A method and device for modeling unmanned aerial vehicles for urban microenvironment assessment

Abstract

The application discloses a kind of unmanned aerial vehicle modeling is applied to the method and device of city microenvironment evaluation, belong to environmental meteorological monitoring technical field, the method includes based on unmanned aerial vehicle flight platform to city street building is tilted and is photographed, obtains topographic feature three-dimensional data;Generation area building and other topographic feature three-dimensional space layout model;Based on unmanned aerial vehicle flight platform obtains the low-altitude atmospheric environment parameter in region;Low-altitude atmospheric environment parameter is superimposed to three-dimensional space layout model, form space-time distribution assimilation data, and generate simulation region's complex boundary condition;Based on the complex boundary condition of simulation region and three-dimensional space layout model, using CFD method calculation obtains air flow field, space-time distribution of atmospheric pollutant concentration field and air quality index, complete city microenvironment evaluation;The application will unmanned aerial vehicle flight platform and corresponding technology be applied to city block scale microenvironment quantitative evaluation, convenient and fast, cost is relatively low.

Description

Technical Field

[0001] This invention relates to a method and apparatus for applying unmanned aerial vehicle (UAV) modeling to urban microenvironment assessment, belonging to the field of environmental meteorological monitoring technology. Background Technology

[0002] High-precision and realistic 3D street block models and environmental meteorological data are of great significance for improving the accuracy and precision of environmental meteorological variable simulation at the urban street block scale. They can also further enable precise assessment of urban air quality, ecological environment, and other aspects, providing a scientific basis for the refined management and control of atmospheric environmental pollution at the urban street block scale.

[0003] Chinese patent CN118133640A provides a method, device, and storage medium for assessing air pollution at the urban block scale, enabling high-precision air pollution assessment at the block scale. However, this method relies on manual data collection for urban modeling and the acquisition of environmental and meteorological spatiotemporal variables, which is very slow and costly. Furthermore, much of the collected data cannot be used in subsequent numerical models, resulting in low efficiency. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method and device for applying UAV modeling to urban micro-environment assessment. It integrates technologies such as oblique shooting modeling and environmental meteorological monitoring based on UAV flight platform with refined aerodynamic numerical methods at the street scale and applies them to urban micro-environment assessment. This method is convenient, fast, and low-cost.

[0005] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0006] In a first aspect, the present invention provides a method for applying unmanned aerial vehicle (UAV) modeling to urban microenvironment assessment, comprising:

[0007] The city streets and buildings are photographed at an angle using a drone flight platform to obtain three-dimensional data of the terrain and features.

[0008] Based on the 3D topographic and feature data, generate a 3D spatial layout model of buildings and other features within the area;

[0009] Based on the UAV flight platform equipped with microenvironment and micrometeorological monitoring equipment, low-altitude atmospheric environmental parameters in the region are obtained;

[0010] By overlaying low-altitude atmospheric environmental parameters onto a three-dimensional spatial layout model and using interpolation and data fusion techniques, spatiotemporal distribution assimilation data of environmental meteorological variables at the urban block scale are generated.

[0011] Based on spatiotemporal distribution assimilation data, complex boundary conditions for the simulated region are generated.

[0012] Based on the complex boundary conditions and three-dimensional spatial layout model of the simulated area, the spatiotemporal distribution of air flow field, atmospheric pollutant concentration field and air quality index are calculated using CFD method to complete the urban microenvironment assessment.

[0013] Furthermore, the method of acquiring three-dimensional terrain and feature data by obliquely photographing urban street buildings using a drone flight platform includes:

[0014] Use a drone equipped with a visible light oblique imaging device to perform high-frequency continuous strip-by-strip imaging of the area of ​​interest.

[0015] During filming, the drone recorded high-resolution footage from multiple angles to capture detailed information about surface buildings and other terrain features;

[0016] Maintain a continuous shooting frequency to ensure that the information repetition rate in the continuously generated photos reaches a set threshold, thereby acquiring three-dimensional terrain and feature data.

