203 results about "Aerial survey" patented technology

The present invention belongs to the technical field of digital mine safety, and particularly relates to a blasting area surface morphology inversion method based on an unmanned aerial vehicle. The method comprises: S01, on-site data collection; S02, blasting area morphology inversion; S03, a muck pile throw distance; and S04, a muck pile surface fragmentation distribution. In the present invention, oblique photography by an unmanned aerial vehicle is used, and three-dimensional model reconstruction is performed by capturing a blasting area image, so that a feasible aerial survey scheme is formulated, and the integrity of collected data is good; and reverse modeling of the blasting area is performed by means of the steps of feature point extraction, spatial information conversion, point cloud generation, grid generation, etc.; voxel grid downsampling, point cloud matching and error detection are used to perform registration on point clouds of a target area before and after blasting, so that a good effect is achieved; and a color-based region growing algorithm is used to perform coarse segmentation of point cloud features on an ore-rock block on the surface of a muck pile, and a PointNet++ algorithm is used to perform fine segmentation of point cloud features on the ore-rock block on the surface of the muck pile, so that the muck pile throw distance and the muck pile surface fragmentation distribution are calculated.

The invention relates to the technical field of landslide geological disaster hidden danger point identification, in particular to a landslide hidden danger point identification method based on an air-space remote sensing fusion neural network, which comprises the following steps: acquiring satellite SAR data, a digital elevation model, a vector boundary map and a precision orbit ephemeris of a research area; carrying out interference processing on the InSAR data, and carrying out deformation rate inversion, terrain residual error correction and atmospheric delay phase modeling and correction; preprocessing an original high-resolution remote sensing image, interpreting a high-resolution image, and outputting spatial distribution of suspected landslide hidden danger points in a research area; planning an aerial survey route of the unmanned aerial vehicle, and performing distortion correction, feature matching, dense point cloud generation and orthoimage generation processing; performing multi-dimensional feature analysis, and performing comprehensive interpretation in combination with an expert knowledge base; according to the method, the key effect of the multi-source remote sensing fusion technology in landslide hidden danger monitoring is displayed from data acquisition to hidden danger recognition.

A method and system for constructing a three-dimensional (3D) aerial survey of a city street scene include obtaining a plurality of video frames from a calibrated multi-camera setup covering a 360-degree view mounted on a moving vehicle. The plurality of video frames is split into a plurality of 3D parts containing a subset of the plurality of video frames and preprocessing the subset of the plurality of video frames of each part of the plurality of parts to obtain a calculated information. Further, constructing, by the processing circuitry, a 3D representation of each part of the plurality of parts based on the calculated information to obtain a plurality of local 3D reconstructed scene intervals. The method includes stitching and filtering, by the processing circuitry, the plurality of local 3D reconstructed scene intervals to construct the 3D city street scene.

The invention relates to the technical field of tunnel construction, and discloses a coal mine goaf karst tunnel construction method which comprises the following steps: S1, performing three-dimensional scanning on the axis and the periphery of a tunnel by adopting a high-frequency geological radar in combination with aerial survey of an unmanned aerial vehicle, and accurately positioning the boundary of a goaf, the development form of a karst cave and filler distribution; and S2, integrating a seismic wave reflection method, drilling and coring data and a geological sketch result, constructing a three-dimensional geological model, and dynamically predicting a potential water inrush and mud inrush risk area. According to the method, a high-frequency geological radar is combined with aerial survey of an unmanned aerial vehicle, three-dimensional scanning is conducted on the axis and the periphery of a tunnel, geological radar data, a point cloud model and tunnel design BIM are integrated, the boundary of a goaf (the error is smaller than or equal to 0.3 m) and the karst cave form are marked, and the collapse risk level is predicted based on rock mass mechanical parameters (compressive strength and fracture density) and hydrological data (seepage paths). Therefore, the method has the advantages of advanced detection, multi-source data fusion and the like, and the resolution of geological forecast is improved.

