Method for generating an air quality model and electronic device

Abstract

The present disclosure relates to a method for generating an air quality model and an electronic device, comprising: obtaining geographical information of a three-dimensional air quality query area and grid data of a three-dimensional grid of the air quality query area; the air quality query area comprising three-dimensional and top-to-bottom air environment layers and geographical layers; for each three-dimensional grid, obtaining a visual air environment feature of the three-dimensional grid according to at least one of meteorological data and pollutant concentration data of the three-dimensional grid; rendering the grid data in the three-dimensional grid corresponding to the grid data in the air environment layers, and rendering the geographical information in the geographical layers, to generate and display an air quality model reflecting the air environment condition of the air quality query area. The method for generating an air quality model proposed by the present disclosure can more intuitively display the visual effect of the air environment of the air quality query area.

Description

Technical Field

[0001] This disclosure relates to the field of environmental protection technology, and more specifically, to a method and electronic device for generating an air quality model. Background Technology

[0002] Currently, the visualization of air quality data in a certain area is mainly presented in the form of two-dimensional charts, static pictures, or simple overlays of graphs, which cannot intuitively and dynamically reflect the true distribution of pollutants in three-dimensional space. Summary of the Invention

[0003] To overcome the problems existing in related technologies, this disclosure provides a method and electronic device for generating an air quality model.

[0004] According to a first aspect of the present disclosure, a method for generating an air quality model is provided, comprising: The system acquires the geographic information of a three-dimensional air quality query area and the grid data of the three-dimensional grid of the air quality query area; the air quality query area includes a three-dimensional air environment layer and a geographic layer from top to bottom, the air environment layer is divided into multiple three-dimensional grids, and the grid data includes at least one of meteorological data and pollutant concentrations; For each of the three-dimensional grids, a visualized air environment feature of the three-dimensional grid is obtained based on the meteorological data of the three-dimensional grid and at least one of the pollutant concentrations; the visualized air environment feature is used to characterize the visualization effect of the air environment in the air quality query area; The grid data is rendered into the 3D grid corresponding to the grid data in the air environment layer, and the geographic information is rendered into the geographic layer to generate and display an air quality model that reflects the air environment conditions of the air quality query area.

[0005] In some possible implementations, for each of the three-dimensional grids, based on the meteorological data of the three-dimensional grid and the pollutant concentration, the visualized air environment characteristics of the three-dimensional grid are obtained, including: For each of the three-dimensional grids, a visual pollution level feature corresponding to the pollutant concentration of the three-dimensional grid is queried from the pollutant mapping table, and a visual wind speed feature of the three-dimensional grid is obtained based on the meteorological data of the three-dimensional grid; wherein, the visual air environment feature includes the visual pollution level feature and the visual wind speed feature, the visual pollution level feature is used to characterize the pollution level of the pollutant concentration, and the visual wind speed feature is used to characterize the atmospheric flow trajectory of the three-dimensional grid. Rendering the mesh data into the atmospheric environment layer corresponding to the 3D mesh data includes: For each of the three-dimensional grids, the visualized pollution level features and the visualized wind speed features of the three-dimensional grids are rendered on the three-dimensional grids.

[0006] In some possible implementations, for each of the three-dimensional grids, based on the meteorological data of the three-dimensional grids, the visualized air environment characteristics of the three-dimensional grids are obtained, including: For each of the three-dimensional grids, the visualized wind speed characteristics and visualized non-wind speed characteristics of the three-dimensional grids are obtained based on the meteorological data of the three-dimensional grids; wherein, the visualized air environment characteristics include the visualized wind speed characteristics and the visualized non-wind speed characteristics, the visualized wind speed characteristics are used to characterize the atmospheric flow trajectory of the three-dimensional grids, and the visualized non-wind speed characteristics are used to characterize the visualization effect of the intensity of the non-wind speed data of the three-dimensional grids. Rendering the mesh data into the atmospheric environment layer corresponding to the 3D mesh data includes: For each of the three-dimensional grids, the visualized wind speed features and the visualized non-wind speed features of the three-dimensional grids are rendered on the three-dimensional grids.

[0007] In some possible implementations, for each of the three-dimensional grids, a visual pollution level feature corresponding to the pollutant concentration of the three-dimensional grid is queried from a pollutant mapping table, including: The pollutant concentration corresponding to the pollutant concentration in the 3D grid is retrieved from the pollutant mapping table; the visualized pollution level features include the pollution color and transparency, and the color depth of the pollution color is positively correlated with the transparency. For each of the three-dimensional grids, the visualized pollution level features and the visualized wind speed features of the three-dimensional grids are rendered on the three-dimensional grids, including: The pollutant concentration corresponding to the pollutant color and transparency, along with the visualized wind speed features, are rendered onto the 3D grid.

[0008] In some possible implementations, obtaining the grid data of the three-dimensional grid of the air quality query area includes: In response to a query operation on the air quality query area, the pollutant concentrations of the air quality query area at different time points are filtered from multiple areas. In response to a query operation on the air quality status of the air quality query area at a specified time point, the pollutant concentration of the air quality query area at the specified time point is filtered from the pollutant concentrations at different time points; In response to a query operation on the air quality status of a specified pollutant in the air quality query area, the pollutant concentration of the specified pollutant is filtered out from the pollutant concentration at a specified time point.

