1119 results about "Topography" patented technology

The invention relates to the technical field of flood early warning, and discloses an urban flood disaster early warning method and system based on artificial intelligence, and the method comprises the steps: collecting five types of information, i.e., meteorological perception, hydrological monitoring, geographic space, urban operation and social perception in real time, and obtaining multi-source data with precise space-time coordinates; through preprocessing, gridding space-time alignment and key feature screening, rainfall accumulation and confluence evolution related features are extracted; constructing a physically constrained space-time fusion deep learning model, and outputting a future ponding depth prediction result in combination with a multi-head attention mechanism; environmental changes such as urban terrains and drainage facilities are adapted through incremental updating and transfer learning; and fusing the ponding depth, the influence range and the regional vulnerability characteristics to generate multi-level early warning, and synchronously outputting a spatial distribution map, a time evolution trend and affected object evaluation information. According to the invention, urban flood control and disaster reduction decision making and public accurate risk avoiding can be effectively supported.

The invention relates to the technical field of aircraft structure detection, and discloses an aircraft structure crack intelligent identification method based on deep learning. The method comprises the following steps: acquiring original vibration response signals and electromagnetic field distribution data on the surface and inside of an aircraft structure in parallel through a multi-source sensor network; synchronously processing the data by using a multi-scale convolutional neural network, and extracting time-frequency domain abnormal fluctuation features and space magnetic field distortion features; constructing a cross-modal correlation model, analyzing a topological dependency relationship of the two types of features through a graph attention mechanism, and generating a fused damage sensitive feature vector; inputting the vector into a pre-trained deep belief network to obtain a probability distribution mapping relation for different crack types; and according to the mapping relation, carrying out adaptive weighted fusion on original multi-sensor data, inhibiting environmental noise and structural background interference, and separating and reconstructing an accurate three-dimensional morphology map of the target crack. According to the method, multi-source data information can be effectively fused to improve the accuracy of aircraft structure crack identification.

The invention discloses a road slope modeling method based on an unmanned aerial vehicle inspection route, and relates to the technical field of unmanned aerial vehicle inspection. The method comprises the following steps: measuring the road slope length, the landform and the geological complexity, and selecting an adaptive unmanned aerial vehicle type and sensor combination according to the road slope length, the landform and the geological complexity; planning unmanned aerial vehicle surface inspection and shallow geological exploration routes, ensuring space matching, and synchronously obtaining high-resolution images and ground penetrating radar data; and processing image data through a photogrammetry technology, generating a digital elevation model and an orthophoto map, and combining to construct a three-dimensional model of the earth surface. Geophysical inversion is carried out on the ground penetrating radar data, reflection features are extracted and projected to the ground surface three-dimensional model, and space correlation between the ground surface and a shallow layer structure is established; the reflection features are digitalized and geometrically reconstructed into three-dimensional surface elements, the three-dimensional surface elements are embedded into an earth surface model to form a three-dimensional geologic body model, time dimensions are introduced, and a dynamic evolution model is constructed. According to the dynamic evolution model, the dynamic analysis of the slope stability is realized.

The invention discloses a lake terrain prediction method based on machine learning fused multi-source satellite data, and relates to the technical field of machine learning, and the method comprises the steps: extracting the optical features of a target lake from an optical satellite image; extracting water features of each water body pixel in the target lake from the SWOT satellite data; performing space-time alignment and fusion on the optical features and the water features to obtain a fusion feature vector; the actually measured water depth point of the real water depth is matched to the geographic position of the corresponding pixel, and then the real water depth and the fusion feature vector of the corresponding pixel form a training sample; selecting a machine learning model and initializing the structure or parameters of the machine learning model; training the initialized machine learning model by using the training sample; utilizing the trained machine learning model to predict the water depth value of the corresponding pixel according to the fusion characteristic vector of each water body pixel; and determining the terrain of the target lake according to each water depth value. According to the method, the terrain of a large-scale lake can be efficiently predicted at low cost.

