339 results about "Aerial survey" patented technology

Methods, systems and apparatus, including computer programs encoded on computer storage media for unmanned aerial vehicle flight for performing an inspection of land, property, structures or other objects. Automated aerial surveys allow a UAV to obtain aerial data without human manual control of a UAV. For certain aerial surveys, a UAV is not capable of completing the survey without refueling, or exchanging out used batteries for fresh batteries. For such aerial surveys, a method and system is needed to allow an operator to automatically perform an aerial survey while determining battery usage and replacement. Also, in circumstances where manual control of the UAV is needed, contingency-based software controls may be needed.

The invention discloses a regional risk monitoring and early warning system based on space-air-ground multi-source data fusion, and relates to the technical field of disaster monitoring and early warning. According to the invention, comprehensive monitoring of regional risks is realized by fusing various data sources such as satellite remote sensing, unmanned aerial vehicle aerial survey and ground-based radar. The system can automatically process data, construct a high-precision three-dimensional real scene model, and identify a potential risk area based on a time sequence InSAR technology and a multi-source data fusion technology. And meanwhile, non-contact high-precision measurement is carried out on key facilities. An interactive monitoring and early warning platform is constructed, functions of deformation graph generation, target detection and risk division, data fusion processing, potential risk surface determination, stress-strain analysis and early warning information release are realized, and support is provided for regional risk prevention. The system has the characteristics of high automation, intelligence and visualization, and is suitable for various application scenes such as earthquakes, floods, landslides and the like.

The invention provides a geographic information visualization intelligent analysis system based on unmanned aerial vehicle surveying and mapping, and belongs to the field of surveying and mapping, and the system comprises an unmanned aerial vehicle aerial survey module which carries out regional aerial survey based on a multi-source sensor carried by an unmanned aerial vehicle, obtains multi-modal geographic data, and carries out the preprocessing of the multi-modal geographic data; the data processing module is used for forming an initial geographic data set under a standard coordinate system; the three-dimensional modeling module is used for obtaining the fused geographic feature data, constructing a three-dimensional geographic information model, optimizing the three-dimensional geographic information model and embedding time dimension information to form a four-dimensional spatio-temporal data set; the analysis and decision module is used for generating an analysis report comprising a terrain evolution trend and disaster risk assessment; and the visual platform module is used for visualizing the analysis report through a preset visual interaction interface and adjusting the rendering precision of the optimized three-dimensional geographic information model in real time according to the change of the visual angle of the user. The system provides an efficient and intelligent solution for geographic surveying and mapping and disaster early warning.

The invention provides an unmanned aerial vehicle route layout method and device for complex terrains, equipment and a medium, and relates to the technical field of unmanned aerial vehicle aerial photogrammetry. The method comprises the following steps: carrying out preliminary region division on a terrain region to be surveyed, and determining a plurality of region units; clustering the area units according to topographic observation data to obtain survey sub-areas; determining a survey priority corresponding to each survey sub-region, and matching a basic flight route corresponding to the unmanned aerial vehicle according to the survey priority; and splicing the different types of basic flight routes corresponding to the survey sub-regions, and performing optimization adjustment on the spliced basic flight routes to obtain a flight route of the target unmanned aerial vehicle so as to perform topographic survey on the topographic region to be surveyed. According to the technical scheme, the route planning of the unmanned aerial vehicle can adapt to various types of landform features, and the safety and aerial survey efficiency of the unmanned aerial vehicle are ensured while the integrity and accuracy of aerial survey data are improved.

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 provides a refuse landfill methane emission monitoring method and system for air-ground combined monitoring, ground sampling points are selected by combining topographic features, possible emission hot spot areas and historical operation information of a refuse landfill, and areas which are difficult to reach by ground sampling can be realized through aerial survey air sampling; by integrating ground sampling and aerial survey, high-resolution methane concentration data can be obtained, and meanwhile interference of flowing wind on hot spot area recognition is reduced; by combining ground surface sampling data and aerial survey data, a Getis-Ord Gi * statistical method and a nuclear density estimation method are adopted to carry out bimodal hot spot area identification, a methane emission source area can be positioned more accurately, the precision and efficiency of methane emission monitoring of the refuse landfill are remarkably improved, and the method is suitable for popularization and application. The methane emission source of the refuse landfill is accurately and efficiently found, the emission amount of the methane emission source is evaluated, targeted suggestions are provided for operation of the landfill, and the method has important environmental protection and economic values.

