328 results about "Geographic coordinate system" patented technology

The invention discloses an unmanned aerial vehicle target intelligent identification and perception system and method based on deep learning, and relates to the technical field of artificial intelligence, and the method comprises the steps: extracting the importance feature of each target region, calculating a region importance score, generating a target region monitoring plan, and obtaining continuous frame images; an improved YOLOv5 model is adopted, continuous frames of images are input, a bounding box of a suspected target wild animal is output and mapped to an actual geographic coordinate system, and actual position coordinates are obtained; key points of the t-th frame image are detected, coordinates of the key points are extracted, visibility scores and confidence coefficients are calculated, and feature descriptors are formed; performing target detection and key point detection on the (t + 1) th frame of image to obtain actual position coordinates and feature descriptors of candidate targets, performing track matching, updating the actual position coordinates and the feature descriptors of the suspected target wild animals if the actual position coordinates and the feature descriptors are matched, and defining new target animals if the actual position coordinates and the feature descriptors are not matched; counting according to the track matching result to obtain the total number of the target wild animals.

The embodiment of the invention provides a three-dimensional ray drawing method and device, and a curve control point is dynamically generated through precise conversion of a geographic coordinate system and a projection coordinate system in combination with an azimuth angle and an earth surface distance. A curvature correction mechanism based on a curved surface projection model is innovatively designed, the influence of the earth curvature on a ray trajectory is considered, and smooth space trajectory generation is realized through a Bezier curve parameter model. According to the system, the coordinate transformation compensation and spherical projection technology is adopted, accurate mapping of a geodetic coordinate system and a display coordinate system is established, accurate rendering of a three-dimensional space curve under different scales and view angles is ensured, and a high-precision technical scheme is provided for geographic information visualization. According to the method, the limitation of traditional straight line drawing is broken through, and the real trajectory expression considering the earth curvature is realized.

The embodiment of the invention discloses an agricultural vehicle positioning method and device, electronic equipment and a storage medium, and the method comprises the steps: determining the posture, position and speed of an agricultural vehicle under a geographic coordinate system according to inertial navigation data obtained by an inertial navigation system; establishing an initial observation equation according to a satellite observation equation corresponding to a global satellite positioning system and a visual observation equation corresponding to a visual sensor; when it is detected that satellite data collected by a global satellite positioning system is valid, the initial observation equation serves as a target observation equation; when it is detected that the satellite data collected by the global satellite positioning system is invalid, the initial observation equation with the satellite observation equations removed serves as a target observation equation; the current error state quantity of the inertial navigation system is corrected according to the target observation equation, and the attitude, position and speed of the agricultural vehicle are corrected according to the updated error state quantity, so that the actual positioning information of the agricultural vehicle is obtained, and the robustness of the positioning result of the agricultural vehicle is improved.

The invention discloses a personnel trajectory low-delay accurate positioning method based on safety production monitoring, and relates to the field of industrial safety monitoring, and the method comprises the steps: obtaining signal data based on UWB anchor points, obtaining distance data through a laser range finder, and obtaining image data through a thermal imaging camera; establishing a three-dimensional geographic coordinate system based on the geographic space of the production workshop; extracting scene features of a production workshop, and constructing a virtual workshop; through timestamp alignment, consistent signal data, consistent distance data and consistent image data are obtained; calculating multi-dimensional positioning data through confidence evaluation; calculating scene feature weights; the multi-dimensional positioning data and the scene feature weight are imported into a virtual workshop, the virtual workshop performs multi-channel splicing on the multi-dimensional positioning data and the scene feature weight, and a positioning model is constructed; and obtaining positioning data. The method has the advantages that through multi-source heterogeneous data fusion and scene feature constraint, the positioning robustness in a complex industrial environment is improved.