The invention discloses a storm surge water increase prediction method and device, electronic equipment and a storage medium, and relates to the technical field of seawater monitoring, and the method comprises the steps: obtaining multi-source observation data of a target sea area, the multi-source observation data comprising satellite remote sensing data, near-shore monitoring data, meteorological mode data and drainage basin data; performing space-time alignment and exception processing on the multi-source observation data to generate standardized space-time grid data; performing hybrid prediction modeling on the standardized space-time grid data through a physical data dual-drive modeling layer to obtain a target probability water increasing field; and dynamically correcting the target probability water increasing field by using real-time observation data to obtain a storm surge water increasing predicted value. A physical mechanism model and a probability generation model are combined, limitation of a single model is overcome, and the nonlinear evolution process of the storm surge is effectively captured; the time-space dual-drive architecture is adapted to complex coast terrains and changeable meteorological conditions, and the risk of missing report or false report is reduced.

The invention relates to the technical field of three-dimensional reconstruction, in particular to a three-dimensional reconstruction method for the peripheral topography and landform of an electric power facility based on a three-dimensional laser point cloud. The method comprises the following steps: performing electric flight laser scanning on the periphery of an electric power facility through an unmanned aerial vehicle, and synchronously collecting near-field point clouds around the electric power facility for space-time synchronous registration and morphological filtering denoising to obtain preprocessed three-dimensional point cloud data around the electric power facility; obtaining a point cloud geometric feature set corresponding to the periphery of the electric power facility through the electric power facility periphery preprocessing three-dimensional point cloud data, and performing electric power facility ground feature point classification and surface triangulation network dense and uniform reconstruction to generate an electric power facility periphery topography three-dimensional initial model; and performing reconstruction smoothing and triangular mesh simplification processing on the three-dimensional initial model of the topography and the landform around the electric power facility to obtain a three-dimensional optimization model of the topography and the landform around the electric power facility. According to the invention, the high-precision three-dimensional reconstruction process of the electric power facility and the surrounding landform thereof can be realized.

The invention discloses an irregular particle three-dimensional shape measurement device and method based on speckle imaging, and belongs to the field of irregular particle three-dimensional shape measurement, and the irregular particle three-dimensional shape measurement device comprises an irregular particle shakeout device which is used for enabling irregular particles to fall in a sparse free falling body form, and is used for forming lamellar laser vertical to the falling direction of the irregular particles, the laser sheet generating module is used for forming complete speckle distribution on the surfaces of the irregular particles; the laser sheet generating module is used for generating a laser sheet, the multi-view image collecting module is used for collecting speckle distribution on the surfaces of irregular particles in a multi-view mode and forming speckle images, the synchronous control system is used for controlling the laser sheet generating module and the multi-view image collecting module and synchronizing the time of the laser sheet generating module and the multi-view image collecting module, and the three-dimensional reconstruction processing unit is used for obtaining three-dimensional shape data of the irregular particles according to the speckle images. According to the invention, the irregular particles can be rapidly, non-destructively and in-situ measured so as to meet the requirements of aeroengine erosion research on the precision, efficiency and integrity of irregular particle data.

The invention discloses a self-adaptive gait control method, system and device for a quadruped robot in a limited space and a medium, and belongs to the technical field of gait control. Identifying terrain categories through a classifier and acquiring initial gait parameters from a gait library; adjusting the gait parameters according to the terrain gradient and the roughness to obtain optimized gait parameters; calculating stability indexes and fusing scores; when the score is lower than a threshold value, an adjustment strategy is determined according to an instability mode to correct gait parameters; a foot end track is generated and control is executed; and the executed information is fed back to terrain perception to form a closed loop. According to the method, the terrain recognition accuracy is improved through multi-modal information fusion, the adaptive mapping from the terrain to the gait is established to achieve automatic gait switching and parameter optimization, the stability is evaluated through multi-index fusion, a targeted adjustment strategy is selected according to an instability mode, the adaptive gait control problem under the limited space and the complex terrain is solved, and the adaptive gait recognition accuracy is improved. And the movement efficiency and the stability are improved.

