Photographic zoning method and device for unmanned aerial vehicle photogrammetry of highways

Abstract

The invention relates to the technical field of highway design and construction, and discloses a photography partitioning method and device for unmanned aerial vehicle photogrammetry of highways. The highway mileage points closest to the maximum and minimum local elevations of the highway center line are used as route partitioning points according to troughs and peaks, and then the partitioning is continued according to whether the straight-line distances from each highway mileage point to the adjacent route partitioning point exceed a threshold value. The partitioning is then continued according to whether the elevation change values ​​of two adjacent route partitioning points exceed the relative altitude of the unmanned aerial vehicle. Finally, the partitioning is performed according to whether the distance between two adjacent route partitioning points exceeds the maximum range of the unmanned aerial vehicle. The invention realizes accurate planning of unmanned aerial vehicle routes taking DEM into consideration, reduces data redundancy, reduces the workload of image stitching and aerial triangulation solution, improves the stitching speed and operation efficiency of on-site unmanned aerial vehicle images, and meets the on-site operation efficiency and emergency needs of project flight.

Description

Technical Field

[0001] The present invention relates to the technical field of highway design and construction, and in particular to a method and device for photographic zoning of unmanned aerial vehicle (UAV) photogrammetry of highways. Background Art

[0002] As my country increases its investment and construction in new infrastructure, it has promoted the rapid development of my country's expressways. In particular, in order to boost economic development in mountainous areas, new routes have been continuously planned in mountainous areas in recent years, making expressway survey and design more complex and demanding, requiring more accurate survey results. The rapidly developing UAV remote sensing technology in recent years has significant advantages such as "precise and accurate, flexible and maneuverable, high safety, fast and efficient, and low operating costs". It can obtain high-precision image maps and digital ground models, bringing new breakthroughs to the methods and efficiency of expressway survey, design and construction.

[0003] Photographic zoning is a key factor in drone photogrammetry, especially for strip highways. Reliable and optimized photographic zoning is the key to obtaining high-precision image maps and digital ground models. At present, drone photography zoning is mostly done manually based on experience and on online maps such as Google Maps, based on reference height difference restrictions. For long-distance strip highways, the elevation fluctuations are relatively large and the roads are many bends. The manual division of photography areas is affected by subjectivity, resulting in unreasonable division of drone photography areas, affecting the accuracy of highway strip image maps and digital ground models, making it difficult to give full play to and promote the advantages of drone photogrammetry in highway surveys, design and construction. Photographic zoning is achieved by dividing drone route zoning points on the highway. The area between two adjacent drone route zoning points constitutes a photographic zone.

[0004] The prior art discloses a method for planning a route in a strip area of ​​a UAV, including the following steps: S1: obtaining the range of the strip area; S2: calculating the route spacing according to preset conditions, and generating waypoints according to the route spacing, wherein the preset conditions include the lateral overlap rate, the ground resolution, and the sensor parameters; the route spacing is the distance between two adjacent routes; S3: generating a target route in the strip area according to the waypoints, wherein the target route consists of at least one route. The target route segmentation of the patent is performed by calculating the total range of the target route, and obtaining the total flight time according to the preset speed; the target route segmentation is performed according to the sortie conditions, and the target route is segmented into multiple routes or multiple routes according to the region, so that the routes and ranges of all sorties match the target routes and ranges, and the routes corresponding to each sortie after segmentation are output; the sortie conditions include the endurance time and maximum range of the UAV. That is, this patent determines the division points of the drone route based on the total range of the route, the drone's endurance and maximum range. The total range of the route is obtained by the length of the highway on the map and referring to the height difference limit, and the division is evenly divided. However, most highway projects are located in mountainous areas, which not only have large height differences, long and irregular routes, but also large on-site disturbances. Therefore, the above method will lead to unreasonable division of the drone photography area, affect the measurement accuracy, and easily cause data redundancy, image stitching and aerial triangulation difficulties. Summary of the invention

[0005] The purpose of the present invention is to provide a method and device for photographic zoning of unmanned aerial vehicle photogrammetry for highways with high efficiency and better accuracy.