The invention discloses an adjacent foundation pit deformation prediction method for a dense building group and a support deformation prediction method, and the method comprises the steps: obtaining SAR satellite images of a to-be-processed region in a period of time sequence, and generating an image stack after registration; screening points of which the amplitude deviation indexes are lower than a threshold value as PS points; calculating the relative displacement sequence of each PS point, inverting the displacement variation and accumulating to obtain the accumulated settlement; before construction, a digital surface model (DSM) is generated through aerial survey of an unmanned aerial vehicle, feature points with stable displacement are recognized by combining SAR images, and the feature points are anchored to an absolute coordinate system of the unmanned aerial vehicle for correction. Therefore, permanent scatterer (PS) identification and time sequence analysis are carried out by utilizing SAR images of a long time sequence, absolute geographic reference is provided by a high-precision digital surface model (DSM) generated by aerial survey of an unmanned aerial vehicle, and reference correction is carried out on a relative displacement field acquired by the InSAR.

The invention provides an aerial survey unmanned aerial vehicle route planning method and system, and the method mainly comprises four steps: map coordinate conversion, polygon processing, polygon decomposition, and path planning, and through the four steps, the aerial survey unmanned aerial vehicle route planning method employs a full-coverage path planning algorithm. After the boundary of the operation area and the coordinate information of the no-fly area are obtained, the air route is automatically generated to avoid the no-fly area and the path is shortest, so that the method is really applied to aerial photogrammetry operation, the reasonable shortest path can be planned for the operation area in any shape, the operation area cannot fly to the no-fly area, the turning frequency is reduced, and the working efficiency is improved. The phenomenon of repeated flight is avoided, and the operation efficiency of the aerial survey unmanned aerial vehicle is improved.

The invention relates to the technical field of ecological monitoring, in particular to a resident-free island resource monitoring method based on a spatial three-dimensional model, and the method comprises the following steps: S1, building a remote sensing image interpretation information base; s2, based on the remote sensing image interpretation information base, generating an island space three-dimensional model containing island land terrain and shoreline distribution; s3, generating a total element three-dimensional dynamic map; s4, the interpretation result and the total element three-dimensional dynamic map in the S3 are superposed, and a reef area comprehensive distribution map is generated; s5, calculating the island resource development intensity and the ecological risk level, and outputting an island ecological assessment report; and S6, generating an island resource monitoring report. According to the invention, unmanned aerial vehicle aerial survey, GNSS measurement, depth sounding technology, image interpretation and ecological assessment are combined, a high-precision total-factor three-dimensional dynamic monitoring system is constructed, accurate analysis and visual expression of the current island resource utilization situation are realized, and scientific decision support is provided for island management and ecological protection.

The invention discloses an electric power aerial patrol operation data mining method, and belongs to the technical field of intelligent patrol. Coordinate values and temperature data of target equipment are synchronously collected through an infrared thermal imager, a visible light camera and a vibration sensor carried by power equipment, infrared coordinates and visible light coordinates are projected to the same geographic coordinate system through affine transformation, space registration is achieved, continuous wavelet transformation is conducted on collected vibration signals, and the temperature of the target equipment is obtained. The method comprises the following steps: extracting vibration feature vectors including global vibration intensity, wavelet energy spectrum and wavelet entropy, calculating the weight of each feature through image quality, carrying out weighted fusion to calculate a state index representing the health state of equipment, judging the state index according to a dynamic threshold value, judging that the equipment is abnormal if the state index exceeds the threshold value, and judging that the equipment is abnormal if the state index does not exceed the threshold value. And a feedback mechanism is triggered to collect data again to monitor the trend, otherwise, the data is stored for subsequent analysis. According to the invention, the precision and reliability of abnormal state identification in electric power aerial patrol operation and the robustness to a complex field environment are significantly improved.

The invention provides an efficient riverway management range demarcation method based on multi-source data fusion and spatial characteristic difference, and the method comprises the steps: constructing a whole-process technical system of law and regulation analysis, multi-source data fusion, characteristic parameter extraction and dynamic optimization, integrating the multi-source data of satellite remote sensing, unmanned aerial vehicle aerial survey, hydrological monitoring, etc. Key parameters such as a central line, a gradient and a curvature of a river channel are extracted by utilizing an intelligent algorithm, and accurate delimiting of a management line is realized by combining design flood level calculation and Kriging interpolation optimization. The invention aims to break through the limitation of the traditional method, improve the demarcation efficiency and precision, provide standardized and executable technical support for scientific management of complex rivers, and assist the cooperative promotion of flood control safety and water resource protection.