The invention relates to the technical field of marine surveying and mapping and submarine topography modeling, and discloses a submarine topography and landform construction method based on multi-source water depth data fusion, which comprises a multi-source data acquisition module, a data preprocessing module, a feature extraction module, a fusion algorithm matching module, a three-dimensional modeling module and an uncertainty evaluation module. A historical submarine topographic map is converted into grid data, namely, submarine topography is discretized into digital representation of regular grid units, water depths of other sources are converted into the grid data, the precision of the water depths of different sources is evaluated by adopting a superposition comparison method, and an error distribution model is established to reasonably correct and fuse the water depth data of various sources. The innovation of the method lies in that topographic feature parameters including the gradient, the curvature matrix and the bionic optimization algorithm are introduced, the defect that a single algorithm is preset in a traditional method is overcome, and the precision of coral reef and fault zone complex areas is improved.

The invention discloses an optical imaging and coding hole technology fused optical imaging system and method, and aims to integrate scattered polarization components in a reflected light signal into coding light field data with clear layers by constructing a polarization coding modulation system, so as to highlight a coupling relationship among optical elements. A refocusing sequence and a focal plane chromatography technology are adopted, spatial geometric information and light intensity distribution characteristics of different depth layers are fully excavated, and a three-dimensional distribution rule of surface topography is disclosed; wavefront correction and deformable mirror control technologies are introduced, imaging parameters of an optical system are adjusted in a self-adaptive mode, and the application range of measurement precision is expanded; light intensity modulation analysis and phase unwrapping window processing are combined, the change trend of the surface curvature is depicted, and key feature points of morphology measurement are grasped; finally, multi-dimensional and multi-level optical measurement information is fused, three-dimensional measurement output with rich content and reliable precision is formed, and comprehensive and high-quality measurement technology resources can be provided for application scenes such as precision optical detection and surface quality evaluation.

The invention relates to the technical field of detection, in particular to a complex shell detection method and system based on structured light scanning. The method comprises the following steps: calculating a wrapped phase value and a phase modulation amplitude of each pixel point under each frequency, calculating discrete probability distribution containing candidate stripe series and a corresponding probability for each pixel point based on a multi-frequency wrapped phase difference, generating an initial pixel confidence map, and constructing an energy function; the penalty weight of the smooth item is determined according to the phase modulation amplitude and the wrapped phase gradient local variance, obtaining an initial fringe order distribution diagram, updating discrete probability distribution by using an initial pixel confidence map, re-minimizing an energy function to obtain a corrected fringe order distribution diagram, and reconstructing a final three-dimensional shape. And iteratively optimizing a projector principal point and a radial distortion coefficient in system calibration parameters. According to the scheme, the geometric details of the surface can be reserved, and the processing effect and the measurement precision of the complex curved surface and the high-curvature area are improved.

The invention relates to the technical field of ecological environment monitoring and geographic information, in particular to a coastal wetland soil sample point quality evaluation method and system based on multi-source environmental data. According to the method, remote sensing, climate, terrain, ocean and historical land coverage data are fused, and indexes are extracted and standardized; an environment similarity score (weighted Markov / neighbor weighted Euclidean), a historical consistency score (multi-temporal coverage + transfer penalty) and a source reliability score (metadata integrity + anomaly detection + NDVI-SOC residual) are constructed respectively; comprehensive scores are obtained through self-adaptive weight fusion, A / B / C grades are divided, and a report and a high-quality sample point set are output. The system comprises a data access module, a scoring engine module and a visualization module, and the precision and robustness of soil mapping and carbon storage evaluation can be remarkably improved.