[0006] In order to achieve the above object, the present invention provides a method for photogrammetry of highways by using unmanned aerial vehicle (UAV) photogrammetry, comprising the following steps:

[0007] S1. Obtain the coordinates of the mileage points of the expressway to be measured and the DEM data along the expressway;

[0008] S2, generating the center line of the expressway according to the coordinates of the highway mileage points;

[0009] S3, with the center line of the expressway as the center, offset a certain distance to both sides of the center line of the expressway to form a strip area, forming a buffer zone, which serves as the aerial photography measurement range of the expressway by drone;

[0010] S4. Calculate the maximum and minimum local elevations of the highway centerline based on the troughs and peaks of the highway area, and use the highway mileage points closest to the maximum and minimum local elevations of the highway centerline as the drone route partition points;

[0011] S5. Calculate the straight-line distance from each highway mileage point between two adjacent drone route partition points to the two drone route partition points. If the straight-line distance from a highway mileage point to a drone route partition point exceeds a threshold, use the highway mileage point as a new drone route partition point until the straight-line distance from each highway mileage point to its adjacent drone route partition point is less than the threshold.

[0012] S6, obtaining the elevation value of each highway mileage point;

[0013] S7, calculating the relative altitude of the UAV;

[0014] S8, calculating the elevation change value of two adjacent UAV route partition points. If the elevation change value of two adjacent UAV route partition points is greater than the relative altitude of the UAV, the highway mileage point between the two UAV route partition points is used as a new UAV route partition point until the elevation change values ​​of all two adjacent UAV route partition points are less than the relative altitude of the UAV.

[0015] S9. Calculate the distance between two adjacent UAV route partition points to obtain the maximum range of the UAV. If the distance between two adjacent UAV route partition points is greater than the maximum range of the UAV, the highway mileage point between the two adjacent UAV route partition points is used as a new UAV route partition point until the distance between all two adjacent UAV route partition points is less than the maximum range of the UAV.

[0016] As a preferred solution, in step S1, the global STRM elevation data is downloaded, the coordinates of the highway mileage points of the highway to be measured are obtained, and the elevation sections along the highway are clipped to obtain the DEM data along the highway.

[0017] As a preferred solution, in step S2, the coordinates of the highway mileage points are converted into a point file, and the pointtoline command is used in arcmap to generate a centerline file of the highway.

[0018] As a preferred solution, in step S4, the peak command in the matlab program is used to find the trough and peak of the area where the expressway is located.

[0019] As a preferred solution, in step S5, the threshold is 300m.

[0020] As a preferred solution, in step S6, the center line of the expressway is overlaid with the DEM data to extract the elevation value of each highway mileage point.

[0021] As a preferred solution, in step S7, the relative altitude of the drone image is determined based on the ground resolution and camera parameters.

[0022] As a preferred solution, in step S8, the elevation change value of two adjacent drone route partition points must be less than 1 / 6 of the drone's relative altitude.

[0023] As a preferred solution, in step S9, the distance between two adjacent drone route partition points must be less than 1 / 5 of the maximum range of the drone.

[0024] The present invention also provides a photography zoning device for unmanned aerial vehicle photogrammetry of highways, comprising:

[0025] The design information collection module is used to collect the design information of the expressway to be measured, including the coordinates of the mileage points of the expressway to be measured and the DEM data along the expressway;

[0026] A centerline generation module is used to generate the centerline of the highway according to the coordinates of the highway mileage points;

[0027] The buffer zone analysis module is used to form a strip-shaped area with the center line of the highway as the center and offset a certain distance to both sides of the center line of the highway to form a buffer zone as the aerial photography measurement range of the highway by drone;

[0028] The curve trough and crest analysis module is used to calculate the maximum and minimum local elevations of the highway centerline according to the troughs and crests of the highway area, and use the highway mileage points closest to the maximum and minimum local elevations of the highway centerline as the drone route partition points;

[0029] The curve curvature analysis module is used to calculate the straight-line distance from each highway mileage point between two adjacent drone route partition points to the two drone route partition points. If the straight-line distance from a highway mileage point to a drone route partition point exceeds a threshold, the highway mileage point is used as a new drone route partition point until the straight-line distance from each highway mileage point to its adjacent drone route partition point is less than the threshold.

[0030] The elevation value extraction module is used to obtain the elevation value of each highway mileage point;

[0031] The altitude calculation module is used to calculate the relative altitude of the UAV;

[0032] The altitude auxiliary analysis module is used to calculate the elevation change value of two adjacent UAV route partition points. If the elevation change value of two adjacent UAV route partition points is greater than the relative altitude of the UAV, the highway mileage point between the two UAV route partition points will be used as the new UAV route partition point until the elevation change values ​​of all two adjacent UAV route partition points are less than the relative altitude of the UAV.

