Water and soil loss monitoring method based on combination of unmanned aerial vehicle oblique photography and laser radar

Abstract

The invention relates to a water and soil loss monitoring method based on combination of unmanned aerial vehicle oblique photography and a laser radar, and belongs to the technical field of water and soil loss monitoring, and the method comprises the following steps: (1) building an oblique photography three-dimensional model of a research area according to point cloud data; (2) forming a research area laser radar data three-dimensional model; and (3) performing data registration on the unmanned aerial vehicle oblique photography remote sensing data and the laser radar point cloud data to the same coordinate system, performing three-dimensional modeling and multi-period fusion data superposition calculation on the registered fusion data through modeling software, and accurately analyzing the water and soil loss condition generated in the railway project construction process to form the intelligent water and soil loss monitoring method. According to the method, the water and soil loss range, strength and development process of the disturbance area are displayed accurately, efficiently, visually and intelligently, and the method has important guiding significance for greatly improving the water and soil loss monitoring level of a railway project, optimizing water and soil conservation measure layout and improving the water and soil conservation working efficiency.

Description

Technical Field

[0001] The invention relates to a soil and water loss monitoring method based on the combination of unmanned aerial vehicle tilt photography and laser radar, belonging to the technical field of soil and water loss monitoring. Background Art

[0002] At present, conventional soil and water loss monitoring methods mainly include the runoff plot method and the erosion gully volume measurement method. The runoff plot method is a standard monitoring method for erosion intensity, but it is often difficult to select sites, difficult to implement, and easily affected by external interference, making it difficult to obtain accurate monitoring data; and continuous observation is required, which is time-consuming and labor-intensive. Although the erosion gully volume measurement method is time-saving, labor-saving, simple and easy to implement, the measurement is very arbitrary and the accuracy is relatively low. Therefore, relying on conventional monitoring methods to carry out soil and water loss monitoring along the railway cannot meet the actual monitoring needs. The adoption of high-precision and high-efficiency monitoring technical means is of great significance for the control of soil and water loss in railway projects.

[0003] With the development and cross-application of industry technologies, the technology in the field of soil and water loss monitoring can now realize dynamic monitoring of points, lines, and surfaces at multiple spatial scales, such as one-dimensional, two-dimensional, and three-dimensional. However, due to the limitations of various factors, the monitoring technology used in soil and water loss monitoring in production and construction projects is still mainly conventional monitoring, supplemented by new technologies.

[0004] At present, the new technologies for soil and water loss monitoring mainly use 3S technology (geographic information system, remote sensing technology, integrated remote sensing of global navigation satellite system), UAV oblique photogrammetry technology, laser radar technology, etc. In the early stage of research, some people carried out remote sensing monitoring experiments for different objects (infrastructure, surrounding environment, etc.) in different regions using different means (microwave, spectrum and comprehensive) to verify the observation capability of domestic satellite experimental platforms. However, the research scale is mainly large-scale range along the railway infrastructure, based on satellite remote sensing data analysis, and there are few applied studies on the application of UAV remote sensing and ground remote sensing technologies such as laser radar detection in small-scale ranges such as slopes to monitor railway soil and water loss.

[0005] Satellite remote sensing is the most widely used remote sensing technology in the fields of soil and water conservation and environmental protection. For example, it is used to carry out soil and water conservation surveys and soil erosion censuses. UAV oblique photogrammetry and lidar detection technology are rarely used at the construction project level. The UAV remote sensing system can quickly obtain spatial information on soil and water conservation of construction projects and complete remote sensing data collection, processing and application analysis. Using UAV monitoring to obtain image results, combined with ground observation and investigation, dynamic monitoring of the entire process and full coverage of linear production and construction projects can be achieved. It can save time, reduce workload, and obtain more information for field monitoring of linear production and construction projects. UAV oblique photography technology is a new technology developed in the field of remote sensing in recent years. Its technical features are: first, the UAV flies at a low altitude, and the multi-angle camera group can obtain the top surface and side image data of the object in multiple directions and with high coverage; second, the heading overlap and lateral overlap between adjacent images are high, and the image expression is rich in content; third, there is a small amount of manual intervention, automated image matching and modeling, and the main processing process is completed by the computer; fourth, the overall cost is low. UAV oblique photogrammetry technology has higher efficiency in data collection and three-dimensional model production, which can reduce time and labor costs. At present, this technology has been experimented and studied in many fields. The three-dimensional model of the project established using UAV oblique photography technology can more intuitively reflect the implementation dynamics of soil erosion and prevention and control projects.

