115 results about "Terrain modeling" patented technology

The invention relates to the technical field of unmanned aerial vehicles, and discloses an unmanned aerial vehicle parking apron dynamic landing point adjustment method and system based on environment awareness, and the method comprises the steps: obtaining environment data and flight parameters, constructing a three-dimensional terrain grid model, and analyzing the stability; loading obstacle data and path constraints to generate a comprehensive evaluation model, and simulating to obtain regulation and control data; training the model to generate initial adjustment parameters, and combining the parameters with the model to obtain dynamic adjustment simulation information; constructing a multi-path optimization model to obtain optimal parameters; and combining real-time sensing to generate a safety probability, and adjusting a landing strategy. The system comprises a data acquisition module, a terrain modeling module and the like. According to the scheme, intelligent optimization and real-time adjustment of a landing point are realized through multi-dimensional environment perception and dynamic modeling, the landing safety and reliability of the unmanned aerial vehicle in a complex environment are improved, and the method is suitable for an intelligent landing scene of the unmanned aerial vehicle.

The invention relates to the technical field of data processing, in particular to an earthwork balancing method based on discrete elevation points and a free-form surface creation technology, and the method comprises the steps: generating topographic feature partition tags through an improved DBSCAN density clustering algorithm, and constructing a regularized elevation field in combination with octree and R * tree mixed indexes; generating an elevation standard deviation thermodynamic diagram based on Gaussian process regression, and outputting a multi-target digging and filling scheme set in combination with an FEM-DEM coupling model; a multi-layer graph model fused with soil bearing capacity is constructed, a collision-free construction path is optimized through an improved D * Lite algorithm, a positioning track and a planning deviation are fused by using Kalman filtering, and an online sequence extreme learning machine is triggered to realize dynamic updating of the model. According to the method, the complex terrain modeling efficiency and the earthwork volume calculation precision are improved, the resource allocation path is optimized, the construction cost is reduced, and the problem of excavation and filling imbalance caused by data discreteness and modeling staticization in a traditional method is solved.

The invention discloses a complex terrain three-dimensional modeling and earthwork volume calculation method based on a multi-source fusion point cloud, belongs to the technical field of surveying and mapping and engineering surveying, and mainly solves the problems of low terrain modeling precision and insufficient earthwork calculation efficiency in a complex scene. The method comprises the following steps: constructing a ground-air integrated multi-source sensing network to synchronously acquire laser point cloud, multi-view images and positioning data; adopting PointNet + +-based initial registration and multi-scale ICP fine registration fusion to generate a unified point cloud; combining semantic segmentation and penetration probability filtering to accurately extract a digital elevation model; constructing a similar triangular prism voxel model by using a constrained Delaunay triangulation network; and finally, the earth volume is rapidly calculated by adopting a GPU parallel voxel cutting and filling algorithm, so that high-precision terrain modeling and rapid engineering quantity calculation are realized, and the method can be efficiently and reliably applied to large-scale projects such as roads and mines.

The invention provides a hydropower station reservoir water level prediction analysis method, a hydropower station reservoir water level prediction analysis system and a storage medium, and relates to the technical field of reservoir water level prediction. A unified modeling path from hydrological element collection to water level prediction is realized, a directed weighted graph reflecting a real hydrological conduction path is formed by fusing a digital elevation model and hydrological data, constructing a space node and a water flow connection relation thereof and giving edge weights, so that the water level prediction is not limited to point data analysis any more, and the water level prediction accuracy is improved. According to the method, modeling of collaborative change of hydrological states in a whole influence basin is changed, a unified framework fusing a terrain structure, a hydrological process and machine learning capability is constructed, coupling modeling of spatial distribution characteristics and time dynamic characteristics is achieved, and the precision and reliability of water level prediction are improved.

The invention discloses an intelligent three-dimensional terrain modeling method and system based on surveying and mapping data, and relates to the technical field of surveying and mapping, and the method comprises the steps: carrying out the comprehensive calculation based on a local terrain complexity index LTCI and a terrain feature line stability index FLSI, and outputting an overall modeling quality index GMQI, and carrying out secondary comparison evaluation based on an overall modeling quality index GMQI result. And when an overall modeling quality index GMQI evaluation result shows that the overall modeling quality does not reach the standard, performing automatic iteration to trigger refined reconstruction, and performing gradual optimization according to a 40% point density improvement strategy every time until the overall modeling quality reaches the standard, thereby realizing global modeling quality control of the mountainous area infrastructure site selection area. According to the method, modeling consistency and detail precision are improved, modeling deviation caused by local terrain sudden change or structure instability is effectively avoided, and reliability and safety of the final three-dimensional terrain model in engineering design application are improved.