[0033] The range auxiliary analysis module is used to calculate the distance between two adjacent UAV route partition points and obtain the maximum range of the UAV. If the distance between two adjacent UAV route partition points is greater than the maximum range of the UAV, the highway mileage point between the two adjacent UAV route partition points will be used as the new UAV route partition point until the distance between all two adjacent UAV route partition points is less than the maximum range of the UAV.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The present invention uses the troughs and peaks of the area where the expressway is located, and uses the highway mileage points closest to the local maximum and minimum elevations of the center line of the expressway as drone route partition points. The partition is then continued based on whether the straight-line distances from each highway mileage point between two adjacent drone route partition points to the two drone route partition points exceed a threshold. The partition is then continued based on whether the elevation change value of the two adjacent drone route partition points exceeds the relative altitude of the drone. Finally, the partition is continued based on whether the distance between the two adjacent drone route partition points exceeds the maximum range of the drone. The present invention achieves accurate planning of drone routes that takes DEM into consideration, reduces data redundancy, reduces the workload of image stitching and aerial triangulation on the basis of ensuring effective heading and lateral overlap, improves the stitching speed and operating efficiency of on-site drone images, and meets the on-site operating efficiency and emergency needs of project flight operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a flow chart of a method for photographic zoning of unmanned aerial vehicle photogrammetry for highways according to an embodiment of the present invention.

[0037] Figure 2 It is the elevation distribution map along the Tianxi Expressway obtained in step S1 of the embodiment of the present invention.

[0038] Figure 3 It is a schematic diagram of Tianxi Expressway obtained after processing in step S2 of an embodiment of the present invention.

[0039] Figure 4 It is a schematic diagram of the Tianxi Expressway obtained after processing in step S3 of the embodiment of the present invention.

[0040] Figure 5 yes Figure 4 A partial enlarged view of .

[0041] Figure 6 It is a distribution map of the highway mileage points and drone route partition points of the Tianxi Expressway obtained after processing in step S4 of the embodiment of the present invention.

[0042] Figure 7It is a connection diagram of the drone route partition points after processing in step S4 of the embodiment of the present invention.

[0043] Figure 8 It is a distribution map of the highway mileage points and drone route partition points of the Tianxi Expressway during the processing of step S5 of an embodiment of the present invention.

[0044] Fig. 9 This is a distribution map of the highway mileage points and drone route partition points of the Tianxi Expressway after processing in step S8 of an embodiment of the present invention.

[0045] Fig.10 yes Fig. 9 Partial schematic diagram at point A in the middle.

[0046] Fig.11 This is a distribution map of the highway mileage points and drone route partition points of the Tianxi Expressway after processing in step S9 of an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0048] In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0049] Embodiment 1

[0050] like Figures 1 to 11 As shown, a photography zoning method for unmanned aerial vehicle photogrammetry of a highway in a preferred embodiment of the present invention comprises the following steps:

[0051] S1. Obtain the coordinates of the mileage points of the expressway to be measured and the DEM data along the expressway;

[0052] S2, generating the center line of the expressway according to the coordinates of the highway mileage points;

[0053] S3, with the center line of the expressway as the center, offset a certain distance to both sides of the center line of the expressway to form a strip area, forming a buffer zone, which serves as the aerial photography measurement range of the expressway by drone;

[0054] S4. Calculate the maximum and minimum local elevations of the highway centerline based on the troughs and peaks of the highway area, and use the highway mileage points closest to the maximum and minimum local elevations of the highway centerline as the drone route partition points;

[0055] S5. Calculate the straight-line distance from each highway mileage point between two adjacent drone route partition points to the two drone route partition points. If the straight-line distance from a highway mileage point to a drone route partition point exceeds a threshold, use the highway mileage point as a new drone route partition point until the straight-line distance from each highway mileage point to its adjacent drone route partition point is less than the threshold.

[0056] S6, obtaining the elevation value of each highway mileage point;

[0057] S7, calculating the relative altitude of the UAV;

[0058] S8, calculating the elevation change value of two adjacent UAV route partition points. If the elevation change value of two adjacent UAV route partition points is greater than the relative altitude of the UAV, the highway mileage point between the two UAV route partition points is used as a new UAV route partition point until the elevation change values ​​of all two adjacent UAV route partition points are less than the relative altitude of the UAV.

