353 results about "Urban area" patented technology

The invention discloses an urban area runoff pollutant transportation process simulation forecasting method, which is characterized in that a building area runoff production calculation method under the influence of a wind field is provided, and the building area runoff production calculation method is coupled with an SWMM rainfall flood model; secondly, constructing a two-dimensional hydrodynamic model based on an FVCOM and a Lagrange particle model, coupling the two-dimensional hydrodynamic model with the SWMM rainfall flood model, and driving the two-dimensional hydrodynamic model by taking the overflow flow and the pollutant concentration simulated by the SWMM rainfall flood model as boundary conditions; simulating a transportation process of pollutants along with evolution of surface ponding by establishing a'concentration-quantity 'conversion relation between the pollutants and particles at grid units and nodes, and obtaining a time sequence pollutant concentration data set; and training and establishing a pollutant concentration prediction model based on the obtained data, and then predicting the pollutant concentration of each prediction point after specific time in an actual rainfall event. According to the method, the runoff pollutant concentration can be predicted, and the urban non-point source pollution risk under the rainstorm weather is reduced.

The invention relates to the technical field of logistics distribution, and discloses a big data analysis method and system based on traffic transportation logistics, and the method comprises the steps: constructing a space-time diagram convolution network model, and predicting the traffic congestion propagation trend of an urban region; based on the congestion propagation trend, the order density and the distribution resource state, executing a space-time dynamic partitioning algorithm, and dividing the urban distribution region into a plurality of dynamic micro-regions; constructing a double-layer intelligent decision-making system, and generating a logistics fleet separation and combination decision and path planning; heterogeneous distribution resource dynamic marshalling is executed, and different types of distribution tools are combined into a miniature formation; using a multi-agent reinforcement learning algorithm to optimize the cooperation process in the micro formation; according to the invention, through fusion of congestion propagation prediction, dynamic micro-area division, double-layer intelligent decision and heterogeneous resource collaboration, key problems of traffic congestion, resource scheduling and'last kilometer 'distribution in urban logistics distribution are effectively solved.

The invention relates to the technical field of value accounting, and discloses an ecological system total production value accounting method based on GIS spatial analysis, and the method comprises the steps: carrying out the accounting of regional basic data and satellite image data, and constructing a bidirectional dynamic semantic mapping library corresponding to land change investigation land parcel classification-ecological system type; internet of Things monitoring data and statistical report data are obtained, and a standardized data set is obtained through space-time fusion of spatial interpolation-boundary correction and a sliding window smoothing method; constructing an urban area-typical district double-level accounting index system, and synchronously calculating a real object quantity and a value quantity; a model correction factor is called based on a GIS, indexes are quantified to grid units, a result is obtained through neighborhood analysis, and after parameters are calibrated, a multi-year ecological value trend map is generated in combination with the GIS; and outputting a customized result according to scenes such as ecological compensation, and outputting a final result after the customized result is qualified through three-level quality control verification. According to the method, the requirements of practical affairs such as ecological compensation and EOD projects on accounting precision and practicability can be met.

The invention provides a wireless network coverage prediction method, which belongs to the technical field of wireless communication, and comprises the following steps: constructing a wireless signal prediction model, setting correction factors and loss parameters according to different geographical environments, and carrying out preliminary prediction on the network coverage condition; taking the test base station as a center, actually measuring base station wireless signal indexes of different distances and ranges according to a geographical environment, and fitting actual measurement data to obtain a network coverage condition; and performing iterative correction on the correction factor and the loss parameter of the prediction model for different geographical environments by combining the prediction data and the actual measurement data of the prediction model to obtain network coverage prediction data in different geographical environments. The method has the advantages that a prediction framework based on multi-model fusion effectively deals with the influence of a complex geographical environment, signal attenuation change caused by topographic relief and building shielding can be accurately quantified, and the pain point of prediction misalignment of a traditional method in variable terrains and dense urban areas is solved.