The invention relates to the technical field of photovoltaic inspection, in particular to an unmanned aerial vehicle photovoltaic inspection positioning method and system based on extended Kalman filtering, and the method comprises the steps: obtaining the GPS positioning data, attitude data and photovoltaic panel image data of an unmanned aerial vehicle in real time based on a sensor carried by the unmanned aerial vehicle; according to the image data of the photovoltaic panel, fault features of the fault photovoltaic panel are identified, and pixel coordinates of the fault photovoltaic panel are extracted; converting the pixel coordinates of the fault photovoltaic panel into initial position information under a geographic coordinate system; constructing an extended Kalman filtering model, inputting the positioning data, attitude data and initial position information of the unmanned aerial vehicle into the extended Kalman filtering model, and establishing a state vector and an observation vector; and iteratively calculating an optimal estimation value through an extended Kalman filtering algorithm according to the state vector, and outputting geographic coordinates of the fault photovoltaic panel. According to the invention, the method achieves the quick and precise positioning of the fault photovoltaic panel, improves the operation and maintenance efficiency of a photovoltaic power station, and reduces the operation and maintenance cost.

The invention relates to a transplanting position quality evaluation method based on image analysis and geometric modeling, in particular to a transplanting position quality evaluation method based on image analysis and geometric modeling. The invention aims to solve the problems of low precision, single evaluation index and lack of space positioning capability of the existing unmanned aerial vehicle remote sensing image rice transplanting position estimation. The method comprises the steps that S1, an unmanned aerial vehicle collects an RGB image data set of unmarked farmland seedling positions; s2, obtaining an RGB image data set marked with farmland seedling positions; s3, obtaining a pre-trained encoder; s4, obtaining a trained farmland rice seedling target detection model; s5, inputting to-be-detected RGB image data into the trained farmland rice seedling target detection model, and outputting farmland seedling positions in the to-be-detected RGB image data; s6, obtaining the transplanting spacing, judging whether seedlings are missing or not, and if not, ending; if not, estimating a seedling missing position; s7, the seedling missing position in the step S6 is converted into a geographic coordinate system. The method is used in the field of transplanting position estimation.

The invention relates to the technical field of unmanned aerial vehicle path planning and electromagnetic environment perception, provides an unmanned aerial vehicle path planning method and system based on a multi-frequency electromagnetic map, and aims to improve the navigation capability of an unmanned aerial vehicle in a complex electromagnetic environment and improve the task execution safety and communication reliability. The method comprises the following steps of: firstly, acquiring geographic information of a target area through GMTED2010 to carry out grid division on the area, and establishing a standardized geographic coordinate system; then, forming a three-dimensional signal to interference plus noise ratio array, extracting two-dimensional slice data through a fixed frequency dimension, and establishing a geographic space mapping relation; then, the signal to interference plus noise ratio is visualized in combination with an RGB color space, a signal to interference plus noise ratio threshold value is set according to communication requirements, a non-flying area is delimited, and finally a multi-frequency signal to interference plus noise ratio feasible region map is generated. The search weight is adjusted through an optimization algorithm, so that the path can avoid a strong interference area; the flight path is optimized by deleting redundant path points, and it is ensured that the unmanned aerial vehicle has the more efficient and stable navigation capacity.

The invention provides an AR positioning and direction correction method and device, equipment and a storage medium, and relates to the technical field of augmented reality, and the method comprises the steps: obtaining a first high-precision positioning point and a second high-precision positioning point, and respectively calculating azimuth angles in a geographic coordinate system and an AR coordinate system; the initial orientation when the device is started is then determined by using the angle difference between the azimuth angles. According to the initial orientation, coordinate orientation rotation can be carried out on three-dimensional scene elements in the AR scene, so that direction correction is completed. By using the high-precision positioning point information, the initial orientation of the equipment can be determined more accurately, so that the accuracy of AR positioning is improved. Moreover, no external auxiliary equipment or infrastructure is needed, and accurate AR positioning and direction correction can be realized only by means of the equipment and known high-precision positioning point information, so that the hardware cost is reduced.

