CN117192075A - Water and soil conservation monitoring method and system of unmanned aerial vehicle in highway construction scene - Google Patents
Water and soil conservation monitoring method and system of unmanned aerial vehicle in highway construction scene Download PDFInfo
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Abstract
The application discloses a water and soil conservation monitoring method and a system of an unmanned aerial vehicle in a highway construction scene, wherein the method comprises the following steps: selecting a target area comprising an area to be monitored for water and soil conservation monitoring in a highway construction scene, wherein at least one image control point is distributed in the area to be monitored; acquiring aerial images acquired by the unmanned aerial vehicle in the target area, wherein the aerial images comprise orthographic aerial images and/or oblique aerial images; constructing a target three-dimensional model based on the aerial photography image, wherein the target three-dimensional model is a model for performing measurement accuracy analysis on candidate three-dimensional models, and the obtained error reaches target accuracy; and based on the target three-dimensional model, monitoring and analyzing the water and soil conservation condition of the region to be monitored in the road construction scene, and utilizing the target three-dimensional model subjected to measurement accuracy analysis to monitor and analyze the water and soil conservation, thereby improving the accuracy of water and soil conservation monitoring.
Description
Technical Field
The disclosure relates generally to the technical field of data monitoring, and in particular relates to a water and soil conservation monitoring method and system of an unmanned aerial vehicle in a highway construction scene.
Background
Unmanned aerial vehicle monitoring is becoming widely used as one of the main monitoring technologies of water and soil conservation monitoring service units.
At present, unmanned aerial vehicles are mainly used for shooting pictures and recording videos in water and soil conservation technical service units, and are insufficient in quantitative application aspects such as data acquisition and the like. Based on the above, how to provide reliable technical support for water and soil conservation monitoring in a highway construction scene of an unmanned aerial vehicle becomes a problem to be solved.
Disclosure of Invention
In view of the above-mentioned drawbacks or shortcomings in the prior art, it is desirable to provide a method and a system for monitoring water and soil conservation in a highway construction scene by using a target three-dimensional model analyzed by measurement accuracy to perform water and soil conservation monitoring analysis, so as to improve accuracy of water and soil conservation monitoring.
In a first aspect, an embodiment of the present application provides a method for monitoring water and soil conservation of an unmanned aerial vehicle in a highway construction scene, including:
selecting a target area comprising an area to be monitored for water and soil conservation monitoring in a highway construction scene, wherein at least one image control point is distributed in the area to be monitored;
acquiring aerial images acquired by the unmanned aerial vehicle in the target area, wherein the aerial images comprise orthographic aerial images and/or oblique aerial images;
Constructing a target three-dimensional model based on the aerial photography image, wherein the target three-dimensional model is a model for performing measurement accuracy analysis on candidate three-dimensional models, and the obtained error reaches target accuracy;
and monitoring and analyzing the water and soil conservation condition of the area to be monitored in the road construction scene based on the target three-dimensional model.
In some embodiments, the performing measurement accuracy analysis on the candidate three-dimensional model includes:
constructing the candidate three-dimensional model based on the aerial image and a construction condition of the candidate three-dimensional model, wherein the construction condition comprises utilizing a control point in the image control point;
selecting at least one check point from a plurality of image control points corresponding to the candidate three-dimensional model, and acquiring a target three-dimensional coordinate corresponding to the check point, wherein the check point and the control point are different image control points;
acquiring true value three-dimensional coordinates corresponding to check points measured based on an RTK measurement system;
and analyzing the error between the target three-dimensional coordinate and the true three-dimensional coordinate, and determining the candidate three-dimensional model as the target three-dimensional model when the error reaches the target precision.
In some embodiments, the errors include a planar error and an elevation error, and when the error reaches the target accuracy, determining the candidate three-dimensional model as the target three-dimensional model includes:
And when the plane error is smaller than 0.3m and the elevation error is smaller than 0.5m, determining the candidate three-dimensional model as the target three-dimensional model.
In some embodiments, the candidate three-dimensional model comprises an orthographic control point encryption model, the constructing the candidate three-dimensional model based on the aerial image and the construction conditions of the candidate three-dimensional model comprising:
acquiring each image control point in the region to be monitored based on the orthographic aerial photography image;
selecting an optimal image control point from the image control points, wherein the optimal image control point comprises a tetrad point group and an encryption point in the middle of the area to be monitored;
and carrying out air triangular calculation based on the optimal image control point to generate the orthographic aerial photography control point encryption model.
In some embodiments, the candidate three-dimensional model includes a tilted aerial non-control point model, the constructing the candidate three-dimensional model based on the aerial image and a construction condition of the candidate three-dimensional model includes:
and performing air triangular calculation based on the inclined aerial image to generate the inclined aerial non-control point model.
In some embodiments, the candidate three-dimensional model comprises a tilted aerial control point encryption model, the constructing the candidate three-dimensional model based on the aerial image and a construction condition of the candidate three-dimensional model comprising:
Acquiring each image control point in the region to be monitored based on the inclined aerial image;
selecting a plurality of encryption control points from the image control points;
and performing air triangular calculation based on the encryption control points to generate the encryption model of the inclined aerial photography control points.
In a second aspect, an embodiment of the present application provides a system for monitoring water and soil conservation of an unmanned aerial vehicle in a highway construction scene, including:
the system comprises a selection module, a control module and a display module, wherein the selection module is used for selecting a target area comprising an area to be monitored for water and soil conservation monitoring in a highway construction scene, and at least one image control point is distributed in the area to be monitored;
the acquisition module is used for acquiring aerial images acquired by the unmanned aerial vehicle in the target area, wherein the aerial images comprise orthographic aerial images and/or oblique aerial images;
the construction module is used for constructing a target three-dimensional model based on the aerial image, wherein the target three-dimensional model is a model for carrying out measurement precision analysis on candidate three-dimensional models, and the obtained error reaches the target precision;
and the analysis module is used for monitoring and analyzing the water and soil conservation condition of the area to be monitored in the highway construction scene based on the target three-dimensional model.
In a third aspect, an embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing a method as described in the embodiment of the present application when the program is executed by the processor.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method as described in embodiments of the present application.