[0059] S9. Calculate the distance between two adjacent UAV route partition points to obtain the maximum range of the UAV. If the distance between two adjacent UAV route partition points is greater than the maximum range of the UAV, the highway mileage point between the two adjacent UAV route partition points is used as a new UAV route partition point until the distance between all two adjacent UAV route partition points is less than the maximum range of the UAV.

[0060] Specifically, in step S1, this embodiment downloads global STRM elevation data, obtains the coordinates of the highway mileage points of the highway to be measured, and cuts out the elevation section along the highway to obtain the DEM data along the highway.

[0061] Furthermore, in step S2, the coordinates of the highway mileage points are converted into a point file, and the pointtoline command is used in arcmap to generate a centerline file of the highway.

[0062] In step S4, the peak command in the Matlab program is used to find the trough and peak of the area where the expressway is located.

[0063] In step S5, the threshold is 300m. That is, if the straight-line distance from a highway mileage point to a drone route partition point exceeds 300m, the highway mileage point will be used as a new drone route partition point until the straight-line distance from each highway mileage point to its adjacent drone route partition point is less than 300m.

[0064] In step S6, the center line of the expressway is overlaid with the DEM data to extract the elevation value of each mileage point on the expressway.

[0065] In step S7, the relative altitude of the drone image is calculated based on the ground resolution of the drone image and the camera parameters.

[0066] In step S8, the elevation change value of two adjacent UAV route partition points must be less than 1 / 6 of the relative altitude of the UAV.

[0067] In step S9, the distance between two adjacent drone route partition points must be less than 1 / 5 of the drone's maximum range.

[0068] Embodiment 2

[0069] The difference between this embodiment and the first embodiment is that, based on the first embodiment, this embodiment further illustrates the specific application of the method in the Tianxi Expressway.

[0070] The photographic zoning method for unmanned aerial vehicle photogrammetry of highways in this embodiment includes the following steps:

[0071] S1. Obtain the coordinates of the highway mileage points and DEM data along the highway to be measured; in this embodiment, obtain relevant information of the Tianxi Expressway, including basic information, road mileage points, elevations along the way, land cover conditions and other information. The starting point of the Tianxi Expressway is located in Lucheng Township, Tianlin County. It is connected to the G78 Baise to Longlin Expressway by setting up the Yingpan Hub Interchange, and ends near Bengguan, Mapeng Town (Badahe), and connects to the Yunnan section of the Yunnan (Qujing) to Guangxi (Baise) Expressway, with a total length of 191.209 kilometers. Specifically, download the STRM global elevation data and cut out the elevation section along the Tianxi Expressway. The elevation of the highest point of the Tianxi Expressway is 1,244 meters, the elevation of the lowest point is 260 meters, and the average elevation is 690 meters. The elevation difference of the entire area is close to 1,000 meters, such as Figure 2 shown.

[0072] S2. Generate the center line of the expressway according to the coordinates of the highway mileage points. In this embodiment, the coordinates of the highway mileage points of the Tianxi Expressway obtained in step S1 are converted into a point file, and the pointtoline command is used in arcmap to generate the center line file of the Tianxi Expressway, such as Figure 3 shown.

[0073] S3, with the center line of the expressway as the center, offset a certain distance to both sides of the center line of the expressway to form a strip area, forming a buffer zone, which serves as the aerial photography measurement range of the expressway. In this embodiment, the center line of Tianxi Expressway is taken as the center, and 400m is extended to both sides of the center line of Tianxi Expressway to generate a buffer zone. The edges of the buffer zone on both sides are lines parallel to the center line of Tianxi Expressway, such as Figure 4 and Figure 5 shown.

[0074] S4. Calculate the maximum and minimum local elevations of the center line of the highway based on the troughs and peaks of the area where the highway is located, and use the highway mileage points closest to the maximum and minimum local elevations of the center line of the highway as the partition points for the UAV route. In this embodiment, the file obtained in step S3 is input into the matlab program. Using the peak command in the matlab program, the troughs and peaks passed by the center line of the Tianxi Expressway are calculated to obtain the maximum and minimum local elevations of the center line of the Tianxi Expressway, that is, the local highest and lowest points of the center line of the Tianxi Expressway are obtained, and the highway mileage points closest to the local highest and lowest points are used as the partition points for the UAV route, such as Figure 6 and Figure 7 shown.

