Investigation method for newly increased cultivated land after land reclamation based on three-dimensional laser scanning

Abstract

The invention discloses a method for investigating newly increased cultivated land after land reclamation based on three-dimensional laser scanning. The method comprises the following steps: step 1, acquiring point cloud data of a target area by adopting an unmanned aerial vehicle to carry a three-dimensional laser scanner; 2, the design height and the height threshold range (a, b) of the newly-added cultivated land are determined; step 3, selecting point cloud data in a height threshold range, namely newly added cultivated land point cloud data; 4, coordinate point (x, y) values are extracted based on the newly-added cultivated land point cloud data, concave packet calculation is carried out based on a spheronization algorithm, a newly-added cultivated land polygon is generated, and boundary points (X, Y) of the newly-added cultivated land point cloud data are obtained; and step 5, calculating a newly added cultivated land area Si based on the boundary points (X, Y). According to the invention, the unmanned aerial vehicle autonomously scans and calculates the mountainous region, detects the new farmland increase condition, regularly, quickly and autonomously identifies and detects the new farmland area of the whole field of the project, detects the construction progress, and reduces the labor cost.

Description

Technical Field

[0001] The present invention relates to the technical field of land consolidation, and in particular to a method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning. Background Art

[0002] 3D laser scanning is a mature measurement technology widely used in surveying and mapping, architecture, archaeology, manufacturing, mining, and other fields requiring precise 3D models. This technology uses a laser beam to scan objects and scenes. By measuring the time or phase change of the laser beam's reflection, the distance from the device can be calculated. This data is then transformed into point cloud data—a series of 3D coordinate points. This point cloud data can be used to create highly accurate 3D models, enabling faster and more accurate terrain measurement, volume calculation, and topographic mapping than traditional methods.

[0003] Currently, the methods used to survey newly added arable land in land consolidation projects generally include ground surveys and remote sensing image recognition. Ground surveys usually require GPS tools and instruments for real-world measurements, and the measuring instruments must be calibrated and qualified.

[0004] During the existing land leveling construction process, regular quality inspection and assessment of completed processes and progress are required to ensure progress and quality. This typically involves organizing inspectors to conduct on-site inspections and actual measurements. This typically involves setting up a sufficient number of mutually visible coordinate control points and elevation leveling points at the construction site. Based on the coordinate control points on the design drawings, three-level coordinate control points are laid out using GPS and connected to the previously communicated coordinate control points for closed-loop measurement. After on-site inspection of the land leveling, the number of acres of newly added arable land should be consistent with the number of acres recorded in the self-inspection records. This data should be recorded and an analysis report submitted to the company's quality management department.

[0005] This on-site measurement process is time-consuming and labor-intensive, making it difficult to quickly and frequently monitor site conditions, especially when the project scope is large and the number of observation points is high. Identifying newly added arable land through remote sensing imagery often requires completing land leveling and performing remote sensing image recognition as crops emerge. Furthermore, due to differences in crop type, growth stage, farmland management practices, and soil type, the spectral characteristics and texture characteristics of arable land images vary greatly. In some areas, the spectral texture characteristics are not distinct, making it easy to mix arable land with other land types when extracting arable land. Summary of the Invention

[0006] The present invention provides a method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning. The method uses drones to autonomously scan and calculate mountains, detect newly added cultivated land, regularly and quickly autonomously identify the newly added cultivated land area of ​​the entire project site, detect construction progress, and reduce labor costs.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0008] The method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning of the present invention comprises the following steps:

[0009] Step 1: Obtain point cloud data of the target area;

[0010] Step 2: Determine the design height and height threshold range (a, b) of the newly added cultivated land;

[0011] Step 3: Select point cloud data within the height threshold range, that is, add farmland point cloud data;

[0012] Step 4: Extract the coordinate point (x, y) values ​​based on the newly added cultivated land point cloud data, calculate the concave hull based on the rolling circle algorithm, generate the newly added cultivated land polygon and obtain the boundary points (X, Y) of the newly added cultivated land point cloud data;

[0013] Step 5: Calculate the newly added cultivated land area S based on the boundary points (X, Y) i .