[0006] Lidar is a product based on traditional radar and combined with modern laser technology. Since the first lidar was manufactured in the United States in the 1960s, lidar has developed rapidly and is widely used in the military, ocean, earth science and meteorological fields. Traditional radar uses millimeter and micrometer frequency bands, which can only have obvious reflection echoes for metal targets, and the echo signals for non-metallic materials are low. Lidar uses ultraviolet, visible light and near-infrared bands in the electromagnetic spectrum, which are shorter than millimeter and micrometer bands, and can also have echo signals for smaller-scale targets. It has unique advantages in detecting fine particles and has higher resolution in detecting distance, speed and angle. According to the application field of lidar, lidar can be divided into laser ranging radar, laser imaging radar, atmospheric detection radar, biological lidar and laser speed radar. Lidar has the characteristics of strong penetration, high measurement accuracy and strong anti-interference ability. It is increasingly used in high-tech fields such as autonomous driving, robots, and mapping, but is rarely used in the field of environmental protection. In the field of natural resource survey and monitoring, lidar can make up for the lack of accuracy of traditional remote sensing technology, can quickly collect and monitor complex environmental information, and has important application value.

[0007] For orthophotos, oblique photogrammetry can observe objects and landforms from multiple angles, and can reflect the actual situation more objectively and truly, which largely makes up for the shortcomings of orthophotos in practical applications. Due to the obstruction of ground buildings or trees, the information collected by oblique photography has a certain deviation, which affects the accuracy of subsequent three-dimensional modeling. Lidar technology can make up for this deficiency and directly obtain the three-dimensional coordinates of the target, becoming an important supplement to aerial photogrammetry technology. The characteristics of the spatial distribution of laser landing points and the density of point clouds directly reflect the spatial distribution state and characteristics of the measured terrain and objects. Different land coverage has different requirements for the density of point clouds, and its density has an important impact on product quality. Only when the corresponding point cloud density is reached can the corresponding scale product be produced; under the premise of realizing oblique photogrammetry, how to use the ability of airborne laser radar to penetrate clouds and vegetation, accurately measure and reflect real terrain information, and achieve the required point position accuracy through data processing of radar laser point clouds, produce surveying and mapping results that meet the accuracy requirements, and then accurately analyze and study the soil and water loss situation in the region, is the technical problem to be solved by the present invention. Summary of the invention

[0008] One of the purposes of the present invention is to address the defects or shortcomings in the prior art and provide a soil erosion monitoring system based on the combination of unmanned aerial vehicle oblique photography and lidar detection, so as to realize the precise, efficient, visualized and intelligent monitoring of soil erosion key areas in railway construction projects during and after the event, and intuitively display the scope, intensity and development process of soil erosion in disturbed areas, which has important guiding significance for significantly improving the level of soil erosion monitoring in railway projects, optimizing the layout of soil and water conservation measures, and improving the efficiency of soil and water conservation work.

[0009] The above object of the present invention is achieved through the following technical solutions:

[0010] A soil and water loss monitoring system based on the combination of unmanned aerial vehicle oblique photography and laser radar is characterized in that: it includes an unmanned aerial vehicle and a laser radar scanning device; image control points are arranged in the flight area, and the unmanned aerial vehicle obtains oblique images of the survey area to form a topographic map of the study area and obtain an oblique photography three-dimensional model; high-precision and high-density laser point cloud data is obtained through the laser radar scanning device, and after data processing, a DEM of the study area is formed; after the oblique photography data and the laser radar point cloud data are integrated, fusion data modeling is performed through modeling software to obtain a three-dimensional model based on the fusion of unmanned aerial vehicle oblique photography and laser radar.

[0011] Another object of the present invention is to provide a soil erosion monitoring method based on the combination of unmanned aerial vehicle oblique photography and laser radar in response to the defects or shortcomings in the prior art, so as to achieve precise, efficient, visualized and intelligent monitoring of soil erosion key areas in the construction process and operation stage of railway construction projects, and intuitively display the scope, intensity and development process of soil erosion in disturbed areas, which has important guiding significance for significantly improving the level of soil erosion monitoring in railway projects, optimizing the layout of soil and water conservation measures, and improving the efficiency of soil and water conservation work.