[0075] S5. Calculate the straight-line distance from each highway mileage point between two adjacent drone route partition points to the two drone route partition points. If the straight-line distance from a highway mileage point to a drone route partition point exceeds a threshold, use the highway mileage point as a new drone route partition point until the straight-line distance from each highway mileage point to its adjacent drone route partition point is less than the threshold. The distance between a highway mileage point and its adjacent drone route partition point is called curvature, and this step adopts a curve curvature analysis method. In the Tianxi Expressway, the threshold of curvature is set to 300 meters. If the curvature of a highway mileage point in the interval between two adjacent drone route partition points exceeds the threshold, use the highway mileage point as a new drone route partition point, and repeat the above actions until the curvature of all highway mileage points in the interval between two adjacent drone route partition points is less than the threshold. Figure 8 shown.

[0076] S6. Obtain the elevation value of each highway mileage point. Overlay and extract the highway mileage points of Tianxi Expressway with the STRM global elevation data to obtain the elevation value of each highway mileage point.

[0077] S7, calculate the relative altitude of the drone. The relative altitude of the drone is calculated based on the ground resolution of the drone image and the camera parameters. The Tianxi Expressway in this embodiment uses a CW007 fixed-wing drone equipped with a CA-103 aerial camera. The physical size of each pixel is about 3.756um, the focal length is 35mm, and the ground resolution of the image is required to be about 100mm. The relative altitude of the drone is 931 meters.

[0078] S8. Calculate the elevation change value of two adjacent UAV route partition points. If the elevation change value of two adjacent UAV route partition points is greater than the relative altitude of the UAV, the highway mileage point between the two UAV route partition points is used as a new UAV route partition point until the elevation change values ​​of all two adjacent UAV route partition points are less than the relative altitude of the UAV. In this embodiment, if the elevation change value of two adjacent UAV route partition points is greater than 1 / 6 of the relative altitude of the UAV, the highway mileage point between the two adjacent UAV route partition points is used as a new UAV route partition point, and the above actions are repeated until the elevation change values ​​of two adjacent UAV route partition points are less than 1 / 6 of the relative altitude of the UAV. Fig. 9 and Fig.10 In this embodiment, the elevation change value of two adjacent drone route partition points is less than 1 / 6 of the drone's relative altitude, which can increase the number of drone route partition points. At the same time, it can avoid high-load operation of the drone, leaving a margin to ensure stable flight of the drone and clear images taken.

[0079] S9. Calculate the distance between two adjacent UAV route partition points to obtain the maximum range of the UAV. If the distance between two adjacent UAV route partition points is greater than the maximum range of the UAV, the highway mileage point between the two adjacent UAV route partition points is used as the new UAV route partition point, until the distance between all two adjacent UAV route partition points is less than the maximum range of the UAV. This embodiment uses the Zongheng CW007 fixed-wing UAV. The Zongheng CW007 fixed-wing UAV has a flight time of 70-90 minutes and a cruising speed of 61 kilometers per hour. The maximum distance of a 70-minute flight is 71 kilometers. To ensure the normal operation of the UAV, therefore, if the distance between two adjacent UAV route partition points is greater than 1 / 5 of the maximum range of the UAV, that is, if the distance between two adjacent UAV route partition points is greater than 14 kilometers, the highway mileage point between the two adjacent UAV route partition points is used as the new UAV route partition point, and the above actions are repeated until the distance between two adjacent UAV route partition points is less than 14 kilometers. Fig.11 shown.

[0080] This embodiment uses three Zongheng CW007 fixed-wing drones to divide the 191-kilometer Tianlin to Xilin (Yunnan-Guangxi border) expressway into three work zones. The three drones fly the entire route in 1-2 days, and the drone images are stitched together in 3 to 4 days to generate a full-course work base map. The three drones fly along the center line of the expressway and the edges of both sides of the buffer zone, and then take photos at each drone route partition point.