[0009] In some possible implementations, after generating and displaying an air quality model reflecting the air environment conditions of the air quality query area, the method further includes: In response to a sectioning operation on at least one side of the air quality model, a specified three-dimensional region is segmented from the air quality model, and the air environment conditions and geographical information of the three-dimensional region are displayed.

[0010] In some possible implementations, obtaining the grid data of the three-dimensional grid of the air quality query area includes: obtaining the grid data of the three-dimensional grid of the air quality query area at different time points; Rendering the grid data into the three-dimensional grid corresponding to the grid data in the air environment layer includes: in response to a playback operation of the air quality status of the air quality query area, dynamically rendering the grid data at different time points to the three-dimensional grid corresponding to the grid data in chronological order, so as to play the evolution process of the air quality status of the air quality query area over time.

[0011] In some possible implementations, the method further includes: When playing the evolution of air quality status in the air quality query area over time, in response to an air quality query operation at any specified time point on the progress bar, the grid data of the specified time point is rendered onto the 3D grid to display the air quality status of the air quality query area at the specified time point; wherein, the progress bar is the playback progress displayed during the playback of the air quality status of the air quality query area.

[0012] In some possible implementations, the method further includes: In response to a touch operation on the 3D grid, the grid data is displayed around the 3D grid.

[0013] According to a second aspect of the present disclosure, an electronic device is provided, comprising: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method for generating the air quality model provided in the first aspect.

[0014] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects: An air quality model reflecting air quality conditions can be displayed on a three-dimensional air quality query area. Through this air quality model, users can intuitively see the distribution and display effect of at least one of the three-dimensional meteorological data and pollutant concentration data in the geographical environment, which makes the overall air quality data visualization effect better and makes it easier for users to intuitively understand the air quality and air environment of the air quality query area.

[0015] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0017] Figure 1 This is a flowchart illustrating the steps of a method for generating an air quality model according to an exemplary embodiment.

[0018] Figure 2 This is a flowchart illustrating the steps of a method for generating an air quality model according to an exemplary embodiment.

[0019] Figure 3 This is a schematic diagram illustrating an air quality model segmented into an air environment layer and a geographic layer according to an exemplary embodiment.

[0020] Figure 4 This is a schematic diagram illustrating an air quality model overlaid on geographic information, according to an exemplary embodiment.

[0021] Figure 5 This is a flowchart illustrating the steps of a method for generating an air quality model according to an exemplary embodiment.

[0022] Figure 6 This is a schematic diagram illustrating an air quality model segmented into an air environment layer and a geographic layer according to an exemplary embodiment.

[0023] Figure 7 This is a flowchart illustrating the steps of a method for generating an air quality model according to an exemplary embodiment.

[0024] Figure 8 This is a flowchart illustrating the steps of a method for generating an air quality model according to an exemplary embodiment.

[0025] Figure 9 This is a schematic diagram illustrating an air quality model cut along different directions according to an exemplary embodiment.

[0026] Figure 10 This is a flowchart illustrating the steps of a method for generating an air quality model according to an exemplary embodiment.

[0027] Figure 11 This is a schematic diagram illustrating a timeline for displaying an air quality model, according to an exemplary embodiment.

[0028] Figure 12 This is a flowchart illustrating the steps of a method for generating an air quality model according to an exemplary embodiment.

[0029] Figure 13 This is a schematic diagram illustrating a three-dimensional grid display of meteorological data in a clickable air quality model according to an exemplary embodiment.

[0030] Figure 14 This is a block diagram illustrating an electronic device according to an exemplary embodiment.

[0031] Figure 15 This is a block diagram illustrating an electronic device according to an exemplary embodiment. Detailed Implementation

[0032] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0033] It should be noted that all actions involving the acquisition of signals, information, or data in this disclosure are carried out in compliance with the relevant data protection laws and policies of the country where the location is situated, and with authorization from the owner of the relevant device.

[0034] Figure 1 This is an exemplary embodiment of the present disclosure, used to illustrate a method for generating an air quality model, the method comprising the following steps: S101, Obtain the geographic information of the three-dimensional air quality query area and the grid data of the three-dimensional grid of the air quality query area.

[0035] Optionally, referring to Figure 3, the air quality query area is a three-dimensional spatial area to be displayed by the user. It is a three-dimensional space composed of the ground and the air environment above the ground. The three-dimensional air quality query area can be divided into a three-dimensional air environment layer and a geographic layer. The air environment layer is located above the geographic layer. The air environment layer is used to carry the display effect of the air environment, and the geographic layer is used to carry the display effect of the geographic environment.

[0036] The air environment layer is divided into multiple three-dimensional grids. Each three-dimensional grid represents a sub-three-dimensional space in the three-dimensional air quality query area. This three-dimensional grid can be called a voxel. Each three-dimensional grid has its own geographic coordinates, which can be represented by three-dimensional coordinates, such as xyz coordinates, longitude, latitude, and altitude.