[0014] The method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning of the present invention further includes step 6: after a period of land consolidation, obtaining point cloud data of the target area again, repeating steps 2-5 to calculate the newly added cultivated land area S i+1 Calculate the newly added area A during a period of land consolidation i , A i =S i+1 -S i , A i B within the construction plan time period i Compare and check whether it meets the construction plan objectives. If it does not meet the construction plan, a warning will be issued.

[0015] The present invention is based on a method for investigating newly added cultivated land after land reclamation using three-dimensional laser scanning. Furthermore, when there are multiple newly added cultivated lands, a height threshold of each newly added cultivated land is determined, and the area of ​​each newly added cultivated land is calculated based on point cloud data within the height threshold range of each newly added cultivated land.

[0016] The present invention is a method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning. Furthermore, an unmanned aerial vehicle equipped with a three-dimensional laser scanner is used to obtain point cloud data of the target area.

[0017] The present invention is based on a method for investigating newly added cultivated land after land consolidation using three-dimensional laser scanning. Furthermore, a three-dimensional laser scanner obtains a point cloud dataset P = {p1, p2, p3...} of a target area, imports it into an unmanned aerial vehicle platform, performs data preprocessing, extracts coordinate information (x, y, z) of the point cloud data, and selects point cloud data whose height z value is within a height threshold range (a, b) and is defined as the newly added cultivated land point cloud data.

[0018] The present invention is based on a method for investigating newly added cultivated land after land consolidation using three-dimensional laser scanning. Furthermore, in step 4, the concave hull calculation is performed based on a rolling algorithm. The specific operations are as follows:

[0019] 1) Initialize an empty concave hull and a marker array for tracking the point cloud data added to the concave hull;

[0020] 2) Determine the rolling ball radius R;

[0021] 3) Find a point with the smallest y value as the initial point A;

[0022] 4) Starting from point A, first find a point B whose distance to A is less than 2R, so that point A and point B both fall on the circle with a diameter of 2R, the distance from point A and point B to the center of the circle is equal to R, and there is no third point with a distance equal to R to the center of the circle. At this point, a circle with a radius of R is stuck on the chord AB. The chord AB is the first boundary line, and point B is a boundary point and is included in the concave hull point array;

[0023] 5) Repeat step 4), starting from point B, determine boundary point C, and add boundary point C to the concave hull point array; repeat the ball rolling process in step 5 until no new boundary points can be added;

[0024] 6) Generate one or more polygons based on the concave point array.

[0025] The present invention is based on a method for investigating newly added cultivated land after land consolidation using three-dimensional laser scanning. Further, when the y values ​​are the same, the point with the largest x value is taken as the initial point A.

[0026] The present invention is based on a method for investigating newly added cultivated land after land consolidation using three-dimensional laser scanning. Furthermore, when the data points of the point cloud data are unevenly distributed, a mechanism for dynamically adjusting the rolling ball radius is introduced. Initially, the radius is set as small as possible to move close to the edge of the details. However, in relatively sparse locations, the radius of the rolling ball is continuously lengthened until the next reasonable boundary point is obtained, and then the radius returns to the original rolling ball size and continues to move forward.

[0027] The present invention is based on a method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning. Further, based on a sequence of boundary points (X1, Y1), (X2, Y2), ..., (X n ,Yn ), calculate the newly added cultivated land area S 耕地面积 , and record S 耕地面积 For S i , S 耕地面积 The calculation formula is as follows:

[0028]

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] The drone is equipped with a three-dimensional laser scanning device. After scanning the terrain, it sets the terrace height threshold to quickly calculate the newly added cultivated land area, reducing labor costs and enabling the drone equipment to conduct regular autonomous inspections of the area of ​​newly added cultivated land after land reclamation, thereby ensuring the progress and quality of the land reclamation project.

[0031] The present invention will be further described below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is the workflow diagram of the present invention. DETAILED DESCRIPTION

[0033] like Figure 1 As shown, the present invention discloses a method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning, comprising the following steps:

[0034] Step 1: Based on the land consolidation construction plan for the target area, determine the location and height of the newly added arable land, and determine how much area the newly added arable land should reach after the set land consolidation construction period. The newly added arable land in mountainous areas is mostly terraced fields.