[0081] Embodiment 3

[0082] This embodiment provides a photography zoning device for unmanned aerial vehicle photogrammetry of highways, comprising:

[0083] The design information collection module is used to collect the design information of the expressway to be measured, including the coordinates of the mileage points of the expressway to be measured and the DEM data along the expressway;

[0084] A centerline generation module is used to generate the centerline of the highway according to the coordinates of the highway mileage points;

[0085] The buffer zone analysis module is used to form a strip-shaped area with the center line of the highway as the center and offset a certain distance to both sides of the center line of the highway to form a buffer zone as the aerial photography measurement range of the highway by drone;

[0086] The curve trough and crest analysis module is used to calculate the maximum and minimum local elevations of the highway centerline according to the troughs and crests of the highway area, and use the highway mileage points closest to the maximum and minimum local elevations of the highway centerline as the drone route partition points;

[0087] The curve curvature analysis module is used to calculate the straight-line distance from each highway mileage point between two adjacent drone route partition points to the two drone route partition points. If the straight-line distance from a highway mileage point to a drone route partition point exceeds a threshold, the highway mileage point is used as a new drone route partition point until the straight-line distance from each highway mileage point to its adjacent drone route partition point is less than the threshold.

[0088] The elevation value extraction module is used to obtain the elevation value of each highway mileage point;

[0089] The altitude calculation module is used to calculate the relative altitude of the UAV;

[0090] The altitude auxiliary analysis module is used to calculate the elevation change value of two adjacent UAV route partition points. If the elevation change value of two adjacent UAV route partition points is greater than the relative altitude of the UAV, the highway mileage point between the two UAV route partition points will be used as the new UAV route partition point until the elevation change values ​​of all two adjacent UAV route partition points are less than the relative altitude of the UAV.

[0091] The range auxiliary analysis module is used to calculate the distance between two adjacent UAV route partition points and obtain the maximum range of the UAV. If the distance between two adjacent UAV route partition points is greater than the maximum range of the UAV, the highway mileage point between the two adjacent UAV route partition points will be used as the new UAV route partition point until the distance between all two adjacent UAV route partition points is less than the maximum range of the UAV.

[0092] The design information collection module, centerline generation module, buffer zone analysis module, curve trough and peak analysis module, curve curvature analysis module, altitude auxiliary analysis module, and range auxiliary analysis module are connected in sequence, and finally the distribution map of the drone route partition points and highway mileage points of the highway is output, such as Fig.11 The design information collection module is connected with the elevation value extraction module, and the elevation value extraction module and the flight height calculation module are connected with the flight height auxiliary analysis module.

[0093] In summary, the embodiment of the present invention provides a photographic zoning method for UAV photogrammetry of highways, which uses the troughs and peaks of the area where the highway is located to take the highway mileage points closest to the local maximum and minimum elevations of the center line of the highway as UAV route zoning points, and then continues to divide according to whether the straight-line distances from each highway mileage point between two adjacent UAV route zoning points to the two UAV route zoning points exceed the threshold, and then continues to divide according to whether the elevation change value of the two adjacent UAV route zoning points exceeds the relative altitude of the UAV, and finally divides according to whether the distance between the two adjacent UAV route zoning points exceeds the maximum range of the UAV. The present invention realizes the accurate planning of UAV routes taking into account DEM, and on the basis of ensuring effective heading and lateral overlap, reduces data redundancy, reduces the workload of image stitching and aerial triangulation, improves the stitching speed and operation efficiency of on-site UAV images, and meets the project flight site operation efficiency and emergency needs. The embodiment of the present invention also provides a photographic zoning device for UAV photogrammetry of highways that implements the above method.

[0094] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention. These improvements and substitutions should also be regarded as the scope of protection of the present invention.

Claims

1. A photozoning method for UAV photogrammetry of highways, characterized by: The steps include: S1. Obtain the coordinates of the mileage points of the expressway to be measured and the DEM data along the expressway; S2, generating the center line of the expressway according to the coordinates of the highway mileage points; S3, with the center line of the expressway as the center, offset a certain distance to both sides of the center line of the expressway to form a strip area, forming a buffer zone, which serves as the aerial photography measurement range of the expressway by drone; S4. Calculate the maximum and minimum local elevations of the highway centerline based on the troughs and peaks of the highway area, and use the highway mileage points closest to the maximum and minimum local elevations of the highway centerline as the drone route partition points; S5. Calculate the straight-line distance from each highway mileage point between two adjacent drone route partition points to the two drone route partition points. If the straight-line distance from a highway mileage point to a drone route partition point exceeds a threshold, use the highway mileage point as a new drone route partition point until the straight-line distance from each highway mileage point to its adjacent drone route partition point is less than the threshold. S6, obtaining the elevation value of each highway mileage point; S7, calculating the relative altitude of the UAV; S8, calculating the elevation change value of two adjacent UAV route partition points. If the elevation change value of two adjacent UAV route partition points is greater than the relative altitude of the UAV, the highway mileage point between the two UAV route partition points is used as a new UAV route partition point until the elevation change values ​​of all two adjacent UAV route partition points are less than the relative altitude of the UAV. S9. Calculate the distance between two adjacent UAV route partition points to obtain the maximum range of the UAV. If the distance between two adjacent UAV route partition points is greater than the maximum range of the UAV, the highway mileage point between the two adjacent UAV route partition points is used as a new UAV route partition point until the distance between all two adjacent UAV route partition points is less than the maximum range of the UAV.