The invention discloses an AUV (Autonomous Underwater Vehicle) path planning and control integrated method for a complex marine environment, and provides an intelligent path control scheme integrating reinforcement learning and local obstacle avoidance mainly aiming at underwater navigation problems such as submarine topography fluctuation, frequent ocean current disturbance and uncertain dynamic obstacle distribution. According to the method, a realistic three-dimensional ocean grid environment is constructed, an improved Q-learning algorithm is utilized to complete global path planning, a group of optimal path point sequences are generated, and it is ensured that the AUV has the macroscopic navigation capability. Local obstacle avoidance is performed in combination with a three-dimensional dynamic window method (3D DWA), and sudden obstacles are dynamically avoided through speed sampling and trajectory prediction. A DDPG control strategy based on deep reinforcement learning is further introduced, end-to-end training of path planning and control execution is realized, and the system can directly output a control instruction according to a real-time sensing state. A cosine attenuation learning rate, a self-adaptive exploration mechanism, an energy consumption penalty function and a dynamic obstacle prediction and control action filtering technology are fused in the method, so that the intelligence of path planning, the stability of control output and the robustness of obstacle avoidance response are effectively improved. According to the invention, the autonomous navigation capability, the environmental adaptability and the safety task completion efficiency of the AUV in a complex marine environment can be obviously enhanced, and reliable intelligent control technical support is provided for underwater operation.

The invention discloses a fringe projection three-dimensional shape measurement method based on frequency domain and time domain joint coding, and the method comprises the following steps: firstly, embedding a multi-frequency three-step phase shift fringe pattern in the vertical direction based on multi-scale region division, introducing four-step phase shift and complementary Gray code joint coding in the horizontal direction, generating a coding pattern set, and carrying out the projection; after an image is collected, frequency domain transformation and time domain decoding are carried out respectively, and a vertical dominant frequency position, a horizontal period number and a wrapped phase are obtained; then, combining a main frequency position in the vertical direction with a period number and a wrapped phase in the horizontal direction, and extracting a space coordinate of a direct illumination component based on frequency position invariance; and finally, establishing a pixel homonymy point mapping relation between the projector and the camera, and realizing high-precision three-dimensional reconstruction. Compared with a traditional frequency shift method, the method has the advantages that projection patterns are greatly reduced, reconstruction precision and anti-interference performance are improved, and the method is suitable for dynamic three-dimensional measurement under complex illumination conditions such as specular reflection, semitransparent shielding and subsurface scattering.

The invention provides a snow eave growth monitoring system based on terrain coupling and a dynamic evolution model, and relates to the technical field of mountain snow disaster monitoring. A sensitive area identification module is used for obtaining environment data of ridge terrain and a wind field, constructing a wind and terrain micro-scale coupling tensor field according to the environment data, and sending the wind and terrain micro-scale coupling tensor field to a dynamic evolution module; identifying a potential formation sensitive area of the snow eave according to a wind and terrain micro-scale coupling tensor field; and the dynamic evolution module is used for establishing a dynamic evolution model fusing pneumatic jump accumulation and a microcosmic sintering mechanism according to the identified snow eave potential formation sensitive area, simulating a snow eave generation and growth process according to the dynamic evolution model, and obtaining a structure expansion result generated by the snow eave according to simulation. According to the invention, a sensitive area identification module fusing a wind field and a terrain micro-scale coupling tensor field is constructed, and a snow eave structure evolution model, a multi-dimensional sensing data fusion mechanism and a zoning risk output module are combined, so that the growth process of a snow eave under specific terrain and meteorological conditions is dynamically described.

The invention discloses a nondestructive testing method for a welding seam of a steel structure. The method comprises the steps that firstly, morphology data of the surface of a building steel structure are obtained through a high-precision laser scanner and an electromagnetic induction technology; coating thickness distribution and weld surface roughness are analyzed based on the morphology data, and a surface information matrix is constructed; then automatically adjusting ultrasonic wave beam parameters of the ultrasonic phased array by using the adaptive parameter regulation and control model and executing detection to obtain a preliminary ultrasonic echo signal; the time-frequency domain difference between the preliminary echo and the reference signal is calculated through an echo signal compensation model, and secondary compensation is completed to obtain an optimized ultrasonic echo signal; fusing the optimized echo signal, the morphology data and the surface information matrix to construct a detection data set, and adopting a pre-trained steel structure detection model to realize defect detection; and finally, evaluating the confidence of a detection result by adopting a three-dimensional confidence evaluation model, performing grading, and performing local re-detection and parameter adjustment on a low-confidence region to form closed-loop optimization. According to the method, the surface state of the steel structure can be adaptively matched, the accuracy of echo signals and the defect detection precision are improved, and the detection reliability is guaranteed through three-dimensional confidence evaluation.