The invention provides an urban area-oriented multi-source remote sensing data joint positioning method and system, and the method comprises the steps: obtaining a plurality of optical stereoscopic images and corresponding connection point data, constructing an optical stereoscopic block, and extracting laser elevation control point data and digital surface model data in the range of the optical stereoscopic block; calculating a ground coverage range of a plurality of optical stereoscopic images, mapping the ground coverage range to a grid unit by adopting a grid lookup table, obtaining a laser point accurate image space coordinate by combining the screened laser elevation control point data, and outputting a laser elevation control point set; calculating a laser elevation control point set based on a rational function model and affine transformation, and constructing a multi-source remote sensing data joint adjustment function model; and resolving the multi-source remote sensing data joint adjustment function model to form an observation error equation, performing heuristic search solution on the observation error equation, and outputting an adjustment model parameter result and a final connection point ground coordinate.

The invention discloses an urban reserve land intelligent classification method and system based on spatial data fusion, and relates to the technical field of data processing, and the method comprises the steps: carrying out the formalized expression of a land use rule of a preset urban region, and constructing a land domain knowledge graph; collecting multi-source spatial data, performing feature extraction and alignment, and generating a high-dimensional feature vector of each plot; and performing hybrid classification evaluation based on the high-dimensional feature vector of each land parcel, synchronously outputting land use types, development potential levels and land reference value intervals of the land parcels, and calling a land domain knowledge graph to perform compliance verification and correction. The technical problems that an existing urban reserve land classification method depends on artificial experience and lacks accurate and multi-dimensional data fusion and compliance check, so that the accuracy and practicability of a classification result are low are solved, and the purpose that the classification accuracy and practicability of the urban reserve land are improved through multi-source spatial data fusion and an intelligent classification framework is achieved. And the accuracy and practicability of urban reserve land classification are improved.

The invention discloses a smart city management system fusing artificial intelligence and big data, and relates to the technical field of smart city management, and the system comprises a data collection and feature extraction module which is used for obtaining and processing multi-source city data, extracting road network topological features, functional area distribution features and people flow dynamic features through a graph neural network, and obtaining a data collection and feature extraction module; generating and storing a structured feature vector; the cross-domain knowledge migration model construction module is used for constructing a city simulator, generating virtual data through a generative adversarial network and reinforcement learning, bridging a source domain and a target domain based on the virtual data, and realizing migration of source domain knowledge to the target domain by utilizing graph matching and an optimal transmission theory; and the model optimization and alignment module is used for aligning feature distribution of a source domain and a target domain through confrontation training of a domain discriminator and a gradient inversion layer, dynamically adjusting data weight, realizing seamless migration from virtual distribution to real distribution of the target domain, and realizing seamless knowledge migration from a mature urban area to a new urban area.

The present invention relates to equipment that can realistically reproduce various types of airflow occurring in environments such as an urban area with tall buildings or regions with mountains and valleys, thereby enabling verification of the flight safety of a multicopter-type drone. The present invention comprises: a housing that provides a tunnel-shaped test space in which a plurality of blowers, together with controllers, are installed along the longitudinal direction of both sidewalls of the interior, the ceiling, and the floor, to generate airflows such as crosswinds, updrafts, downdrafts, and vortices; and an integrated control unit that selectively or simultaneously controls some or all of the plurality of controllers installed in the housing so as to form airflows in pattern corresponding to user input or settings.

The invention provides a remote sensing building group depth detection and change intelligent evaluation method for urban planning, and the method comprises the steps: carrying out the multi-modal data collection of a target urban region, and carrying out the standardization processing, abnormal value elimination, multi-modal alignment and interference suppression processing, and obtaining a multi-modal data set; constructing a multi-branch hybrid network, and performing triplet feature extraction on the multi-modal data set through the multi-branch hybrid network to obtain a building group fusion feature map; performing change area detection and change type classification on the two building group fusion feature maps with different time phases to obtain building group change information; and constructing a dynamic evaluation index based on the urban planning core demand, and performing building group change evaluation in combination with the building group change information. According to the method, through multi-source and multi-modal data acquisition and processing, multi-branch hybrid network triplet feature extraction and change detection and dynamic evaluation index application, urban planning core requirements are adapted, and building group detection precision and change evaluation effectiveness are improved.

