area, and to obtain the airborne lidar point cloud data corresponding to the target area, wherein the target area is a densely vegetated area;

[0039] Point cloud extraction module: used to perform ground point cloud extraction processing on the airborne laser point cloud data based on the moving surface fitting method to obtain extracted ground point cloud data;

[0040] Model building module: used to process the extracted ground point cloud data to build a regular digital elevation model based on the minimum difference algorithm, and obtain the regular digital elevation model corresponding to the extracted ground point cloud data;

[0041] Measurement module: Used to measure the earthwork filling and excavation volume of the target area using the rule-based digital elevation model and the design rule-based digital elevation model, and to obtain the earthwork filling and excavation volume measurement results of the target area.

[0042] In addition, embodiments of the present invention also provide an electronic device, including a processor and a memory, wherein the processor runs a computer program or code stored in the memory to implement the earthwork measurement method for densely vegetated areas as described in any of the above embodiments.

[0043] In addition, embodiments of the present invention also provide a computer-readable storage medium for storing a computer program or code, which, when executed by a processor, implements the earthwork measurement method for densely vegetated areas as described above.

[0044] In this embodiment of the invention, the airborne lidar, mounted on a flight device, travels along a preset flight path in a preset airspace to collect and process airborne lidar point cloud data of a target area, obtaining airborne lidar point cloud data corresponding to the target area. Ground point cloud extraction is performed on the airborne lidar point cloud data using a moving surface fitting method, obtaining extracted ground point cloud data. A regular digital elevation model (DEM) is constructed using the extracted ground point cloud data based on a minimum difference algorithm, obtaining the corresponding DEM. The DEM and the designed DEM are then used to measure the earthwork filling and excavation volumes of the target area, obtaining the earthwork filling and excavation volume measurement results for the target area. This method effectively filters out vegetation points, then generates a DEM based on the ground point cloud data, and finally calculates the earthwork filling and excavation volumes based on the DEM. This significantly improves the measurement accuracy in densely vegetated areas while reducing labor costs. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a flowchart illustrating the earthwork measurement method for densely vegetated areas based on laser point clouds in an embodiment of the present invention.

[0047] Figure 2 This is a schematic diagram of the structural composition of the earthwork measurement device for densely vegetated areas based on laser point clouds in an embodiment of the present invention.

[0048] Figure 3 This is a schematic diagram of the structural composition of the electronic device in an embodiment of the present invention;

[0049] Figure 4 This is a vegetation cover map of the target area in an application embodiment of the present invention;

[0050] Figure 5 In another embodiment of the present invention, a vegetation cover map of the target area of ​​the application embodiment is used;

[0051] Figure 6 This is a digital elevation model of the target area before earthwork filling and excavation in an embodiment of the present invention.

[0052] Figure 7 This is the original point cloud map of the target area in the application embodiment of the present invention;

[0053] Figure 8 This is a ground point cloud map of the target area in an embodiment of the present invention.

[0054] Figure 9 This is a digital elevation model of the target area in an embodiment of the present invention. Detailed Implementation

[0055] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] Example 1, please refer to Figure 1 , Figure 1This is a flowchart illustrating the earthwork measurement method for densely vegetated areas based on laser point clouds in an embodiment of the present invention.

[0057] like Figure 1 As shown, a method for measuring earthwork in densely vegetated areas based on laser point clouds is applied to a flight device equipped with an airborne lidar. The method includes:

[0058] S101: The flight equipment, equipped with the airborne lidar, performs airborne laser point cloud data acquisition and processing on the target area in a preset airspace along a preset route to obtain airborne laser point cloud data corresponding to the target area, wherein the target area is a densely vegetated area.

[0059] In the specific implementation of this invention, airborne LiDAR, a direct positioning technology for acquiring surface spatial information through laser scanning of the ground, is a novel method of ground mapping. Airborne LiDAR has advantages that other methods do not possess. Based on the target area (i.e., densely vegetated area), the corresponding technical process (mainly including airspace application, route design, and aerial photography implementation) is executed to form a preset heading. Then, according to the preset route, airborne laser point cloud data is collected and processed in the preset airspace to obtain the airborne laser point cloud data corresponding to the target area.

[0060] S102: The airborne laser point cloud data is processed by ground point cloud extraction based on the moving surface fitting method to obtain extracted ground point cloud data;

[0061] In the specific implementation of this invention, the step of performing ground point cloud extraction processing on the airborne laser point cloud data based on the moving surface fitting method to obtain extracted ground point cloud data includes: performing point cloud denoising processing on the airborne laser point cloud data based on the radius filtering algorithm to obtain denoised airborne laser point cloud data; and performing ground point cloud extraction processing on the denoised airborne laser point cloud data based on the moving surface fitting method to obtain extracted ground point cloud data.

[0062] Furthermore, the step of performing point cloud denoising processing on the airborne laser point cloud data based on the radius filtering algorithm to obtain denoised airborne laser point cloud data includes: setting the filtering radius r of the radius filtering algorithm; forming a sphere with any point in the airborne laser point cloud data and the filtering radius r; and searching for the number n of neighborhood points in the sphere with the center point as the neighborhood range; setting a threshold t; if the number of neighborhood points n is less than the threshold t, then the center point cloud is determined to be a noise point and the noise point is removed; until all points in the airborne laser point cloud data have been traversed to obtain the denoised airborne laser point cloud data.