The invention relates to the technical field of river channel model construction, and provides a river channel model generation method and system and a medium, and the method comprises the steps: obtaining a remote sensing image and satellite height measurement data of a target river channel, extracting a river channel thalweg line based on the image, extracting feature points from a waterline, and giving an elevation value in combination with the height measurement data; dividing the river channel into independent interpolation areas on the left side and the right side by taking the thalweg as a boundary, and setting a direction attenuation coefficient and a distance attenuation coefficient according to the characteristics of the river reach; generating direction control points along the thalweg according to the minimum width of the dry-season river channel, calculating the local direction angle of each river section, and combining the direction angle, direction attenuation and distance attenuation coefficients to construct a weighting function; spatial interpolation is carried out on the feature points on the left side and the right side through the function, double-side digital elevation models are generated respectively, finally, a complete river channel model is obtained through splicing, and refined expression of the river channel terrain is achieved. According to the method, the precision and physical rationality of complex river channel terrain modeling can be improved.

The invention discloses a mountain photovoltaic layout optimization method and system based on multi-point illumination dynamic data, and relates to the technical field of photovoltaic construction, and the method comprises the steps: constructing a virtual mountain structure and configuring a three-dimensional landform stereo structure through mountain geographical and landform data; based on the historical illumination data, establishing an illumination simulation model, and quantifying the illumination performance of the virtual mountain structure; randomly arranging virtual photovoltaic modules in the photovoltaic layout area, determining position nodes and angles, and forming a virtual photovoltaic arrangement strategy; and calculating an illumination intensity accumulation parameter and a total parameter of each virtual photovoltaic module, evaluating layout optimization in combination with layout cost, and screening an optimization strategy. According to the method, through refined terrain modeling, dynamic illumination simulation and multi-target optimization, the energy efficiency and economical efficiency of mountain photovoltaic layout are remarkably improved, and scientific support is provided for planning of a complex terrain photovoltaic power station.

The invention discloses an airborne laser radar point cloud three-dimensional target detection method based on terrain guidance, and belongs to the technical field of three-dimensional target detection. The objective of the invention is to solve the problem that the existing three-dimensional target detection does not consider the influence caused by terrain complexity and target-background similarity, so that the detection effect needs to be improved. According to the invention, based on the VoxelNext network, a multi-stage terrain guidance module is introduced to predict terrain distribution and guide the processes of height compression, region-of-interest generation and proposal prediction, and effective combination of terrain modeling and pipeline detection is realized; according to the method, voxels are randomly sampled and grouped through a sparse feature enhancement module, middle layer features are aggregated, and two auxiliary tasks of foreground segmentation and voxel up-sampling are introduced to enhance the feature expression ability of the network.

The invention discloses a photovoltaic station unmanned aerial vehicle three-dimensional route planning method and system based on field angle self-adaption and terrain modeling. The method comprises the following steps: acquiring geographic position information of a photovoltaic panel; determining a vertical field angle according to the unmanned aerial vehicle image equipment parameters; generating a reference point based on geographic position information, performing horizontal clustering by adopting a density clustering algorithm to form an initial row group, and completing row-column grouping through linear fitting completion and correction of a row structure; dynamically determining a flight height for each waypoint through geometric model calculation based on a grouping result in combination with a vertical field angle and a pitch angle, and generating a three-dimensional waypoint; and determining a waypoint connection sequence based on a distance optimal principle, detecting and optimizing acute-angle turning, and generating a smooth three-dimensional flight path. According to the invention, full-automatic three-dimensional planning of the photovoltaic inspection route is realized, the system can adapt to complex terrains, the shooting quality is ensured, and the inspection efficiency is improved.

The invention provides a hydropower station reservoir area three-dimensional terrain modeling method and device based on multi-source data fusion, and relates to the technical field of three-dimensional terrain modeling, and the method comprises the steps: obtaining a multi-source data set containing point cloud data, image data, texture data and actual measurement data of a hydropower station reservoir area; preprocessing the multi-source data set to obtain a preprocessed data set; and according to the preprocessed data set, constructing a three-dimensional terrain model by using an improved Delou inner triangulation algorithm, a non-uniform rational B-spline surface reconstruction technology and a Laplacian smoothing operator. The geometric accuracy and the natural form of the three-dimensional terrain model can be remarkably improved.