The invention relates to a mangrove forest vegetation carbon sink monitoring and metering method based on an unmanned aerial vehicle and an AI technology, and the method comprises the steps: constructing a mangrove forest recognition model of a U-Net improved model based on a PyTorch deep learning framework through the unmanned aerial vehicle AI technology, achieving the intelligent recognition and discrimination of various mangrove forest vegetations, and the area and number of regions thereof, and achieving the accuracy of 90% or above; through regular aerial photography monitoring of an unmanned aerial vehicle, in combination with growth parameters measured on site and variable parameters derived from aerial photography data of the unmanned aerial vehicle, an optimal fitting model of mangrove forest height crown breadth, overground biomass and unit leaf area based on aerial survey of the unmanned aerial vehicle is constructed, and the carbon reserve and carbon sequestration amount of mangrove forest region vegetation are accurately calculated. And comprehensively evaluating the mangrove forest carbon sequestration capability in the monitoring area. According to the application, intelligent, digital and comprehensive monitoring and evaluation of the mangrove forest wetland vegetation carbon sequestration capability are realized.

The invention discloses an air-ground integrated measurement method for an original terrain, and relates to the technical field of engineering surveying, and the method comprises the steps: S1, carrying multi-sensor aerial survey by an unmanned aerial vehicle, obtaining an image and POS positioning data, scanning a blind area of the unmanned aerial vehicle by using a three-dimensional laser scanner, obtaining laser point cloud data, and carrying out the scanning of the laser point cloud data; constructing a multi-source data set including optical images, POS positioning data and laser point cloud, and forming an air-ground complementary data acquisition mode; s2, geometric correction and aerial triangulation encryption are carried out on the unmanned aerial vehicle image, denoising and multi-station registration are carried out on the laser point cloud data, and the data quality is improved; s3, unifying a multi-source data space reference through coordinate system unification, feature fusion and decision-level fusion, and realizing feature complementation; s4, constructing a digital elevation model and a digital surface model based on the fused data, and generating a topographic mapping map; the method breaks through the limitation of a single technology through air-ground technology complementation, and ensures the global data coverage of complex terrains.

The invention discloses a geological mineral exploration data extraction method and system, and relates to the technical field of geological mineral exploration data extraction, and the method comprises the steps: carrying out the data collection of a target region through a multi-source data collection method, obtaining satellite remote sensing data, unmanned aerial vehicle aerial survey data and ground geophysical prospecting data, and obtaining an original data set; preprocessing the collected data by adopting a preliminary data processing method, removing noise and correcting errors to obtain a high-quality data set; integrating data from different sources in the high-quality data set by adopting a weighted fusion algorithm to generate a comprehensive database and obtain a comprehensive data set; performing high-resolution geophysical exploration on the fused comprehensive data set by adopting a geophysical exploration technology to obtain underground structure information; analyzing the exploration data by adopting a geophysical inversion technology, and identifying the position of a potential ore body to obtain an ore body distribution map; the method is based on the comprehensive data set, underground structure information and the ore body distribution diagram.

Disclosed in the present invention are a multi-source aviation remote sensing data acquisition apparatus, system and control method, which are applied to the technical field of aerial survey remote sensing. The apparatus comprises: a flight platform and an airborne device disposed on the flight platform. The airborne device comprises: a multi-sensor ultra-compact integrated device, an airborne integrated synchronization control device, and a GNSS receiving antenna. The multi-sensor ultra-compact integrated device and the airborne integrated synchronization control device are connected by means of cables, and the GNSS receiving antenna is disposed on an upper end face of the flight platform. The multi-sensor ultra-compact integrated device is used for acquiring multi-source remote sensing data; and the airborne integrated synchronization control device is used for controlling the operation of the multi-sensor ultra-compact integrated device. The present invention ultra-compactly integrates a LiDAR, a hyperspectral camera, a thermal infrared camera, and a visible-light camera on the basis of a high-precision inertial navigation system, and achieves efficient synchronous acquisition of texture, spectral, temperature, and geometric information by means of using an integrated control subsystem.