The invention discloses a geological disaster risk evaluation method and system based on big data, and the method comprises the following steps: S1, obtaining multi-source geological disaster data, including geological structure data, landform data, meteorological and hydrological data, human activity data and historical disaster data; s2, performing space-time alignment and standardization processing on the multi-source geological disaster data, and constructing a geological disaster space-time data set; s3, constructing a geological disaster risk evaluation model based on the deep learning network, wherein the geological disaster risk evaluation model comprises a feature extraction module, a space-time correlation module and a risk prediction module; s4, calculating a weight coefficient of each evaluation index by adopting a dynamic weight distribution method; s5, calculating a geological disaster risk index through the geological disaster risk evaluation model, and generating a risk grade zoning map; according to the invention, more intelligent geological disaster risk evaluation of the urban area is realized.

The invention discloses an urban low-altitude gridding management process control method and system based on unmanned aerial vehicle analysis, and belongs to the technical field of unmanned aerial vehicle flight management.The urban low-altitude gridding management process control method comprises the steps that urban three-dimensional data are obtained, an urban area is divided into multiple grid units, meteorological data are obtained, and a building interference evaluation model is constructed; importing the open angle and the building surrounding rate of each grid unit into a building interference evaluation model to calculate the building intensity, evaluating the reflection interference on the unmanned aerial vehicle through the number and intensity of reflection paths, constructing a meteorological interference model, obtaining the cloud cluster humidity distribution, raindrop particle size and wind parameters of the grid units, and calculating the building intensity. The method comprises the following steps: importing meteorological data into a meteorological interference model to evaluate a rainfall interference condition and a wind disturbance condition, constructing a flight risk evaluation model, and importing building density, a multi-path reflection error index, a rainfall interference index and wind disturbance intensity into the flight risk evaluation model to evaluate the flight risk degree of the unmanned aerial vehicle. And the safety of the flight path of the unmanned aerial vehicle is improved.

The embodiment of the invention discloses an underground pipeline simulation operation method and device based on spatial distribution. A specific embodiment of the method comprises the steps of collecting a multi-source underground pipeline data set in a target city area; performing data standardization on each piece of multi-source underground pipeline data in the multi-source underground pipeline data set to generate a standardized multi-source underground pipeline data set; establishing an initial underground pipeline three-dimensional structure model; performing pipeline space alignment on the initial underground pipeline three-dimensional structure model to generate a target pipeline three-dimensional structure model; and adding the target pipeline three-dimensional structure model to a three-dimensional pipe network visual distribution diagram layer in a preset target urban area underground distribution network global twin space, and performing underground pipeline simulation operation on the three-dimensional pipe network visual distribution diagram layer according to preset pipeline operation parameters. According to the embodiment, the accuracy of the generated target pipeline three-dimensional structure model can be improved.

The invention discloses a fire-fighting spatial-temporal trajectory data processing and off-line data warehouse construction method based on a stream batch fusion architecture, and relates to the field of digital fire fighting, and the core steps of the method are as follows: after multi-source data are collected by an edge gateway, high throughput distribution and storage are realized by Kafka; real-time optimization such as track cross repair and offset correction is completed through Flink streaming calculation; performing offline batch processing on the historical data by the Spark to generate an analysis result; generating an optimal rescue path through a distributed Dijkstra algorithm in combination with road topology, real-time traffic and fire fighting truck parameters; the method comprises the following steps: realizing mixed storage by adopting ElasticSearch secondary index and HBase total storage; based on hot and cold data hierarchical management, intelligent applications such as fire-fighting commanding and dispatching, battle comment and review and the like are supported. Practice verifies that the method can shorten the fire control time of the main urban area by 60%, significantly improves the fire emergency response capability, and is suitable for large-scale fire track data scenes.