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 discloses a submarine topography real-time surveying and mapping system based on a sonar array, and relates to the technical field of sonar topography surveying and mapping. The system comprises a sonar array, a data acquisition and preprocessing module, a control and communication module, a data processing and terrain modeling module and a power supply module. According to the sonar array, a self-adaptive matrix is formed by multi-frequency-band sensors, real-time calibration, high-speed parallel sampling for data acquisition and advanced algorithm noise reduction are achieved, a control module optimizes parameters according to the environment, and communication is diversified and safe; the processing module adopts deep learning modeling, grids are divided according to curvature, a power supply adopts multi-source complementation and energy recovery, and energy is managed and distributed. The surveying and mapping precision is high, and the constructed three-dimensional model is accurate. The device adapts to complex marine environment and has strong stability. Multi-source power supply and energy recovery are adopted, the energy consumption is low, and the endurance is long; the system is excellent in data processing and analysis capability, integrates multi-source data, has the functions of safety protection, path planning and the like, and comprehensively guarantees efficient completion of surveying and mapping tasks.

The invention discloses an unmanned aerial vehicle route generation system which comprises a generation system body, the generation system body comprises a three-dimensional terrain modeling module, a multi-source sensor fusion module, an intelligent task planning module, a dynamic obstacle avoidance and safety module and a man-machine interaction and data management module, and the three-dimensional terrain modeling module is based on ASTER GDEM and DSM elevation data; the multi-source sensor fusion module is used for generating a three-dimensional digital elevation model (DEM) of an operation area, centimeter-level terrain matching is realized by combining an RTK positioning technology, and the multi-source sensor fusion module is used for integrating a laser radar, a visible light camera and an infrared sensor, collecting features of ground objects such as towers and vegetation in real time, and is used for dynamically adjusting an air route. The optimal route is automatically generated through an intelligent algorithm, manual intervention is reduced, route planning efficiency is remarkably improved, meanwhile, terrain adaptability can be enhanced, a terrain following algorithm is adopted, the flight height is automatically adjusted according to topographic relief, and accuracy and integrity of surveying and mapping data are ensured.

The invention relates to the technical field of three-dimensional modeling, in particular to a terrain modeling method and device based on a domestic three-dimensional graphic platform Railworks, and the method comprises the steps: collecting terrain data along a rail transit engineering project, and generating a structured original data pool; the method comprises the following steps: extracting and processing a discrete three-dimensional point set through a Railworks platform, and generating a triangular mesh by adopting a Gift Wrapping algorithm and a Delaunay triangulation algorithm; reconstructing a three-dimensional terrain surface model, adding an attribute database, and integrating elevation and gradient attributes according to industrial standards; and a downstream bridge and roadbed design module is connected through a data synchronization mechanism, so that design parameters are automatically updated. The device correspondingly realizes functions of each step. According to the method, the problems of high data security risk and low collaboration efficiency caused by dependence on foreign software are solved, an autonomous solution is provided, and the data processing security and the cross-professional design collaboration efficiency are improved.

The invention discloses an unmanned aerial vehicle autonomous path planning and high-precision surveying and mapping integrated system, and relates to the technical field of unmanned aerial vehicle surveying and mapping. The system comprises a terrain modeling module, a task configuration and scheduling module, a path planning module, an unmanned aerial vehicle flight control module, a surveying and mapping sensing module, a data caching and transmission module and a ground control and result processing module. The terrain modeling module constructs three-dimensional terrain modeling through remote sensing image interpretation and a digital elevation model; the path planning module fuses simulated annealing, an adaptive genetic algorithm and a large neighborhood search algorithm to realize route static optimization and multi-aircraft cooperative path generation; the flight control module autonomously completes flight according to the path instruction; the data caching module provides breakpoint resume and edge relay support; and the ground platform completes image processing, splicing modeling and result exporting. According to the invention, intelligent route planning and high-precision and multi-source surveying and mapping data acquisition under complex terrains are realized, and the surveying and mapping automation level and the data accuracy are remarkably improved.