[0012] The above object of the present invention is achieved through the following technical solutions:

[0013] A soil and water loss monitoring method based on the combination of UAV oblique photography and laser radar, the steps are as follows:

[0014] (1) Use drones to obtain oblique photography remote sensing images of the survey area, process them to generate oblique photography point cloud data, and establish an oblique photography 3D model of the study area based on the point cloud data;

[0015] (2) Use an unmanned aerial vehicle (UAV) flying platform equipped with a laser radar scanning device to obtain high-precision, high-density laser radar point cloud data and form a three-dimensional laser radar data model of the study area;

[0016] (3) The UAV oblique photography remote sensing data and the LiDAR point cloud data are aligned to the same coordinate system, and the aligned fused data are 3D modeled by modeling software. The multi-period fused data are superimposed and calculated to accurately analyze the soil and water loss caused by the construction process of the railway project, forming an intelligent monitoring method for soil and water loss.

[0017] Preferably, step (1) is specifically as follows: first, carry out UAV flight operations, divide the study area into several aerial photography zones according to the UAV flight time, control radius and terrain conditions of the study area; set the UAV relative altitude, heading overlap, lateral overlap and other parameters; deploy image control points in the flight area; use the UAV to obtain oblique images of the survey area; generate oblique image point cloud data through aerial triangulation, and establish an oblique photography three-dimensional model of the study area.

[0018] Preferably, step (2) is specifically as follows: a multi-rotor UAV flight platform (DJI M300 RTK) equipped with a laser radar scanning device (DJI Zenmuse L1 camera) is used to establish a three-dimensional model of the study area through technical processes such as point cloud denoising, point cloud filtering, point cloud sparse compression, and hole repair.

[0019] Preferably, step (3) is as follows:

[0020] 1) Get data

[0021] The oblique photography point cloud data of the drone was obtained by using the drone flight platform (DJI M300RTK) equipped with a gimbal camera (DJI Zenmuse P1), and the laser radar point cloud data was obtained by using the drone flight platform (DJI M300RTK) equipped with a laser radar device (DJI Zenmuse L1). Data of the study area was collected from different perspectives and heights to obtain effective data that can reflect the three-dimensional characteristics of the study area. The study area was divided into multiple aerial photography zones according to the flight time, control radius and terrain conditions of the drone platform. The flight altitude of the drone was set to 200m. Based on the 24 / 35 / 50mm lens of the gimbal camera (Zenmuse P1) (with an integrated 3-axis gimbal with 20MP pixels and intelligent tilt capture function), 3cm resolution orthophotos and 5cm resolution oblique photography were obtained; based on the laser radar device (DJI Zenmuse L1 is an integrated integration of laser radar, mapping camera and high-precision inertial navigation system), the ground point cloud data of the study area with an elevation accuracy of 5cm and a plane accuracy of 10cm were obtained; both data can show detailed information on soil erosion in the study area;

[0022] 2) Data preprocessing

[0023] Since there may be interference factors such as noise, outliers, and occlusions during data collection, it is necessary to perform point cloud denoising, point cloud filtering, and point cloud thinning on the UAV oblique photography point cloud and airborne lidar point cloud data to remove invalid and redundant information; use an outlier removal algorithm based on statistical analysis to remove outliers and noise points. Noise points mainly include points or point groups below the ground, points or point groups that are significantly higher than the surface targets, and moving ground points;

[0024] 3) Data Registration

[0025] The RANSAC algorithm is used for coarse registration to reduce the influence of noise and occlusion; the point-to-plane ICP algorithm is used for fine registration, and the nearest point distance minimization principle is used for optimization to improve the accuracy of registration; through the above steps, the two data are fused into the same coordinate system;

[0026] 4) Data Fusion

[0027] According to the characteristics of point cloud data, in order to improve data accuracy, only the lidar data was retained in the overlapping part of the drone oblique photography point cloud and the airborne lidar point cloud. Finally, the DJI Terra software was used to perform aerial triangulation and three-dimensional modeling on the two point clouds. The micro-topography elevation change data was extracted based on the three-dimensional model, and time-series-based difference analysis was performed to calculate indicators such as slope soil erosion amount and soil erosion modulus.