[0017] Furthermore, the method also includes: performing error correction on the image data obtained by tilted shooting, using the following formula:

[0018] (1);

[0019] (2);

[0020] In the formula, x represents the image point coordinates along the flight direction at the horizontal position after error correction, y represents the image point coordinates along the lateral direction at the horizontal position after error correction, x' represents the correction value for the error caused by film deformation along the flight direction at the horizontal position, and y' represents the correction value for the error caused by film deformation along the lateral direction at the horizontal position. This represents the correction value for the error caused by lens distortion along the heading direction in the horizontal position. dx represents the correction value for the error caused by lens distortion in the horizontal direction along the lateral direction, dy represents the correction value for the error caused by atmospheric refraction in the horizontal direction along the heading direction, δx represents the correction value for the error caused by the curvature of the Earth in the horizontal direction along the heading direction, and δy represents the correction value for the error caused by the curvature of the Earth in the horizontal direction along the lateral direction.

[0021] Furthermore, the step of generating a three-dimensional spatial layout model of buildings and other features within the area based on the three-dimensional terrain and feature data includes:

[0022] Import the 3D terrain and feature data acquired by the camera into 3D modeling software and algorithms;

[0023] The algorithm is used to process 3D terrain and feature data to generate 3D spatial coordinates of a large number of ground image points in the area of ​​interest.

[0024] Generate a 3D spatial layout model of buildings and other land features based on their 3D spatial coordinates.

[0025] Furthermore, the method of obtaining low-altitude atmospheric environmental parameters within the region based on the unmanned aerial vehicle (UAV) flight platform equipped with microenvironment and micrometeorological monitoring equipment includes:

[0026] Equip drones with microenvironment and microweather monitoring devices, including anemometers, hygrometers, thermometers, and air quality sensors;

[0027] During flight, the drone monitors and records low-altitude atmospheric environmental parameters in real time, including low-altitude wind speed, humidity, temperature information, and air quality data at the ground and low altitudes. The air quality data includes the concentration of air pollutants and the spatiotemporal distribution of atmospheric visibility. The air pollutants include PM2.5. 2.5 PM 10 CO and NO2.

[0028] Furthermore, based on the complex boundary conditions and three-dimensional spatial layout model of the simulated region, the spatiotemporal distribution of the airflow field, the atmospheric pollutant concentration field, and the air quality index are calculated using the CFD method, including:

[0029] The three-dimensional spatial layout model is imported into the aerodynamics calculation formula to generate a mesh and optimize the mesh quality. Finally, the mesh is exported.

[0030] Based on the complex boundary conditions of the grid and the simulated region, the spatiotemporal distribution of the air flow field, the atmospheric pollutant concentration field, and the air quality index are calculated.

[0031] The aerodynamic calculation formula is as follows:

[0032] (3);

[0033] (4);

[0034] In the formula Let be the fluid density, t be time, and u be the fluid velocity vector. For gradient operators, This represents the rate of change of fluid density over time. It represents the rate of change of velocity over time, reflecting the acceleration of the fluid. For the convection term, it describes the effect of fluid velocity on its own flow. For fluid pressure, The pressure gradient term represents the effect of pressure changes on fluid motion. Kinematic viscosity, The Laplace operator represents the spatial variation of the velocity field. This is the viscosity term, describing the viscous effect within the fluid. This is the external force term, representing the external force acting on the fluid.

[0035] Furthermore, the method also includes: generating a corresponding near-surface wind field or concentration field spatial grid numerical simulation field based on a three-dimensional spatial layout model, performing four-dimensional variational assimilation with environmental meteorological field monitoring spatial station data, and generating a high-resolution gridded environmental meteorological variable field of near-surface urban blocks;

[0036] The four-dimensional variational assimilation calculation formula is as follows:

[0037] (5);

[0038] (6);

[0039] In the formula, K represents the gain matrix. k Indicates the analysis-forecast cycle step number, y k For the observation vector, Indicates the first k Analysis field of time step, For the background field, H k For observation operators, variables in the model space are transformed to the observation space, M. k This is the forecast mode.

[0040] Furthermore, the method also includes: visualizing and interactively displaying the three-dimensional spatial layout model and its temporal dynamics through a user interface for quantitative assessment of the microenvironment at the urban block scale.

[0041] Secondly, the present invention provides an apparatus for applying drone modeling to urban micro-environment assessment, comprising:

[0042] The first acquisition module is used to acquire three-dimensional terrain and feature data obtained by obliquely photographing urban street buildings based on a drone flight platform.

[0043] The first generation module is used to generate a three-dimensional spatial layout model of buildings and other features within the area based on the three-dimensional terrain and feature data.

[0044] The second acquisition module is used to acquire low-altitude atmospheric environmental parameters in the area based on the microenvironment and micrometeorological monitoring equipment carried on the UAV flight platform.