The application has the beneficial effects that:
1. according to the water and soil conservation monitoring method of the unmanned aerial vehicle in the highway construction scene, the target area comprising the area to be monitored for water and soil conservation monitoring in the highway construction scene is selected, the aerial image acquired by the unmanned aerial vehicle in the target area is acquired, and the target three-dimensional model which is subjected to measurement precision analysis and has the error reaching the target precision is constructed based on the aerial image, so that the constructed target three-dimensional model is closer to the actual state of the area to be monitored, the error between the constructed target three-dimensional model and the actual disturbance change is lower, the disturbance situation can be better reflected, and the result of monitoring analysis on the water and soil conservation situation of the area to be monitored in the highway construction scene based on the target three-dimensional model is more accurate finally, and the method has better guidance on actual highway construction. Meanwhile, the method utilizes the RTK measuring system with high-precision centimeter-level positioning to carry out measurement precision analysis on the candidate three-dimensional model, ensures the reliability of the precision of the target three-dimensional model obtained through measurement precision analysis, and provides precision support for water and soil conservation monitoring by utilizing the target three-dimensional model.
2. Through a great deal of practical analysis of the applicant, the accuracy of the orthographic aerial photography control point encryption model and the accuracy of the 20-60-DEG inclined aerial photography control point encryption model are stable aiming at the water and soil conservation monitoring scene in the highway construction scene, and the method can be directly applied to the three-dimensional modeling process of water and soil conservation monitoring in the highway construction scene. That is, when water and soil conservation is monitored in a highway construction scene, the orthographic aerial photography image can be directly used for constructing an orthographic aerial photography control point encryption model to monitor and analyze water and soil staff conditions, or the oblique aerial photography image can be directly used for constructing an oblique aerial photography control point encryption model to monitor and analyze water and soil staff conditions.
3. The applicant provides a technical scheme with optimal synergistic effect of 45-degree inclination, a control point encryption model and multi-check point mutually combined shooting for the first time, solves the technical problem of low measurement precision of the unmanned aerial vehicle in the field of water and soil conservation monitoring in highway construction scenes, and meanwhile, compared with the traditional 90-degree shooting precision, which is generally accepted by technicians in the field, the application is obtained through a great amount of experimental researches, the 45-degree inclination, the control point encryption model and the multi-check point mutually combined shooting precision is superior to the traditional 90-degree shooting, and the traditional shooting mode and data processing thinking are broken. Therefore, the water and soil conservation monitoring analysis is carried out by using the target three-dimensional model subjected to the measurement accuracy analysis, and the accuracy of the water and soil conservation monitoring is improved.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the accompanying drawings in which:
fig. 1 shows an implementation environment architecture diagram of a water and soil conservation monitoring method of an unmanned aerial vehicle in a highway construction scene according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a water and soil conservation monitoring method of an unmanned aerial vehicle in a highway construction scene according to an embodiment of the present application;
FIG. 3 is a schematic diagram showing a relationship between a target area and an area to be monitored according to an embodiment of the present application;
FIG. 4 is a schematic diagram of an exemplary route configuration of an orthographic aerial camera according to an embodiment of the present application;
FIG. 5 illustrates a schematic diagram of an airline configuration for a tilt aerial camera provided by an embodiment of the present application;
FIG. 6 is a schematic diagram of a configuration of aerial fly height provided by an embodiment of the present application;
fig. 7 is a schematic flow chart of a water and soil conservation monitoring method of an unmanned aerial vehicle in a highway construction scene according to another embodiment of the present application;
FIG. 8 is a schematic diagram showing the accuracy of a three-dimensional model of a target according to an embodiment of the present application;
FIG. 9 is a schematic flow chart of constructing a candidate three-dimensional model according to an embodiment of the present application;
FIG. 10 is a schematic diagram showing error conditions of an orthographic control point encryption model according to an embodiment of the present application;
FIG. 11 is a schematic diagram showing an error condition of a tilt-aerial non-control-point model according to an embodiment of the present application;
FIG. 12 is a schematic diagram showing error conditions of an encryption model of a tilt navigation control point according to an embodiment of the present application;
fig. 13 is a schematic structural diagram of a water and soil conservation monitoring system of an unmanned aerial vehicle in a highway construction scene according to an embodiment of the present application;
fig. 14 shows a schematic diagram of a computer system suitable for use in implementing an embodiment of the application.
Detailed Description
The application is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be noted that, for convenience of description, only the portions related to the application are shown in the drawings.
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
The water and soil conservation monitoring working method mainly comprises manual field investigation and construction material analysis, but the manual field investigation is time-consuming and labor-consuming to acquire monitoring data, and the error of data acquisition is large due to improper operation of an instrument, limitation of topography and topography conditions and subjectivity of manual measurement and calculation. When the water and soil conservation monitoring personnel analyzes the related data, the used construction data is mainly provided by construction units, the water and soil conservation monitoring personnel cannot ensure that the data are objective, relatively accurate and timely, and the monitoring data obtained by too relying on the data analysis have great problems and cannot meet the objective and active working requirements of water and soil conservation monitoring. In conclusion, the water and soil conservation monitoring method has the problems of time consumption, labor consumption, larger limitation by the topography and topography conditions, poorer objectivity of data acquisition, lager time for data acquisition of analysis data and the like, and cannot meet the requirements of the water and soil conservation monitoring work at the present stage.
The unmanned aerial vehicle remote sensing technology utilizes an unmanned flight control platform which is mature, combines with a low-altitude remote sensing technology, and completes acquisition, screening, processing, analysis, comparison and application of remote sensing information such as landforms, space environments, ground structures and the like by means of a computer. And the automatic degree, the monitoring efficiency and the monitoring precision of the water and soil conservation monitoring work can be effectively improved by combining with the existing water and soil conservation monitoring technical means.
Based on the method, the application provides a water and soil conservation monitoring method and a system of the unmanned aerial vehicle in a highway construction scene.
The specific implementation environment of the water and soil conservation monitoring method of the unmanned aerial vehicle in the road construction scene is shown in fig. 1. Fig. 1 shows an implementation environment architecture diagram of a water and soil conservation monitoring method of an unmanned aerial vehicle in a highway construction scene.
As shown in fig. 1, the implementation environment architecture includes: the unmanned aerial vehicle device 100, the image acquisition system 200 and the server 300.