The invention discloses a visual imaging method and system combined with unmanned aerial vehicle multi-temporal automatic comparison, and the system comprises an unmanned aerial vehicle aerial survey module which is used for carrying out the repeated aerial survey of the same target region at different time points, and obtaining multi-period image data; the data transmission and storage module is used for transmitting the multi-period image data acquired by the unmanned aerial vehicle aerial survey module in real time; the method has the beneficial effects that the aerial survey of the unmanned aerial vehicle supports dynamic route adjustment, multi-sensor cooperative acquisition is realized, the overlap ratio of multiple aerial survey paths is high, the image data integrity and consistency are high, and the manual intervention and data supplementary acquisition cost is greatly reduced; multi-stage image automatic registration, feature extraction and change detection are realized through deep learning, the processing precision is high, a large amount of manual operation is not needed, and the efficiency is remarkably improved; three-dimensional modeling and multi-mode comparison are supported, dynamic changes of ground objects can be clearly displayed, interaction functions are rich, and the requirements for single-person detail checking and multi-person collaborative rechecking can be met.

The invention belongs to the technical field of marine environment monitoring, and particularly relates to an air-sea cooperation-based enteromorpha identification and density estimation method and system, and the method comprises the steps: carrying out the aerial survey of a target sea area through an unmanned plane, collecting a sequence image, processing the sequence image based on a deep learning model, and generating an enteromorpha distribution probability graph and a density estimation graph; carrying out marine navigation and fixed-point sampling through an acoustic sensor carried by an unmanned ship to obtain actually measured density data of enteromorpha; the unmanned aerial vehicle sends the generated enteromorpha distribution probability graph and / or density estimation graph to the unmanned ship, the unmanned ship receives the enteromorpha distribution probability graph and / or density estimation graph, plans a navigation path and sampling points according to the enteromorpha distribution probability graph and / or density estimation graph, and goes to a high-probability or high-uncertainty area for fixed-point sampling; and the unmanned aerial vehicle receives actually measured density data returned by the unmanned ship and fuses the actually measured density data with own identification and estimation results so as to update and optimize the deep learning model and form an air-sea collaborative monitoring closed loop.

The invention relates to the technical field of earthwork calculation, in particular to an earthwork calculation method based on an unmanned aerial vehicle aerial survey technology. According to the technical scheme, the method comprises the steps of image control point layout and data acquisition, unmanned aerial vehicle image data acquisition, aerial triangulation processing and model generation. Based on an unmanned aerial vehicle aerial survey technology, image control points are scientifically arranged to collect high-precision coordinates, high-quality image data are obtained, a high-precision model is generated through aerial triangulation processing, the precision is strictly verified, data are extracted through professional software to construct an optimized DTM model, and precise earth-rock volume calculation is achieved; a calculation result is encrypted and stored by means of a block chain and is in butt joint with a construction management system, and a GIS platform and a BIM model are combined to generate a visual progress diagram, simulate slag yard capacity early warning and the like, so that the precision and efficiency of earth-rock calculation are comprehensively improved, powerful support is provided for engineering construction management, auditing tracing and ecological restoration decision, and the method is suitable for popularization and application. And the scientificity and informatization level of project management are obviously improved.

The application discloses a high-precision earthwork measurement algorithm and system for constructing a three-dimensional model based on unmanned aerial vehicle aerial survey, and the method comprises the following steps: arranging image control points and check points in a to-be-measured area in advance; starting unmanned aerial vehicle aerial survey image data collection, and performing supplementary measurement on an obstacle-shielded area to obtain supplementary data; importing the aerial survey image data to generate a real scene three-dimensional model; finding an image control point mark position on the three-dimensional model and corresponding puncture points of actual measured image control points, converting model latitude and longitude coordinates into project coordinates after matching all the image control points, regenerating a three-dimensional model, and importing check point coordinate data to verify the model precision. Seed points are added to remove obstacles and restore the ground terrain, and then drawings and design elevations are imported to perform high-precision earthwork calculation, so that the problems of complex calculation operation, easy errors and large time consumption of manual operation combined with other software are solved, accurate data support is provided for earthwork construction, and the project construction period is saved.