The invention discloses a low-orbit satellite communication terminal power consumption optimization method, and relates to the technical field of satellite mobile communication and wireless communication terminal power consumption management. A candidate set is generated based on satellite ephemeris and shielding information, so that a terminal only scans a limited frequency band, and energy waste caused by full-frequency-band blind scanning is fundamentally avoided; in a dense urban scene, signal interruption is caused by high-rise buildings, and a traditional terminal needs to repeatedly scan to maintain connection, however, a predictive scanning mechanism of the method can activate scanning in advance before signal attenuation and reduce response delay, so that a power consumption curve is smoothed, and a power consumption peak value caused by sudden switching is avoided; secondly, the energy consumption perceptual sorting mechanism dynamically evaluates the power consumption performance of the candidate satellites through historical data and context features, and preferentially selects low-energy-consumption options, so that the scanning process is more targeted.

The invention provides an urban facility updating method and device based on a large language model, equipment and a medium, and relates to the technical field of urban planning, and the method comprises the steps: inputting a division cue word into a plan large language model, and obtaining a plurality of communities corresponding to a to-be-planned urban region outputted by the plan large language model; the division prompt words are used for indicating the plan big language model to divide the to-be-planned city area into a plurality of communities; the plan big language model is constructed based on a general multi-modal big language model; for each community, determining a target facility updating sub-scheme corresponding to the community through a plan big language model; and based on the target facility updating sub-schemes corresponding to all communities, determining an urban facility updating scheme corresponding to the to-be-planned urban area. According to the technical scheme, the urban facility updating scheme is constructed through the large language model, participation of experts and residents is not needed, negative influences caused by human factors are eliminated, and the efficiency and accuracy of planning the urban facility updating scheme are improved.

The invention discloses an element quantitative fusion-based urban coastal zone landscape evaluation and prediction method, which comprises the following steps of delimiting a vector boundary of a target urban coastal zone based on land change data, and dividing an area covered by the vector boundary into a plurality of grid units; associating the preprocessed spatial element data to the corresponding grid units, and constructing a structured spatial database; establishing a multi-element quantitative index system, calculating a combined weight, and outputting a comprehensive evaluation score of each grid unit through weighted summation; calculating global and local Moran's I indexes based on the comprehensive evaluation score, and identifying a spatial aggregation region and an abnormal region with statistical significance; obtaining dynamic monitoring data in a coastal zone range of a target urban area, and updating the structured spatial database; and based on the updated structured spatial database, comprehensively evaluating the score and the recognition results of the spatial accumulation area and the abnormal area, and generating an evaluation and prediction result.

The invention discloses a distributed MIMO (Multiple Input Multiple Output) integrated system and method based on a reconfigurable notch chaotic optoelectronic oscillator, belongs to the field of microwave photons, and solves the problems of spectrum resource conflict, difficulty in multi-node synchronization, discrete inductance functions and the like. According to the system, a plurality of independent chaotic OEOs are combined with an optical frequency comb to drive an FIR filtering effect, MIMO chaotic signals with reconfigurable notch frequency points and quantity are generated, and dynamic allocation of spectrum resources is realized. The notch frequency band is used as a communication channel embedded modulation signal, and supports multi-spectrum sharing with 2.4 G, 5G, Wi-Fi and the like; a non-notch frequency band is reserved as a radar signal, and the range resolution is improved by using the broadband characteristic of the chaotic waveform. The star topology optical network expands the coverage area of a distributed system, and a centralized processing architecture reduces the complexity of multi-node collaboration. The invention provides an integrated solution of high-precision environment perception and high-reliability communication for smart cities, Internet of Vehicles and the like, and is suitable for dense urban areas with resource shortage and dynamic multi-service environments.