The unmanned aerial vehicle device 100 includes an unmanned aerial vehicle flight system 101, a flight monitoring system 102, a ground remote control system 103, a data transmission system 104, and the like.
The unmanned aerial vehicle flight system 101 is usually an unmanned aerial vehicle body and a power system thereof, and comprises an unmanned aerial vehicle body, a power device, an electric power system and the like. The flight monitoring system 102 is used for acquiring the geospatial position, flight attitude, etc. of the unmanned aerial vehicle, and mainly comprises an aircraft control instrument, a GPS system, a speed sensor, a multidirectional motion sensor, an barometric pressure altitude sensor, etc. The ground remote control system 103 is configured to receive information such as geospatial position and flight attitude information of the unmanned aerial vehicle collected by the flight monitoring system 102, generate a corresponding flight control instruction, and control a power device in the unmanned aerial vehicle flight system 101 to fly according to the flight control instruction. The ground remote control system 103 mainly comprises a wireless remote control device, a signal transmitting and receiving device, a monitoring device and the like. The data transmission 104 is used for providing hardware support for signal transmission and reception for the ground remote control system 103, and mainly includes an external antenna and the like.
The image acquisition system 200 is used for acquiring remote sensing information, and mainly comprises a camera, a cradle head and the like. The image acquisition system 200 is provided on the unmanned aerial vehicle device 100.
The server 300 may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs, basic cloud computing services such as big data and artificial intelligence platforms, and the like. The server 300 is configured to receive a remote sensing image acquired by the image acquisition system 200 set on the unmanned aerial vehicle in a highway construction scene, and geospatial position and flight attitude information of the unmanned aerial vehicle device 100, so as to analyze soil and water conservation conditions in the highway construction scene.
The unmanned aerial vehicle device 100 and the image acquisition system 200 are respectively connected with the server 300 directly or indirectly through wired or wireless communication. Alternatively, the wireless network or wired network described above uses standard communication techniques and/or protocols. The network is typically the Internet, but may be any network including, but not limited to, a local area network (Local Area Network, LAN), metropolitan area network (Metropolitan Area Network, MAN), wide area network (Wide Area Network, WAN), mobile, wired or wireless network, private network, or any combination of virtual private networks.
The water and soil conservation monitoring method of the unmanned aerial vehicle in the highway construction scene can be implemented by a water and soil conservation monitoring system of the unmanned aerial vehicle in the highway construction scene, and the water and soil conservation monitoring system of the unmanned aerial vehicle in the highway construction scene can be installed on a server.
In order to further explain the technical solution provided by the embodiments of the present application, the following details are described with reference to the accompanying drawings and the detailed description. Although embodiments of the present application provide method operational instruction steps as illustrated in the following embodiments or figures, more or fewer operational instruction steps may be included in the method, either on a regular or non-inventive basis. In steps where there is logically no necessary causal relationship, the execution order of the steps is not limited to the execution order provided by the embodiments of the present application. The methods may be performed sequentially or in parallel as shown in the embodiments or the drawings when the actual processing or the apparatus is performed.
Referring to fig. 2, fig. 2 is a flow chart illustrating a method for monitoring water and soil conservation in a highway construction scene by using an unmanned aerial vehicle according to an embodiment of the application. As shown in fig. 2, the method includes:
Step 201, selecting a target area including an area to be monitored for water and soil conservation monitoring in a highway construction scene, wherein at least one image control point is distributed in the area to be monitored.
The content of the water and soil conservation monitoring mainly comprises aspects of disturbing soil conditions, water and soil loss conditions, prevention and control effects, water and soil loss damage and the like in each stage of the whole project construction process. In the aspect of disturbing the land, the method mainly monitors the actual permanent and temporary occupied land, the disturbed vegetation area of the ground surface, the permanent and temporary slag discarding quantity, the change condition and the like; in the aspect of water and soil loss conditions, the actual water and soil loss area, distribution, soil loss amount, change conditions and the like are monitored; in the aspect of water and soil loss prevention and control effect, the positions and the quantity of water and soil conservation projects, plants and temporary measures which are actually adopted are monitored in an important way, and the prevention and control effect before and after the water and soil conservation measures are implemented is compared with the control effect; in the aspect of water and soil loss hazard, the influence and hazard of water and soil loss on main engineering, peripheral important facilities and the like are monitored in an important mode.
The area to be monitored is an area needing to be concerned by monitoring, and can be exemplified by a disturbed land area, a water and soil loss concerned area and the like. It should be understood that, in order to avoid that blurring, distortion, etc. of edge object information appear when aerial images are subjected to internal processing, it is necessary to plan a target area for aerial photography in advance in order to avoid losing information of an area to be monitored.
In a possible embodiment, the target area for aerial photography is an area extending a preset distance to the periphery of the area to be monitored, and the preset distance is preferably 20m. Taking fig. 3 as an example, after a preset distance is extended from the periphery of the area to be monitored, a target area is determined, and a aerial route is planned in the target area.
It should be understood that before planning the route, the area to be monitored is preliminarily determined in software such as Google Earth, an Orvey map and the like, the topography of the area to be monitored is known, reasonable flight frame sub-division is performed, the aviation scheme is optimized, the operation efficiency is improved, and the occurrence of collision accidents is avoided. For the area lacking satellite map assistance, the area to be monitored and the target area need to be set according to the position of the unmanned aerial vehicle in combination with manual judgment, specifically, after arriving at the aerial photography site, the unmanned aerial vehicle is manually operated to control the unmanned aerial vehicle to navigate around the target area for one circle in comparison with the aerial photography image received, so that the boundary and the route of the target area can be accurately determined.
The imaging control point is a point which is artificially set and used for registering the camera coordinate system and the actual coordinate system. The image control points can be divided into control points and check points, wherein the control points are used for defining a reference coordinate system of the three-dimensional model by combining camera coordinates, and the check points are used for analyzing the measurement accuracy of the three-dimensional model.
Step 202, aerial images acquired by the unmanned aerial vehicle in a target area are acquired, wherein the aerial images comprise orthographic aerial images and/or oblique aerial images.
After the unmanned aerial vehicle is planned in the route, the elevation angle of an image acquisition device (such as a cradle head) is adjusted to form 90 degrees with the ground, and a camera sensor is perpendicular to the ground to acquire the shooting mode of the aerial image.