[0035] According to the regional conditions of the target area, the UAV flight range, path and scanning interval are determined, and the point cloud terrain data of the target area is prepared.

[0036] The initial point cloud data of the target area is obtained by using a 3D laser scanner mounted on a UAV. The 3D laser scanner obtains a point cloud dataset P = {p1, p2, p3...} of the target area, which is imported into the UAV platform for data preprocessing and the coordinate information (x, y, z) of the point cloud data is extracted.

[0037] Step 2: Determine the estimated location and height of the newly added farmland. Determine the height threshold range (a, b) based on the target area's design height. Have the drone platform record the height threshold range (a, b). If there are multiple newly added farmlands, determine the height threshold for each piece of land. Calculate the area of ​​each piece of newly added farmland based on the point cloud data within the height threshold range.

[0038] Step 3: Select the point cloud data whose height z value is within the height threshold range (a, b) and define it as the newly added farmland point cloud data.

[0039] Step 4: Extract the coordinate point (x, y) values ​​based on the newly added cultivated land point cloud data, calculate the concave hull based on the rolling circle algorithm, generate the newly added cultivated land polygon and obtain the boundary points (X, Y) of the newly added cultivated land point cloud data.

[0040] The specific operations for calculating the concave hull based on the rolling algorithm are as follows:

[0041] 1) Initialize an empty concave hull and a marker array to keep track of which points have been added to the hull.

[0042] 2) Determine the rolling ball radius R. The rolling ball radius R has a significant impact on the algorithm's performance and output. The size of radius R needs to be determined based on the point cloud data point density, the size of the point cloud dataset, and the application requirements. If the point cloud data points are densely distributed, appropriately increasing radius R may help to include more points in the same concave hull and avoid missing some points in the concave hull. Conversely, if the points are sparsely distributed, reducing radius R may be more appropriate to avoid including unrelated points in the same concave hull.

[0043] 3) Find a point with the smallest y value as the initial point A. If the y values ​​are the same, take the point with the largest x value as the initial point A.

[0044] 4) Starting from point A, first find a point B whose distance to A is less than 2R, so that point A and point B fall on the circle with a diameter of 2R at the same time, the distance from point A and point B to the center of the circle is equal to R, and there is no third point with a distance from the center of the circle equal to R. At this time, a circle with a radius of R is stuck on the chord AB. The chord AB is the first boundary line, and point B is a boundary point, which is included in the concave hull point array.

[0045] 5) Repeat step 4), starting at point B, to determine boundary point C and add it to the concave hull point array. Repeat the ball rolling process in step 5 until no new boundary points can be added. This usually means that all points are contained in the concave hull or a predetermined number of iterations or accuracy requirements have been met.

[0046] 6) Generate one or more polygons based on the concave point array, whose vertices are composed of the concave points found by the rolling ball method, and whose sides are composed of the chords. The range is the newly added cultivated land area during the stage construction.

[0047] In the above steps, when the data points of the point cloud data are unevenly distributed, a mechanism for dynamically adjusting the rolling ball radius is introduced. Initially, the radius is set as small as possible to move close to the edge of the details. However, in relatively sparse locations, the radius of the rolling ball is continuously lengthened until the next reasonable boundary point is obtained. The radius is then returned to the original rolling ball size and continued to move forward.

[0048] Step 5: Calculate the newly added cultivated land area S based on the boundary points (X, Y) i Before construction begins, the newly added cultivated land area should be initialized to 0 hectares. The specific calculation method is as follows:

[0049] Based on the boundary point sequence (X1, Y1), (X2, Y2), ..., (X n ,Y n ), calculate the newly added cultivated land area S 耕地面积 , and record S 耕地面积 For S i , S 耕地面积 The calculation formula is as follows:

[0050]

[0051] Step 6: After a period of land consolidation, obtain the target area point cloud data again and repeat steps 2-5 to calculate the newly added cultivated land area S i+1 Calculate the newly added area A during a period of land consolidation i , A i =S i+1 -S i , A i B within the construction plan time period i Compare and check whether it meets the construction plan objectives. If it does not meet the construction plan, that is, A i <B i , the UAV platform controls the UAV to issue a warning.