[0028] Beneficial effects:

[0029] The beneficial effects of the soil and water loss monitoring system and method based on the combination of drone and laser radar of the present invention are mainly reflected in the following three aspects:

[0030] (1) The fusion application of UAV oblique photography and LiDAR scanning can simultaneously realize the collection of large-scale remote sensing images, improve the level of monitoring visibility, and realize accurate measurement of key areas, greatly reducing manpower and time costs, improving monitoring efficiency, and meeting the requirements of soil and water loss monitoring and high-quality development of environmental water conservation in railway projects;

[0031] (2) At present, the soil and water loss status of construction projects is mostly output in the form of data, and the visibility of monitoring results is poor. The use of remote sensing technology can display the monitoring results more intuitively, which is conducive to the precise implementation of soil and water loss control measures;

[0032] (3) Accurately assessing the soil and water loss situation in key ecological disturbance areas of railway projects, such as waste dumps and construction access road slopes, can further support key soil and water conservation tasks of railway projects, such as optimizing slag stacking methods, verifying the ecological restoration effects of disturbed areas, and taking timely prevention and control measures.

[0033] The soil and water loss monitoring system and method based on the combination of an unmanned aerial vehicle and a laser radar of the present invention can realize the precise, efficient, visualized and intelligent monitoring of the construction process and operation period of key soil and water loss areas in railway construction projects, and intuitively display the scope, intensity and development process of soil and water loss in disturbed areas. It has important guiding significance for significantly improving the level of soil and water loss monitoring in railway projects, optimizing the layout of soil and water conservation measures, and improving the efficiency of soil and water conservation work.

[0034] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings and specific embodiments, but those skilled in the art will understand that the embodiments described below are part of the embodiments of the present invention, rather than all of the embodiments, and are only used to illustrate the present invention, and should not be regarded as limiting the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a flow chart of the soil and water loss monitoring method based on the combination of UAV oblique photography and laser radar in Example 1 of the present invention. DETAILED DESCRIPTION

[0036] Unless otherwise specified, in the following embodiments, the components described are all conventional components available on the market in this field, the connections between the components are all conventional connections, the software involved are all conventional software in this field, and the methods described are all conventional methods in this field.

[0037] Example 1

[0038] like Figure 1 , which is a schematic diagram of the process of a soil and water loss monitoring method based on a combination of a drone and a laser radar in Example 1 of the present invention;

[0039] The soil and water loss monitoring method based on the combination of unmanned aerial vehicle tilt photography and laser radar of the present invention comprises the following steps:

[0040] (1) Use a drone equipped with a gimbal camera to obtain oblique images of the study area and establish an oblique photography 3D model of the study area

[0041] First, carry out UAV flight operations. According to the UAV endurance, control radius and terrain conditions of the study area, divide the study area into several aerial photography zones; set the relative altitude, heading overlap, lateral overlap and other parameters of the UAV; deploy image control points in the flight area. To ensure the accuracy of the results, deploy an image control point every 200m to 300m to ensure that the control points have a wide field of view and are evenly distributed, and appropriately increase the number of checkpoints; use the UAV equipped with a gimbal camera to obtain the oblique image of the study area; generate oblique image point cloud data through aerial triangulation, and establish an oblique photography 3D model of the study area;

[0042] Oblique photography is to take images when the camera's main optical axis and the plumb line have a certain inclination angle. Oblique photogrammetry is to carry multiple sensors on the same flight platform and collect images from different angles such as vertical and four oblique angles at the same time. While obtaining spatial geographic information, it also obtains all-round texture information of the research slope, which can more realistically and vividly express the typical slope. Oblique photogrammetry collects images of the shooting object from multiple angles, obtains multiple multi-resolution and multi-scale image data, provides more abundant data support for the construction of regional three-dimensional models, and facilitates the measurement of spatial information. In addition, the data acquisition speed is fast and the processing automation level is high, which is conducive to the timely update of data. UAV oblique photogrammetry technology can use multi-view images for joint adjustment, especially for the processing of traditional photogrammetry image occlusion and data avoidance, improves the connection effect between geographic elements during the measurement process, and thus improves the accuracy of the basic data for three-dimensional modeling. UAV oblique photogrammetry can increase the density of image information, and through dense matching, a wider range of research slope attribute information can be obtained, especially the acquisition of feature point, line, and surface attribute information; Oblique photography three-dimensional model is obtained through image matching, aerial triangulation and other processing.