[0045] The fusion module is used to overlay low-altitude atmospheric environmental parameters onto a three-dimensional spatial layout model. Through interpolation and data fusion techniques, it generates spatiotemporal distribution assimilation data of environmental meteorological variables at the urban block scale.

[0046] The second generation module is used to generate complex boundary conditions for the simulated region based on spatiotemporal distribution assimilation data.

[0047] The calculation module is used to calculate the spatiotemporal distribution of airflow field, atmospheric pollutant concentration field and air quality index based on the complex boundary conditions and three-dimensional spatial layout model of the simulated area using CFD methods, and to complete the urban micro-environment assessment.

[0048] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0049] Fourthly, the present invention provides a computer device, comprising:

[0050] Memory, used to store computer programs / instructions;

[0051] A processor for executing the computer program / instructions to implement the steps of any of the methods described above.

[0052] Fifthly, the present invention provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of any of the methods described above.

[0053] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0054] This invention provides a method and apparatus for applying unmanned aerial vehicle (UAV) modeling to urban microenvironment assessment, utilizing a UAV flight platform and related technologies for quantitative assessment of the microenvironment at the urban block scale. The UAV flight platform collects three-dimensional spatial location information of ground feature points and near-surface atmospheric environmental parameters to establish a refined three-dimensional model at the urban block scale. Based on this model, further simulations and calculations of atmospheric flow and pollutant diffusion at the block scale are conducted. This invention provides refined assessment of urban air quality and ecological environment, and offers technical support for related refined management and control.

[0055] The key technical point of this invention is that it utilizes a drone flight platform to perform three-dimensional modeling of terrain and features, and to collect low-altitude and near-ground environmental and meteorological data. This data can be integrated to generate initial boundary conditions for subsequent CFD numerical calculations. Ultimately, this technology will serve the work of three-dimensional refined micro-environment and micro-meteorological assessment at the urban block scale. Attached Figure Description

[0056] Figure 1 This is a schematic diagram of the overall technical process for integrating drone modeling and data monitoring technologies into urban micro-environment assessment;

[0057] Figure 2 This is a schematic diagram of the drone's start-up test flight in an embodiment of the present invention;

[0058] Figure 3 This is a schematic diagram of a multivariate linear equation that can be established by continuously acquiring images of the same location from different angles during the tilting shooting process of a drone and combining the three-dimensional position information of the shooting position.

[0059] Figure 4 This is a schematic diagram showing the partial effect of key areas within the aforementioned panoramic area;

[0060] Figure 5 This is a schematic diagram of a three-dimensional model of the terrain and features of a certain study area, established using a street-scale model.

[0061] Figure 6 This is a schematic diagram of the results of near-surface environmental meteorological assessment at the urban block scale based on the fusion technology of UAV modeling and data monitoring. The arrows indicate wind direction and the color codes indicate wind speed.

[0062] Figure 7 This is a schematic diagram of the results of near-surface environmental meteorological assessment at the urban block scale based on the fusion technology of UAV modeling and data monitoring. The arrows indicate wind direction and the color codes indicate turbulence intensity.

[0063] Figure 8 This is a schematic diagram of environmental meteorological assessment results applied to urban block-scale based on the fusion technology of UAV modeling and data monitoring. Streamlines represent airflow trajectories, and color codes represent wind speed.

[0064] Figure 9 This is a schematic diagram of environmental meteorological assessment results applied to urban block-scale environments based on the fusion technology of UAV modeling and data monitoring. Streamlines represent the trajectory of pollutant diffusion, and color bars represent pollutant concentrations. Detailed Implementation

[0065] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0066] Example 1: This example introduces a method for applying drone modeling to urban microenvironment assessment, including:

[0067] The city streets and buildings are photographed at an angle using a drone flight platform to obtain three-dimensional data of the terrain and features.

[0068] Based on the 3D topographic and feature data, generate a 3D spatial layout model of buildings and other features within the area;

[0069] Based on the UAV flight platform equipped with microenvironment and micrometeorological monitoring equipment, low-altitude atmospheric environmental parameters in the region are obtained;

[0070] By overlaying low-altitude atmospheric environmental parameters onto a three-dimensional spatial layout model and using interpolation and data fusion techniques, spatiotemporal distribution assimilation data of environmental meteorological variables at the urban block scale are generated.