[0037] Among them, geographic information is used to represent spatial maps of the Earth's surface topography. This geographic information may include digital elevation models, administrative boundaries, city locations, etc. Among them, digital elevation models are three-dimensional data models used for calculation, which can express each three-dimensional space in the entire air quality query area through three-dimensional coordinates such as longitude, latitude, and altitude.

[0038] Each 3D grid contains at least one type of data: meteorological data and pollutant concentration data.

[0039] Meteorological data reflects the air environment status of this three-dimensional grid. This meteorological data includes wind speed data and non-wind speed data of the three-dimensional grid. Wind speed data includes wind speed, wind direction, and other data, while non-wind speed data includes temperature, humidity, air pressure, precipitation, and other data.

[0040] Pollutant concentration is used to characterize the air quality status of this three-dimensional grid. The pollutant concentration can include the hourly pollutant concentration of any pollutant such as PM2.5, PM10, O3, NO2, SO2, and CO.

[0041] Understandably, three-dimensional meteorological data and pollutant concentrations can be output from different gridded forecasting models, such as WRF-Chem (Weather Research and Forecasting Model coupled with Chemistry), CMAQ (Community Multiscale Air Quality Modeling System), and NAQPMS (Nested Air Quality Prediction Modeling System). For meteorological data, the meteorological field of the air quality query area can be input into the gridded forecasting model to obtain meteorological data for different three-dimensional grids. For pollutant concentrations, pollutant parameters such as pollutant emissions and station concentrations obtained from various monitoring stations in the air quality query area can be input into the gridded forecasting model to obtain pollutant concentrations for different three-dimensional grids.

[0042] Of course, these gridded forecasting models can also predict real-time and / or future meteorological data based on historical meteorological data and weather fields, and can also predict real-time and / or future pollutant concentrations based on historical pollutant concentrations and pollutant emissions.

[0043] S102, for each of the three-dimensional grids, based on at least one of the meteorological data and the pollutant concentration data of the three-dimensional grid, the visualized air environment characteristics of the three-dimensional grid are obtained.

[0044] The visualized air environment features are used to characterize the visualization effect of the air environment in the air quality query area. They reflect the quality and distribution of air quality in various geographical environments within the query area. These visualized air environment features can include features based on at least one of the following elements: visualized pollution level features, visualized wind speed features, and visualized non-wind speed features. The visualized pollution level features characterize the pollution level of the pollutant concentration; the visualized wind speed features characterize the atmospheric flow trajectory of the three-dimensional grid; and the visualized non-wind speed features characterize the visualization effect of the intensity of the non-wind speed data in the three-dimensional grid.

[0045] S103, the grid data is rendered into the three-dimensional grid corresponding to the grid data in the air environment layer, and the geographic information is rendered into the geographic layer, generating and displaying an air quality model that reflects the air environment status of the air quality query area.

[0046] Optionally, geographic information can be rendered on the bottom geographic layer first, and then the visualized air environment features can be rendered on the top air environment layer, so that the three-dimensional visualized air environment features can be overlaid on the geographic information for display.

[0047] For the geographic layer of the air quality model, a global topographic map or a custom topographic map (DEM) can be imported to obtain a topographic map for each coordinate, and then the topographic map can be loaded and rendered into the geographic layer.

[0048] It is understood that the air quality model disclosed herein utilizes WebGL (Web Graphics Library) 3D graphics technology. This technology allows for the rendering of 3D graphics / scenes directly in a browser without requiring plugins on electronic devices, thus supporting the display of the air quality model on a webpage. This web browser can be extended with a 3D geographic information visualization engine (such as Cesium), capable of loading 3D geographic information and time-series data (such as pollutant concentrations or meteorological data at different points in time). However, this visualization engine does not integrate multi-source pollutant concentration and meteorological data. This disclosure integrates the evolution of pollutant concentration and meteorological data into the 3D geographic information provided by the visualization engine, thereby providing a 3D diffusion process of pollutants changing with meteorological data such as wind speed and temperature, and updating the 3D air quality model in real time.

[0049] The above technical solution can display an air quality model that reflects the air quality status on a three-dimensional air quality query area. Users can intuitively see the distribution and display effect of at least one of the three-dimensional meteorological data and pollutant concentration data in the geographical environment through the air quality model, which makes the overall air quality data visualization effect better and makes it easier for users to intuitively understand the air quality and air environment of the air quality query area.

[0050] Figure 2 This is an exemplary embodiment of the present disclosure, used to illustrate an exemplary embodiment of rendering wind speed data and pollutant concentration from meteorological data in a three-dimensional grid onto a geographic environment, including the following steps: S104, for each of the three-dimensional grids, query the pollutant mapping table for the visual pollution level feature corresponding to the pollutant concentration of the three-dimensional grid, and obtain the visual wind speed feature of the three-dimensional grid based on the meteorological data of the three-dimensional grid.

[0051] In this embodiment, the air environment layer can be an air pollution display layer, used to display the degree of pollution of pollutants in the air and the trajectory of atmospheric flow.