The tilting aerial camera is more complex, the unmanned aerial vehicle is completed through the multi-lens tilting aerial camera, one sensor is perpendicular to the ground for aerial camera acquisition, and the other 4 sensors form 90 degrees in different directions and form the same angle with the ground for aerial camera acquisition. Wherein, aerial photographs acquired by sensors perpendicular to the ground are called orthographic photographs, aerial photographs acquired by the other 4 sensors are called oblique aerial photographs, the oblique aerial photographs comprise front view, rear view, left view and right view, that is, the unmanned aerial vehicle acquires oblique aerial photographs through 1 orthographic aerial photograph and 4 oblique aerial photographs. The tilting aerial image based on the light and small consumer unmanned aerial vehicle simulates the operation of a multi-lens tilting aerial camera by adopting a five-way flight mode through a single-lens unmanned aerial vehicle, adjusts the pitch angle of a cradle head, enables the single-lens unmanned aerial vehicle to perform aerial shooting acquisition on a sensor perpendicular to the ground once, thereby obtaining an orthographic aerial film, and then forms a certain angle with the ground and performs aerial shooting acquisition on the sensor in 4 different directions for 4 times respectively, thereby obtaining the tilting aerial film. The single-lens unmanned aerial vehicle obtains all-dimensional information of the ground object through aerial photography in different directions for a plurality of times, so that simulation of the multi-lens inclined aerial photography instrument is realized.
In one possible embodiment, when the unmanned aerial vehicle performs aerial photography, the inclination angle between the main optical axis of the camera on the unmanned aerial vehicle and the plumb line should not exceed 20 ° in normal shooting aerial photography, the corresponding range is 20 ° to 60 ° in oblique aerial photography, the larger the inclination angle setting is, the farther the aircraft deviates from the center of the aerial photography area, so the inclination angle setting should not be too large, preferably 45 °, and the inclination angle setting can be properly reduced when the flight airspace is limited.
By way of example, fig. 4 shows the relationship between the course and the area to be monitored when the unmanned aerial vehicle is panning, and fig. 5 shows the relationship between the course and the area to be monitored when the unmanned aerial vehicle is tilting. It should be understood that the unmanned aerial vehicle forms a specific inclined included angle with the area to be monitored by adjusting the relationship between the route and the area to be monitored, and the like unmanned aerial vehicle image acquisition device realizes the inclined aerial photography meeting the requirements.
It should be noted that, whether the normal-shooting aerial shooting or the oblique aerial shooting is performed, it is necessary to ensure the ground resolution of the image obtained by the aerial shooting. GSD (Ground Sample Distance, actual ground distance) is the actual ground distance corresponding to the center points of two adjacent pixels in the aerial image, also called ground resolution, and has a direct influence on the accuracy quality and resolution of the final aerial image. Accordingly, embodiments of the present application provide a method for selecting an appropriate voyage based on a ground resolution GSD.
Specifically, as shown in fig. 6, there is a certain proportional relationship between the pixel point on the aerial photograph and the ground resolution GSD, based on which, the flying height of the unmanned aerial vehicle may be related to the ground resolution GSD according to the focal length of the lens, the distance between the pixel point, and the following relationship exists:
wherein h is the flying height of the unmanned aerial vehicle, f is the focal length of the lens, a is the pixel point distance, and GSD is the ground resolution.
Further, the absolute altitude of the unmanned aerial vehicle comprises the flight altitude and the average plane altitude, that is, after determining the flight altitude, the actual flight altitude of the unmanned aerial vehicle can be obtained in combination with the actual altitude of the area to be monitored.
GSD is the actual ground distance corresponding to the center points of two adjacent pixels in the image, and has direct influence on the precision quality and resolution of the final orthographic image result. For the same camera, the lower the flying height, the higher the ground resolution of the photographed picture, but the corresponding flying time increases.
The longest dead time of a consumer unmanned aerial vehicle powered by a battery is typically around 20 minutes, so that the flight time approaches its upper limit, which requires consideration of zoned mapping or elevation of the flight altitude. Another factor limiting the flying height is the terrain factor, and for undulating mountains and urban populated areas, there are obstacles such as trees, poles, buildings, mountains, etc., and when the flying height is lower than the obstacle height, a crashing accident occurs. Therefore, for safety, the flying height should be ensured to be greater than the highest ground object of the thousand business area.
Based on the method, the water and soil conservation monitoring method of the unmanned aerial vehicle in the highway construction scene is realized, the aerial image is used for constructing the target three-dimensional model which is analyzed by the measurement precision and has the error reaching the target precision, so that the constructed target three-dimensional model is closer to the actual state of the area to be monitored, the error between the constructed target three-dimensional model and the actual disturbance change is lower, the disturbance situation can be better reflected, the result of monitoring and analyzing the water and soil conservation situation of the area to be monitored in the highway construction scene based on the target three-dimensional model is more accurate, the actual highway construction is better guided, the endurance time of the unmanned aerial vehicle is better effectively utilized, and the precision of image processing and the safety of the unmanned aerial vehicle are both considered.
And 203, constructing a target three-dimensional model based on the aerial image, wherein the target three-dimensional model is a model for performing measurement accuracy analysis on the candidate three-dimensional model, and the obtained error reaches the target accuracy.
In the road construction scene, the water and soil conservation monitoring has guiding significance for engineering evaluation and the like, so that the construction of the three-dimensional model with higher precision is a precondition for realizing accurate water and soil conservation monitoring analysis.
In one possible embodiment, as shown in fig. 7, performing measurement accuracy analysis on the candidate three-dimensional model includes:
and 701, constructing a candidate three-dimensional model based on the aerial image and the construction condition of the candidate three-dimensional model.
It should be noted that, the aerial image may be spliced by using image processing software, and then candidate three-dimensional models may be constructed according to different three-dimensional model construction conditions. Wherein the build conditions include, but are not limited to, utilizing control points in the imaging control points.
In one possible embodiment, agisoft Photoscan software may be selected for aerial image stitching.
Step 702, selecting at least one check point from a plurality of image control points corresponding to the candidate three-dimensional model, and obtaining a target three-dimensional coordinate corresponding to the check point, wherein the check point and the control point are different image control points.