[0063] Furthermore, the ground point cloud extraction processing of the denoised airborne laser point cloud data based on the moving surface fitting method to obtain the extracted ground point cloud data includes: establishing an index in the denoised airborne laser point cloud data based on the KD tree method; selecting the point m with the lowest elevation in the denoised airborne laser point cloud data according to the index, and two other points with the lowest elevation within a preset range centered on point m to form a ground point set G, and using other points within the preset range centered on point m as a candidate point set Q; performing plane fitting processing on the plane equation using the points in the ground point set G to form a fitting plane; selecting the point c closest to the fitting plane from the candidate point set Q, and setting the plane coordinates X of point c... c Y c Substitute into the plane equation to calculate the fitted coordinates z c If the fitted coordinate z c Elevation Z of point c c If the threshold is exceeded, point c is considered a non-ground point; otherwise, point c is transferred from the candidate point set Q to the ground point set G to form an updated ground point set G. Plane fitting is then performed using the definite plane equation of the updated ground point set G to form an updated fitting plane. This process continues until the number of points in the updated ground point set G equals the preset number. Then, a new quadratic surface point set S is created using the updated ground point set G, with the number of points in the quadratic surface point set S remaining constant. A quadratic surface is constructed using the quadratic surface point set S to fit the terrain surface. The point f closest to the quadratic surface is selected from the candidate point set Q, and the plane coordinates X of point f are... f Y f Substitute into the equation of the quadratic surface to calculate the fitted coordinates z f If the fitted coordinates z f Elevation Z of point f f If the threshold is exceeded, point f is considered a non-ground point. Otherwise, point f is transferred from the candidate point set Q to the ground point set G and the quadratic surface point set S. The oldest point is deleted in the quadratic surface point set S. This process continues until all points in the denoised airborne laser point cloud data have been traversed. Finally, the obtained ground point set G is used as the extracted ground point cloud data.

[0064] Specifically, since the target area is a densely vegetated area, the airborne laser point cloud data corresponding to the target area contains a large number of vegetation points. Therefore, it is necessary to accurately remove the vegetation points in order to extract the corresponding ground point cloud data. Thus, point cloud denoising is required first, and then ground point cloud extraction is performed.

[0065] Since the acquired airborne laser point cloud data contains outliers, elevation anomalies, and other noise points, these noise points can affect subsequent ground point cloud extraction and earthwork volume calculation. Therefore, noise reduction algorithms such as radius filtering and statistical filtering are required. This technical solution uses a radius filtering algorithm. Specifically, a filtering radius *r* is set, and a sphere is formed using any point in the airborne laser point cloud data and the filtering radius *r*. The number of neighboring points *n* within the sphere, with the center point as the neighborhood, is searched. A threshold *t* is then set. If the number of neighborhood points *n* is less than the threshold *t*, the center point cloud is identified as a noise point and removed. This process is repeated until all points in the airborne laser point cloud data have been traversed to complete the noise reduction, resulting in the denoised airborne laser point cloud data.

[0066] The denoised airborne laser point cloud data still contains vegetation points and ground points, requiring a ground filtering algorithm to extract the ground points. For areas containing dense trees, shrubs, or grasslands, a moving surface fitting algorithm can more accurately remove vegetation points; the specific implementation is as follows:

[0067] First, an index is established. This technical solution uses the KD-tree method to create a certain number of indexes in the denoised airborne laser point cloud data. Then, based on the indexes, the point m with the lowest elevation in the denoised airborne laser point cloud data is selected, along with two other points with the lowest elevation within a preset range centered on point m, to form a ground point set G. Other points within the preset range centered on point m are used as a candidate point set Q. Finally, the points in the ground point set G are used to perform plane fitting on the plane equation to form a fitted plane, where the plane equation is: ; These are given constants.

[0068] Then, select point c from the candidate point set Q that is closest to the fitted plane, and set the plane coordinates X of point c to... c Y c Substitute into the plane equation to calculate the fitted coordinates z c If the fitted coordinate z c Elevation Z of point c cIf the threshold is exceeded, point c is considered a non-ground point; otherwise, point c is transferred from the candidate point set Q to the ground point set G to form an updated ground point set G. Plane fitting is then performed using the definite plane equation of the updated ground point set G to form an updated fitting plane. This process is repeated, selecting the point c closest to the fitting plane from the candidate point set Q, until the number of points in the updated ground point set G equals a preset number (typically set to 6). Then, a quadratic surface point set S is created using the updated ground point set G, with the number of points in S remaining constant. A quadratic surface is constructed using the quadratic surface point set S to fit the terrain surface. The point f closest to the quadratic surface is selected from the candidate point set Q, and the plane coordinates X of point f are... f Y f Substitute into the equation of the quadratic surface to calculate the fitted coordinates z f The equation of the quadratic surface is as follows: ; These are given constants.

[0069] If the fitted coordinate z f Elevation Z of point f f If the threshold is exceeded, point f is considered a non-ground point. Otherwise, point f is transferred from the candidate point set Q to the ground point set G and the quadratic surface point set S. The oldest point is deleted in the quadratic surface point set S. This process continues until all points in the denoised airborne laser point cloud data have been traversed. Finally, the obtained ground point set G is used as the extracted ground point cloud data.

[0070] S103: Based on the minimum difference algorithm, the extracted ground point cloud data is used to construct a regular digital elevation model to obtain the regular digital elevation model corresponding to the extracted ground point cloud data.