The invention discloses a remote sensing image cloud removal method and system based on geographic coordinate embedding, and the system employs a geographic coordinate system embedding module to encode pixel longitude and latitude information into high-dimensional features, and achieves the joint modeling of an absolute position and a relative space relation through spherical coordinate mapping and a rotation matrix. And in combination with a multi-head self-attention mechanism and residual connection, the position sensitivity of the feature space is enhanced. Meanwhile, by using a multi-level feature extraction network and a cloud distortion compensation module, through a residual block and convolution operation, cloud interference features are extracted, a position sensing correction vector is generated, nonlinear offset of a cloud coverage area is corrected, and earth surface textures are recovered. According to the method, the adaptability of a cross-regional scene is remarkably improved, texture distortion and information loss of a large-scale cloud region are effectively reduced, the method has the advantages of high precision and high robustness in the fields of remote sensing image preprocessing, agricultural monitoring, land cover change analysis and the like, and a new scheme is provided for high-quality application of optical remote sensing data.

The invention relates to the technical field of artificial intelligence, in particular to a video GIS intelligent analysis method based on deep learning, and the method comprises the steps: detecting a target in a video in real time through a predefined target detection model, and generating a space-time mark which comprises a bounding box and category information; thirdly, associating target tracks of different cameras by using a dynamic graph model and a dynamic graph neural network to form a space-time ID and a track chain; then, combining a visual inertial odometer and a geographic information system to calibrate a homography matrix, and mapping the trajectory chain to a geographic coordinate system to obtain space-time trajectory data; then, constructing a neural network model and a trajectory generation model, and respectively predicting crowd density distribution and pedestrian motion trajectories; and finally, carrying out real-time alarm according to the track and the multi-level geo-fencing rule. According to the invention, intelligent analysis of video data is realized, target tracking and alarm capabilities are improved, and the method is widely applicable to the fields of crowd management and safety monitoring.

The invention discloses a boundary grid node-oriented shipborne unmanned aerial vehicle delivery scheduling method and system, and relates to the technical field of shipborne unmanned aerial vehicle path optimization, and the method comprises the steps: carrying out the systematic grid division of a boundary region based on a geographic coordinate system and marine environment constraints, and constructing a boundary grid node set; mapping attribution is carried out based on boundary grid nodes, and path feasibility is evaluated; and according to an evaluation result, screening and scheduling candidate tasks, generating a corresponding time window, constructing an optimal path, and completing dynamic scheduling and path planning of multiple tasks through time, space and platform constraint linkage. By constructing a task space mapping structure, an airspace schedulability scoring mechanism and a path multi-dimensional cost evaluation model, dynamic, efficient and safe scheduling of the shipborne unmanned aerial vehicle in a boundary sea area is realized, the task matching precision, the path feasibility and the system robustness are remarkably improved, and the method has high intelligent cooperation capability and environmental adaptability.

The invention discloses a three-dimensional space modeling method, system and device and a storage medium, and relates to the technical field of digital twinning, and the method comprises the steps: processing the physical space data of a digital twinning display application according to a target hierarchy, and obtaining the hierarchy model data of each target hierarchy; the target hierarchy comprises a city hierarchy, a park hierarchy, a building hierarchy, a floor hierarchy and a room hierarchy; constructing a digital twinborn model for each target hierarchy based on the data structure of the corresponding hierarchy model data; the data structure comprises three-dimensional geometric structure data, shell model data and semantic description metadata; and converting the digital twinborn model from the model coordinate system to a geographic coordinate system, and performing hierarchical storage according to corresponding hierarchies. And each hierarchy can obtain accurate hierarchy model data. The accurate digital twinborn model is constructed based on the data structure of the hierarchical model data of each target hierarchy, so that the characteristics of a physical space are reflected more truly, and the accuracy and practicability of the model are enhanced.

The invention relates to the technical field of building risk monitoring, in particular to an InSAR building scatterer positioning method, device and equipment, a storage medium and a computer program product. According to the method, urban point cloud data is segmented to obtain an urban building monomer instance point cloud set; based on the point cloud set, adopting a surface reconstruction algorithm to construct a building grid model; based on the grid model and the SAR satellite imaging parameters, adopting an SAR simulation technology to identify a radar illuminable vector frame of the building; converting the vector frame from a geographic coordinate system into an SAR image coordinate system, performing bilinear interpolation based on the geographic coordinates of the angular points of the vector frame, and determining the geographic coordinates of the scatterer in the vector frame; and if the scatterer is located in the overlapping region of the plurality of vector frames, performing overlay identification on the pixel points in the vector frames based on the geographic coordinates, determining the unique geographic coordinates, and determining the geographic positioning of the building scatterer in combination with the deformation information of the scatterer, thereby improving the positioning precision of the building scatterer.