Step 703, obtaining true value three-dimensional coordinates corresponding to the check point measured by the RTK measurement system.
The RTK measuring system is a Real-time differential positioning measuring system, and when the image control points are distributed, the RTK measuring system is used for measuring the image control points to obtain centimeter-level positioning of the image control points.
And step 704, analyzing the error between the target three-dimensional coordinate and the true three-dimensional coordinate, and determining the candidate three-dimensional model as the target three-dimensional model when the error reaches the target precision.
That is, the method compares the target three-dimensional coordinates of the check point in the three-dimensional model constructed based on the aerial image of the unmanned aerial vehicle with the high-precision true three-dimensional coordinates measured by the RTK measuring system, if the error reaches the target precision, determines that the construction mode of the candidate three-dimensional model can highly restore the actual state of the area to be monitored by water and soil conservation, takes the candidate three-dimensional model as the target three-dimensional model, aerial photographs the area to be monitored according to the preset frequency and constructs the target three-dimensional model, and further analyzes the water and soil conservation according to the three-dimensional model changes in different periods.
If the error does not reach the target precision, determining that the construction mode of the candidate three-dimensional model can not highly restore the actual state of the area to be monitored for water and soil conservation, and cannot meet the precision requirement for monitoring the area to be monitored for water and soil conservation.
In one possible embodiment, it is determined whether the error has reached the target accuracy by comparing the root mean square error of the target three-dimensional coordinates and the true three-dimensional coordinates in the X-direction, Y-direction, Z-direction, and plane.
Specifically, the following formula may be employed:
wherein Xi, yi and Zi are three-dimensional coordinates of the ith image control point; x is X RTKi ，Y RTKi ，Z RTKi Three-dimensional coordinates of an ith image control point measured by an RTK measuring system; RMSEx, RMSEy, RMSEZ, RMSEH is the root mean square error of X, Y, Z and plane; n is the number of check points.
In one possible embodiment, the errors include a plane error and an elevation error, and the candidate three-dimensional model is determined to be the target three-dimensional model when the plane error is less than 0.3m and the elevation error is less than 0.5 m.
And 204, monitoring and analyzing the water and soil conservation condition of the area to be monitored in the road construction scene based on the target three-dimensional model.
It should be noted that the target three-dimensional model may provide an orthographic image DOM of the area to be monitored and a digital elevation model DEM, where the orthographic image DOM may provide disturbance conditions of the area to be monitored, for example, the distribution range and the area of the disturbance land are determined by images in different periods, and the digital elevation model DEM may provide volume change conditions of the area to be monitored, for example, the change conditions of the square quantity are determined by models in different periods.
As shown in fig. 8, accuracy analysis was performed by using the target three-dimensional models corresponding to the two aerial and oblique modes, wherein the accuracy of the target three-dimensional model corresponding to the aerial and oblique mode was 86.54% to 99.64%, the average accuracy was 95.36%, the accuracy of the target three-dimensional model corresponding to the oblique aerial mode was 90.19% to 98.74%, and the average accuracy was 95.20%. Therefore, the target three-dimensional model subjected to measurement accuracy analysis can provide higher accuracy, so that the actual condition of the region to be monitored during aerial photography can be well expressed by the target three-dimensional model, reliable data support can be provided for water and soil conservation monitoring, and reliable data guarantee can be provided for water and soil conservation monitoring analysis and highway construction.
According to the water and soil conservation monitoring method of the unmanned aerial vehicle in the highway construction scene, the target area comprising the area to be monitored for water and soil conservation monitoring in the highway construction scene is selected, the aerial image acquired by the unmanned aerial vehicle in the target area is acquired, and the target three-dimensional model which is subjected to measurement precision analysis and has the error reaching the target precision is constructed based on the aerial image, so that the constructed target three-dimensional model is closer to the actual state of the area to be monitored, the error between the constructed target three-dimensional model and the actual disturbance change is lower, the disturbance situation can be better reflected, and the result of monitoring analysis on the water and soil conservation situation of the area to be monitored in the highway construction scene is more accurate finally based on the target three-dimensional model, and the method has better guidance on actual highway construction. Meanwhile, the method utilizes the RTK measuring system with high-precision centimeter-level positioning to carry out measurement precision analysis on the candidate three-dimensional model, ensures the reliability of the precision of the target three-dimensional model obtained through measurement precision analysis, and provides precision support for water and soil conservation monitoring by utilizing the target three-dimensional model.
In one possible embodiment, as shown in fig. 9, the candidate three-dimensional model includes an orthographic control point encryption model, and constructing the candidate three-dimensional model based on the aerial image and the construction conditions of the candidate three-dimensional model includes:
Step 901, acquiring each image control point in an area to be monitored based on the orthographic aerial image.
It should be appreciated that in performing embodiments of the present application, it may be desirable to control the drone to perform an orthoaerial camera to obtain an orthoaerial image. The image control points are arranged in the target area in advance, and optionally, at least 5 image control points, preferably 5-10 image control points, are arranged in the target area according to the actual condition of the target area and the accuracy requirement of water and soil conservation monitoring, wherein each image control point is at least arranged on 5 aerial pictures so as to ensure that the position information of the image control points can be obtained through the aerial pictures. The location information of the image control point acquired based on the orthographic aerial image includes, but is not limited to, the identification, longitude, latitude, and altitude of the image control point.
And step 902, selecting an optimal image control point from the image control points, wherein the optimal image control point comprises a tetrad point group and encryption points in the area to be monitored.
It should be understood that the set of four corners is an image control point disposed at four corners of the area to be monitored. The number of encryption points can be selected according to the number of the layout, and is determined according to the size of the area to be monitored, and the application is not particularly limited.
And 903, performing aerial triangle calculation based on the optimal image control point to generate an orthographic aerial photography control point encryption model.
Specifically, a triangular mesh model of the area to be monitored can be constructed according to the longitude, latitude and elevation of each optimal image control point obtained by the orthographic aerial photography image, and then mesh calculation is carried out to obtain an orthographic aerial photography control point encryption model.