[0071] In the specific implementation of this invention, the step of using the extracted ground point cloud data to construct a regular digital elevation model based on the minimum difference algorithm to obtain the regular digital elevation model corresponding to the extracted ground point cloud data includes: dividing the two-dimensional plane of the target area into regular grids according to squares of preset side lengths, and projecting the extracted ground point cloud data into the regular grids according to the planar coordinates of each ground point to form a projected regular grid; taking the elevation value of the ground point with the lowest elevation among all ground points in each grid in the projected regular grid as the elevation value of the corresponding grid; if there is no projected ground point in one of the grids, searching all ground points in the adjacent grids and selecting the ground point with the lowest elevation in the adjacent grids as the elevation value of the grid where there is no projected ground point; and forming the regular digital elevation model corresponding to the extracted ground point cloud data from the elevation values ​​corresponding to each grid in the regular grid.

[0072] Specifically, the lowest point difference algorithm is used to construct a regular digital elevation model. This involves dividing the two-dimensional plane of the target area into regular grids using squares of preset side lengths. Then, the extracted ground point cloud data is projected onto these regular grids according to the planar coordinates of each ground point, forming a projected regular grid. The elevation value of the ground point with the lowest elevation among all ground points in each grid within the projected regular grid is used as the elevation value of the corresponding grid. Next, it is determined whether each grid has a projected ground point. If a grid does not have a projected ground point, all ground points in adjacent grids are searched, and the ground point with the lowest elevation among the adjacent grids is selected as the elevation value of the grid without a projected ground point. After setting the corresponding elevation value for each grid, the regular digital elevation model corresponding to the extracted ground point cloud data is formed from the elevation values ​​of each grid within the regular grid.

[0073] S104: Using the aforementioned rule-based digital elevation model and the design rule-based digital elevation model, the earthwork filling and excavation volumes of the target area are measured and processed to obtain the earthwork filling and excavation volume measurement results of the target area.

[0074] In the specific implementation of this invention, the step of measuring the earthwork filling and excavation volumes of the target area using the regular digital elevation model and the design regular digital elevation model to obtain the earthwork filling and excavation volume measurement results of the target area includes: extracting the elevation value of each grid in the regular digital elevation model and extracting the elevation value of each grid in the design regular digital elevation model, wherein each grid in the regular digital elevation model and each grid in the design regular digital elevation model have the same area; calculating the earthwork filling and excavation volume of each grid based on the area of ​​each grid, the elevation value of each grid in the regular digital elevation model, and the elevation value of each grid in the design regular digital elevation model; and obtaining the earthwork filling and excavation volume measurement results of the target area based on the earthwork filling and excavation volume of each grid.

[0075] Furthermore, the step of obtaining the earthwork fill volume measurement result and the earthwork cut volume measurement result of the target area based on the earthwork fill and cut volume of each grid includes: determining whether the earthwork fill and cut volume of each grid is greater than 0; if the earthwork fill and cut volume of each grid is less than 0, then the earthwork fill and cut volume of the grid with volume less than 0 is considered as the earthwork cut volume; otherwise, the earthwork fill and cut volume of the grid with volume greater than 0 is considered as the earthwork fill volume; calculating the sum of the earthwork fill volume of all grids with volume greater than 0 as the earthwork fill volume measurement result of the target area, and calculating the sum of the earthwork cut volume of all grids with volume less than 0 as the earthwork cut volume measurement result of the target area.

[0076] Specifically, the calculation of earthwork volume can be divided into calculating the volume of excavated earthwork and the volume of filled earthwork after the construction of earthwork and rock filling. That is, in earthwork prediction, the volume of earthwork to be excavated and filled can be predicted based on the design rule digital elevation model and the regular digital elevation model; that is, the design rule digital elevation model F and the regular digital elevation model B can be constructed before the excavation and filling; the difference between the two models is the volume of earthwork to be excavated and filled. The specific implementation process is as follows:

[0077] Assuming both the regular digital elevation model (DEM) and the design DEM have n grid cells, and the area of ​​each grid cell is s, then the elevations of the two models for the i-th grid cell are respectively... , The earthwork volume of the i-th grid is ,like A value less than 0 represents the excavation volume. A value greater than 0 represents the fill volume; finally, calculate all values ​​less than 0. The sum of these values ​​represents the measured earthwork volume for the target area; all values ​​greater than 0... The sum of these values ​​represents the measured volume of earthwork filling in the target area.

[0078] The key to earthwork surveying is ensuring the accuracy of the regular digital elevation model (DEM). For models used to establish DEMs, field measurements should be conducted to verify their accuracy and statistically analyze the results. Field measurements can be collected using the RTK method, and the accuracy should be statistically analyzed using the same precision testing method. The calculation formula is as follows:

[0079] ;

[0080] in, This refers to the error in the model elevation. The total number of checkpoints; The elevation value of the model; This is the true elevation value of the checkpoint.

[0081] In this embodiment of the invention, the airborne lidar, mounted on a flight device, travels along a preset flight path in a preset airspace to collect and process airborne lidar point cloud data of a target area, obtaining airborne lidar point cloud data corresponding to the target area. Ground point cloud extraction is performed on the airborne lidar point cloud data using a moving surface fitting method, obtaining extracted ground point cloud data. A regular digital elevation model (DEM) is constructed using the extracted ground point cloud data based on a minimum difference algorithm, obtaining the corresponding DEM. The DEM and the designed DEM are then used to measure the earthwork filling and excavation volumes of the target area, obtaining the earthwork filling and excavation volume measurement results for the target area. This method effectively filters out vegetation points, then generates a DEM based on the ground point cloud data, and finally calculates the earthwork filling and excavation volumes based on the DEM. This significantly improves the measurement accuracy in densely vegetated areas while reducing labor costs.

[0082] In this embodiment, a specific application implementation is provided as follows:

[0083] Applied to a construction project, the survey area was in the rainy season after excavation and filling, and vegetation was growing rapidly, with half of the area covered by 1 to 2 meters of grass. The survey area and its current condition are as follows. Figure 4 and Figure 5 As shown.