The invention provides a dead wood quantity counting and positioning method based on an unmanned aerial vehicle ortho-video. The method comprises the following steps: constructing a data set according to an original video frame of the unmanned aerial vehicle ortho-video and synchronous positioning data; a deep learning model based on a single-stage detection architecture is trained, target detection is performed on frame-by-frame images, basic tracking is realized by detecting an associated multi-target tracker, periodic enhanced detection is performed in combination with a slice detection strategy, a redundant detection frame is eliminated through an overlapping region fusion algorithm, and a high-confidence target detection result is formed; based on a target motion track and space-time continuity analysis, appearance-tracking-loss-recovery period management of a dead wood target is realized; based on the mapping relation between the pixel coordinate system and the geographic coordinate system, the target position is converted into a GPS coordinate in combination with the flight parameters of the unmanned aerial vehicle, and a dead wood statistical result containing the space-time distribution characteristics and geographic positioning information are output.

The invention relates to the technical field of embedded maps, and provides a vector map display method under a VxWorks system, which comprises the following steps: S1, analyzing a vector map source file through an MITAB library, and extracting geometric space topological data, geographic coordinate system parameters, style attributes and projection parameters; s2, constructing a hierarchical storage structure based on SQLite3, and storing vector map information including a spatial data table, a style configuration table and a metadata table into a geographic information database; s3, creating a map display control MapWidget inherited from a QGraphics View class based on a Qt framework, loading the geographic information database through a dynamic configuration interface, and initializing a coordinate system conversion module, a multi-level view window module and a covering management system; and S4, dynamically rendering and outputting an interactive vector map interface through a layer priority scheduling strategy in a VxWorks real-time operating system. Through the design of the cross-platform data middle layer, the extensible general symbology system and the resource efficiency optimization, the data compatibility problem of the embedded system and the commercial GIS software is solved.

The invention provides an unmanned aerial vehicle target identification and positioning method and system based on multispectral fusion. The method comprises the following steps: firstly, acquiring multispectral image data, then analyzing the multispectral image data of multiple time phases into pixel-level data, then identifying an early infection area of the plant diseases and insect pests, then constructing a geometric distortion correction model, and then determining the relative position of the early infection area of the plant diseases and insect pests through multi-view space intersection calculation. And finally, fusing the real-time differential global navigation satellite system positioning data of the unmanned aerial vehicle and the relative position of the disease and insect pest early-stage infection area to output absolute geographic coordinates of the disease and insect pest early-stage infection area. According to the technical scheme provided by the invention, accurate conversion from a local coordinate system to a global geographic coordinate system is realized, an exact spatial position basis is provided for precise agricultural operation, and precise positioning of a pest and disease damage area is realized.

The invention provides a as-built drawing multi-element extraction and vectorization method and device, equipment and a storage medium. Relates to the technical field of as-built drawing processing. The method comprises the following steps: segmenting a as-built drawing to obtain binary mask images of a field parcel, a road, a water channel, a building and a wellhead; performing opening and closing operation, morphological smoothing, noise removal and / or hole filling operation on each binary mask image to generate an optimized single-category mask; dividing the optimized single-category masks into three categories of planar elements, linear elements and point-shaped elements according to geometric types of the elements, and respectively adopting a vectorization strategy to generate vector files; and writing the geographic coordinate system and the projection parameters of the as-built drawing into the corresponding vector file to generate an independent layer file with geographic coordinate reference. According to the method, the as-built drawing element extraction precision, the complex element processing capability and the vectorization quality and efficiency are remarkably improved, and the robustness of the model in a complex scene is enhanced.