In the embodiment of the application, after the orthographic control point encryption model is obtained, target three dimensions corresponding to a plurality of check points are read from the orthographic control point encryption model as target three dimensions, true three-dimensional coordinates corresponding to the plurality of check points are read from RTK measurement system measurement, and errors between the target three-dimensional coordinates and the true three-dimensional coordinates are analyzed, so that whether the errors of the orthographic control point encryption model reach target precision is judged.
By way of example, fig. 10 shows a plane error and an elevation error corresponding to a plurality of checkpoints in an orthographic control point encryption model corresponding to a region to be monitored, and the plane error on the plane of the orthographic control point encryption model is 0.123m, the root mean square error is 0.143m, the average error on the elevation is 0.280m, and the elevation error is 0.374m through calculation and analysis. Therefore, the plane error corresponding to the orthographic aerial photography control point encryption model is smaller than 0.3m, and the elevation error is smaller than 0.5m, so that the method can be used as a target three-dimensional model of the area to be monitored.
In one possible embodiment, the candidate three-dimensional model includes a tilting aerial non-control point model, and constructing the candidate three-dimensional model based on the aerial image and the construction conditions of the candidate three-dimensional model includes: and performing aerial triangle calculation based on the inclined aerial image to generate an inclined aerial non-control point model.
It should be noted that, when executing the embodiment of the present application, it is necessary to control the unmanned aerial vehicle to perform oblique shooting, so as to obtain an oblique shooting aerial image. Based on the description about the single-lens unmanned aerial vehicle, 5 routes can be planned, the image acquisition device (cradle head) acquires the orthographic aerial lens when the route 1 is executed, the cradle head pitch angle is adjusted to be-45 degrees when the routes 2, 3, 4 and 5 are executed, and the inclined aerial lens is acquired from four directions of front, back, left and right (shown in fig. 5) respectively, so that the inclined aerial image of the single-lens unmanned aerial vehicle is acquired.
And after obtaining the inclined aerial image, performing triangular calculation according to the image information of the inclined aerial image to generate an inclined aerial non-control point model.
In the embodiment of the application, after the inclined aerial photography non-control point model is obtained, reading target three dimensions corresponding to a plurality of check points from the inclined aerial photography non-control point model as target three dimensions, reading true three-dimensional coordinates corresponding to the plurality of check points from RTK measurement system measurement, and analyzing errors between the target three-dimensional coordinates and the true three-dimensional coordinates, so as to judge whether the errors of the inclined aerial photography non-control point model reach target precision.
By way of example, fig. 11 shows a plane error and an elevation error corresponding to a plurality of checkpoints in an oblique aerial control point model corresponding to a region to be monitored, where the plane error on the plane of the orthographic aerial control point encryption model is 0.426m, the root mean square error is 0.458m, the average error on the elevation is 1.832m, and the elevation error is 1.842m. Therefore, the plane error corresponding to the inclined aerial photography non-control point model is larger than 0.3m, the elevation error is larger than 0.5m, and the target precision is not reached, so that the inclined aerial photography non-control point model cannot be used as a target three-dimensional model of the area to be monitored.
In one possible embodiment, the candidate three-dimensional model includes a tilting aerial control point encryption model, and constructing the candidate three-dimensional model based on the aerial image and the construction conditions of the candidate three-dimensional model includes: acquiring each image control point in the area to be monitored based on the inclined aerial image; selecting a plurality of encryption control points from the image control points; and performing air triangular calculation based on the encryption control points to generate an encryption model of the inclined aerial photography control points.
It should be understood that 5 routes can be planned, the image acquisition device (cradle head) acquires the orthographic aerial lens when the route 1 is executed, the cradle head pitch angle is adjusted to be-45 degrees when the routes 2, 3, 4 and 5 are executed, and the oblique aerial lens is acquired from four directions of front, back, left and right (as shown in fig. 5) respectively, so that an oblique aerial image of the single-lens unmanned aerial vehicle is acquired.
Then, a plurality of encryption control points in the area to be monitored are selected from the oblique aerial image, wherein the number of the encryption control points reaches a plurality of control points of encryption degree. It should be appreciated that unlike orthographic control point encryption, the oblique aerial control point encryption model need not select a particular set of four corners.
Further, a triangular grid model of the area to be monitored can be constructed according to the longitude, latitude and elevation of each encryption control point obtained by oblique shooting aerial photography images, and then grid calculation is carried out to obtain the encryption model of the oblique aerial photography control points.
In the embodiment of the application, after the oblique aerial photography control point encryption model is obtained, reading target three dimensions corresponding to a plurality of check points from the oblique aerial photography control point encryption model as target three dimensions, reading true three-dimensional coordinates corresponding to the plurality of check points from RTK measurement system measurement, and analyzing errors between the target three-dimensional coordinates and the true three-dimensional coordinates, so as to judge whether the errors of the oblique aerial photography control point encryption model reach target precision.
By way of example, fig. 12 shows a plane error and an elevation error corresponding to a plurality of checkpoints in an oblique aerial control point encryption model corresponding to an area to be monitored, where the plane error on the plane of the oblique aerial control point encryption model is 0.112m, the root mean square error is 0.134m, the average error on the elevation is 0.249m, and the elevation error is 0.316m. Therefore, the plane error corresponding to the orthographic aerial photography control point encryption model is smaller than 0.3m, and the elevation error is smaller than 0.5m, so that the method can be used as a target three-dimensional model of the area to be monitored.
The point numbers in fig. 10-12 are ID identifications of the image control points, and the same check points can be selected from the candidate three-dimensional model and the RTK measurement system for accuracy verification according to the ID identifications of the image control points.
It should be noted that, through a great deal of practical analysis of the applicant, the accuracy of the orthographic aerial photography control point encryption model and the 20-60-degree preferably 45-degree inclined aerial photography control point encryption model is stable aiming at the water and soil conservation monitoring scene in the highway construction scene, and the method can be directly applied to the three-dimensional modeling process of water and soil conservation monitoring in the highway construction scene. That is, when water and soil conservation is monitored in a highway construction scene, the orthographic aerial photography image can be directly used for constructing an orthographic aerial photography control point encryption model to monitor and analyze water and soil staff conditions, or the oblique aerial photography image can be directly used for constructing an oblique aerial photography control point encryption model to monitor and analyze water and soil staff conditions. The photographed data and comparative test results of fig. 10-12 are specifically referred to in the following table 1:
TABLE 1 influence of different shooting modes on the plane and elevation error of soil and water conservation monitoring area
It should be understood that in the actual application process, the accuracy analysis may be performed on the candidate three-dimensional models before monitoring, and then at least one target three-dimensional model with the highest actual accuracy may be selected for subsequent monitoring analysis.