The invention relates to a landslide motion analysis method based on unmanned aerial vehicle remote sensing aerial survey and three-dimensional geological modeling, which comprises the following steps: acquiring high-resolution topographic data of a landslide hidden danger area by utilizing a laser scanner technology carried by an unmanned aerial vehicle, and calculating landslide instability failure ranges and stability coefficients under different scenes by utilizing finite element Geostudio software; and taking the stability coefficient as a reduction coefficient of a rock-soil body strength parameter, then determining the rock-soil body strength parameter under different scenes in discrete element PFC software, and realizing three-dimensional failure motion process analysis of the landslide under different scenes by using discrete elements. According to the invention, through PFC software, landslide occurrence scales under different rainfall and earthquake scenes and motion characteristics of landslides of different scales after instability can be compared; large deformation under the fluid-solid coupling condition can be effectively simulated, rock-soil body strength parameters under different rainfall (or earthquake) scenes can be determined, and the landslide three-dimensional motion process under different scenes can be carried out.

The invention discloses a high-precision earthwork measurement and calculation method and system for constructing a three-dimensional model based on aerial survey of an unmanned aerial vehicle. The method comprises the steps that image control points and check points are arranged in a to-be-measured area in advance; starting to collect aerial survey image data of the unmanned aerial vehicle, and performing supplementary measurement on an obstacle shielding area to obtain supplementary measurement data; importing the aerial survey image data to generate a live-action three-dimensional model; and finding an image control point identification position on the three-dimensional model, performing corresponding point pricking on the image control point identification position and an actually measured image control point, performing conversion from longitude and latitude coordinates of the model to project coordinates after all the image control points are matched, regenerating the three-dimensional model, importing check point coordinate data, and checking the precision of the model. Seed points are added to remove obstacles to restore the surface topography, then drawings and design elevations are imported to carry out earthwork high-precision calculation, the problems that manual calculation combined with other software is complex in operation and prone to making mistakes and consumes a large amount of time are solved, accurate data support is provided for earthwork construction, and the project construction period is shortened.

The invention belongs to the technical field of hydraulic engineering measurement, and discloses a seawall measurement method and system based on multi-source data fusion, and the method comprises the steps: collecting geological data and hydrological data through a data collection module; the route planning module formulates a route; the overwater data acquisition equipment and the underwater data acquisition equipment are used for monitoring; the auxiliary equipment provides a high-precision positioning reference; the meteorological data module obtains meteorological data; the data processing module processes the data; the three-dimensional modeling module carries out point cloud registration and DEM model construction; the comprehensive analysis module performs comprehensive evaluation and predicts potential problems and risks; when an abnormal condition or a potential risk is monitored, the early warning module gives an alarm. Multi-source data acquisition equipment such as unmanned aerial vehicle aerial survey, a laser radar, a multi-beam depth finder, a side-scan sonar, a shallow profiler and a micro-motion exploration instrument are integrated, seawall overwater and underwater full-dimensional data acquisition, processing, modeling and volume calculation are realized, and high precision and reliability of measurement results are ensured.

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 relates to the technical field of ecological restoration and carbon sink evaluation, and discloses a river and lake ecological buffer zone carbon sink potential evaluation and restoration construction system which comprises a carbon sink potential evaluation module, an intelligent restoration construction module and a collaborative verification module. The carbon sink potential evaluation module is used for collecting soil and vegetation data and calculating the carbon sink potential; the intelligent restoration construction module executes ecological restoration based on a carbon sink potential evaluation result; and the collaborative verification module verifies the repair effect through multi-source data fusion, and returns an optimization instruction to the carbon sink potential evaluation module and the intelligent repair construction module. The vegetation coverage index and the root biomass density are acquired by using a multispectral sensor array, a carbon sink model is constructed by combining the organic carbon content of soil, dynamic weight adjustment is introduced, and the weight is updated according to aerial survey data of an unmanned aerial vehicle in each quarter, so that a more accurate and more economical carbon sink potential evaluation basis can be provided for ecological restoration, and the ecological restoration efficiency is improved. And resource waste and invalid repair are avoided.