The invention relates to the field of land reclamation engineering, in particular to a land reclamation engineering progress monitoring system based on time sequence image analysis, which comprises a data storage module, an engineering progress image recognition engine, an engineering quality detection module, a meteorological condition compensation module and an early warning module. A Riemannian geometric model of a terrain curved surface is constructed, a project progress is analyzed and quantified through a geodesic network, a project progress image recognition engine comprises an image registration module, a Riemannian geometric terrain modeling module and a geodesic analysis module, and the Riemannian geometric terrain modeling module constructs a terrain surface model through manifold parameterization and measurement tensor calculation. The geodesic analysis module quantifies engineering progress indexes such as the earthwork completion rate, the road hardening rate and the greening coverage rate based on geodesic network changes, the system further integrates quality evaluation functions such as slope stability detection and drainage system integrity detection, and the reliability of a monitoring result is improved through meteorological condition compensation.

The invention belongs to the technical field of radio wave propagation, particularly discloses a complex path ASF prediction method based on parameter optimization three-dimensional FDTD, and aims to solve the problem of ASF prediction errors caused by neglecting a transverse diffraction effect in a two-dimensional method and the problem of poor precision caused by accumulated phase errors when a traditional three-dimensional FDTD method is applied to large-area ASF prediction. By means of three-dimensional terrain modeling, the electromagnetic propagation characteristics of the complex irregular terrain are accurately presented, and therefore the accuracy of the ASF prediction result of the complex path is remarkably improved. In addition, according to the complex path ASF prediction method based on parameter optimization three-dimensional FDTD, dispersion optimization parameters are introduced, phase accumulation errors are reduced, and therefore the calculation efficiency is improved while the precision is guaranteed. The method can provide an efficient solution for ASF prediction in a large-scale complex terrain scene, and is more suitable for popularization and application in engineering.

The invention provides a river topography modeling method and device. The method comprises the following steps: acquiring section measurement data of each actually measured cross section in a target river; determining coordinate information of measurement points of all actually measured cross sections based on the section measurement data; performing cubic spline resampling on the actually measured cross section based on the coordinate information of the measurement points according to a preset number of sampling points to obtain coordinates of resampling points; performing linear interpolation on the adjacent actually-measured cross sections according to the coordinates of the re-sampling points in the river channel direction of the target river channel to obtain encrypted river channel cross sections and encrypted section data; and constructing a river channel model based on the encrypted cross section of the river channel and the encrypted section data. By means of cubic spline resampling and linear interpolation, terrain details are reserved, data requirements are reduced, cross section terrain data are supplemented, accurate supplement of the cross section of the river channel is achieved by means of the distance and gradient change between the cross section to be supplemented and the known sampling elevation cross section of the river channel, and therefore the model precision is improved.

The invention discloses a cloud-based surveying and mapping data processing method and system, and the method comprises the steps: collecting a multi-source surveying and mapping data set, and carrying out the data fusion of the multi-source surveying and mapping data set based on an improved hierarchical Transform model in a cloud platform; and establishing an MTL-DNN surveying and mapping data analysis model based on an MTL-DNN multi-task deep learning network, performing pruning operation on the model by using a fine-grained pruning device, and inputting the fused multi-source surveying and mapping data set into the target MTL-DNN surveying and mapping data analysis model to perform terrain modeling, ground feature classification and risk prediction, so that model parameters and calculation amount can be reduced, and the modeling efficiency is improved. The deployment efficiency is improved; accurate and efficient data support and decision basis are provided for the fields of surveying and mapping engineering, disaster early warning and the like.

The invention provides a marine electromagnetic take-off and landing transportation system based on a heavy-load unmanned aerial vehicle, and belongs to the technical field of unmanned aerial vehicle marine heavy-load transportation. The system comprises a shipborne electromagnetic take-off and landing subsystem, a shore-based electromagnetic take-off and landing subsystem, a heavy-load fixed-wing unmanned aerial vehicle, a marine low-altitude communication monitoring network and a comprehensive scheduling platform; the shipborne electromagnetic take-off and landing subsystem is of a multi-section coil array structure, the effective length of a coil array of the shipborne electromagnetic take-off and landing subsystem can be matched with the available space of a fishing ship deck, the take-off and landing distance is controllable, and therefore the problem of take-off and landing in the narrow space of the deck is solved. The shore-based electromagnetic take-off and landing subsystem is integrated with a three-dimensional terrain modeling module, the real-time environment of a landing area is pre-judged through laser radar and satellite remote sensing data, parameters of an electromagnetic propulsion device and an electromagnetic adsorption device of the shore-based electromagnetic take-off and landing subsystem are dynamically adjusted, then the shore-based electromagnetic take-off and landing subsystem adapts to rugged terrain, and the limitation that a traditional unmanned aerial vehicle depends on a flat take-off and landing field is avoided. And through data linkage and intelligent scheduling of multiple subsystems, the overall efficiency and reliability of marine transportation are greatly improved.