[0043] (2) Use a UAV flight platform equipped with a laser radar scanning device to obtain high-precision, high-density laser point cloud data and establish a three-dimensional laser radar point cloud model of the study area.

[0044] A multi-rotor UAV flight platform (DJI M300 RTK) equipped with a laser radar scanning device (Zenmuse L1 camera) was used to obtain high-precision and high-density laser point cloud data. Point cloud denoising, point cloud filtering, point cloud thinning and other technical processes were adopted to form a three-dimensional model of the study area.

[0045] (3) The UAV oblique photography point cloud and the LiDAR point cloud are processed by registration and other processes to form a fused point cloud. The fused point cloud data is modeled by modeling software, and the multi-period model is superimposed and analyzed and calculated to obtain the characteristic data of soil and water loss in the study area, and an intelligent soil and water loss monitoring method is constructed. After obtaining the data, data preprocessing is first carried out. Noise, outliers, occlusion and other interference factors are removed by point cloud denoising, point cloud filtering, point cloud thinning and other processes; an outlier removal algorithm based on statistical analysis is used to remove outliers and noise points such as points or point groups below the ground, points or point groups that are significantly higher than the surface targets, and moving ground objects. After the processed data is processed, data registration is carried out. The RANSAC algorithm (RANSAC is the abbreviation of Random Sample Consensus, which is an algorithm that calculates the mathematical model parameters of the data based on a set of sample data sets containing abnormal data to obtain valid sample data. It was first proposed by Fischler and Bolles in 1981) is used for coarse registration to reduce the influence of noise and occlusion; Cloud The fine registration function in the Compare software sets the overlap rate to 20%. According to the nearest point correspondence between the oblique photography and lidar point cloud data, the two types of point cloud data are precisely registered by iteratively optimizing the transformation parameters to improve the registration accuracy. Through the above steps, the two types of data are fused into the same coordinate system. Finally, the data fusion operation is performed. According to the characteristics of the point cloud data, in order to improve the data accuracy, only the lidar data is retained in the overlapping part of the drone oblique photography point cloud and the airborne lidar point cloud. The two point clouds are aerially triangulated and three-dimensionally modeled using the DjiTerra software (DJI Terra is a PC application software that provides autonomous route planning, flight aerial photography, two-dimensional orthophotos and three-dimensional model reconstruction). According to the three-dimensional model, the micro-topography elevation change data is extracted, and the time-series-based difference analysis is performed to calculate the soil erosion amount, soil erosion modulus and other soil and water loss characteristic indicators of the railway project waste dump or construction slope.

[0046] The beneficial effects of the soil erosion monitoring system and method based on the combination of unmanned aerial vehicle and laser radar of the present invention are mainly reflected in the following three aspects: (1) The integrated application of unmanned aerial vehicle oblique photography and laser radar scanning can simultaneously realize the collection of remote sensing images on a larger scale, improve the monitoring visibility level, and realize accurate measurement of key areas at the same time, greatly reduce manpower and time costs, improve monitoring efficiency, and meet the requirements of high-quality development of soil erosion monitoring and environmental water conservation in railway projects; (2) The soil erosion status of current construction projects is mostly output in the form of data, and the visibility of monitoring results is poor. The use of remote sensing technology can more intuitively display the monitoring results, which is conducive to the precise implementation of soil erosion control measures; (3) Accurately assessing the soil erosion status in key ecological disturbance areas of railway projects such as abandoned slag yards and construction access road slopes can further support key tasks of soil and water conservation in railway projects such as optimizing slag stacking methods, verifying the ecological restoration effect of disturbed areas, and taking timely prevention and control measures.

[0047] The soil and water loss monitoring system and method based on the combination of an unmanned aerial vehicle and a laser radar of the present invention can realize the precise, efficient, visualized and intelligent monitoring of the construction process and operation period of key soil and water loss areas in railway construction projects, and intuitively display the scope, intensity and development process of soil and water loss in disturbed areas. It has important guiding significance for significantly improving the level of soil and water loss monitoring in railway projects, optimizing the layout of soil and water conservation measures, and improving the efficiency of soil and water conservation work.