[0084] DEM before excavation of the target area, such as Figure 6 As shown; the raw laser point cloud collected by an airborne lidar device carried by a flight-borne equipment is as follows. Figure 7 As shown, the ground point cloud after filtering the original laser point cloud is as follows: Figure 8 As shown, vegetation points with higher elevations have been filtered out; the DEM generated from the ground point cloud is as follows: Figure 9 As shown in Table 1, to check the accuracy of the DEM, a total of 3192 checkpoints were collected. The difference between the checkpoint elevations and the DEM elevations was compared, and the accuracy calculation results are shown in Table 1.

[0085] Table 1. Elevation Data Comparison (Unit: meters)

[0086]

[0087] The calculated elevation error of the model is 22.68 cm, which is less than the 25 cm requirement of the "General Specification for Engineering Surveying" (GB 55018-2021), and the accuracy meets the requirements. Subsequently, comparing the above DEM with the DEM before cut and fill, the calculated fill volume is 42568.06 cubic meters, and the cut volume is 1324.99 cubic meters; the total fill and cut volume is the difference between the two, 41243.07 cubic meters. Using the traditional earthwork surveying method, the calculated fill volume is 41903.54 cubic meters, and the cut volume is 1528.67 cubic meters; the total fill and cut volume is the difference between the two, 40374.87 cubic meters. The difference in the total fill and cut volume calculated by the two methods is 868.2 cubic meters. The difference in the total fill and cut volume calculated by the method in this paper compared to the traditional method is 2.15%, which meets the requirements of the "Urban Surveying Specification" (CJJ / T). The requirement of 3% in (8-2011) is met; the comparison of earthwork volume calculated by the two methods is shown in Table 2.

[0088] Table 2

[0089]

[0090] Compared to traditional earthwork measurement methods, the laser point cloud-based earthwork measurement method has a significant efficiency advantage. Using traditional methods, two engineers would need two days to collect elevation data for 1 square kilometer in sparsely vegetated areas. For the aforementioned experimental survey area, two engineers would need ten days per square kilometer to complete the field elevation data collection, during which time weeds also need to be cleared, resulting in high workload. Data processing would take half a day. With the new method, two engineers can complete laser point cloud data collection in just one day and data processing in half a day. For some railway and highway projects, the survey areas are often remote, overgrown with trees, and without road access, making manual measurement difficult. The new method can significantly reduce manual labor, and as the survey area increases, the efficiency of airborne point cloud data collection becomes even more pronounced compared to manual collection.

[0091] Example 2, please refer to Figure 2 , Figure 2 This is a schematic diagram of the structural composition of the earthwork measurement device for densely vegetated areas based on laser point clouds in an embodiment of the present invention.

[0092] like Figure 2 As shown, a device for measuring earthwork in densely vegetated areas based on laser point clouds is applied to a flight-borne device equipped with an airborne lidar. The device includes:

[0093] Data acquisition module 201: used for the flight equipment to carry the airborne lidar along a preset route in a preset airspace to collect and process airborne lidar point cloud data of the target area, and to obtain airborne lidar point cloud data corresponding to the target area, wherein the target area is a densely vegetated area;

[0094] In the specific implementation of this invention, airborne LiDAR, a direct positioning technology for acquiring surface spatial information through laser scanning of the ground, is a novel method of ground mapping. Airborne LiDAR has advantages that other methods do not possess. Based on the target area (i.e., densely vegetated area), the corresponding technical process (mainly including airspace application, route design, and aerial photography implementation) is executed to form a preset heading. Then, according to the preset route, airborne laser point cloud data is collected and processed in the preset airspace to obtain the airborne laser point cloud data corresponding to the target area.

[0095] Point cloud extraction module 202: used to perform ground point cloud extraction processing on the airborne laser point cloud data based on the moving surface fitting method to obtain extracted ground point cloud data;

[0096] In the specific implementation of this invention, the step of performing ground point cloud extraction processing on the airborne laser point cloud data based on the moving surface fitting method to obtain extracted ground point cloud data includes: performing point cloud denoising processing on the airborne laser point cloud data based on the radius filtering algorithm to obtain denoised airborne laser point cloud data; and performing ground point cloud extraction processing on the denoised airborne laser point cloud data based on the moving surface fitting method to obtain extracted ground point cloud data.

[0097] Furthermore, the step of performing point cloud denoising processing on the airborne laser point cloud data based on the radius filtering algorithm to obtain denoised airborne laser point cloud data includes: setting the filtering radius r of the radius filtering algorithm; forming a sphere with any point in the airborne laser point cloud data and the filtering radius r; and searching for the number n of neighborhood points in the sphere with the center point as the neighborhood range; setting a threshold t; if the number of neighborhood points n is less than the threshold t, then the center point cloud is determined to be a noise point and the noise point is removed; until all points in the airborne laser point cloud data have been traversed to obtain the denoised airborne laser point cloud data.