The invention relates to the technical field of bionic navigation orientation and positioning, in particular to a carrier course angle measuring method based on polarized light imaging in a non-Rayleigh atmosphere. Comprising the steps of real-time sky polarized light imaging, atmospheric polarization mode resolving based on Mueller matrix imaging, non-Rayleigh polarization information interference removal, polarization orientation resolving based on Rayleigh scattering, space projection conversion and sun position information resolving. Alignment information of the sun in a carrier coordinate system is obtained by utilizing a Rayleigh scattering model and actual sky polarization imaging, and then a carrier course angle is obtained according to the orientation of the sun in a local geographic coordinate system, so that an orientation function is realized; meanwhile, the error influence caused by image registration and time-sharing rotation measurement of the multi-view-field polarization detector and the interference of environmental factors on a single point are avoided, the method can adapt to sunny and cloudy weather, is also applicable to cloudy and other non-Rayleigh weather, and is wide in application range.

The invention discloses a photovoltaic station assembly defect positioning method, device and equipment and a medium, and the method comprises the steps: obtaining the vertex pixel coordinates of a photovoltaic station image and the conversion relation between a photovoltaic station pixel coordinate system and a geographic coordinate system, and calculating the vertex geographic coordinates of a photovoltaic station; determining the station boundary length of the photovoltaic station based on the geographic coordinates of the vertexes, determining the number of photovoltaic station images to be split based on the station boundary length and a preset sub-station boundary length, and splitting the photovoltaic station images to obtain a plurality of photovoltaic station sub-images and the position relationship between each photovoltaic station sub-image and the photovoltaic station images; detecting component defect information in each photovoltaic station subgraph based on a pre-trained component defect detection model; and mapping the component defect information to a geographic coordinate system to obtain a component defect positioning result of the photovoltaic station. Through the technical scheme, the accuracy of a component defect judgment result and the timeliness of defect positioning can be improved.

The invention provides a measurement method of a shipborne three-dimensional scanning wind measurement laser radar, and the method comprises the steps: obtaining the attitude information of a ship through a combined inertial navigation system, and the attitude information comprises a heading angle, a pitching angle and a rolling angle; according to the attitude information and a coordinate transformation model between a preset radar coordinate system and a geographic coordinate system, determining an azimuth angle and a pitch angle of a laser beam of the shipborne three-dimensional scanning wind measurement laser radar in the geographic coordinate system; according to the azimuth angle and the pitch angle, controlling the shipborne three-dimensional scanning wind measurement laser radar to emit a laser beam, and receiving a reflection echo signal; and acquiring three-dimensional velocity component information of the wind field according to the reflection echo signal to obtain a three-dimensional wind field.

The invention discloses a high-precision map construction method and a related device, and relates to the technical field of automatic driving. The high-precision map construction method comprises the steps that image data representing the surrounding road environment of a vehicle is obtained, a semantic topology network diagram containing nodes and associated edges is constructed based on the image data, the nodes are information units which are extracted from the surrounding road environment of the vehicle and carry semantic and spatial features, and the associated edges are associated with the nodes. The associated edge represents a node relationship of spatial and semantic dimensions between the nodes. Then determining a target anchor point meeting a space reference condition from the semantic topology network diagram, then mapping the target anchor point to a geographic coordinate system in combination with the real-time pose of the vehicle, and finally determining the spatial position of each node according to the relationship between the target anchor point and the node in the geographic coordinate system so as to generate a high-precision map. Finally, real-time and accurate road environment structured information is provided for automatic driving, and safe and efficient driving of the automatic driving vehicle is guaranteed.

The invention relates to a multi-modal-based tower crane construction process object pose detection method and device, and belongs to the technical field of multi-modal data fusion, and the method comprises the steps: obtaining the spatial position information of goods hoisted by a tower crane in real time through an RTK positioning system; based on a label detection function of a monocular camera, obtaining space attitude and position information of the hoisted goods in a camera coordinate system; unifying the geographic coordinate system information and the camera coordinate system information; the space position information of the cargo hoisted by the tower crane and the position information in the camera coordinate system are fused to generate object space position information of the hoisted cargo; and according to the spatial position information of the object, a 3D animation model of the hoisted goods and 6D position and posture information under a preset coordinate system are generated, and the moving track and posture change of the goods in the tower crane construction process are displayed in real time. According to the invention, high-precision and stable acquisition of the position information and the posture of the cargo is realized, and the hoisting process of the cargo is dynamically displayed in a visual mode of 3D animation.