The invention relates to the technical field of unmanned aerial vehicle ad hoc network cluster management and control scheme design based on intelligent street lamps and satellite communication, in particular to an unmanned aerial vehicle ad hoc network cluster management and control system based on intelligent street lamps and satellite communication. The system comprises an intelligent street lamp subsystem, a satellite communication subsystem, an unmanned aerial vehicle cluster node and a dynamic cooperative control platform. The innovative scheme comprises the following steps: (1) the multimode communication gateway realizes seamless conversion between a satellite protocol and a ground Internet of Things protocol; (2) a street lamp sensor generates a dynamic risk map to guide cluster obstacle avoidance; (3) supporting signal interruption emergency networking by a rapid clustering algorithm based on geometric topology; (4) task priority drives time slot distribution to improve communication efficiency; and (5) the satellite-street lamp-relay unmanned aerial vehicle multistage redundancy guarantee system is continuously controllable. According to the scheme, the communication reliability, the environmental adaptability and the cooperative capability of the cluster in a complex urban area are remarkably enhanced.

The invention relates to an air-ground integrated three-dimensional scene automatic modeling method, system and device and a storage medium, and the method comprises the steps: carrying out the point cloud fusion and coordinate registration of a preprocessed air original point cloud and a preprocessed ground original point cloud, and obtaining an air-ground fusion point cloud image; performing semantic segmentation on the air-ground fusion point cloud image through a pre-trained point cloud semantic segmentation network to obtain a composite point cloud cluster containing multiple semantic categories; extracting a building outer contour of the building type point cloud cluster, simplifying the building outer contour according to a preset simplification rule, and constructing a building three-dimensional simplified model according to the simplified outer contour; extracting category feature parameters of the non-building type point cloud clusters, searching a standard model conforming to the category feature parameters from the preset model library, and replacing the corresponding point cloud clusters with the standard model to obtain a non-building three-dimensional simplified model; and performing archiving according to the semantic layer to form a structured three-dimensional model of the to-be-modeled urban area.

The invention provides an urban area attribute determination method and device, equipment, a medium and a program product, relates to the technical field of artificial intelligence, and aims to solve the problem that urban area characterization methods in related technologies lack fine-grained sensing ability. The method comprises the following steps: acquiring first group movement data, wherein the first group movement data is used for representing position change information of a target user group in a plurality of areas within a preset time period; performing state updating on initial state vectors of a plurality of regions based on the first group mobile data to obtain region dynamic representations of the plurality of regions at each moment in the preset time period; and performing region attribute prediction based on the region dynamic representation of the plurality of regions at the target moment to obtain target attribute values of the plurality of regions at the target moment. According to the method, fine-grained urban region representation can be generated, and the accuracy of region attribute prediction is improved.

The invention relates to the technical field of urban drainage and waterlogging prevention, in particular to a plain river network large-scale drainage and waterlogging prevention project group optimization scheduling method and system. The method comprises the steps of determining a typical composite waterlogging event of a plain river network, establishing a hydrodynamic model to analyze the typical composite waterlogging event to identify key nodes of waterlogging, determining a linkage relationship between a drainage facility scheduling behavior and hydrological response of the key nodes, and establishing a multi-target optimization scheduling model with waterlogging risk minimization and operation cost optimization. And gradually decomposing a global scheduling target into a local scheduling target, establishing a mapping relationship between the local scheduling target and a flood drainage facility scheduling decision, obtaining a multi-target optimization scheduling model for potential individuals predicted in different candidate scheduling scheme populations, performing real solution, constructing an expectation improvement matrix, and selecting an optimal solution to obtain an optimal scheduling scheme. According to the method, the scheduling timeliness requirement is effectively met in combination with the machine learning prediction capability and the optimization algorithm, and optimal scheduling of the large-scale drainage and waterlogging prevention project group in the plain river network urban area is realized.