[0098] Furthermore, the ground point cloud extraction processing of the denoised airborne laser point cloud data based on the moving surface fitting method to obtain the extracted ground point cloud data includes: establishing an index in the denoised airborne laser point cloud data based on the KD tree method; selecting the point m with the lowest elevation in the denoised airborne laser point cloud data according to the index, and two other points with the lowest elevation within a preset range centered on point m to form a ground point set G, and using other points within the preset range centered on point m as a candidate point set Q; performing plane fitting processing on the plane equation using the points in the ground point set G to form a fitting plane; selecting the point c closest to the fitting plane from the candidate point set Q, and setting the plane coordinates X of point c... c Y c Substitute into the plane equation to calculate the fitted coordinates z cIf the fitted coordinate z c Elevation Z of point c c If the threshold is exceeded, point c is considered a non-ground point; otherwise, point c is transferred from the candidate point set Q to the ground point set G to form an updated ground point set G. Plane fitting is then performed using the definite plane equation of the updated ground point set G to form an updated fitting plane. This process continues until the number of points in the updated ground point set G equals the preset number. Then, a new quadratic surface point set S is created using the updated ground point set G, with the number of points in the quadratic surface point set S remaining constant. A quadratic surface is constructed using the quadratic surface point set S to fit the terrain surface. The point f closest to the quadratic surface is selected from the candidate point set Q, and the plane coordinates X of point f are... f Y f Substitute into the equation of the quadratic surface to calculate the fitted coordinates z f If the fitted coordinates z f Elevation Z of point f f If the threshold is exceeded, point f is considered a non-ground point. Otherwise, point f is transferred from the candidate point set Q to the ground point set G and the quadratic surface point set S. The oldest point is deleted in the quadratic surface point set S. This process continues until all points in the denoised airborne laser point cloud data have been traversed. Finally, the obtained ground point set G is used as the extracted ground point cloud data.

[0099] Specifically, since the target area is a densely vegetated area, the airborne laser point cloud data corresponding to the target area contains a large number of vegetation points. Therefore, it is necessary to accurately remove the vegetation points in order to extract the corresponding ground point cloud data. Thus, point cloud denoising is required first, and then ground point cloud extraction is performed.

[0100] Since the acquired airborne laser point cloud data contains outliers, elevation anomalies, and other noise points, these noise points can affect subsequent ground point cloud extraction and earthwork volume calculation. Therefore, noise reduction algorithms such as radius filtering and statistical filtering are required. This technical solution uses a radius filtering algorithm. Specifically, a filtering radius *r* is set, and a sphere is formed using any point in the airborne laser point cloud data and the filtering radius *r*. The number of neighboring points *n* within the sphere, with the center point as the neighborhood, is searched. A threshold *t* is then set. If the number of neighborhood points *n* is less than the threshold *t*, the center point cloud is identified as a noise point and removed. This process is repeated until all points in the airborne laser point cloud data have been traversed to complete the noise reduction, resulting in the denoised airborne laser point cloud data.

[0101] The denoised airborne laser point cloud data still contains vegetation points and ground points, requiring a ground filtering algorithm to extract the ground points. For areas containing dense trees, shrubs, or grasslands, a moving surface fitting algorithm can more accurately remove vegetation points; the specific implementation is as follows:

[0102] First, an index is established. This technical solution uses the KD-tree method to create a certain number of indexes in the denoised airborne laser point cloud data. Then, based on the indexes, the point m with the lowest elevation in the denoised airborne laser point cloud data is selected, along with two other points with the lowest elevation within a preset range centered on point m, to form a ground point set G. Other points within the preset range centered on point m are used as a candidate point set Q. Finally, the points in the ground point set G are used to perform plane fitting on the plane equation to form a fitted plane, where the plane equation is: ; These are given constants.

[0103] Then, select point c from the candidate point set Q that is closest to the fitted plane, and set the plane coordinates X of point c to... c Y c Substitute into the plane equation to calculate the fitted coordinates z c If the fitted coordinate z c Elevation Z of point c c If the threshold is exceeded, point c is considered a non-ground point; otherwise, point c is transferred from the candidate point set Q to the ground point set G to form an updated ground point set G. Plane fitting is then performed using the definite plane equation of the updated ground point set G to form an updated fitting plane. This process is repeated, selecting the point c closest to the fitting plane from the candidate point set Q, until the number of points in the updated ground point set G equals a preset number (typically set to 6). Then, a quadratic surface point set S is created using the updated ground point set G, with the number of points in S remaining constant. A quadratic surface is constructed using the quadratic surface point set S to fit the terrain surface. The point f closest to the quadratic surface is selected from the candidate point set Q, and the plane coordinates X of point f are... f Y f Substitute into the equation of the quadratic surface to calculate the fitted coordinates z f The equation of the quadratic surface is as follows: ; These are given constants.

[0104] If the fitted coordinate z f Elevation Z of point f f If the threshold is exceeded, point f is considered a non-ground point. Otherwise, point f is transferred from the candidate point set Q to the ground point set G and the quadratic surface point set S. The oldest point is deleted in the quadratic surface point set S. This process continues until all points in the denoised airborne laser point cloud data have been traversed. Finally, the obtained ground point set G is used as the extracted ground point cloud data.

[0105] Model building module 203: is used to perform regular digital elevation model construction processing on the extracted ground point cloud data based on the minimum difference algorithm, so as to obtain the regular digital elevation model corresponding to the extracted ground point cloud data.

[0106] In the specific implementation of this invention, the step of using the extracted ground point cloud data to construct a regular digital elevation model based on the minimum difference algorithm to obtain the regular digital elevation model corresponding to the extracted ground point cloud data includes: dividing the two-dimensional plane of the target area into regular grids according to squares of preset side lengths, and projecting the extracted ground point cloud data into the regular grids according to the planar coordinates of each ground point to form a projected regular grid; taking the elevation value of the ground point with the lowest elevation among all ground points in each grid in the projected regular grid as the elevation value of the corresponding grid; if there is no projected ground point in one of the grids, searching all ground points in the adjacent grids and selecting the ground point with the lowest elevation in the adjacent grids as the elevation value of the grid where there is no projected ground point; and forming the regular digital elevation model corresponding to the extracted ground point cloud data from the elevation values ​​corresponding to each grid in the regular grid.