The invention discloses a bridge differential settlement assessment method based on an SAR image. The method comprises the following steps: step 1, carrying out Lee filtering processing on a high-resolution No.3 data original image; 2, geocoding the SAR data by using the SRTM DEM data as reference data, and converting the SAR data from a radar coordinate system to a geographic coordinate system; 3, bridge extraction is carried out according to data processing results in the step 1 and the step 2; 4, performing differential settlement monitoring according to a bridge extraction result; and step 5, performing differential settlement evaluation. According to the invention, comprehensive and efficient monitoring of the bridge is realized, limitations of a traditional monitoring method and other image monitoring technologies are overcome, and tiny changes and potential safety hazards of the bridge structure can be found in time. Scientific basis is provided for maintenance and reinforcement of the bridge, decision makers are helped to take effective measures in time, safe operation of the bridge is guaranteed, the risk of safety accidents is reduced, and remarkable economic and social benefits are achieved.

The invention discloses a picture-based power grid facility ledger extraction method and system capable of defining a range, and belongs to the technical field of image processing, and the method comprises the steps: carrying out the picture boundary cutting of a meteorological picture to match a map region; registering the meteorological picture with a map geographic coordinate system to form a longitude and latitude-pixel registration dictionary; the method comprises the following steps: defining and drawing a polygonal region on a meteorological picture to specify a range for extracting power grid facility information, and determining a judgment region by describing a vertex of a polygon to realize extraction of pixel coordinates in a self-defined polygonal range in the meteorological picture; pixel coordinates in the self-defined polygon range in the extracted meteorological picture are converted into corresponding actual longitudes and latitudes through the longitude and latitude-pixel registration dictionary; and extracting and summarizing the power grid facility information in the set range of the geographic coordinates according to the actual longitude and latitude to form a ledger for exporting the power grid facility information. The purpose of quickly and accurately extracting the power grid facility information ledger in the self-defined area from the meteorological picture is achieved.

The invention provides a GIS-based intelligent livestock breeding full-chain visualization method and system, and the method comprises the steps: collecting the basic information of a farm, livestock information, production process data and other multi-source data through a standardized data interface, and carrying out the correlation mapping of business data and GIS spatial data based on a geographic coordinate system; constructing a three-dimensional data model containing spatial information, attribute information and relation information; three-dimensional scene rendering is realized by utilizing a WebGL technology, a macroscopic visual engine, a mesoscopic visual engine and a microcosmic visual engine are constructed, and multi-scale visual display is realized; constructing a full-life-cycle data model of the livestock products, and realizing visual display of full-chain traceability of the livestock products; based on a visual data analysis method, a decision support system for industrial layout analysis, breeding scale prediction, epidemic disease risk assessment and market supply and demand analysis is constructed. Visual management of the whole industry chain of livestock breeding is achieved, the industry management efficiency is improved, the epidemic disease risk prevention and control capacity is enhanced, and data support is provided for decision making of the livestock industry.

The invention belongs to the technical field of automatic control, and particularly relates to a memory tracking method for a two-axis photoelectric holder. The method comprises the following steps: S1, fixing a two-axis photoelectric holder on a carrier; s2, performing stable tracking on the tracking target by adopting a stable tracking mode, and calculating the movement speed # imgabs0 # of the tracking target under the geographic coordinate system; s3, judging whether the tracked target is in a shielded state in the tracking process of the two-axis photoelectric holder, if so, executing the step S4, and otherwise, executing the step S5; s4, the azimuth guide angular rate and the pitching guide angular rate of the two-axis photoelectric holder are solved reversely, and memory tracking of the tracking target is achieved until the visual axis of the two-axis photoelectric holder points to the tracking target again; and S5, judging whether the tracking task continues to be executed or not, if so, executing the step S2, and otherwise, ending the tracking task for the tracking target. According to the invention, memory tracking is carried out when the tracking target is lost, so that the target can be automatically captured and re-tracked when the tracking target appears again.