The invention provides an urban multi-modal large model training method, device and equipment and a medium, and relates to the technical field of artificial intelligence. Constructing an image-text interlaced data set according to the satellite image description text corresponding to each satellite image and the streetscape image description text corresponding to each streetscape image; and training the city multi-modal large model based on the image-text interlaced data set, and adjusting perceptron parameters corresponding to the perceptron in the city multi-modal large model and large language model parameters corresponding to the large language model to obtain a trained target city multi-modal large model. According to the technical scheme, the problems that in the prior art, a training data source is single, and images and texts are independently processed are solved, the trained target city multi-mode large model has good understanding on the city environment, and the space structure and function characteristics of a city can be comprehensively captured.

The invention discloses a dynamic cooperative scheduling method and system for an urban area tunnel network, and belongs to the technical field of tunnel network intelligent management, and the method comprises the steps of environment perception modeling, multi-dimensional prediction evaluation, dynamic cooperative scheduling and strategy execution optimization. According to the method, a space-time diagram multi-dimensional prediction method is adopted to perform multi-dimensional prediction evaluation, unified modeling and short-time prediction are performed on traffic operation, an air environment, an equipment state and an emergency channel condition in the tunnel network, potential congestion points, pollution hotspots and high-risk areas can be identified in advance, and the risk identification efficiency and accuracy are improved; a multi-objective optimization tunnel network intelligent scheduling method is adopted for dynamic cooperative scheduling, comprehensive balance of traffic smoothness, air quality and energy consumption is achieved, and on the premise that safety constraints are met, the performability of a scheduling strategy and the timeliness of emergency response are improved through layered optimization and an emergency priority strategy.

The invention discloses an SAR radiation cross calibration method based on an urban wide strong scattering reference point target, and the method comprises the steps: analyzing a meta-file of to-be-calibrated SAR data, extracting corresponding system parameter information and imaging region information, selecting multi-scene reference SAR data from calibrated historical SAR data, and extracting an absolute calibration constant; cutting and registering an area which coincides with the imaging area of the reference SAR data and the to-be-calibrated SAR data and is located in an urban area to make an SSDH data set; carrying out one-round screening and two-round screening on the SSDH data set based on a standard strong scattering point model, and extracting a radiation-stable high-value reference point target appearing in a full time domain; rCS data of the reference point target in the to-be-calibrated SAR data and RCS data of the reference point target in the reference SAR data are calculated; and comparing the RCS data of the same reference point target in the to-be-calibrated SAR data with the RCS data of the calibrated reference SAR data, and performing cross calibration to obtain an absolute radiometric calibration constant of the to-be-calibrated SAR data. According to the invention, low-cost and normalized SAR radiometric calibration processing is realized.

The invention discloses an urban logistics unmanned aerial vehicle take-off and landing point layout optimization method and system, and belongs to the technical field of path planning, and the method comprises the steps: taking all existing express cabinets in an urban region as a candidate take-off and landing point set, and obtaining the express cabinet transformation cost of each candidate take-off and landing point; obtaining the distribution cost from each candidate take-off and landing point to the demand point; determining customer coverage of all existing express cabinets in the urban area; obtaining all paths from each candidate take-off and landing point to the demand point without passing through the no-fly zone, and determining a plurality of take-off and landing point layout schemes corresponding to the selected take-off and landing points and the delivery paths based on all the paths as to-be-optimized individuals; a multi-objective optimization model is constructed by taking minimization of the sum of the transformation cost and the distribution cost of the express cabinet and maximization of the customer coverage degree as objectives, optimization is carried out on individuals to be optimized, and the optimal take-off and landing point layout and the planning result of the demand point range of the service of the take-off and landing point layout are determined. According to the method, reasonable and efficient operation of urban unmanned aerial vehicle logistics can be realized.

The invention discloses an unmanned aerial vehicle image intelligent perception plotting method and system based on view GIS fusion. The method comprises the steps that a sequence image of a target area is collected through an unmanned aerial vehicle platform; target detection, classification and tracking are carried out based on deep learning, and target pixel coordinates are identified; constructing an intelligent mapping model from a pixel coordinate system to a geographic coordinate system to realize geographic positioning of a target; precise space calibration is carried out on the illegal target; and in combination with space calibration, interactive plotting and visualization of target illegal behaviors are realized at a WebGIS end, and a structured law enforcement evidence packet is formed. According to the method, the POS data and the visual information are deeply fused, the dynamic projection plane estimation technology is adopted, the geographic positioning precision better than that of a traditional method is achieved, the method has obvious advantages especially in complex environments such as urban areas, and high positioning precision can be achieved.