[0052] The pollutant mapping table records the visual pollution level characteristics corresponding to each pollutant concentration. These visual pollution level characteristics characterize the degree of pollution at each pollutant concentration; for example, the higher the pollutant concentration, the higher the corresponding visual pollution level. This visual pollution level includes pollution color; the higher the pollutant concentration, the darker the corresponding pollution color. For instance, as pollutant concentrations increase sequentially, different pollution colors such as white, light yellow, yellow, dark yellow, and red can be used to represent these sequential increases.

[0053] The visualized wind speed feature is used to characterize the atmospheric flow trajectory within a 3D grid, including the airflow's speed (wind speed) and direction (wind direction). The atmospheric flow trajectory within the 3D grid represents the movement of airflow under the influence of wind direction and speed. The length of this trajectory represents the distance the airflow travels under the influence of wind speed and direction; a longer trajectory indicates a greater distance traveled and a wider area of ​​influence. The visualized wind speed feature can also include wind speed color, which represents the magnitude of the wind speed. A higher wind speed corresponds to a darker color. This wind speed color can be rendered onto the atmospheric flow trajectory, thus displaying not only the airflow's range but also the corresponding wind speed. It's understandable that airflow carries pollutants, so the atmospheric flow trajectory can also be used to characterize the movement of pollutants.

[0054] A wind speed mapping table can also be pre-configured, which records different levels of wind speed and their corresponding colors. For each 3D grid, the wind speed color corresponding to the wind speed of that 3D grid can be obtained from the wind speed mapping table.

[0055] The steps for obtaining the visualized wind speed characteristics of a three-dimensional grid based on meteorological data include: obtaining the location of pollutants at multiple time points based on the wind speed, wind direction, and time step in the meteorological data of the three-dimensional grid; and then connecting the locations of pollutants at multiple time points to form an atmospheric flow trajectory to obtain the visualized wind speed characteristics.

[0056] For example, the wind speed and direction in this meteorological data can include east-west wind speed (U component) and north-south wind speed (V component). The airflow in the 3D grid is abstracted as a particle with the original coordinates (x, y). If the wind speed is U = 2 m / s (eastward) and V = 1 m / s (northward), and the time step is Δt, the distance the particle moves eastward is calculated as U × Δt = 2 × 0.1 = 0.2 m, and the distance it moves northward is V × Δt = 1 × 0.1 = 0.1 m. Finally, the new position of the particle after moving under the wind speed and direction for a time step Δt is (x + 0.2, y + 0.1). The particle position is calculated repeatedly for each time step, and the particle positions at multiple time points are connected to form a line to obtain the particle's trajectory. This trajectory of the particle is the atmospheric flow trajectory.

[0057] S105, for each of the three-dimensional grids, the visualized pollution level features and the visualized wind speed features of the three-dimensional grids are rendered on the three-dimensional grids, and the geographic information is rendered on the geographic layer, generating and displaying an air quality model that reflects the air environment conditions of the air quality query area.

[0058] For example, see Figure 3 As shown, taking the visualization of pollutant levels, including pollution color, and the visualization of wind speed, including atmospheric flow trajectories, as examples, for each 3D grid in the air environment layer of the air quality query area, the pollution color and atmospheric flow trajectory of the 3D grid can be rendered on the 3D grid; and the geographic information is rendered on the geographic layer located below the air environment layer, thereby generating and displaying... Figure 4 The air quality model shown reflects the current atmospheric flow and air pollution status above the geographical environment of the air quality query area.

[0059] Optionally, the atmospheric flow trajectory displayed on the air quality model has a lifecycle, which refers to the display duration of the atmospheric flow trajectory from its appearance to its disappearance. For example, the atmospheric flow trajectory can be displayed intermittently at 1-second intervals. It can also dynamically display the atmospheric flow trajectory according to the modified lifecycle in response to user modifications. Of course, users can also modify the number of 3D grids and the appearance of the 3D grids in the air quality query area.

[0060] The above technical solution renders the pollution color and atmospheric flow trajectory of the 3D grid onto the 3D grid; and after rendering the geographic information on the geographic layer located below the air environment layer, this layered rendering structure with the air environment layer on top and the geographic layer below allows the generated air quality model to intuitively reflect the current state of atmospheric flow and air pollution above the geographic environment. On the one hand, it avoids the visual confusion caused by the superposition of multi-source data, and on the other hand, it allows users to more intuitively understand the air conditions in various environments in the current air quality query area.

[0061] Figure 5 This is an exemplary embodiment of the present disclosure, used to illustrate an exemplary embodiment of rendering wind speed data and non-wind speed data from a three-dimensional grid of meteorological data onto a geographic environment, including the following steps: S106, for each of the three-dimensional grids, obtain the visualized wind speed characteristics and visualized non-wind speed characteristics of the three-dimensional grid based on the meteorological data of the three-dimensional grid.

[0062] In this embodiment, the air environment layer can be a meteorological display layer, used to display the intensity of non-wind speed data in the air and the atmospheric flow trajectory.

[0063] Among them, the visualized non-wind speed feature is used to characterize the intensity of non-wind speed data in the three-dimensional grid, such as the intensity of non-wind speed data such as temperature, humidity, air pressure and rainfall. This visualized non-wind speed feature can be represented by at least one parameter such as color, data label, and equal face value. Taking color as an example, the higher the temperature, the more reddish the corresponding color; the lower the temperature, the more blue the corresponding color.