The invention discloses a high-precision target positioning method based on distortion calibration and a matched DEM, and the method comprises the steps: S1, enabling a camera to be installed on an unmanned plane platform, enabling a whole imaging system and a carrier platform to serve as a system for testing, carrying out the indoor preliminary statistical calibration, and determining the distortion rate of each pixel point; s2, establishing a conversion relation from an image coordinate system to a geographic coordinate system, and performing coordinate conversion and calculation on a camera field angle, a focal length and resolution content and a ground shooting field range; s3, transforming the relation of the unmanned aerial vehicle, the camera and the image; s4, loading elevation DEM data based on latitude and longitude information, and determining the elevation of the target point; s5, performing statistical analysis on the system error by combining outdoor calibration, and solving the system error compensation amount increased in the longitude and latitude process; and S6, obtaining high-precision position information of the target based on the steps S3, S4 and S5. According to the method, the target positioning difficulty can be greatly reduced, and the effects of reducing the holder load, reducing the cost and reducing the operation difficulty are achieved by fully utilizing the internal reference of the camera and the DEM data.

The invention relates to the technical field of image processing, in particular to a cultivated land monitoring method and system based on an unmanned aerial vehicle. The method comprises the following steps: obtaining adjacent key image frames of unmanned aerial vehicle video data, and splicing the adjacent key image frames to obtain a panoramic image; performing panoramic segmentation on the panoramic image and obtaining masks reflecting different types of cultivated land through an SEEM model; and extracting the contour of the mask, converting the extracted contour into coordinates in a geographic coordinate system, and mapping each coordinate point with the land category to which the coordinate point belongs. According to the application, farmland monitoring can be carried out by using the aerial image of the unmanned aerial vehicle, the farmland is monitored in real time, meanwhile, image processing is carried out by using the panoramic image splicing technology and the SEEM model, a wider view can be obtained, the limitation of a single image is eliminated, and refined management of the farmland is realized.

The present invention provides a method for extracting features of the nearshore wave breaking process based on time series video images; wherein, the method comprises: setting at least one pixel sampling area in a plane geographic coordinate system, collecting time series video images of ocean nearshore waves, quickly converting them into plane geographic coordinate images through a coordinate model, and then stacking cross-shore pixel values ​​of several pixel sampling areas within a set time to generate a cross-shore pixel value and time relationship sequence diagram, mining the time-varying signal of the wave propagating toward the shore, combining the geometric relationship between the camera angle of view and the plane projection of the wave breaking, and calculating key wave breaking features such as the wave breaking point position, wave breaking water depth, and wave breaking height; the method can continuously monitor the nearshore wave breaking features efficiently, automatically, and stably, effectively making up for the shortcomings of traditional monitoring and analysis methods, and providing strong technical support for the refined research and management of nearshore beach dynamic landforms.

The invention discloses a loess collapsibility evaluation method and system based on a geophysical prospecting test technology, and relates to the field of land exploration, and the method comprises the steps: laying regular detection grids in a to-be-evaluated loess site, and constructing a site geographic coordinate system; collecting Rayleigh wave signals in real time, inverting a transverse wave velocity profile, and collecting apparent resistivity data; a shallow soil sample is drilled, soil property parameters are measured, and a model is constructed according to the mapping relation between the field geophysical prospecting parameters and the soil property parameters; inputting the acquired data into the wave velocity-water content correlation model and the resistivity-dry density correlation model to generate a water content distribution field and a dry density distribution field; and calculating the collapsibility of loess in each detection grid based on a geophysical prospecting response equation of the collapsibility coefficient, outputting a collapsibility coefficient contour cloud picture, and judging the collapsibility grade of each grid and the distribution range of collapsed loess. The method has the advantages that the collapsibility distribution field and the contour cloud picture are generated through accurate non-intrusive data acquisition and model analysis, and a scientific basis is provided for engineering construction.