[0071] Based on spatiotemporal distribution assimilation data, complex boundary conditions for the simulated region are generated.

[0072] Based on the complex boundary conditions and three-dimensional spatial layout model of the simulated area, the spatiotemporal distribution of air flow field, atmospheric pollutant concentration field and air quality index are calculated using CFD method to complete the urban microenvironment assessment.

[0073] The method for applying UAV modeling to urban micro-environment assessment provided in this embodiment involves the following steps:

[0074] 1. Oblique photography and modeling of urban street buildings based on UAV flight platform: Using UAVs equipped with visible light oblique photography equipment, high-frequency continuous strip photography is carried out on the area of ​​interest to record the surface buildings and other terrain features of the area of ​​interest from multiple angles and at high resolution. In addition, a certain frequency should be maintained in continuous shooting to ensure that the information in the continuously generated photos has a sufficient repetition rate (generally more than 70%), and finally obtain the relevant data files of terrain features.

[0075] 2. Based on the obtained terrain and feature data files, and with the help of 3D modeling algorithms and imaging software, generate the 3D spatial coordinates of a large number of ground image points in the area of ​​interest: filter and integrate the image data, atmospheric environmental parameters, and pollutant concentration data collected by the UAV flight platform, add ground control point measurement data, and use 3D modeling software to obtain the initial 3D model of the simulated area through aerial triangulation calculation, multi-view influence matching, point cloud model construction, and texture mapping;

[0076] Error correction is performed on the image data obtained by tilted shooting, using the following formula:

[0077] (1);

[0078] (2);

[0079] In the formula, x represents the image point coordinates along the flight direction at the horizontal position after error correction, y represents the image point coordinates along the lateral direction at the horizontal position after error correction, x' represents the correction value for the error caused by film deformation along the flight direction at the horizontal position, and y' represents the correction value for the error caused by film deformation along the lateral direction at the horizontal position. This represents the correction value for the error caused by lens distortion along the heading direction in the horizontal position. dx represents the correction value for the error caused by lens distortion in the horizontal position along the lateral direction, dy represents the correction value for the error caused by atmospheric refraction in the horizontal position along the heading direction, δx represents the correction value for the error caused by the curvature of the Earth in the horizontal position along the heading direction, and δy represents the correction value for the error caused by the curvature of the Earth in the horizontal position along the lateral direction.

[0080] Based on the data after error correction, a three-dimensional spatial layout model of buildings and other land features within the area is further generated.

[0081] 3. The environmental meteorological sensor based on the flight platform is used to collect low-altitude and near-surface atmospheric environmental parameters of the area of ​​interest, including but not limited to low-altitude wind speed, humidity and temperature information, and air quality data of the ground and low altitude, such as the concentration of major air pollutants and the spatiotemporal distribution information of atmospheric visibility.

[0082] The main air pollutants include, but are not limited to, PM2.5. 2.5 PM 10 The six atmospheric environmental parameters, including CO and NO2, as well as other air pollutants in specific industrial or process areas, such as volatile organic compounds emitted by human activities and natural vegetation, and malodorous gases such as methanethiol.

[0083] 4. The collected environmental and meteorological variables and their spatial distributions are superimposed into the three-dimensional spatial layout model of the city, interpolated, and the three-dimensional data fusion and post-processing are completed to form spatiotemporal distribution assimilation data of environmental and meteorological variables at the urban block scale, providing refined initial boundary conditions for the next step of numerical solution of air flow and pollution diffusion at the urban block scale.

[0084] The inventor provides a method, device and storage medium for assessing air pollution at the urban block scale in CN118133640A. This method enables high-precision numerical simulation of air pollution at the block scale. The spatiotemporal distribution of air flow field and air pollutant concentration field and air quality index of the area of ​​interest at the block scale are obtained through CFD method.

[0085] Its features include: importing the initial three-dimensional model into the aerodynamics calculation formula, generating a mesh and optimizing the mesh quality, and finally exporting the mesh;

[0086] The aerodynamic calculation formula is as follows:

[0087] (3);

[0088] (4);

[0089] In the formula Let be the fluid density, t be time, and u be the fluid velocity vector. For gradient operators, This represents the rate of change of fluid density over time. It represents the rate of change of velocity over time, reflecting the acceleration of the fluid. For the convection term, it describes the effect of fluid velocity on its own flow. For fluid pressure, The pressure gradient term represents the effect of pressure changes on fluid motion. Kinematic viscosity, The Laplace operator represents the spatial variation of the velocity field. This is the viscosity term, describing the viscous effect within the fluid. This is the external force term, representing the external force acting on the fluid.