[0064] A non-wind speed mapping table can be pre-configured. The non-wind speed mapping table records non-wind speed data of different degrees and corresponding visualized non-wind speed features. For each 3D grid, the visualized non-wind speed features corresponding to the non-wind speed data of that 3D grid can be obtained from the non-wind speed mapping table.

[0065] S107, for each of the three-dimensional grids, the visualized wind speed features and the visualized non-wind speed features of the three-dimensional grids are rendered on the three-dimensional grids, and the geographic information is rendered on the geographic layer, generating and displaying an air quality model that reflects the air environment conditions of the air quality query area.

[0066] For example, see Figure 6As shown, taking the visualization of non-wind speed features including temperature values ​​and the visualization of wind speed features including atmospheric flow trajectories as examples, for each three-dimensional grid in the air environment layer of the air quality query area, the temperature values ​​and atmospheric flow trajectories of the three-dimensional grid can be rendered on the three-dimensional grid; and the geographic information is rendered on the geographic layer located below the air environment layer, thereby generating and displaying an air quality model that can reflect the current state of atmospheric flow and temperature distribution above the geographic environment of the air quality query area.

[0067] The above technical solution renders the visual non-wind speed features and atmospheric flow trajectories of the 3D grid onto the 3D grid. After rendering the geographic information on the geographic layer below the air environment layer, this layered rendering structure, with the air environment layer on top and the geographic layer below, allows the generated air quality model to intuitively reflect the current atmospheric flow status above the geographic environment and the intensity distribution of non-wind speed data. On the one hand, it avoids the visual confusion caused by the superposition of multi-source data, and on the other hand, it allows users to more intuitively understand the meteorological conditions such as temperature, humidity, and air pressure in the current air quality query area.

[0068] Figure 7 This is an exemplary embodiment involving steps S104 and S105 above, which is used to interpret an exemplary embodiment of generating and displaying an air quality model reflecting the air environment conditions of the air quality query area by rendering the visualized pollution level features and visualized wind speed features of the three-dimensional grid on the three-dimensional grid and rendering geographic information on the geographic layer, including the following steps: S104-1, Query the pollutant color and transparency corresponding to the pollutant concentration of the three-dimensional grid from the pollutant mapping table.

[0069] Among them, the visualization of pollution level features includes the pollution color and transparency corresponding to the pollution concentration. The color depth of the pollution color is positively correlated with the transparency of the pollution color. For example, the darker the pollution color, the higher the transparency of the corresponding pollution color. Thus, the darker the pollution color rendered on the 3D mesh, the higher the transparency of the 3D mesh.

[0070] Optionally, the transparency of the pollution color can also be modified in response to the user's setting of the overall transparency of the pollution color.

[0071] S105-1, The pollution color and transparency corresponding to the pollutant concentration of the three-dimensional grid and the visualized wind speed feature are rendered on the three-dimensional grid, and the geographic information is rendered on the geographic layer, generating and displaying an air quality model that reflects the air environment status of the air quality query area.

[0072] Optionally, for the air environment layer and the geographic layer, users can set different display modes. In different display modes, the air environment layer and the geographic layer can be displayed separately or overlaid.

[0073] For example, if a user triggers the overlay display mode of the air environment layer and the geographic layer, and the air environment layer is the air pollution display layer, the air quality model will overlay and display the visual pollution level features and geographic information, and the presented air quality model will be a display effect of pollution clouds forming on the geographic terrain.

[0074] For example, if a user triggers the mode that displays geographic information separately, the air quality model will display geographic terrain separately.

[0075] Optionally, after rendering the geographic information onto the ground area of ​​the air quality query area, different forms of geographic information can be displayed on the ground of the air quality query area in response to the user's switching operation on the geographic information.

[0076] For example, different forms of geographic information are used to represent geographic information and display it in different forms in the air quality model. These different forms of geographic information include topography, administrative divisions, rivers and roads, monitoring stations (monitoring stations are used to monitor pollutant concentrations), etc. Users can switch the ground area of ​​the air quality model to be displayed in the form of topography, or in the form of administrative divisions (showing the boundaries of different administrative divisions such as Province A and Province B), or in the form of monitoring stations, showing the layout of monitoring stations in the entire ground area.

[0077] Through the above technical solution, firstly, by rendering pollution color and transparency onto the 3D grid of the second layer in the air quality query area, and rendering geographic information onto the air environment layer in the air quality query area, since the color depth of pollution color is positively correlated with transparency, the deeper the pollution color, the higher the transparency of the corresponding pollution color. This improves the visualization of geographic information in the geographic layer when the pollution color is deeper, avoiding the situation where users cannot see the geographic information below the air environment layer due to excessively dark pollution color, allowing users to intuitively see the geographical location of the air quality status. Secondly, it supports users to set different display modes to display the air quality model. The air quality model can display the air environment layer or the geographic layer separately, or these layers can be arbitrarily overlaid, making the way users view air quality status more diverse, thus greatly satisfying users' diverse interactive needs for the air quality model.