The invention relates to the technical field of aerial survey of unmanned aerial vehicles, in particular to a mountainous area aerial survey data processing method and device based on an unmanned aerial vehicle and a storage medium. The aerial survey assembly comprises a main control module, a high-precision positioning module, a laser radar module, a multispectral imaging module, a hardware synchronization module, a data fusion processing module and a wireless transmission module. The system has the advantages that the synchronization of data acquisition is ensured through aerial survey equipment integrating the high-precision positioning module, the laser radar module and the multi-spectral imaging module and the hardware synchronization module, the problem of space-time inconsistency of multi-source remote sensing data in a mountainous area complex environment is solved, and the multi-source remote sensing data is obtained through a combined adjustment processing method. The synchronously collected multispectral image and laser point cloud data are subjected to combined processing, precise three-dimensional coordinates provided by the laser point cloud constrain aerial triangulation of the multispectral image, and texture information of the multispectral image corrects a point cloud splicing error.

The invention discloses a geothermal water multi-factor remote sensing detection method, system and device, a medium and a product, and the method comprises the steps: obtaining a thermal radiation anomaly index and a surface temperature anomaly index through multi-temporal thermal infrared preliminary screening and surface temperature inversion; the method comprises the following steps: extracting a vegetation stress index VIBS by utilizing the characteristic that terrestrial heat inhibits vegetation, and obtaining a comprehensive altered mineral index MI according to mineral alteration characteristics and a spectral unmixing method; based on ALOS PALSAR, a fracture-fracture zone is extracted, and a construction advantage degree SF is quantified; gRACE gravity image data are introduced to form hydrological favorable degree HF; geothermal water indication characteristics are integrated, multi-factor scoring and grading are fused to obtain a comprehensive geothermal anomaly distribution map, and finally boundary refinement and field verification are carried out through unmanned aerial vehicle thermal infrared / multispectral aerial survey. According to the method, false detection and missing detection can be remarkably reduced, and the accuracy and field efficiency of geothermal anomaly recognition are improved.

The invention discloses a geological disaster hidden danger point rapid identification method based on aerial survey of an unmanned aerial vehicle, and relates to hidden danger point rapid identification. An airborne camera image sequence, the acceleration and angular velocity of an inertial measurement unit, the propeller rotating speed, the flight height, the wind speed and direction and a machine body vibration signal are collected, and image exposure time is used as a unified time axis; the method comprises the following steps: forming a time sequence sample, establishing rotor underwash near-earth boundary layer momentum entrainment prior based on the time sequence sample, calculating underwash dynamic pressure field time sequence estimation, a particle mobilization probability time sequence and an equivalent micro-attitude disturbance spectrum, performing sub-pixel level optical flow and phase accumulation analysis on an image sequence, performing time cross-correlation with the equivalent micro-attitude disturbance spectrum, and obtaining a target object. Coupling evidence is obtained, joint judgment of the triggering intensity and the coupling degree is carried out, a flight parameter self-adaptive fine tuning strategy is triggered, space risk analysis is carried out on the image after compensation reconstruction, a space risk calibration graph is generated, and geological disaster hidden danger points in a critical stable state can be effectively recognized.

The invention discloses a multi-dimensional construction safety risk management and control method for a high-altitude highway, particularly relates to the field of construction risk management and control, and is used for solving the problems of slope monitoring lag and passive safety management and control caused by complex terrain in the existing high-altitude highway construction process. The method comprises the following steps: acquiring aerial survey images and laser point cloud data of a construction slope area according to a fixed period, generating a time sequence three-dimensional live-action model sequence, identifying and tracking natural feature points and artificial structure feature points in the model sequence, calculating a feature point displacement field based on precision registration among multiple periods of models, and obtaining a feature point displacement field. The method comprises the following steps: identifying risk deformation data in space-time association with a construction activity in combination with historical construction activity records, performing spatial clustering analysis on the risk deformation data to mark a potential instability region, and generating a prospective construction risk grading control signal according to the space range of the potential instability region and construction information data; and dynamic pre-judgment and graded response of high-altitude highway construction risks are realized.