The invention discloses an underwater three-dimensional scene data completion method and system based on deep learning, relates to the technical field of computer graphics, and solves the technical problem of data missing caused by sound shadow shielding, strong filtering or semantic segmentation in submarine topography surveying and mapping data. According to the technical scheme, the method is characterized in that a synthetic training set based on programmed terrain modeling is constructed, and high-resolution and large-scale training data are provided; a double-discriminator generative adversarial network comprising a completion network, a context discriminator and a boundary quality discriminator is designed, stable convergence of the network is achieved through a three-stage progressive training strategy, and meanwhile self-adaptive processing facing different missing scales is achieved. Wherein the boundary quality discriminator is used for enhancing the boundary continuity of the complementation area. According to the method, rapid and high-quality completion of the multi-scale underwater three-dimensional data is realized, the structural consistency of the completion area is remarkably improved while the calculation efficiency is maintained, and an effective solution is provided for real-time underwater surveying and mapping application.

The invention belongs to the technical field of radio wave propagation, and particularly discloses a rugged topography path low-frequency ground wave propagation characteristic prediction method based on an FD algorithm, and the method comprises the steps: firstly building a 3DPE model under an irregular topography, then building a discretization matrix equation, combining boundary impedance conditions based on a unilateral approximation method, and then carrying out the iteration solving of a field matrix, thereby achieving the prediction of the rugged topography path low-frequency ground wave propagation characteristic. And finally, the magnetic field intensity and the secondary time delay of radio wave propagation are solved by utilizing a field result in the whole calculation area. According to the method, the problem that low-frequency ground wave propagation characteristics are not accurately represented in transverse irregular terrain modeling through a 2DPE method is effectively solved, and meanwhile, the limitation that low-frequency ground wave propagation prediction precision is insufficient in a complex rugged terrain environment through a traditional 3DPE model is overcome; theoretical guidance can be provided for performance optimization of a low-frequency radio navigation time service system, and the navigation positioning and time service precision in a complex terrain area is further improved.

The invention discloses a DEM map dynamic obstacle avoidance path planning method and system based on a rime algorithm, DEM terrain modeling, rime algorithm meteorological prediction and an improved A * path planning algorithm are combined, safe path planning in a dynamic environment is achieved, the method and system can be applied to unmanned aerial vehicle inspection (such as power line icing monitoring), mountain rescue, automatic driving and other scenes, and the method and system have good application prospects. The problems that a traditional A * algorithm is limited, multi-constraint fusion is difficult, pure real-time meteorological data lags behind and the like are solved, and a safer and more reliable path planning navigation scheme is formed.

This invention discloses a method for scheduling unmanned vehicle swarms to maximize smokescreen coverage considering terrain constraints, belonging to the field of unmanned vehicle swarm scheduling technology. The method includes collecting raw terrain data of the task area and preprocessing it to obtain a standardized terrain dataset. This standardized terrain dataset is then input into an IMUNet network to achieve accurate terrain modeling of the task area and extract terrain constraints for unmanned vehicle operation. A smokescreen coverage model under terrain constraints is constructed based on these constraints. The total effective smokescreen coverage area of ​​the unmanned vehicles under different parameters is calculated. Using the total effective smokescreen coverage area as the optimization objective and the terrain constraints as the constraints, the QSMODE algorithm is used to solve the unmanned vehicle swarm scheduling optimization model to obtain the optimal unmanned vehicle swarm scheduling scheme. This invention improves the adaptability and robustness of the scheduling method, accurately handles complex terrain scenarios, and ensures maximum smokescreen coverage of the task area.

The invention relates to the field of underwater acoustic detection, and particularly discloses a global real-time mapping query-based sonar intrinsic coordinate system terrain modeling method, which comprises the following steps of: S1, establishing a position-variable sonar intrinsic coordinate system according to an initial attitude and a position vector of a sonar in a global reference coordinate system, constructing a transfer relation between the intrinsic coordinates and the global reference coordinates; s2, establishing a global terrain model for acquiring terrain elevation by horizontal coordinates; s3, creating a real-time mapping query interface, inputting three-dimensional coordinates of the intrinsic coordinate system, transmitting the three-dimensional coordinates to the global coordinate system, performing matching judgment on the three-dimensional coordinates and the global terrain elevation, and determining an intrinsic terrain elevation; and S4, traversing field point coordinates on all detection sound rays in the intrinsic coordinate system, and circularly calling a real-time mapping query interface until complete terrain modeling of the detection area is completed. The problems that traditional interpolation modeling is large in error, high in model numerical calculation complexity and the like are solved, and terrain modeling precision, flexibility and calculation efficiency are effectively improved.