[0048] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A soil and water loss monitoring system based on the combination of UAV oblique photography and laser radar, characterized by: It includes unmanned aerial vehicles and laser radar scanning equipment; image control points are arranged in the flight area, and the unmanned aerial vehicle obtains oblique images of the survey area to form a topographic map of the study area and obtain an oblique photography 3D model; high-precision and high-density laser point cloud data is obtained through the laser radar scanning equipment, and after data processing, the DEM of the study area is formed; after the oblique photography data and the laser radar point cloud data are integrated, fusion data modeling is performed through modeling software to obtain a 3D model based on the fusion of unmanned aerial vehicle oblique photography and laser radar.

2. A soil erosion monitoring method based on the combination of UAV oblique photography and laser radar, the steps of which are as follows: (1) Use drones to obtain oblique photography remote sensing images of the survey area, process them to generate oblique photography point cloud data, and establish an oblique photography 3D model of the study area based on the point cloud data; (2) Use an unmanned aerial vehicle (UAV) flying platform equipped with a laser radar scanning device to obtain high-precision, high-density laser radar point cloud data and form a three-dimensional laser radar data model of the study area; (3) The UAV oblique photography remote sensing data and the LiDAR point cloud data are aligned to the same coordinate system. The aligned fused data are then 3D modeled using modeling software. Multi-period fused data are superimposed and calculated to accurately analyze the soil and water loss caused by the construction of the railway project, thus forming an intelligent soil and water loss monitoring method.

3. The method for monitoring soil and water loss based on the combination of drone tilt photography and laser radar according to claim 2 is characterized by: Step (1) is as follows: First, carry out UAV flight operations, divide the study area into several aerial photography zones according to the UAV flight time, control radius and terrain conditions of the study area; set the UAV relative altitude, heading overlap, lateral overlap and other parameters; deploy image control points in the flight area; use the UAV to obtain oblique images of the survey area; generate oblique image point cloud data through aerial triangulation, and establish an oblique photography 3D model of the study area.

4. The method for monitoring soil and water loss based on the combination of unmanned aerial vehicle tilt photography and laser radar according to claim 3 is characterized by: Step (2) is as follows: a multi-rotor UAV flying platform equipped with a laser radar scanning device is used to establish a three-dimensional model of the study area through technical processes such as point cloud denoising, point cloud filtering, point cloud sparse compression, and hole repair.

5. The method for monitoring soil and water loss based on the combination of unmanned aerial vehicle oblique photography and laser radar according to claim 4 is characterized in that: Step (3) is as follows: 1) Get data Use the drone flight platform equipped with a gimbal camera to obtain the drone oblique photography point cloud data, and use the drone flight platform equipped with a laser radar device to obtain the laser radar point cloud data. Collect data from different perspectives and heights in the study area to obtain effective data reflecting the three-dimensional characteristics of the study area. According to the drone platform's endurance time, control radius, and the terrain conditions of the study area, the study area is divided into multiple aerial photography zones; Based on the laser radar equipment, obtain the study area ground point cloud data with an elevation accuracy of 5cm and a plane accuracy of 10cm; Both data can show detailed information on soil erosion in the study area; 2) Data preprocessing Perform point cloud denoising, point cloud filtering, and point cloud thinning on the UAV oblique photography point cloud and airborne laser radar point cloud data to remove invalid and redundant information; use an outlier removal algorithm based on statistical analysis to remove outliers and noise points. Noise points mainly include points or point groups below the ground, points or point groups significantly above the surface targets, and moving ground points; 3) Data registration The RANSAC algorithm is used for coarse registration to reduce the influence of noise and occlusion; the point-to-plane ICP algorithm is used for fine registration, and the nearest point distance minimization principle is used for optimization to improve the accuracy of registration; through the above steps, the two data are fused into the same coordinate system; 4) Data Fusion In the overlapping part of the UAV oblique photography point cloud and the airborne LiDAR point cloud, only the LiDAR data is retained. Finally, the two point clouds are subjected to aerial triangulation and three-dimensional modeling using the Dji Terra software. The micro-topography elevation change data is extracted based on the three-dimensional model, and time-series-based difference analysis is performed to calculate the slope soil erosion amount and soil erosion modulus indicators.

6. The method for monitoring soil and water loss based on the combination of unmanned aerial vehicle oblique photography and laser radar according to claim 5 is characterized in that: In step 1), the flight altitude of the drone is set to 200m, and based on the 24 / 35 / 50mm lens of the gimbal camera, 3cm resolution orthophotos and 5cm resolution oblique photography are obtained.

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