The utility model relates to the technical field of unmanned plane flight state switching, especially to a state switching structure of amphibious unmanned plane, including land walking mechanism for land walking and aerial flight mechanism for aerial flight, and the aerial flight mechanism includes state turnover assembly and drive assembly, the utility model combines two application fields of land tunnel survey and aerial survey, land free steering, fuselage structure change, land-air flight state free switching control, through changing the body structure, reducing the volume, possessing the ability of crossing limited space, can realize the monitoring and measurement to the underground and aboveground environment, the fuselage structure and the flight state change make that the unmanned plane can obtain the lift of multiple angles, when unmanned plane and bottom level, can provide the lift upwards / downwards, and the unmanned plane can execute aerial survey task, when unmanned plane and bottom vertical, can provide the thrust forwards / backwards, and the unmanned plane can execute tunnel survey task.

The invention aims to provide an intelligent surveying and mapping method and system based on aerial survey of an unmanned aerial vehicle in order to solve the problem that in the prior art, timeliness requirements of scenes such as disaster emergency and engineering monitoring are difficult to meet, and the intelligent surveying and mapping method comprises the steps that S1, a geographic boundary of a target area is input, and an anti-wind-disturbance self-adaptive route is generated based on a digital elevation model (DEM) and real-time meteorological data; s2, synchronously acquiring point cloud, image and spectral data through a laser radar, a five-lens oblique camera and a hyperspectral sensor carried by the unmanned aerial vehicle; s3, fusing GPS / I MU positioning data and visual SLAM feature points, and performing dynamic pose correction on the point cloud data; s4, registering multi-period point clouds by adopting an improved I CP algorithm, and extracting a ground object vector boundary through a semantic segmentation neural network (U-Net + + variant); and S5, fusing the vector boundary with the oblique photography model, outputting a three-dimensional live-action model with an attribute tag, reducing the number of supplementary flight times by adopting the adaptive route, and preprocessing data in real time by an edge calculation carrier plate.

1. The name of the design product: unmanned aerial vehicle (QF-3 type). 2. The use of the design product: for reconnaissance, aerial survey, forest fire prevention and power patrol, etc. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The application discloses a kind of railway three-dimensional geographic scene data service production methods based on red blue stereo sheet, comprising: S1, preparation basic data, S2, organization data, S3, production stereo sheet, S4, associated railway line position data, S5, stereo scene map service release.The method of the application constructs stereo pair using aerial survey original aerial photograph, generates red blue stereo sheet, realizes that only low-cost red blue glasses can be viewed stereo scene;Through the analysis of stereo pair coverage and railway mileage point positioning information, the association of stereo pair and railway line position is realized, and the interested area is quickly searched and positioned;By making red blue stereo sheet into standard format map service data and publishing service, multiple users can be quickly called and observed through network transmission.

The utility model discloses a reservoir aerial survey unmanned aerial vehicle with a modularized sensor mounting device. The reservoir aerial survey unmanned aerial vehicle comprises an unmanned aerial vehicle body, a square mounting support and a square butt joint sliding seat, a modular sensor is mounted on the bottom surface of the butt joint sliding seat; a vertical support is arranged in the middle of a frame body of the unmanned aerial vehicle body, a mounting support is fixed to the lower end of the vertical support, two T-shaped grooves are inwards formed in one end face of the mounting support side by side in the length direction of the mounting support, two T-shaped sliding blocks are arranged on the upper surface of a butt joint sliding base side by side, and the two T-shaped sliding blocks are sleeved with the two T-shaped grooves in a matched mode. According to the unmanned aerial vehicle, the butt joint sliding seats are correspondingly arranged on the winches of the camera device and the water quality detection sensor, and the butt joint sliding seats can be rapidly in butt joint with and detached from the mounting supports through the T-shaped sliding blocks, so that convenient switching between the camera device and the water quality detection sensor and the unmanned aerial vehicle is realized; the unmanned aerial vehicle can deal with various tasks such as water level and water body monitoring and water body sampling, the reservoir monitoring efficiency is improved, and the manpower and material resource cost is reduced.