2. The method for photogrammetry of highways by drone photogrammetry according to claim 1 is characterized in that: In step S1, the global STRM elevation data is downloaded, the coordinates of the highway mileage points of the highway to be measured are obtained, and the elevation sections along the highway are clipped to obtain the DEM data along the highway.

3. The method for photogrammetry of highways by drone photogrammetry according to claim 2, characterized in that: In step S2, the coordinates of the highway mileage points are converted into point files, and the pointtoline command is used in arcmap to generate the centerline file of the highway.

4. The method for photozoning by drone photogrammetry for highways according to claim 2 is characterized in that: In step S4, the peak command in the Matlab program is used to find the trough and peak of the area where the expressway is located.

5. The method for photozoning by drone photogrammetry for highways according to claim 1, characterized in that: In step S5, the threshold is 300m.

6. The method for photozoning by drone photogrammetry for highways according to claim 1, characterized in that: In step S6, the center line of the expressway is overlaid with the DEM data to extract the elevation value of each mileage point on the expressway.

7. The method for photozoning by drone photogrammetry for highways according to claim 1, characterized in that: In step S7, the relative altitude of the drone image is calculated based on the ground resolution of the drone image and the camera parameters.

8. The method for photozoning by drone photogrammetry for highways according to claim 1, characterized in that: In step S8, the elevation change value of two adjacent UAV route partition points must be less than 1 / 6 of the relative altitude of the UAV.

9. The method for photozoning by drone photogrammetry for highways according to claim 1, characterized in that: In step S9, the distance between two adjacent drone route partition points must be less than 1 / 5 of the drone's maximum range.

10. A photo zoning device for drone photogrammetry of highways, characterized in that: include: The design information collection module is used to collect the design information of the expressway to be measured, including the coordinates of the mileage points of the expressway to be measured and the DEM data along the expressway; A centerline generation module is used to generate the centerline of the highway according to the coordinates of the highway mileage points; The buffer zone analysis module is used to form a strip-shaped area with the center line of the highway as the center and offset a certain distance to both sides of the center line of the highway to form a buffer zone, which serves as the aerial photography measurement range of the highway by drone. The curve trough and crest analysis module is used to calculate the maximum and minimum local elevations of the highway centerline according to the troughs and crests of the highway area, and use the highway mileage points closest to the maximum and minimum local elevations of the highway centerline as the drone route partition points; The curve curvature analysis module is used to calculate the straight-line distance from each highway mileage point between two adjacent drone route partition points to the two drone route partition points. If the straight-line distance from a highway mileage point to a drone route partition point exceeds a threshold, the highway mileage point is used as a new drone route partition point until the straight-line distance from each highway mileage point to its adjacent drone route partition point is less than the threshold. The elevation value extraction module is used to obtain the elevation value of each highway mileage point; The altitude calculation module is used to calculate the relative altitude of the UAV; The altitude auxiliary analysis module is used to calculate the elevation change value of two adjacent UAV route partition points. If the elevation change value of two adjacent UAV route partition points is greater than the relative altitude of the UAV, the highway mileage point between the two UAV route partition points will be used as the new UAV route partition point until the elevation change values ​​of all two adjacent UAV route partition points are less than the relative altitude of the UAV. The range auxiliary analysis module is used to calculate the distance between two adjacent UAV route partition points and obtain the maximum range of the UAV. If the distance between two adjacent UAV route partition points is greater than the maximum range of the UAV, the highway mileage point between the two adjacent UAV route partition points will be used as the new UAV route partition point until the distance between all two adjacent UAV route partition points is less than the maximum range of the UAV.

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