In summary, according to the method for monitoring the water and soil conservation of the unmanned aerial vehicle in the highway construction scene, the target area including the area to be monitored for water and soil conservation in the highway construction scene is selected, the aerial image acquired by the unmanned aerial vehicle in the target area is acquired, and the target three-dimensional model which is subjected to measurement accuracy analysis and has the error reaching the target accuracy is constructed based on the aerial image, so that the constructed target three-dimensional model is closer to the actual state of the area to be monitored, the error between the constructed target three-dimensional model and the actual disturbance change is lower, the disturbance situation can be better reflected, and the result of monitoring analysis on the water and soil conservation of the area to be monitored in the highway construction scene is more accurate finally based on the target three-dimensional model, and the method has better guidance on actual highway construction. Meanwhile, the method utilizes the RTK measuring system with high-precision centimeter-level positioning to carry out measurement precision analysis on the candidate three-dimensional model, ensures the reliability of the precision of the target three-dimensional model obtained through measurement precision analysis, and provides precision support for water and soil conservation monitoring by utilizing the target three-dimensional model.
It should be noted that although the operations of the method of the present application are depicted in the drawings in a particular order, this does not require or imply that the operations must be performed in that particular order or that all of the illustrated operations be performed in order to achieve desirable results.
Fig. 13 shows a schematic structural diagram of a water and soil conservation monitoring system of an unmanned aerial vehicle in a highway construction scene according to an embodiment of the present application.
As shown in fig. 13, the water and soil conservation monitoring system 10 of the unmanned aerial vehicle in a highway construction scene includes:
the selecting module 11 is configured to select a target area including an area to be monitored for water and soil conservation monitoring in a highway construction scene, where at least one image control point is arranged in the area to be monitored;
an acquisition module 12, configured to acquire aerial images acquired by the unmanned aerial vehicle in the target area, where the aerial images include orthographic aerial images and/or oblique aerial images;
the construction module 13 is used for constructing a target three-dimensional model based on the aerial image, wherein the target three-dimensional model is a model for carrying out measurement precision analysis on candidate three-dimensional models, and the obtained error reaches the target precision;
and the analysis module 14 is used for monitoring and analyzing the water and soil conservation condition of the area to be monitored in the highway construction scene based on the target three-dimensional model.
In some embodiments, the building module 13 is further configured to:
constructing the candidate three-dimensional model based on the aerial image and a construction condition of the candidate three-dimensional model, wherein the construction condition comprises utilizing a control point in the image control point;
Selecting at least one check point from a plurality of image control points corresponding to the candidate three-dimensional model, and acquiring a target three-dimensional coordinate corresponding to the check point, wherein the check point and the control point are different image control points;
acquiring true value three-dimensional coordinates corresponding to check points measured based on an RTK measurement system;
and analyzing the error between the target three-dimensional coordinate and the true three-dimensional coordinate, and determining the candidate three-dimensional model as the target three-dimensional model when the error reaches the target precision.
In some embodiments, the errors include a plane error and an elevation error, and the candidate three-dimensional model is determined to be the target three-dimensional model when the plane error is less than 0.3m and the elevation error is less than 0.5 m.
In some embodiments, the candidate three-dimensional model includes an orthographic control point encryption model, construction module 13, further configured to:
acquiring each image control point in the region to be monitored based on the orthographic aerial photography image;
selecting an optimal image control point from the image control points, wherein the optimal image control point comprises a tetrad point group and an encryption point in the middle of the area to be monitored;
and carrying out air triangular calculation based on the optimal image control point to generate the orthographic aerial photography control point encryption model.
In some embodiments, the candidate three-dimensional model includes a tilt aerial non-control point model, construction module 13, further configured to:
and performing air triangular calculation based on the inclined aerial image to generate the inclined aerial non-control point model.
In some embodiments, the candidate three-dimensional model includes a tilt panning control point encryption model, construction module 13, further configured to:
acquiring each image control point in the region to be monitored based on the inclined aerial image;
selecting a plurality of encryption control points from the image control points;
and performing air triangular calculation based on the encryption control points to generate the encryption model of the inclined aerial photography control points.
It should be appreciated that the elements or modules described in the water and soil conservation monitoring system 10 of the drone in the highway construction scenario correspond to the various steps in the method described with reference to fig. 2. Thus, the operations and features described above with respect to the method are equally applicable to the soil and water conservation monitoring system 10 of the unmanned aerial vehicle in a highway construction scenario and the units contained therein, and are not described in detail herein. The water and soil conservation monitoring system 10 of the unmanned aerial vehicle in the road construction scene can be realized in a browser of the electronic equipment or other security applications in advance, and can be loaded into the browser of the electronic equipment or the security applications thereof in a downloading mode or the like. Corresponding units in the water and soil conservation monitoring system 10 of the unmanned aerial vehicle in the highway construction scene can be matched with units in the electronic equipment to realize the scheme of the embodiment of the application.
The division of the modules or units mentioned in the above detailed description is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.
Referring now to fig. 14, fig. 14 shows a schematic diagram of a computer system suitable for use in implementing an electronic device or server of an embodiment of the application,
as shown in fig. 14, the computer system includes a Central Processing Unit (CPU) 1401, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 1402 or a program loaded from a storage section 1408 into a Random Access Memory (RAM) 1403. In the RAM1403, various programs and data required for operation instructions of the system are also stored. The CPU1401, ROM1402, and RAM1403 are connected to each other through a bus 1404. An input/output (I/O) interface 1405 is also connected to the bus 1404.
The following components are connected to the I/O interface 1405; an input section 1406 including a keyboard, a mouse, and the like; an output portion 1407 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 1408 including a hard disk or the like; and a communication section 1409 including a network interface card such as a LAN card, a modem, and the like. The communication section 1409 performs communication processing via a network such as the internet. The drive 1410 is also connected to the I/O interface 1405 as needed. Removable media 1411, such as magnetic disks, optical disks, magneto-optical disks, semiconductor memory, and the like, is installed as needed on drive 1410 so that a computer program read therefrom is installed as needed into storage portion 1408.