The application discloses a kind of unmanned vehicle's route planning method, device, unmanned vehicle and storage medium, the method includes: determining the boundary of target aerial survey area;Determine the minimum circumscribed rectangle corresponding to the boundary of target aerial survey area;According to the minimum circumscribed rectangle and the boundary of target aerial survey area, the route of the unmanned vehicle is generated.The method can optimize the unmanned aerial vehicle survey method of small watershed of soil and water conservation by determining the minimum circumscribed rectangle of the boundary of target aerial survey area and generating the route of the unmanned vehicle in combination with the boundary of target aerial survey area, can cover small watershed of soil and water conservation all at once, make the number of unmanned aerial vehicle turning and heading along the aerial survey direction minimum, save the flight energy and aerial survey time of unmanned aerial vehicle, simultaneously avoid the invalid aerial survey data generated due to repeated aerial survey or missing of unmanned aerial vehicle, effectively reduce the data volume of aerial survey, reduce the processing difficulty of aerial survey data, shorten the data processing time.

The application discloses a rockfill material gradation detection method and device based on unmanned aerial vehicle aerial survey and instance segmentation, and comprises the following steps: establishing a conversion relationship between surface gradation and overall gradation by relying on local surface rockfill material images before density pit excavation and rockfill material screening results of the density pit; obtaining a rockfill dam filling bin surface image by using unmanned aerial vehicle close-range photogrammetry technology; generating an orthographic image of the filling bin surface; making an image dataset based on the orthographic image; training an instance segmentation model jointly constructed by YOLOv8 and Unet to obtain an instance segmentation model for rockfill material segmentation; obtaining an orthographic image of a rockfill dam filling bin surface to be predicted and cutting it into small blocks, using the instance segmentation model to perform prediction, realizing pixel-level instance segmentation and morphology extraction; splicing the predicted blocks, performing morphology quantitative analysis on the rockfill material instances obtained by prediction, and obtaining overall bin surface rockfill gradation through gradation conversion. The application realizes accurate and efficient gradation detection of overall bin surface rockfill.

The invention relates to the technical field of water conservancy project construction, and discloses a water conservancy project construction intelligent surveying and mapping method and system based on an unmanned aerial vehicle, and the method comprises a surveying and mapping task preparation step, an aerial survey operation step, a data processing step, a modeling analysis step and a result output step. The system corresponds to the method. According to the invention, through surveying and mapping task preparation, accurate adaptation of route planning and construction requirements is realized, and targeting of surveying and mapping operation is enhanced; through aerial survey operation, collaborative acquisition of multi-source heterogeneous data is realized, and comprehensiveness, integrity and reliability of data acquisition are guaranteed; by constructing a high-precision and multi-type three-dimensional model, the fine measurement requirements of hydraulic engineering construction on landforms and structural forms are met; through result output, seamless linkage of surveying and mapping results and a construction management platform is achieved, data application collaboration and the digital and visual level of engineering management are improved, and therefore efficient, accurate and comprehensive surveying and mapping technical support can be provided for hydraulic engineering construction.

The invention discloses a precise evaluation method for negative shear of a mountain wind power plant, and the method comprises the steps: high-resolution mountain topographic feature parameterization extraction: extracting microscopic topographic parameters in an evaluation region through a topographic feature recognition algorithm based on digital elevation model data; space-time fusion correction of multi-source observation data: integrating anemometer tower data, unmanned aerial vehicle aerial survey data and meteorological satellite data, and constructing a space-time continuous wind speed data set through a space-time interpolation algorithm; negative shear characteristic simulation based on improved CFD: adopting a double-layer calculation strategy of'macroscopic simulation + local encryption ', and performing airflow motion simulation in combination with terrain parameters and fused wind speed data; quantitative evaluation and visual output of negative shear characteristics: calculating negative shear characteristic parameters based on the three-dimensional wind speed field obtained through simulation, and outputting an evaluation result through a GIS platform; the technical problem that in the prior art, precision is insufficient due to neglecting of terrain complexity, or engineering application is difficult due to too high cost and low efficiency is solved.