The invention provides a titanium plate performance analysis method and system, and relates to the technical field of metal material detection.The method comprises the steps that an optical scanner is adopted to establish a three-dimensional structure on the surface of a titanium plate, and test areas are divided; synchronously acquiring stress, hardness and conductivity data of a test point by using a multi-probe collaborative detection device; constructing a dual-branch feature extraction network, wherein the dual-branch feature extraction network comprises a surface topography feature branch and a physical feature branch; performing statistical integration on the features in the test area, calculating distribution features and determining a weight coefficient; and generating a performance analysis result through feature fusion and a multi-task output layer, and finally determining the performance grade of the titanium plate. According to the method, deep fusion of morphology information and physical characteristics is realized, and the accuracy and reliability of titanium plate performance evaluation are improved.

The invention discloses an image recognition system for industrial part defect detection, and particularly relates to the field of part defect detection, which comprises a multi-axis controllable light source array module, a high-speed polarization camera module, an edge computing node module, a double-branch semantic segmentation network module and a physical constraint post-processing module, according to the invention, through combination of time-sharing stroboscopic illumination and polarization image sequence acquisition, multi-dimensional perception of surface topography and material differences is realized; generating an elevation map and a normal map by using photometric stereo solution, constructing a differential rendering layer reverse matching CAD model, and extracting flash sensitive features; a double-branch U-Net network is adopted to fuse geometric and polarization characteristics, the characterization capability is enhanced through a trans-attention mechanism, and a pixel-level mask is output; and finally, mapping a two-dimensional result to a three-dimensional coordinate system by means of calibration parameters, carrying out geometric verification in combination with a tolerance zone and a height threshold value, and automatically generating a structured defect report containing position, size, grade and visual information.

The invention discloses a submarine topography super-resolution reconstruction method based on window displacement multi-source fusion, and aims to solve the problem of precision attenuation caused by absence of multi-beam truth value evaluation and resolution improvement of an existing neural network submarine topography reconstruction method. The method comprises the following steps of: obtaining gravity anomaly, gravity vertical gradient, vertical line deviation component, submarine topography background and ship survey water depth multi-source data of a target sea area; constructing a residual U-Net attention neural network model, and performing training by taking multi-source data extracted by a 11 * 11 window and position codes as input; moving the trained model sampling window in a staggered manner according to a target resolution step length; extracting data points in the window during movement and injecting position codes; and outputting a high-resolution water depth predicted value based on the position code and the window data. The reconstruction precision is improved by fusing physical quantities, the multi-resolution robustness is guaranteed by a window displacement mechanism, and the medium-frequency feature reconstruction capability is enhanced by a residual U-Net attention model.

The invention relates to the technical field of urban planning, and particularly discloses an urban planning construction land management and control system based on big data, and the system comprises the steps: obtaining geological environment, landform, engineering construction and human activity data through multi-source data collection; multi-source data fusion analysis is adopted to construct a construction land comprehensive evaluation field including geological stability, engineering suitability and environmental bearing capacity; a development suitability partition is generated based on a density peak value spatial clustering method; updating the development suitability level by dynamically monitoring the verification process; according to the method, accurate analysis and early warning of the three-dimensional deformation field are realized, and scientificity and safety of urban planning in a complex geological environment are improved.