[0052] When A i ≥B i When the acceptance is passed.

[0053] Repeat the above steps until the land reclamation construction is completed.

[0054] The embodiments described above are merely descriptions of preferred implementations of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should fall within the scope of protection determined by the claims of the present invention.

Claims

1. A method for investigating newly added cultivated land after land consolidation based on 3D laser scanning, characterized in that: The following steps are involved: Step 1: Obtain point cloud data of the target area; Step 2: Determine the design height and height threshold range (a, b) of the newly added cultivated land; Step 3: Select point cloud data within the height threshold range, that is, add farmland point cloud data; Step 4: Extract the coordinate point (x, y) values ​​based on the newly added cultivated land point cloud data, calculate the concave hull based on the rolling circle algorithm, generate the newly added cultivated land polygon and obtain the boundary points (X, Y) of the newly added cultivated land point cloud data; Step 5: Calculate the newly added cultivated land area S based on the boundary points (X, Y) i .

2. The method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning according to claim 1, characterized in that: It also includes step 6: After a period of land consolidation, obtain the target area point cloud data again and repeat steps 2-5 to calculate the newly added cultivated land area S i+1 Calculate the newly added area A during a period of land consolidation i , A i =S i+1 -S i , A i B within the construction plan time period i Compare and check whether it meets the construction plan objectives. If it does not meet the construction plan, a warning will be issued.

3. The method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning according to claim 1, characterized in that: When there are multiple newly added cultivated lands, the height threshold of each newly added cultivated land is determined, and the area of ​​each newly added cultivated land is calculated based on the point cloud data within the height threshold of each newly added cultivated land.

4. The method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning according to claim 1, characterized in that: A UAV equipped with a 3D laser scanner is used to obtain point cloud data of the target area.

5. The method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning according to claim 4, characterized in that: The 3D laser scanner obtains the point cloud dataset P = {p1, p2, p3...} of the target area, imports it into the UAV platform, performs data preprocessing, extracts the coordinate information (x, y, z) of the point cloud data, and selects the point cloud data with a height z value within the height threshold range (a, b) and defines it as the newly added farmland point cloud data.

6. The method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning according to claim 1, characterized in that: In step 4, the specific operations for calculating the concave hull based on the rolling algorithm are as follows: 1) Initialize an empty concave hull and a marker array for tracking the point cloud data added to the concave hull; 2) Determine the rolling ball radius R; 3) Find a point with the smallest y value as the initial point A; 4) Starting from point A, first find a point B whose distance to A is less than 2R, so that point A and point B both fall on the circle with a diameter of 2R, the distance from point A and point B to the center of the circle is equal to R, and there is no third point with a distance equal to R to the center of the circle. At this point, a circle with a radius of R is stuck on the chord AB. The chord AB is the first boundary line, and point B is a boundary point and is included in the concave hull point array; 5) Repeat step 4), starting from point B, determine boundary point C, and add boundary point C to the concave hull point array; repeat the ball rolling process in step 5 until no new boundary points can be added; 6) Generate one or more polygons based on the concave point array.

7. The method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning according to claim 6, characterized in that: When the y values ​​are the same, the point with the largest x value is taken as the initial point A.

8. The method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning according to claim 6, characterized in that: When the data points of the point cloud data are unevenly distributed, a mechanism for dynamically adjusting the rolling ball radius is introduced. Initially, the radius is set as small as possible to move close to the edge of the details. However, in sparse locations, the radius of the rolling ball is continuously lengthened until the next reasonable boundary point is obtained. The ball is then returned to its original size and continues to move forward.

9. The method for investigating newly added cultivated land after land consolidation based on three-dimensional laser scanning according to claim 1, characterized in that: Based on the boundary point sequence (X1, Y1), (X2, Y2), ..., (X n ,Y n ), calculate the newly added cultivated land area S 耕地面积 , and record S 耕地面积 For S i , S 耕地面积 The calculation formula is as follows:

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