The invention provides a dam slope monitoring method and system based on radar interference and aerial survey data, and relates to the technical field of deformation measurement. The method comprises the following steps: acquiring radar interference measurement data of a target dam slope area, and carrying out multi-temporal registration and phase difference processing to obtain displacement time sequence data; determining displacement change data based on the displacement time sequence data, and determining a first risk area according to the displacement change data; controlling the flight platform to collect aerial survey data of the first risk area; performing feature extraction on the image data to obtain an image structure feature map, and performing terrain gridding modeling and curvature calculation on the point cloud data to obtain a terrain curvature distribution map; performing coordinate alignment on the image structure feature map and the terrain curvature distribution map to obtain a combined feature map; and determining a risk scoring value by using the risk scoring function, and determining a second risk area based on the risk scoring value. According to the scheme, the accuracy of dam slope anomaly recognition can be improved while the monitoring coverage is ensured.

The invention belongs to the technical field of agricultural condition monitoring, and particularly relates to an unmanned aerial vehicle agricultural condition monitoring aerial survey method based on space sampling optimization, which comprises the following steps: constructing a digital farmland base model, and dividing minimum agricultural units with independent agricultural attributes; the number of sampling points of each unit is calculated based on a sampling model, Monte Carlo random sampling is executed, abnormal points are eliminated in combination with a space coordinate verification mechanism, and dynamic sampling planning is achieved; generating an intelligent route by adopting a traveling salesman problem optimization algorithm; the aerial survey task is automatically controlled by calculating the flight height; and dynamically adjusting the sampling density according to the crop growth heterogeneity coefficient to obtain the agricultural condition information of the minimum agricultural unit, and integrally generating a plot-level monitoring report. According to the unmanned aerial vehicle agricultural condition monitoring aerial survey method based on space sampling optimization, the efficiency and precision of farmland monitoring can be remarkably improved through the collaborative design of the multi-target ant colony algorithm optimization air route and the dynamic stratified sampling mechanism, and accurate decision support is provided for farmland management.

A method of performing an adaptive aerial survey includes capturing images of a target area, by at least one camera system disposed on an aerial vehicle, as the aerial vehicle travels along a flight map that includes a plurality of flight lines. The method also includes determining coverage of the target area based on the images captured by the at least one camera system, and adjusting at least one of the flight map and an orientation of the at least one camera system based on the coverage of the target area determined based on the images captured by the at least one camera system. The method can be performed by a control system including circuitry to perform the above steps.

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 agricultural automatic driving, in particular to a coarse-to-fine agricultural aerial survey path generation method and system. The method comprises the following steps: acquiring an orthographic aerial survey image generated by aerial survey of an unmanned aerial vehicle; carrying out image segmentation on the obtained orthographic aerial survey image, and carrying out crude extraction to obtain an operable area and a crop area; according to different operation types, an operation path and a transportation path are planned in the workable area; and the operation path and the transportation path are input into the agricultural robot, and full-autonomous operation is achieved. The method is extremely high in efficiency, and is very suitable for unmanned vehicle operation deployment in orchards or farmlands with ultra-large planting areas.

The invention relates to a railway electronic map generation method, which comprises the following steps: firstly, determining an aerial survey area and finding out a no-fly range, and then selecting an unmanned aerial vehicle take-off and landing point through field investigation and verifying image quality. In the course planning stage, it is ensured that the image overlapping rate meets the high-precision requirement. Performing aerial survey by using the unmanned aerial vehicle, and acquiring detailed geographic information of the railway yard; the accurate selection and collection of the control points further improve the accuracy of the map. And finally, based on the aerial survey data and the control point data, generating a high-quality railway electronic map. The method has the advantages of high efficiency, high precision, high flexibility and the like.

The invention discloses a large prefabricated part critical dimension detection method and device, electronic equipment and a storage medium. The method comprises the steps that S1, a prefabricated part BIM model is constructed based on the BIM technology; s2, a factory processing stage: constructing a millimeter-level point cloud model of the prefabricated part according to the prefabricated part BIM model, the unmanned aerial vehicle and the three-dimensional laser scanner, and carrying out prefabricated part inspection and key size precision detection; and S3, in a field installation stage, an overall centimeter-level and prefabricated part millimeter-level construction site large-scene live-action three-dimensional model and a BIM + GIS fusion platform are constructed through an unmanned aerial vehicle and a three-dimensional laser scanner to realize automatic detection of key size precision in the field installation stage, and it is ensured that acceptance specification requirements are met. According to the method, the BIM, the unmanned aerial vehicle aerial survey technology and the three-dimensional laser scanning technology are subjected to advantage complementation, so that the detection efficiency and the detection precision of the large workpiece are improved, and the situation that the prefabricated part is returned to a factory for the second time and the field installation positioning precision is low is prevented.