The invention discloses a tunnel-pile interaction experiment method and device based on a 3D printing technology, and belongs to the technical field of civil engineering underground structure tests. The method comprises the steps that the geometric and mechanical similarity ratio is determined according to an engineering prototype, a tunnel lining model and a pile group model are prepared through the 3D printing technology, and controllable adjustment of the rigidity of the tunnel model is achieved by adjusting the type, the filling rate and the internal structure of a printing material; controllable adjustment of the rigidity of the pile foundation model is realized by adjusting the size of the magnetic field; the model is placed in a soil body groove, the shield tunnel excavation process is simulated, and deformation data of a tunnel and a pile foundation are collected through a PIV technology and a sensor. Accurate control over the rigidity of the tunnel and pile foundation model is achieved through 3D printing, the influence of shield tunnel construction on the pile group foundation can be simulated under the condition that the similarity criterion is met, and the device has the advantages of being adjustable in structure, high in experiment efficiency and the like and can be used for researching a dense urban area tunnel-pile deformation coupling mechanism and optimizing related engineering parameters.

The invention relates to the technical field of urban planning and spatial information, in particular to an urban landscape style assessment method and system based on three-dimensional reconstruction, and the method comprises the following steps: S1, generating a live-action three-dimensional model of a target urban area; s2, dividing the target urban area into a plurality of space grid units on a horizontal plane; s3, extracting three-dimensional visual feature parameters in each vision field range; s4, calculating a visual space oppression index according to the geometrical relationship of the buildings in the visual field range; s5, calculating a landscape style and feature comprehensive evaluation value of the space grid unit; and S6, mapping the comprehensive evaluation value of the landscape style to the geographic position of the landscape style, and generating an urban landscape style evaluation thermodynamic diagram. According to the method, through three-dimensional modeling, visual feature extraction and comprehensive quantitative evaluation, three-dimensional, standardized and visual evaluation of urban landscape styles and features is realized, and scientific support is provided for urban planning and styles and features management.

The invention relates to the technical field of three-dimensional modeling and geographic information processing, and discloses a three-dimensional city model generation optimization method and system, and the method comprises the steps: obtaining a central city area three-dimensional data set of a target city; generating a second fusion data set of unified three-dimensional point cloud representation; based on the key feature point set, a random consistency verification mechanism is adopted to execute preliminary registration operation; and generating a high-precision three-dimensional city model. In the prior art, in a multi-source three-dimensional data fusion process, coordinate system offset and scale difference exist among an oblique photography image, LiDAR point cloud, BIM data and a topographic map, and especially under a large-scale central urban area modeling condition, high-precision and automatic unified alignment is difficult to realize. And dislocation of building boundaries or fracture of terrain curved surfaces are caused. Due to the fact that depth feature extraction and cross-source feature alignment are combined with random consistency verification, the space consistency and modeling reliability of the three-dimensional city model are improved.

The invention relates to a city domain vehicle envelope line generation method and device, computer equipment and a storage medium, and the method comprises the steps that vehicle body data submitted by a first user, bogie data submitted by a second user and track data submitted by a third user are acquired, and the vehicle body data comprise allowable tolerances of vehicle parts in the manufacturing and mounting process; according to the vehicle body data, the bogie data and the track data, constructing a vehicle-track dynamics model; a dynamic load is loaded in the vehicle-track dynamics model to simulate vehicle operation, a corresponding displacement set of the vehicle at each moment is obtained, and the displacement set comprises the displacement corresponding to each observation point; and according to the displacement set corresponding to each moment and the tolerance, determining a dynamic envelope line changing along with time.