[0107] Specifically, the lowest point difference algorithm is used to construct a regular digital elevation model. This involves dividing the two-dimensional plane of the target area into regular grids using squares of preset side lengths. Then, the extracted ground point cloud data is projected onto these regular grids according to the planar coordinates of each ground point, forming a projected regular grid. The elevation value of the ground point with the lowest elevation among all ground points in each grid within the projected regular grid is used as the elevation value of the corresponding grid. Next, it is determined whether each grid has a projected ground point. If a grid does not have a projected ground point, all ground points in adjacent grids are searched, and the ground point with the lowest elevation among the adjacent grids is selected as the elevation value of the grid without a projected ground point. After setting the corresponding elevation value for each grid, the regular digital elevation model corresponding to the extracted ground point cloud data is formed from the elevation values ​​of each grid within the regular grid.

[0108] Measurement module 204: Used to measure the earthwork filling and excavation volume of the target area using the rule digital elevation model and the design rule digital elevation model, and to obtain the earthwork filling and excavation volume measurement results of the target area.

[0109] In the specific implementation of this invention, the step of measuring the earthwork filling and excavation volumes of the target area using the regular digital elevation model and the design regular digital elevation model to obtain the earthwork filling and excavation volume measurement results of the target area includes: extracting the elevation value of each grid in the regular digital elevation model and extracting the elevation value of each grid in the design regular digital elevation model, wherein each grid in the regular digital elevation model and each grid in the design regular digital elevation model have the same area; calculating the earthwork filling and excavation volume of each grid based on the area of ​​each grid, the elevation value of each grid in the regular digital elevation model, and the elevation value of each grid in the design regular digital elevation model; and obtaining the earthwork filling and excavation volume measurement results of the target area based on the earthwork filling and excavation volume of each grid.

[0110] Furthermore, the step of obtaining the earthwork fill volume measurement result and the earthwork cut volume measurement result of the target area based on the earthwork fill and cut volume of each grid includes: determining whether the earthwork fill and cut volume of each grid is greater than 0; if the earthwork fill and cut volume of each grid is less than 0, then the earthwork fill and cut volume of the grid with volume less than 0 is considered as the earthwork cut volume; otherwise, the earthwork fill and cut volume of the grid with volume greater than 0 is considered as the earthwork fill volume; calculating the sum of the earthwork fill volume of all grids with volume greater than 0 as the earthwork fill volume measurement result of the target area, and calculating the sum of the earthwork cut volume of all grids with volume less than 0 as the earthwork cut volume measurement result of the target area.

[0111] Specifically, the calculation of earthwork volume can be divided into calculating the volume of excavated earthwork and the volume of filled earthwork after the construction of earthwork and rock filling. That is, in earthwork prediction, the volume of earthwork to be excavated and filled can be predicted based on the design rule digital elevation model and the regular digital elevation model; that is, the design rule digital elevation model F and the regular digital elevation model B can be constructed before the excavation and filling; the difference between the two models is the volume of earthwork to be excavated and filled. The specific implementation process is as follows:

[0112] Assuming both the regular digital elevation model (DEM) and the design DEM have n grid cells, and the area of ​​each grid cell is s, then the elevations of the two models for the i-th grid cell are respectively... , The earthwork volume of the i-th grid is ,like A value less than 0 represents the excavation volume. A value greater than 0 represents the fill volume; finally, calculate all values ​​less than 0. The sum of these values ​​represents the measured earthwork volume for the target area; all values ​​greater than 0... The sum of these values ​​represents the measured volume of earthwork filling in the target area.

[0113] The key to earthwork surveying is ensuring the accuracy of the regular digital elevation model (DEM). For models used to establish DEMs, field measurements should be conducted to verify their accuracy and statistically analyze the results. Field measurements can be collected using the RTK method, and the accuracy should be statistically analyzed using the same precision testing method. The calculation formula is as follows:

[0114] ;

[0115] in, This refers to the error in the model elevation. The total number of checkpoints; The elevation value of the model; This is the true elevation value of the checkpoint.

[0116] In this embodiment of the invention, the airborne lidar, mounted on a flight device, travels along a preset flight path in a preset airspace to collect and process airborne lidar point cloud data of a target area, obtaining airborne lidar point cloud data corresponding to the target area. Ground point cloud extraction is performed on the airborne lidar point cloud data using a moving surface fitting method, obtaining extracted ground point cloud data. A regular digital elevation model (DEM) is constructed using the extracted ground point cloud data based on a minimum difference algorithm, obtaining the corresponding DEM. The DEM and the designed DEM are then used to measure the earthwork filling and excavation volumes of the target area, obtaining the earthwork filling and excavation volume measurement results for the target area. This method effectively filters out vegetation points, then generates a DEM based on the ground point cloud data, and finally calculates the earthwork filling and excavation volumes based on the DEM. This significantly improves the measurement accuracy in densely vegetated areas while reducing labor costs.

[0117] This invention provides a computer-readable storage medium storing a computer program. When executed by a processor, this program implements the earthwork measurement method for densely vegetated areas described in any of the above embodiments. The computer-readable storage medium includes, but is not limited to, any type of disk (including floppy disks, hard disks, optical disks, CD-ROMs, and magneto-optical disks), ROM (Read-Only Memory), RAM (Random Access Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic cards, or optical cards. In other words, the storage device includes any medium that can store or transmit information in a readable form by a device (e.g., a computer, a mobile phone), and can be a read-only memory, a disk, or an optical disk, etc.