This invention provides a method and system for constructing a negative obstacle risk map, relating to the field of robot environmental perception technology. The method includes: acquiring multimodal sensing data of a legged robot in the current operating environment to obtain the types of negative obstacles, multiple candidate regions, and the corresponding confidence and uncertainty of each candidate region; using a risk diffusion algorithm, performing ink blurring processing based on the type, confidence, and uncertainty to generate a continuous risk field corresponding to each candidate region; dividing the continuous risk field to generate a continuous risk gradient distribution corresponding to each candidate region; performing terrain modeling based on laser point clouds, updating the continuous risk gradient distribution using Bayesian fusion to obtain a multi-level grid map, and then performing tactile closed-loop correction on the multi-level grid map to generate a risk cost map. This invention improves the accuracy of constructing a negative obstacle risk map.

The application discloses a photovoltaic station unmanned aerial vehicle three-dimensional route planning method and system based on field of view angle self-adaption and terrain modeling. The method comprises the following steps: acquiring photovoltaic panel geographic position information; determining a vertical field of view angle according to an unmanned aerial vehicle image device parameter; generating a reference point based on the geographic position information, performing horizontal clustering by using a density clustering algorithm to form an initial row grouping, and then completing row and column grouping by linear fitting completion and correction of row structure; dynamically determining a flight height for each flight point by a geometric model calculation based on the grouping result, a vertical field of view angle and a pitch angle, and generating a three-dimensional flight point; determining a flight point connection sequence based on a distance optimization principle, detecting an optimized acute angle turning, and generating a smooth three-dimensional flight path. The application realizes full-automatic three-dimensional planning of a photovoltaic inspection route, can adapt to complex terrains, guarantees shooting quality and improves inspection efficiency.

This invention discloses a three-dimensional terrain construction method based on multimodal semantic constraints, belonging to the field of three-dimensional terrain modeling technology. This method acquires optical remote sensing images and digital surface models and constructs unified spatial reference data. Guided by multimodal semantic constraints, it performs joint semantic parsing of ground features to generate a set of semantic masks with structural consistency. Furthermore, based on the mapping relationship between semantic categories and surface physical attributes, it performs regional geometric reconstruction of the digital surface model to form three-dimensional terrain entities that conform to the spatial expression characteristics of ground features. Simultaneously, by parsing engineering cost documents and extracting spatially oriented engineering cost data, under spatial and semantic consistency constraints, it associates and maps engineering cost information with three-dimensional terrain entities, ultimately forming a three-dimensional terrain data result that integrates terrain geometric information and engineering economic attributes.

The invention discloses a three-dimensional terrain model generation method and device, electronic equipment and a readable storage medium, and relates to the technical field of three-dimensional models.The method comprises the steps that first terrain data and second terrain data of a terrain to be modeled are obtained, and the data types of the first terrain data and the second terrain data are different; filtering the first topographic data to obtain first modeling data, and performing format conversion and filtering on the second topographic data to obtain second modeling data; fusing the second modeling data with the first modeling data to obtain third modeling data; and in response to a modeling instruction, generating a three-dimensional terrain model of the terrain to be modeled based on the first modeling data, the second modeling data or the third modeling data. The method has the effect of improving the calculation efficiency while ensuring the terrain modeling precision.

The invention provides a map data generation method and device, electronic equipment and a computer readable storage medium. The method comprises the following steps: acquiring point cloud data and motion state data, and fusing the point cloud data and the motion state data to obtain pose estimation data; performing ground elevation modeling based on the pose estimation data and the point cloud data to obtain an elevation map corresponding to the point cloud data; performing incremental mapping processing based on the elevation map corresponding to the multi-frame point cloud data to obtain a global elevation map; performing feature extraction on the global elevation map to obtain topographic feature data of each grid in the global elevation map, and determining a traffic risk score of each grid based on the topographic feature data of each grid; and based on the traffic risk score of each grid, updating the global elevation map to obtain a target map. According to the invention, the integrity of terrain modeling and the accuracy of traffic risk detection can be improved.