[0078] Figure 8This is an exemplary embodiment involving step S101 above, which is used to interpret an exemplary scheme for progressively filtering grid data, including the following steps: S101-1, in response to a query operation on the air quality query area, filter the pollutant concentrations of the air quality query area at different time points from multiple areas.

[0079] Users can enter the desired air quality query area in the query input box, such as City A, and the system will automatically filter out grid data for City A at different time points from multiple areas.

[0080] S101-2, in response to a query operation on the air quality status of the air quality query area at a specified time point, filter the pollutant concentration of the air quality query area at the specified time point from pollutant concentrations at different time points.

[0081] After entering the area for air quality queries, users can also enter a specific time point to query, such as 2026-02-28, to filter grid data for 2026-02-28 from grid data at different time points in City A.

[0082] S101-3, in response to a query operation on the air quality status of a specified pollutant in the air quality query area, the pollutant concentration of the specified pollutant is filtered out from the pollutant concentration at a specified time point.

[0083] After entering a specified time point, users can also enter a specific pollutant they want to query, such as CO, so that the CO pollutant concentration can be filtered out from the grid data of City A on February 28, 2026.

[0084] It is understood that the above three steps S101-1 to S101-3 can be performed in parallel or in chronological order, and this disclosure does not impose any restrictions on this.

[0085] S101-4, For each three-dimensional grid, query the pollutant concentration of a specified pollutant at a specified time point in the pollutant mapping table to obtain the visual pollution degree characteristics, and obtain the atmospheric flow trajectory in the three-dimensional grid based on the meteorological data of the three-dimensional grid.

[0086] Optionally, for each 3D grid, the visual pollution features corresponding to the pollutant concentration of a specified pollutant at a specified time point in the specified air quality query area can be rendered onto the 3D grid.

[0087] S101-5, for each of the three-dimensional grids, the visualized pollution level features and the atmospheric flow trajectory are applied to the three-dimensional grid, and the geographic information is rendered on the geographic layer to generate and display an air quality model that reflects the air environment status of the air quality query area.

[0088] Optionally, after obtaining the air quality model of the air quality query area, in response to a sectioning operation on at least one side of the air quality model, a specified three-dimensional region is segmented from the air quality query area, and the air environment conditions and geographical information of the three-dimensional region are displayed.

[0089] For example, see Figure 9 As shown, the cutting operation includes at least one of the following operations on the air quality model: a cutting operation in a first direction, a cutting operation in a second direction, and a cutting operation in a third direction, wherein the first direction, the second direction, and the third direction are perpendicular to each other.

[0090] For example, taking the first direction as X, the second direction as Y, and the third direction as Z, users can set the display range in the X direction, the display range in the Y direction, and the display range in at least one of the Z directions, thereby cutting out a three-dimensional region from the air quality model. The side of this three-dimensional region can intuitively display the meteorological distribution or pollution level distribution above the geographical environment.

[0091] The system can also display three coordinate progress bars on the air quality model display interface. In response to dragging any of the three progress bars, the system obtains the display range corresponding to the dragged progress bar position and displays the air quality model corresponding to that range on the display interface. For example, if the display interface shows X-coordinate, Y-coordinate, and Z-coordinate progress bars, the user can drag the X-coordinate progress bar to display a portion of the air quality model.

[0092] Optionally, after obtaining the air quality model of the air quality query area, the system can also control the air quality model to rotate in the direction set by the user in response to the rotation operation of the air quality model, so as to facilitate the user to view the meteorological conditions or air pollution conditions above different geographical boundaries in the air quality query area, and bring convenience to the user in operating the air quality model.

[0093] Optionally, after obtaining the air quality model of the air quality query area, the scaling factor of the air quality model can be determined in response to the scaling operation of the air quality model; then, the viewpoint distance corresponding to the scaling factor can be determined from the viewpoint distance mapping table; then, the resolution corresponding to the viewpoint distance can be determined based on the resolution mapping table; and finally, the resolution of the air quality model can be adjusted to the resolution corresponding to the viewpoint distance.

[0094] The scaling factor refers to the scaling factor of the air quality model, which can be increased or decreased. Users can scale the air quality model using any method, such as fingers, touch devices, mice, or keyboards.

[0095] The viewpoint distance refers to the distance from the human eye's observation point to the air quality model. It determines how close the user's eyes are to the image. The larger the scaling factor, the smaller the corresponding viewpoint distance, indicating that the human eye expects to see more details in the air quality model.

[0096] The resolution refers to the resolution of the air quality model. Each 3D grid in the air quality model has a fixed minimum resolution, such as 1 kilometer. The resolution mapping table records the mapping relationship between different viewpoint distances and different resolutions. The larger the viewpoint distance, the lower the resolution accuracy, and the fewer details of the air quality model can be displayed. When the user zooms in on the air quality model, the viewpoint distance corresponding to the zoom factor is first determined, then the resolution matching the viewpoint distance is determined, and finally, when displaying the air quality model at this resolution, the target 3D grids that need to be retained at this resolution are selected from multiple 3D grids for rendering, while the unretained 3D grids are not rendered. Furthermore, the distance between the retained target 3D grids is the distance corresponding to the adjusted lower resolution.