The invention relates to the field of aerial survey, and discloses a three-dimensional reconstruction method and device for incremental sub-scene merging and a medium, and the method comprises the steps: obtaining an initial overall scene graph G of an aerial survey image of an unmanned aerial vehicle, and segmenting the initial overall scene graph G into sub-graphs Gs of different sub-scenes; expanding the sub-scenes by using a maximum clique, and increasing the number of common connection points of the sub-scenes to obtain expanded sub-scenes; for the expanded sub-scenes, starting from the angle of the optimized gradient direction of the co-overlapping image camera parameters among different sub-scenes, calculating the consistency of the optimized gradient direction of the overlapping image camera parameters; performing incremental sub-scene combination according to the consistency of the optimized gradient direction to obtain a final live-action three-dimensional model; according to the method, high-precision merging of the sub-scenes is realized, accumulative errors occurring in the sub-scene merging process can be reduced, the precision of the final merging model is ensured, and high-precision data support is provided for unmanned aerial vehicle image three-dimensional reconstruction and live-action three-dimensional model application.

The invention relates to the technical field of ecological protection, in particular to an ecological protection red line basic survey method based on territorial space planning, which comprises the following steps of: acquiring data including satellite remote sensing, unmanned aerial vehicle aerial survey, ground sensors and the like; and high-precision spatial data of ecological elements such as vegetation coverage, surface water distribution and soil erosion intensity are obtained. And combining spatial-temporal feature matching and an improved spatial clustering algorithm to dynamically partition the ecological factors to generate a dynamic partition map of the ecological factors. Based on the graph, a three-dimensional ecological sensitivity evaluation model is constructed, and a dynamic threshold adjustment algorithm is adopted to carry out automatic optimization of the red line boundary. And finally, through multi-dimensional verification and evaluation of natural ecological stability, regional economic bearing degree, social acceptance and the like, generating a final ecological protection red line scheme. According to the method, the adaptability and flexibility of red line delimiting are improved, and the method can be widely applied to the fields of ecological protection, territorial space planning, environment management and the like.

The invention discloses a water-land integrated all-terrain DEM surveying method and system based on UAV-USV-GIS, and belongs to the field of terrain surveying. The method comprises the steps of determining a research area range, planning an unmanned aerial vehicle route, and laying image control points; performing aerial survey on the planned route by using an unmanned aerial vehicle to obtain ground point cloud data and images, and respectively processing the ground point cloud data and images into a land DEM and an orthoimage; the boundaries of the subsidence water area are extracted through the orthoimages, the measurement route of the unmanned ship is planned, and underwater topographic data are measured; processing the underwater topographic data, generating a water area DEM, uniformly selecting inspection points by using RTK and sounding equipment to carry out sampling measurement on the underwater elevation, and verifying the accuracy of the water area DEM underwater topographic data; and fusing the land DEM and the water area DEM to generate a complete water-land integrated all-terrain DEM. The technical bottlenecks that the efficiency is low, the data at the junction of water and land is not accurate, and only the elevation data of a single area of the land or the water can be obtained in the subsidence water area terrain modeling by a traditional single measurement means are effectively solved.

The invention relates to the field of unmanned aerial vehicle aerial survey, and particularly discloses a regional geology and landform processing method based on unmanned aerial vehicle aerial survey, and the method comprises the following steps: S1, carrying out the preliminary division of the geology and landform of a to-be-measured region through intelligent region planning, and forming a plurality of basic grids; s2, intelligently and dynamically adjusting the size of the grid; S2, performing terrain complexity evaluation: performing terrain complexity evaluation on each position in the to-be-detected region by using a terrain complexity evaluation function; s22, dynamically adjusting the size of the grid; through intelligent area planning and dynamic grid adjustment, the method can reasonably allocate aerial survey resources according to actual conditions, and in a complex or key area, grid division is finer so as to ensure high density and precision of data; and in a flat or secondary area, the grids are relatively sparse so as to improve the overall efficiency of aerial survey, and the dynamic adjustment mode avoids unnecessary repeated shooting and resource waste.

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.