The invention relates to the technical field of ocean engineering digital twinning and three-dimensional visualization, and provides a method and system for generating dredging terrain twinning based on a right-angle triangular mesh, and the method comprises the steps: obtaining regular grid elevation unified to an engineering plane coordinate system or preprocessed sampling height data, determining a covered space range, reading the space range and density parameters, and calculating the total row number and the total column number of the grids based on the space range and the density parameters; generating regularly arranged vertexes in the covered space, and constructing a topological structure of an isosceles right triangle grid; dividing the global grid into a plurality of Chunk blocks according to a fixed size by taking a vertex as a unit, establishing a triangular index mapping relationship between global rows and columns and the Chunk blocks, filling three vertexes of an isosceles right triangle and elevation / height data in each Chunk block in parallel, and generating local VBO, IBO and AABB; and performing batch rendering and coloring according to a height color table on all Chunk blocks to realize visualization of the terrain.

The invention discloses a leveling method and system for PCB processing in an integrated circuit, and relates to the related field of printed circuit boards, the method comprises the following steps: collecting surface data of a to-be-processed PCB, obtaining a morphology data set, and establishing a three-dimensional morphology model of the to-be-processed PCB based on the morphology data set; performing three-dimensional deviation identification on the to-be-processed PCB through the three-dimensional shape model, and extracting a three-dimensional deviation area; mapping to an integrated circuit for leveling analysis according to the three-dimensional deviation area, setting a leveling priority mapping graph, and performing dynamic leveling planning based on the leveling priority mapping graph to generate a leveling path; the leveling path is executed for leveling monitoring, flatness verification is carried out according to multi-source monitoring data, leveling quality parameters are obtained and backtracked to the leveling path for iterative updating, and self-adaptive leveling is carried out on the PCB to be processed. The technical problem that existing PCB machining leveling is insufficient in adaptability and precision is solved, and the technical effect of high-precision self-adaptive leveling is achieved.

The invention provides a point cloud rapid splicing method and system for surface confocal surface topography, and relates to the technical field of point cloud splicing, and the method comprises the steps: carrying out the regional scanning of a target object through a surface confocal microscope, so as to obtain a plurality of point cloud data sets; voxel filtering is sequentially carried out on the point cloud data set to obtain a transition point cloud set, radius filtering is carried out on the transition point cloud set to obtain a standard point cloud set, and the standard point cloud set comprises a source point cloud and a target point cloud; iCP registration is carried out on the source point cloud and the target point cloud, and a preliminary splicing point cloud is acquired; and converting the preliminary splicing point cloud into a depth map corresponding to the preliminary splicing point cloud, and performing inverse conversion operation on the depth map to obtain a final splicing point cloud. According to the invention, the integrity and geometric accuracy of the final spliced point cloud can be improved.

The invention relates to the technical field of artificial intelligence and electric power system prediction, and discloses a wind power short-term output prediction method based on multi-modal data, and the method comprises the steps: obtaining the multi-modal data, such as historical output, numerical weather forecast, actually measured weather of an anemometer tower, landform and fan operation state; performing sliding window segmentation on the output sequence and identifying a mutation interval; calculating a local optimal alignment path of each mode in the mutation interval based on a dynamic time warping algorithm; non-uniform resampling is carried out in this way, and a time-synchronized multi-modal alignment feature sequence is generated; and inputting a hybrid neural network formed by a gating circulation unit and an attention mechanism, and outputting a high-precision output prediction value in the next 15 minutes. The system comprises corresponding function modules. According to the method, through dynamic time alignment and cross-modal feature fusion, the wind power short-term prediction precision is remarkably improved, the root-mean-square error in a sudden change scene is reduced by 23.7%, and reliable support is provided for power grid dispatching.

The disclosure provides an improved canopy height correction method. The method includes: obtaining GEDI LiDAR data, airborne canopy height data, GDEM with high resolution and land cover product within the selected target area and timeframe; performing quality filtering and spatial-scale filtering on GEDI footprints; extracting laser pointing parameters and waveform parameters; extracting reference canopy height from airborne data for each footprint; extracting laser pointing parameters and waveform parameters; preprocessing the GDEM and calculating topographic parameters, including topographic variability index (TVI); constructing the Laser Pointing and Topographic Index (LPTI) according to the 3D forest-ground geometry model; inputting the waveform parameters, even topographic parameters, TVI and LPTI as independent variables, and the reference canopy height as the dependent variable to modeling an improved forest canopy height extraction, and utilizing the improved canopy height extraction model to correct the twofold influence of topographic on GEDI canopy height extraction.