[0097] For example, if each 3D grid has a resolution of 1 kilometer, and the initial air quality model has a low resolution of 10 kilometers (for example, showing the approximate terrain and air conditions of a city in the air quality query area), then the distance between two adjacent 3D grids in the displayed air quality model is 10 kilometers, and the 9 3D grids in between are discarded and not rendered. When the user zooms in on the air quality model to view the terrain and air conditions of a street in a city in the air quality query area, the scaling factor after the user performs the zoom operation can be obtained, for example, 10 times. At this time, based on the scaling factor - viewpoint distance - resolution query, the higher resolution after zooming in is obtained, which is 1 kilometer. In this case, there is no need to discard the 3D grids, and the distance between two 3D grids is 1 kilometer. Then all the 3D grids will be rendered, thus displaying the terrain and air conditions at a higher resolution.

[0098] Optionally, the display interface for displaying the air quality model is also equipped with two-dimensional display controls and three-dimensional display controls. The two-dimensional display controls are used to display an overview view of the air quality query area; the three-dimensional display controls are used to display a three-dimensional view of the air quality query model in three-dimensional space.

[0099] It can respond to touch operations on two-dimensional display controls to obtain meteorological data and pollutant concentrations in a two-dimensional air quality query area; the meteorological data and pollutant concentrations are obtained through instrument monitoring; then the meteorological data and pollutant concentrations are rendered onto the two-dimensional air quality query area to generate and display an air quality status map reflecting the air quality status of the air quality query area.

[0100] In response to touch operation of the 3D display control, the above steps S101-1 to S101-5 can be executed to generate and display an air quality status map reflecting the air quality status of the air quality query area.

[0101] It is understandable that since the meteorological data and pollutant concentrations obtained by the monitoring stations are two-dimensional data, and multiple monitoring stations are deployed in the air quality query area to monitor and sense the surrounding meteorological data and pollutant concentrations, the accuracy of the obtained meteorological data and pollutant concentrations is relatively high. Naturally, the accuracy of the aerial view of the air quality query area based on accurate meteorological data and pollutant concentrations is also relatively high.

[0102] The above technical solution achieves several advantages. Firstly, before rendering the air quality model, the visual pollution features corresponding to the pollutant concentrations of specified pollutants in the specified air quality query area at a specified time point can be filtered and rendered onto the 3D grid in a step-by-step manner, rather than cutting out the required air quality model according to user needs after rendering the overall air quality model. This results in less rendering data, faster rendering speed, and reduced query and transmission time for air quality data. Secondly, users can arbitrarily slice the displayed air quality model to view the meteorological or air pollution conditions above different sub-geographical areas in the air quality query area, enhancing the user's interactive experience with the air quality model. Thirdly, when users are viewing an air quality model at a lower resolution, the target 3D mesh can be selected from multiple 3D meshes in the air quality query area for rendering, without loading the full 3D mesh data for rendering. This significantly reduces the amount of data rendering, making the rendering and generation of the air quality model faster. Furthermore, since the number of target 3D meshes to be rendered is smaller, when users switch and rotate the viewing angle of the air quality model, the air quality model from different perspectives can be loaded more quickly, making the operation of switching the viewing angle of the air quality model smoother and less laggy.

[0103] Figure 10 This is an exemplary embodiment of the present disclosure, which is an exemplary scheme for interpreting the dynamic display effect of air quality models at different time points, including the following steps: S108, Obtain the grid data of the three-dimensional grid of the air quality query area at different time points.

[0104] It is understandable that the above-mentioned gridded product model can output gridded data of the air quality query area at different points in time, such as historical, current and future. Therefore, gridded data at different points in time can be obtained from this part of the gridded product model.

[0105] S109, in response to the playback operation of the air quality status of the air quality query area, dynamically render the grid data at different time points to the three-dimensional grid corresponding to the grid data in chronological order, so as to play the evolution process of the air quality status of the air quality query area over time.

[0106] Optionally, the server can preload grid data at different points in time into a message queue. The front end uses WebSocket or a timed polling mechanism to retrieve grid data at different points in time from the message queue and renders the grid data at different points in time onto the corresponding 3D grid, thereby realizing the rendering of the 3D grid.

[0107] Optionally, when playing the evolution of the air quality status in the air quality query area over time, in response to an air quality query operation at any specified time point on the progress bar, the grid data of the specified time point is rendered onto the three-dimensional grid to display the air quality status of the air quality query area at the specified time point.

[0108] Among them, see Figure 11 As shown, the progress bar is the playback progress displayed during the playback of the air quality query area. The progress bar is a visual timeline control, and each touch point on the playback progress corresponds to a time point. When the user pauses the playback of the air quality model and drags the progress bar to a specified time point, the front end will automatically pull the grid data at that time point from the server and render it on the 3D grid.

[0109] Optionally, the server can also perform spatiotemporal alignment between meteorological data and pollutant concentration data. Spatially, if the number of monitoring stations is small, resulting in limited pollutant concentration data and some 3D grids lacking pollutant concentration data, interpolation can be performed on the pollutant concentration data of the 3D grids containing pollutant concentration data to obtain the pollutant concentration data for the partially blank 3D grids. Similarly, for meteorological data, a similar method can be used to calculate meteorological data for each 3D grid. Temporally, the meteorological data and pollutant concentration data will be aligned at the same point in time.