[0090] 6. Based on the above three-dimensional model, generate a corresponding near-surface wind field or concentration field spatial grid numerical simulation field, and perform four-dimensional variational assimilation with the environmental meteorological field monitoring spatial station data to generate a more realistic near-surface urban block high-resolution gridded environmental meteorological variable field.

[0091] The four-dimensional variational assimilation calculation formula is as follows:

[0092] (5);

[0093] (6);

[0094] In the formula, K represents the gain matrix. k Indicates the analysis-forecast cycle step number, y k For the observation vector, Indicates the first k Analysis field of time step, For the background field, H k For observation operators, variables in the model space are transformed to the observation space, M. k This is the forecast mode.

[0095] 7. The refined spatial environment meteorological three-dimensional model and its temporal dynamics obtained from the monitoring and simulation calculations are visualized and interactively displayed through the user interface, which is used for quantitative assessment of the microenvironment at the urban block scale.

[0096] This embodiment applies an unmanned aerial vehicle (UAV) flight platform and related technologies to the quantitative assessment of the microenvironment at the urban block scale. The UAV flight platform collects three-dimensional spatial location information of ground feature points and near-surface atmospheric environmental parameters to establish a refined three-dimensional model at the urban block scale. Based on this model, further simulations and calculations of atmospheric flow and pollutant diffusion at the block scale are conducted. This invention provides technical support for refined assessment of urban air quality and the ecological environment, as well as related refined management and control.

[0097] The key technical point of this invention is the use of UAV flight platforms to perform 3D modeling of terrain and features, and to collect low-altitude and near-ground environmental and meteorological data, thereby enabling the fusion of these data to generate initial boundary conditions for subsequent CFD numerical calculations. This technology will ultimately serve the work of 3D refined microenvironment and micrometeorological assessment at the urban block scale.

[0098] The following description, in conjunction with a preferred embodiment, illustrates the content involved in the above embodiments.

[0099] The specific process of this embodiment is as follows: Figure 1 Using a drone flight platform, aerial photography is conducted on complex urban building blocks that require micro-environment assessment and management, and environmental meteorological data is collected. After data fusion and assimilation, high-resolution three-dimensional spatial complex boundary conditions of the region are generated. Further, a spatial unstructured grid required for numerical calculation is constructed. On this basis, numerical simulation is performed to generate a refined three-dimensional distribution of wind field, turbulence and concentration diffusion within the region.

[0100] Preparation:

[0101] Based on the needs of the target area, a detailed inspection is conducted on various aspects, including the compatibility of the UAV system, onboard battery power, and the working condition of sensors and cameras, to ensure the smooth progress of the mission and the orderly conduct of on-site surveying.

[0102] GPS calibration is performed on the drone to ensure sufficient satellite signal reception in open areas, and the calibration status is checked after connecting the drone to the software. Professional flight planning software is used to set up control points and plan flight routes for the target area, ensuring flight safety while maximizing the fulfillment of simulation requirements.

[0103] Step 1: The drone takes aerial photos along the prescribed route and collects environmental meteorological data and three-dimensional topographic and feature data;

[0104] After the equipment debugging and flight path mapping plan are confirmed, the UAV will take off as follows: Figure 3As shown. Following the prescribed flight path, the aircraft enters cruise mode and uses its equipped five-dimensional flight camera to photograph the ground and extract coordinate data. Under the premise of meeting flight attitude requirements, the aircraft will theoretically take multiple images of the same ground location; however, at specific flight paths, it can collect data from five different aerial angles at the same ground location.

[0105] Furthermore, by matching flight speed with shutter speed, multiple angles are used to capture continuous images of the same location. Then, combined with the 3D position information of the camera, a multivariate linear equation is established to solve for the 3D position coordinates of each image point. Finally, a high-resolution geometric shape of all terrain features within the area is generated, as shown in the specific imaging effect. Figure 4 As shown.

[0106] Meanwhile, the drone is equipped with meteorological sensors, including devices for detecting wind speed, humidity, temperature, and atmospheric pollutant concentrations, to collect environmental meteorological data of the area during flight. Data can be collected periodically or continuously and transmitted back to the ground station for analysis in real time.