[0118] This invention also provides a computer application running on a computer, which is used to execute the earthwork measurement method for densely vegetated areas in any of the above embodiments.

[0119] also, Figure 3 This is a schematic diagram of the structural composition of the electronic device in an embodiment of the present invention.

[0120] This invention also provides an electronic device, such as... Figure 3 As shown. The electronic device includes a processor 302, a memory 303, an input unit 304, and a display unit 305, among other devices. Those skilled in the art will understand that... Figure 3 The structural components of the illustrated electronic device do not constitute a limitation on all devices and may include more or fewer components than illustrated, or combine certain components. Memory 303 can be used to store application program 301 and various functional modules. Processor 302 runs application program 301 stored in memory 303, thereby performing various functional applications and data processing of the device. Memory can be internal memory or external memory, or both. Internal memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, or random access memory. External memory may include hard disks, floppy disks, ZIP disks, USB flash drives, magnetic tapes, etc. The memory disclosed in this invention includes, but is not limited to, these types of memory. The memory disclosed in this invention is only an example and not a limitation.

[0121] Input unit 304 is used to receive signal input and user-input keywords. Input unit 304 may include a touch panel and other input devices. The touch panel can collect user touch operations on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch panel) and drive the corresponding connection device according to a pre-set program; other input devices may include, but are not limited to, one or more of physical keyboards, function keys (such as play control buttons, power buttons, etc.), trackballs, mice, joysticks, etc. Display unit 305 can be used to display user-input information or information provided to the user, as well as various menus of the terminal device. Display unit 305 may be in the form of a liquid crystal display, organic light-emitting diode, etc. Processor 302 is the control center of the terminal device, connecting various parts of the entire device through various interfaces and lines, and performing various functions and processing data by running or executing software programs and / or modules stored in memory 303, and calling data stored in memory.

[0122] As one embodiment, the electronic device includes: one or more processors 302, a memory 303, and one or more application programs 301, wherein the one or more application programs 301 are stored in the memory 303 and configured to be executed by the one or more processors 302, and the one or more application programs 301 are configured to perform the earthwork measurement method for densely vegetated areas corresponding to any of the embodiments described above.

[0123] In this embodiment of the invention, the airborne lidar, mounted on a flight device, travels along a preset flight path in a preset airspace to collect and process airborne lidar point cloud data of a target area, obtaining airborne lidar point cloud data corresponding to the target area. Ground point cloud extraction is performed on the airborne lidar point cloud data using a moving surface fitting method, obtaining extracted ground point cloud data. A regular digital elevation model (DEM) is constructed using the extracted ground point cloud data based on a minimum difference algorithm, obtaining the corresponding DEM. The DEM and the designed DEM are then used to measure the earthwork filling and excavation volumes of the target area, obtaining the earthwork filling and excavation volume measurement results for the target area. This method effectively filters out vegetation points, then generates a DEM based on the ground point cloud data, and finally calculates the earthwork filling and excavation volumes based on the DEM. This significantly improves the measurement accuracy in densely vegetated areas while reducing labor costs.

[0124] Furthermore, the above provides a detailed description of the method and related apparatus for measuring earthwork in densely vegetated areas based on laser point clouds, as provided in the embodiments of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for earthwork measurement in a vegetation dense area based on a laser point cloud, characterized in that, The method is applied to a flight device carrying an airborne laser radar, and the method comprises the following steps: The flight device carries the airborne laser radar to collect and process airborne laser point cloud data of a target region on a preset air route in a preset airspace, to obtain airborne laser point cloud data corresponding to the target region, the target region being a dense vegetation region; Ground point cloud data is extracted from the airborne laser point cloud data based on a moving surface fitting method, to obtain extracted ground point cloud data; A regular digital elevation model is constructed based on a minimum difference algorithm using the extracted ground point cloud data, to obtain a regular digital elevation model corresponding to the extracted ground point cloud data; a two-dimensional plane of the target region is divided into a regular grid according to a square of a preset side length, and the extracted ground point cloud data is projected in the regular grid according to the planar coordinates of each ground point, to form a projected regular grid; the elevation value of the ground point with the lowest elevation in each grid in the projected regular grid is taken as the elevation value of the corresponding grid; if there is no projected ground point in one grid, all ground points in adjacent grids are searched, and the ground point with the lowest elevation in the adjacent grid is taken as the elevation value of the grid without the projected ground point; the elevation value of each grid in the regular grid is taken as the regular digital elevation model corresponding to the extracted ground point cloud data; The regular digital elevation model and a design regular digital elevation model are used to measure the earthwork filling amount and the earthwork digging amount of the target region, to obtain the earthwork filling amount measurement result and the earthwork digging amount measurement result of the target region; the elevation value of each grid in the regular digital elevation model and the elevation value of each grid in the design regular digital elevation model are extracted, wherein the area of each grid in the regular digital elevation model is the same as the area of each grid in the design regular digital elevation model; the earthwork filling and digging amount of each grid is calculated according to the area of each grid, the elevation value of each grid in the regular digital elevation model, and the elevation value of each grid in the design regular digital elevation model; and the earthwork filling amount measurement result and the earthwork digging amount measurement result of the target region are obtained according to the earthwork filling and digging amount of each grid.

2. The method of earthwork measurement of vegetation dense area according to claim 1, characterized in that, The method comprises the following steps: Point cloud denoising is performed on the airborne laser point cloud data based on a radius filtering algorithm, to obtain denoised airborne laser point cloud data; Ground point cloud data is extracted from the denoised airborne laser point cloud data based on a moving surface fitting method, to obtain extracted ground point cloud data.