The invention relates to the technical field of workpiece detection, and discloses an intelligent visual detection method and system for the surface of a workpiece, and the method comprises the steps: projecting a polarization structure light pattern to the surface of the workpiece, and synchronously collecting an image of the polarization structure light pattern after deformation on the surface of the workpiece; separating a structured light component and a polarized light component from the image, reconstructing a surface three-dimensional shape according to the structured light component, and generating surface polarization degree distribution according to the polarized light component; performing multi-scale gradient scanning on the surface three-dimensional morphology, extracting edge change features, performing texture consistency analysis on the surface polarization degree distribution, and identifying an abnormal texture mode; identifying a mirror reflection area based on the surface polarization degree distribution, performing height compensation on a corresponding area in the surface three-dimensional morphology, generating a corrected surface three-dimensional morphology, and combining edge change features and an abnormal texture mode; according to the invention, the accuracy and robustness of defect identification can be improved, and the reliability and efficiency of the system in industrial field application are enhanced.

The invention discloses an ecological restoration effect evaluation method for a land and space comprehensive improvement area, and relates to the technical field of ecological environment monitoring. A terrain structure data set and a moisture dynamic data set are obtained after data analysis and image feature extraction; the method comprises the following steps: carrying out terrain disturbance evaluation by constructing a terrain disturbance response index Rtz, carrying out hydrological back-up state evaluation by constructing a hydrological back-up trend index Gsh when the terrain has an unsteady disturbance region, carrying out ecological adaptation evaluation by constructing an ecological adaptation comprehensive index SSZ when the hydrological back-up meets the standard, and generating a landform base map of a renovation region by calling DEM (Digital Elevation Model) data. And each evaluation result is subjected to visual partition display through GIS space rendering, and a repair effect report is automatically generated. According to the method, multi-dimensional quantitative evaluation of terrain disturbance, hydrological refilling and ecological adaptability of the renovation area is realized.

The invention relates to an intelligent drainage basin management method, device and equipment based on digital twinning and a medium of the intelligent drainage basin management method and device based on digital twinning. The method comprises the steps that core terrain attributes are extracted through terrain feature decoupling and coding, and a disaster response function of an optimal source drainage basin is migrated based on terrain and rainfall similarity; a hydrodynamic model and a migration function are combined to generate a physically constrained synthetic disaster situation data set, a two-channel neural network model fusing topographic features and rainfall dynamics is constructed, and model parameters are dynamically calibrated through Bayesian continuous learning by using real-time monitoring data of a target drainage basin. Finally, a digital twinborn system with flood routing prediction capability is formed, the problem of rapid construction of a flood prediction model under the condition of no historical data is solved, and the timeliness and accuracy of early warning of sudden flood in small and medium-sized watersheds are remarkably improved.

The invention discloses a submarine topography reconstruction system and method based on optical mobile measuring and scanning, and relates to the technical field of ocean exploration, and the system comprises the following units: an image collection unit, which is used for coordinating the emission of 532nm pulse laser and the collection of a gating camera image through a synchronous sequential circuit, a triangulation measurement optical structure with separated emission and reception is adopted, and a submersible can be carried for mobile measurement and scanning; the system calibration unit is used for carrying out joint calibration on camera parameters and a laser plane so as to determine system calibration parameters, so that the spatial position of a laser stripe accurately corresponds to the actual coordinate of the target surface; and the image processing unit is used for preprocessing the image acquired by the system and further extracting the coordinates of the center line of the laser stripe in the preprocessed image. According to the invention, adjacent splicing can be carried out through continuously collected laser stripe images to construct two-dimensional submarine landform information, and three-dimensional reconstruction of submarine topography can be carried out by using generated point cloud data.