[0107] The system will also capture and locate the main air pollution emission sources within the area, including traffic emissions from key roads, catering emissions, and residential emissions, and obtain real-time monitoring data on their emission intensity by replacing the existing pollution-related sensors.

[0108] Step 2: Perform multi-source fusion and post-processing of environmental meteorological data and 3D topographic and feature data.

[0109] Based on the above UAV imaging data acquisition results, a detailed 3D model was created within a 1km x 1km area surrounding the case location. The model effect is as follows. Figure 4

[0110] Furthermore, based on project requirements, the spatial range and computational grid resolution required for the final 3D numerical simulation are determined.

[0111] While prioritizing the distribution pattern of the flow field around the building, some irregular details and shape complexity of the building were appropriately simplified to reduce the number of meshes and numerical calculations required for subsequent 3D environmental meteorological variables. A specific 3D model example is shown below. Figure 5 .

[0112] The collected real-time emission intensity monitoring data and the obtained real-time monitoring data of regional environmental meteorological variables (mainly including wind speed, wind direction, surface temperature, humidity, etc.) are superimposed on the urban three-dimensional spatial layout model, interpolated, and the three-dimensional data fusion and post-processing are completed to form the spatiotemporal distribution assimilation data of environmental meteorological variables at the urban block scale, which provides refined initial boundary conditions for the next step of numerical solution of air flow and pollution diffusion at the urban block scale.

[0113] Step 3: Numerical Simulation of Street-Scale Micrometeorology and Microenvironment

[0114] The inventors provided a method, device and storage medium for assessing air pollution at the urban block scale in CN118133640A. This method enables high-precision numerical simulation of air pollution at the block scale. The spatiotemporal distribution of air flow field and air pollutant concentration field and air quality index of the area of ​​interest at the block scale are obtained through CFD methods.

[0115] Step 4: Assimilate the numerical simulation field using monitoring data to generate a more realistic, high-resolution, gridded environmental meteorological variable field for near-ground urban blocks.

[0116] The collection density of environmental meteorological field monitoring data is lower than that of topographic and ground feature data, but it is mainly located in the vertical space of the atmosphere (point or vertical column) rather than on the ground surface. It needs to be preprocessed by specialized environmental meteorological software (such as NCL, netCDF) to generate three-dimensional spatial station data.

[0117] After generating the corresponding near-surface wind field or concentration field spatial grid numerical simulation field based on the above-mentioned 3D building model, the environmental meteorological field monitoring spatial station data mentioned in this section are assimilated with it to improve the spatial resolution and accuracy of the final output results. The final simulation results are referenced. Figure 6 , Figure 7 , Figure 8 and Figure 9 .

[0118] Step 5: Based on the environmental meteorological field simulation results, combined with sensitivity experiments on the initial values ​​related to the layout of urban buildings and pollution sources, conduct scientific demonstrations of urban air quality attainment planning and emission reduction measures, including micro-environmental air quality assessment, assessment of the contribution of main pollutant components and major sources, and assessment of the effectiveness of regional governance decisions.

[0119] Example 2: This example provides a device for applying drone modeling to urban micro-environment assessment, comprising:

[0120] The first acquisition module is used to acquire three-dimensional terrain and feature data obtained by obliquely photographing urban street buildings based on a drone flight platform.

[0121] The first generation module is used to generate a three-dimensional spatial layout model of buildings and other features within the area based on the three-dimensional terrain and feature data.

[0122] The second acquisition module is used to acquire low-altitude atmospheric environmental parameters in the area based on the microenvironment and micrometeorological monitoring equipment carried on the UAV flight platform.

[0123] The fusion module is used to overlay low-altitude atmospheric environmental parameters onto a three-dimensional spatial layout model. Through interpolation and data fusion techniques, it generates spatiotemporal distribution assimilation data of environmental meteorological variables at the urban block scale.

[0124] The second generation module is used to generate complex boundary conditions for the simulated region based on spatiotemporal distribution assimilation data.

[0125] The calculation module is used to calculate the spatiotemporal distribution of airflow field, atmospheric pollutant concentration field and air quality index based on the complex boundary conditions and three-dimensional spatial layout model of the simulated area using CFD methods, and to complete the urban micro-environment assessment.

[0126] The specific functions of each module described above are explained in the relevant content of the method in Embodiment 1, and will not be repeated here.

[0127] Example 3: This example provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described in Example 1.