The utility model discloses an image control point identification device for aerial survey of an unmanned aerial vehicle. The image control point identification device comprises a connecting rod, a plurality of plug pin bodies are hinged to the bottom of the circumference of the connecting rod, an identification panel is arranged at the top of the connecting rod, an adjusting mechanism is arranged at the top of the connecting rod, and a limiting mechanism is arranged on the side portion of the adjusting mechanism. And the adjusting mechanism comprises an adjusting rod located below the identification panel, an adjusting groove is formed in the bottom of the adjusting rod, the inner wall of the adjusting groove is in threaded connection with the connecting rod, and a rotating groove is formed in the outer wall of the top of the adjusting rod. The position of the connecting rod can be changed in the inner wall of the adjusting groove, and angle adjustment operation can be performed in cooperation with rotation of the rotating rod in the rotating groove, so that the height of the identification equipment can be adjusted, the indication can be prevented from being shielded by grass and trees, and the effect of ensuring the measurement and control precision of the unmanned aerial vehicle is achieved.

The application discloses a visible light and laser radar aerial survey target, and relates to the field of aerial surveying and mapping, which comprises a transparent box body, a composite corner reflector and an adjustable supporting mechanism. A visible light image control pattern is arranged on the top plate of the transparent box body, and the geometric center of the visible light image control pattern is coaxially locked with the geometric center of the composite corner reflector with multiple symmetrical corner reflection units in the box. Regardless of the change of the ground slope and the angle of the box body, there is no relative displacement, and the systematic registration error caused by the center misalignment due to the two-time layout of the separated target is completely eliminated from the physical structure. The box body is adjusted to be absolutely horizontal through the adjustable supporting mechanism, the visible light image control pattern is guaranteed to be perpendicular to the unmanned aerial vehicle aerial photography optical axis without perspective distortion, the laser signal capture rate is improved through the configuration of the composite corner reflector comprising multiple symmetrical corner reflection units, and the aerial survey precision in mountainous areas is significantly improved.

The invention is entitled Route planning for ground vehicles through unfamiliar terrain. A method is provided for supporting one or more ground vehicles in performing a mission that includes traversing a ground area. The method includes accessing geospatial data generated from an aerial survey of the ground area and performing an analysis of the geospatial data to produce terrain data that describes the ground area. The terrain data is weighted based on constraints of the one or more ground vehicles and a priority order of mission criteria. A map is constructed in which the ground area is represented as a geospatial mapping array of the weighted terrain data, and a path is searched on the map that satisfies the mission criteria. The path is described by a series of waypoints that define a route through the ground area, and the route indication is output for use by the one or more ground vehicles in traversing during the mission.

The invention relates to the crossing field of intelligent agricultural insurance and intelligent agriculture, in particular to a corn planting income insurance double-precision double-reduction technology integrated intelligent system based on space-space-ground multi-source data, which comprises a space-space-ground multi-source data acquisition module, a corn planting income insurance management module, a corn planting income insurance management module and a corn planting income insurance management module, the multi-dimensional data acquisition module is used for acquiring multi-dimensional data such as satellite remote sensing, unmanned aerial vehicle aerial survey fine monitoring, ground Internet of Things intelligent sensing, meteorological monitoring, government affairs and markets in the whole corn planting period; according to the method, according to the CGCS2000 national geodetic coordinate system standard, the space, growth state and environment monitoring of a corn planting area are collected, space-air-ground multi-source data and a DSSAT corn growth model are fused, a standardized data set is output, the variety identification accuracy is larger than or equal to 95%, the planting area underwriting error is smaller than or equal to 2%, the yield prediction accuracy is larger than or equal to 92%, and the method is suitable for large-scale popularization and application. According to the method, yield loss-price fluctuation double risk association is integrated, yield and price data are dynamically updated, the insurance claim settlement efficiency and precision are greatly improved, the pain points of single data and inaccurate accounting of traditional agricultural insurance are solved, and a solid data support is provided for double-precision and double-reduction.