In particular, the process described above with reference to flowchart fig. 2 may be implemented as a computer software program according to an embodiment of the application. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program contains program code for performing the method shown in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication portion 1409 and/or installed from the removable medium 1411. The above-described functions defined in the system of the present application are performed when the computer program is executed by a Central Processing Unit (CPU) 1401.
The computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation instructions of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, blocks shown in two separate connections may in fact be performed substantially in parallel, or they may sometimes be performed in the reverse order, depending on the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules involved in the embodiments of the present application may be implemented in software or in hardware. The described units or modules may also be provided in a processor, for example, as: the processor comprises a selection module, an acquisition module, a construction module and an analysis module. The names of the units or modules do not limit the units or modules, for example, selecting modules, and may also be described as "selecting a target area including an area to be monitored for water and soil conservation in a highway construction scene, where at least one image control point is disposed in the area to be monitored".
As another aspect, the present application also provides a computer-readable storage medium that may be included in the electronic device described in the above embodiment or may exist alone without being incorporated in the electronic device. The computer readable storage medium stores one or more programs that when used by one or more processors perform the soil and water conservation monitoring method described in the present application for the unmanned aerial vehicle in a highway construction scene.
The above description is only illustrative of the preferred embodiments of the present application and of the principles of the technology employed. It will be appreciated by persons skilled in the art that the scope of the disclosure referred to in the present application is not limited to the specific combinations of technical features described above, but also covers other technical features which may be formed by any combination of the technical features described above or their equivalents without departing from the spirit of the disclosure. Such as the above-mentioned features and the technical features disclosed in the present application (but not limited to) having similar functions are replaced with each other.
Claims (10)
1. A method for monitoring soil and water conservation of an unmanned aerial vehicle in a highway construction scene, comprising the steps of:
Selecting a target area comprising an area to be monitored for water and soil conservation monitoring in a highway construction scene, wherein at least one image control point is distributed in the area to be monitored;
acquiring aerial images acquired by the unmanned aerial vehicle in the target area, wherein the aerial images comprise orthographic aerial images and/or oblique aerial images;
constructing a target three-dimensional model based on the aerial photography image, wherein the target three-dimensional model is a model for performing measurement accuracy analysis on candidate three-dimensional models, and the obtained error reaches target accuracy;
and monitoring and analyzing the water and soil conservation condition of the area to be monitored in the road construction scene based on the target three-dimensional model.
2. The method of monitoring according to claim 1, wherein the performing measurement accuracy analysis on the candidate three-dimensional model includes:
constructing the candidate three-dimensional model based on the aerial image and a construction condition of the candidate three-dimensional model, wherein the construction condition comprises utilizing a control point in the image control point;
selecting at least one check point from a plurality of image control points corresponding to the candidate three-dimensional model, and acquiring a target three-dimensional coordinate corresponding to the check point, wherein the check point and the control point are different image control points;
Acquiring true value three-dimensional coordinates corresponding to check points measured based on an RTK measurement system;
and analyzing the error between the target three-dimensional coordinate and the true three-dimensional coordinate, and determining the candidate three-dimensional model as the target three-dimensional model when the error reaches the target precision.
3. The method of monitoring of claim 2, wherein the errors include a planar error and an elevation error, and wherein determining the candidate three-dimensional model as the target three-dimensional model when the error reaches the target accuracy comprises:
and when the plane error is smaller than 0.3m and the elevation error is smaller than 0.5m, determining the candidate three-dimensional model as the target three-dimensional model.
4. The method of monitoring of claim 2, wherein the candidate three-dimensional model comprises an orthographic control point encryption model, the constructing the candidate three-dimensional model based on the aerial image and a construction condition of the candidate three-dimensional model comprising:
acquiring each image control point in the region to be monitored based on the orthographic aerial photography image;
selecting an optimal image control point from the image control points, wherein the optimal image control point comprises a tetrad point group and an encryption point in the middle of the area to be monitored;
And carrying out air triangular calculation based on the optimal image control point to generate the orthographic aerial photography control point encryption model.
5. The method of monitoring of claim 2, wherein the candidate three-dimensional model comprises a tilted aerial non-control point model, the constructing the candidate three-dimensional model based on the aerial image and a construction condition of the candidate three-dimensional model comprising:
and performing air triangular calculation based on the inclined aerial image to generate the inclined aerial non-control point model.
6. The method of monitoring of claim 2, wherein the candidate three-dimensional model comprises a tilted aerial control point encryption model, the constructing the candidate three-dimensional model based on the aerial image and a construction condition of the candidate three-dimensional model comprising:
acquiring each image control point in the region to be monitored based on the inclined aerial image;
selecting a plurality of encryption control points from the image control points;
and performing air triangular calculation based on the encryption control points to generate the encryption model of the inclined aerial photography control points.
7. A water and soil conservation monitoring system of an unmanned aerial vehicle in a highway construction scene, comprising:
The system comprises a selection module, a control module and a display module, wherein the selection module is used for selecting a target area comprising an area to be monitored for water and soil conservation monitoring in a highway construction scene, and at least one image control point is distributed in the area to be monitored;
the acquisition module is used for acquiring aerial images acquired by the unmanned aerial vehicle in the target area, wherein the aerial images comprise orthographic aerial images and/or oblique aerial images;
the construction module is used for constructing a target three-dimensional model based on the aerial image, wherein the target three-dimensional model is a model for carrying out measurement precision analysis on candidate three-dimensional models, and the obtained error reaches the target precision;
and the analysis module is used for monitoring and analyzing the water and soil conservation condition of the area to be monitored in the highway construction scene based on the target three-dimensional model.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements a soil and water conservation monitoring method of the unmanned aerial vehicle in a highway construction scene as claimed in any one of claims 1-6 when executing the program.
9. A computer readable storage medium, on which a computer program is stored, which program, when being executed by a processor, implements a method for monitoring the conservation of water and soil in a road construction scene for an unmanned aerial vehicle according to any one of claims 1-6.
10. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements a method for monitoring the water and soil conservation of a drone according to any one of claims 1-6 in a highway construction scene.
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