[0128] Example 4: This example provides a computer device, including:

[0129] Memory, used to store computer programs / instructions;

[0130] A processor for executing the computer program / instructions to implement the steps of any of the methods described in Embodiment 1.

[0131] Example 5: This example provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the method described in any one of Examples 1.

[0132] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

[0133] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0134] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0135] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0136] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0137] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this disclosure and not to limit its protection scope. Although this disclosure has been described in detail with reference to the above embodiments, those skilled in the art should understand that after reading this disclosure, they can still make various changes, modifications or equivalent substitutions to the specific implementation of the invention, but these changes, modifications or equivalent substitutions are all within the protection scope of the pending claims.

Claims

1. A method for applying unmanned aerial vehicle (UAV) modeling to urban microenvironment assessment, characterized in that, include: The city streets and buildings are photographed at an angle using a drone flight platform to obtain three-dimensional data of the terrain and features. Based on the 3D topographic and feature data, generate a 3D spatial layout model of buildings and other features within the area; Based on the UAV flight platform equipped with microenvironment and micrometeorological monitoring equipment, low-altitude atmospheric environmental parameters in the region are obtained; By overlaying low-altitude atmospheric environmental parameters onto a three-dimensional spatial layout model and using interpolation and data fusion techniques, spatiotemporal distribution assimilation data of environmental meteorological variables at the urban block scale are generated. Based on spatiotemporal distribution assimilation data, complex boundary conditions for the simulated region are generated. Based on the complex boundary conditions and three-dimensional spatial layout model of the simulated region, CFD methods are used to calculate the spatiotemporal distribution of airflow field, atmospheric pollutant concentration field, and air quality index, completing the urban microenvironment assessment, specifically including: The three-dimensional spatial layout model is imported into the aerodynamics calculation formula to generate a mesh and optimize the mesh quality. Finally, the mesh is exported. Based on the complex boundary conditions of the grid and the simulated region, the spatiotemporal distribution of the air flow field, the atmospheric pollutant concentration field, and the air quality index are calculated. The aerodynamic calculation formula is as follows: In the formula, ρ is the fluid density, t is time, and u is the fluid velocity vector. For gradient operators, This represents the rate of change of fluid density over time. It represents the rate of change of velocity over time, reflecting the acceleration of the fluid. This is the convection term, describing the effect of fluid velocity on its own flow, where p is the fluid pressure. The pressure gradient term represents the effect of pressure changes on fluid motion, where v is the kinematic viscosity. The Laplace operator represents the spatial variation of the velocity field. f is the viscosity term, describing the viscous effect inside the fluid, and f is the external force term, representing the external force acting on the fluid.

2. The method for applying UAV modeling to urban micro-environment assessment according to claim 1, characterized in that, The method of using an unmanned aerial vehicle (UAV) flight platform to perform oblique photography of urban streets and buildings to obtain three-dimensional terrain and feature data includes: Use a drone equipped with a visible light oblique imaging device to perform high-frequency continuous strip-by-strip imaging of the area of ​​interest. During filming, the drone recorded high-resolution footage from multiple angles to capture detailed information about surface buildings and other terrain features; Maintain a continuous shooting frequency to ensure that the information repetition rate in the continuously generated photos reaches a set threshold, thereby acquiring three-dimensional terrain and feature data.

3. The method for applying UAV modeling to urban micro-environment assessment according to claim 1, characterized in that, The method further includes: performing error correction on the image data obtained by tilted shooting, using the following formula: x = x' + Δx + dx + δx (1); y=y'+Δy+dy+δy (2); In the formula, x represents the image point coordinates along the flight direction at the horizontal position after error correction, y represents the image point coordinates along the lateral direction at the horizontal position after error correction, x' represents the correction value of the error caused by film distortion along the flight direction at the horizontal position, y' represents the correction value of the error caused by film distortion along the lateral direction at the horizontal position, Δx represents the correction value of the error caused by lens distortion along the flight direction at the horizontal position, Δy represents the correction value of the error caused by lens distortion along the lateral direction at the horizontal position, dx represents the correction value of the error caused by atmospheric refraction along the flight direction at the horizontal position, dy represents the correction value of the error caused by atmospheric refraction along the lateral direction at the horizontal position, δx represents the correction value of the error caused by the curvature of the Earth along the flight direction at the horizontal position, and δy represents the correction value of the error caused by the curvature of the Earth along the lateral direction at the horizontal position.