3. The method of earthwork measurement of vegetation dense area according to claim 2, characterized in that, The method comprises the following steps: A filtering radius r of the radius filtering algorithm is set, a sphere is formed by any one point in the airborne laser point cloud data and the filtering radius r, and the number n of neighborhood points in the sphere within the neighborhood range of the center point is searched; A threshold t is set, if the number of field points n is less than the threshold t, it is judged that the center point cloud is a noise point, and the noise point is removed; Until all points in the airborne laser point cloud data are traversed, the de-noised airborne laser point cloud data is obtained.

4. The method of earthwork measurement of vegetation dense area according to claim 2, wherein, The ground point cloud extraction processing is performed on the de-noised airborne laser point cloud data based on the moving surface fitting method, and the extracted ground point cloud data is obtained, including: An index is established in the de-noised airborne laser point cloud data based on the KD tree method; The point m with the lowest elevation is selected in the de-noised airborne laser point cloud data according to the index, and another two points with the lowest elevation in a preset range centered on the point m are used to form a ground point set G, and other points in the preset range centered on the point m are used as a candidate point set Q; The points in the ground point set G are used for plane fitting processing in a plane equation to form a fitting plane; selecting a point c closest to the fitting plane from the candidate point set Q and substituting the plane coordinates X c , Y c of the point c into the plane equation to calculate a fitting coordinate z c , if the fitting coordinate z c and the elevation Z c of the point c exceed a preset threshold, then the point c is considered as a non-ground point, otherwise the point c is transferred from the candidate point set Q to the ground point set G to form an updated ground point set G, and plane fitting processing is performed in the plane equation using the updated ground point set G to form an updated fitting plane; Until the number of points in the updated ground point set G is equal to the preset number, a new quadratic surface point set S is established using the updated ground point set G, and the number of points in the quadratic surface point set S remains unchanged; the quadratic surface point set S is used to construct a quadratic surface to fit the terrain surface; Selecting a point f closest to the quadric surface from the set of alternative points Q, and substituting the planar coordinates X f , Y f of the point f into the quadric surface equation to calculate a fitted coordinate z f ; If the fitting coordinate z f and the elevation Z f of the point f exceeds a preset threshold, then the point f is considered as a non-ground point, otherwise the point f is transferred from the candidate point set Q to the ground point set G and the quadric surface point set S, and the oldest point is deleted in the quadric surface point set S, and after all the points in the denoised airborne laser point cloud data are traversed, the obtained ground point set G is taken as the extracted ground point cloud data.

5. The method of earthwork measurement of vegetation dense area according to claim 1, wherein, The filling and digging earthwork amount of each grid is obtained, and the filling amount measurement result and the digging amount measurement result of the earthwork of the target area are obtained, including: It is judged whether the filling and digging earthwork amount of each grid is greater than 0; If the filling and digging earthwork amount of each grid is less than 0, it is considered that the filling and digging earthwork amount of the grid less than 0 is the digging earthwork amount; otherwise, it is considered that the filling and digging earthwork amount of the grid greater than 0 is the filling earthwork amount; The sum of the filling earthwork amount of all grids greater than 0 is calculated as the filling amount measurement result of the earthwork of the target area, and the sum of the digging earthwork amount of all grids less than 0 is calculated as the digging amount measurement result of the earthwork of the target area.

6. A device for measuring earthwork in a vegetation dense area based on a laser point cloud, characterized in that, The device is applied to a flight equipment carrying an airborne laser radar, and includes: A data acquisition module is configured to acquire airborne laser point cloud data of a target area by the flight equipment carrying the airborne laser radar and flying a preset route in a preset airspace, the target area being a vegetation dense area; A point cloud extraction module is configured to extract ground point cloud data from the airborne laser point cloud data based on a moving surface fitting method; The model construction module is configured to: construct a regular digital elevation model based on the extracted ground point cloud data using a minimum difference algorithm; divide a two-dimensional plane of the target area into a regular grid according to a preset square side length, and project the extracted ground point cloud data on the regular grid according to the plane coordinates of each ground point to form a projected regular grid; take the elevation value of the ground point with the lowest elevation among all the ground points in each grid of the projected regular grid as the elevation value of the corresponding grid; if there is no projected ground point in one grid, search for all the ground points in adjacent grids, and take the ground point with the lowest elevation in the adjacent grids as the elevation value of the grid without the projected ground point; and form a regular digital elevation model corresponding to the extracted ground point cloud data from the elevation value of each grid of the regular grid. The measurement module is configured to: measure the earthwork filling amount and the earthwork digging amount of the target area using the regular digital elevation model and a design regular digital elevation model, and obtain the earthwork filling amount measurement result and the earthwork digging amount measurement result of the target area; extract the elevation value of each grid in the regular digital elevation model and the elevation value of each grid in the design regular digital elevation model, wherein the area of each grid in the regular digital elevation model is the same as the area of each grid in the design regular digital elevation model; calculate the earthwork filling and digging amount of each grid according to the area of each grid, the elevation value of each grid in the regular digital elevation model, and the elevation value of each grid in the design regular digital elevation model; and obtain the earthwork filling amount measurement result and the earthwork digging amount measurement result of the target area according to the earthwork filling and digging amount of each grid.

7. An electronic device comprising a processor and a memory, characterized in that The processor runs a computer program or code stored in the memory to implement the vegetation dense area earthwork measurement method according to any one of claims 1 to 5.

8. A computer readable storage medium for storing a computer program or code, characterized in that, When the computer program or code is executed by the processor, the vegetation dense area earthwork measurement method according to any one of claims 1 to 5 is implemented.

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