4. The method for applying UAV modeling to urban micro-environment assessment according to claim 1, characterized in that, The process of generating a three-dimensional spatial layout model of buildings and other features within the area based on three-dimensional terrain and feature data includes: Import the 3D terrain and feature data acquired by the camera into 3D modeling software and algorithms; The algorithm is used to process 3D terrain and feature data to generate 3D spatial coordinates of a large number of ground image points in the area of ​​interest. Generate a 3D spatial layout model of buildings and other land features based on their 3D spatial coordinates.

5. The method for applying UAV modeling to urban micro-environment assessment according to claim 1, characterized in that, The method involves using a drone flight platform equipped with microenvironment and micrometeorological monitoring equipment to obtain low-altitude atmospheric environmental parameters within the region, including: Equip drones with microenvironment and microweather monitoring devices, including anemometers, hygrometers, thermometers, and air quality sensors; During flight, the drone monitors and records low-altitude atmospheric environmental parameters in real time, including low-altitude wind speed, humidity, temperature information, and air quality data at the ground and low altitudes. The air quality data includes the concentration of air pollutants and the spatiotemporal distribution of atmospheric visibility. The air pollutants include PM2.

5. 2.5 PM 10 CO and NO2.

6. The method for applying UAV modeling to urban microenvironment assessment according to claim 1, characterized in that, The method further includes: generating a corresponding near-surface wind field or concentration field spatial grid numerical simulation field based on a three-dimensional spatial layout model, performing four-dimensional variational assimilation with environmental meteorological field monitoring spatial station data, and generating a high-resolution gridded environmental meteorological variable field of near-surface urban blocks; The four-dimensional variational assimilation calculation formula is as follows: In the formula, K represents the gain matrix, k represents the analysis-forecast cycle step number, and y k For the observation vector, Let the analysis field at time step k be denoted as . For the background field, H k For observation operators, variables in the model space are transformed to the observation space, M. k This is the forecast mode.

7. The method for applying UAV modeling to urban micro-environment assessment according to claim 1, characterized in that, The method also includes: visualizing and interactively displaying the three-dimensional spatial layout model and its temporal dynamics through a user interface for quantitative assessment of the microenvironment at the urban block scale.

8. A device for applying unmanned aerial vehicle (UAV) modeling to urban microenvironment assessment, characterized in that, include: The first acquisition module is used to acquire three-dimensional terrain and feature data obtained by obliquely photographing urban street buildings based on a drone flight platform. The first generation module is used to generate a three-dimensional spatial layout model of buildings and other features within the area based on the three-dimensional terrain and feature data. The second acquisition module is used to acquire low-altitude atmospheric environmental parameters in the area based on the microenvironment and micrometeorological monitoring equipment carried on the UAV flight platform. The fusion module is used to overlay low-altitude atmospheric environmental parameters onto a three-dimensional spatial layout model. Through interpolation and data fusion techniques, it generates spatiotemporal distribution assimilation data of environmental meteorological variables at the urban block scale. The second generation module is used to generate complex boundary conditions for the simulated region based on spatiotemporal distribution assimilation data. The computation module, based on the complex boundary conditions and three-dimensional spatial layout model of the simulated area, uses CFD methods to calculate the spatiotemporal distribution of airflow field, atmospheric pollutant concentration field, and air quality index, completing the urban microenvironment assessment. Specifically, it includes: The three-dimensional spatial layout model is imported into the aerodynamics calculation formula to generate a mesh and optimize the mesh quality. Finally, the mesh is exported. Based on the complex boundary conditions of the grid and the simulated region, the spatiotemporal distribution of the air flow field, the atmospheric pollutant concentration field, and the air quality index are calculated. The aerodynamic calculation formula is as follows: In the formula, ρ is the fluid density, t is time, and u is the fluid velocity vector. For gradient operators, This represents the rate of change of fluid density over time. It represents the rate of change of velocity over time, reflecting the acceleration of the fluid. This is the convection term, describing the effect of fluid velocity on its own flow, where p is the fluid pressure. The pressure gradient term represents the effect of pressure changes on fluid motion, where v is the kinematic viscosity. The Laplace operator represents the spatial variation of the velocity field. f is the viscosity term, describing the viscous effect inside the fluid, and f is the external force term, representing the external force acting on the fluid.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When executed by a processor, the program implements the steps of the method described in any one of claims 1-7.

Images