[0110] Optionally, the server will also uniformly convert meteorological data and pollutant concentration data into a data format that the front end can recognize. For example, for the three-dimensional coordinates of the 3D grid, the three-dimensional coordinates will be converted into GeoJSON format; for the pollutant concentration data and meteorological data of each 3D grid, they will be uniformly converted into PNG format or binary format; and for the pollutant mapping table between the pollutant concentration data and the corresponding visualized pollution level features in each 3D grid, it can be converted into JSON format, so that the front end can more efficiently read the grid data and geographic information output from the server.

[0111] The above technical solution can provide users with a playback control that dynamically displays the air quality model at different points in time. Users can touch the playback control to play or pause the display of the air quality model at different points in time. In this way, the air quality model will dynamically display the evolution of pollutant concentration or meteorological conditions over the geographic area of ​​the air quality query region.

[0112] Figure 12 This is an exemplary embodiment of the present disclosure, used to interpret the display of grid data of a three-dimensional grid on an air quality model after touch input, including the following steps: S110, in response to a touch operation on the three-dimensional mesh, the mesh data is displayed around the three-dimensional mesh.

[0113] The air quality model consists of multiple three-dimensional grids, each with a visual pollution level feature or a visual non-wind speed feature. Therefore, a mapping table can be established between each three-dimensional grid and its corresponding grid data. The mapping table contains the mapping relationship between the three-dimensional coordinates of the three-dimensional grid and the grid data. When a mouse, keyboard, user finger, or certain touch devices touch the three-dimensional grid on the air quality model, the mapping table will be queried to determine the grid data corresponding to the three-dimensional coordinates of the three-dimensional grid and display the grid data.

[0114] For example, taking pollutant concentration as the grid data, the system can first respond to the input air quality query area, the selected specified pollutant, and the input specified time point to obtain the air quality model of the specified pollutant in the air quality query area at the specified time point. Then, in response to the touch operation of the target 3D grid in the multiple 3D grids of the air quality model, the system can query the target pollutant concentration corresponding to the target 3D grid from the mapping relationship table and display the target pollutant concentration around the target 3D grid.

[0115] For example, see Figure 13 As shown, taking meteorological data as an example, the system can first respond to the input air quality query area and the input specified time point to generate an air quality model of the air quality query area at the specified time point. Then, in response to the touch operation of the target 3D grid in the multiple 3D grids of the air quality model, the system can query the target meteorological data (e.g., northwest wind 1.2m / s, level 1) corresponding to the target 3D grid from the mapping relationship table and display the target meteorological data around the target 3D grid.

[0116] Using the above technical solution, when a user touches a 3D grid on the air quality model, the corresponding pollutant concentration or meteorological data will be displayed around the grid. This eliminates the need for users to consult tables to determine the pollutant concentration or meteorological data on the 3D grid, making it more convenient for users to query and display pollutant concentration or meteorological data for a specific area. For example, if the 3D grid represents area A on street A in city A, clicking on the 3D grid will display the pollutant concentration or meteorological data for street A in city A.

[0117] Figure 14 This is a block diagram illustrating an electronic device 1400 according to an exemplary embodiment. For example... Figure 14 As shown, the electronic device 1400 may include a processor 1401 and a memory 1402. The electronic device 1400 may also include one or more of a multimedia component 1403, an input / output (I / O) interface 1404, and a communication component 1405.

[0118] The processor 1401 controls the overall operation of the electronic device 1400 to complete all or part of the steps in the above-described method for generating an air quality model. The memory 1402 stores various types of data to support the operation of the electronic device 1400. This data may include, for example, instructions for any application or method operating on the electronic device 1400, and application-related data such as contact data, sent and received messages, pictures, audio, video, etc. The memory 1402 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. Multimedia component 1403 may include a screen and an audio component. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory 1402 or transmitted via communication component 1405. The audio component also includes at least one speaker for outputting audio signals. I / O interface 1404 provides an interface between processor 1401 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual or physical buttons. Communication component 1405 is used for wired or wireless communication between the electronic device 1400 and other devices. Wireless communication may include Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, or 4G, or a combination of these. Therefore, the corresponding communication component 1405 may include a Wi-Fi module, a Bluetooth module, or an NFC module.

[0119] In an exemplary embodiment, the electronic device 1400 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described method for generating the air quality model.

[0120] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the air quality model generation method described above. For example, the computer-readable storage medium may be the memory 1402 including the program instructions described above, which may be executed by the processor 1401 of the electronic device 1400 to complete the air quality model generation method described above.

[0121] In another exemplary embodiment, a computer program product is also provided, which includes a computer program executable by a processor, which, when executed by the processor, implements the steps of the above-described method for generating an air quality model.

[0122] Figure 15 This is a block diagram illustrating an electronic device 1500 according to an exemplary embodiment. For example, the electronic device 1500 may be provided as a server. (Refer to...) Figure 15 The electronic device 1500 includes a processor 1522, which may be one or more, and a memory 1532 for storing computer programs executable by the processor 1522. The computer program stored in the memory 1532 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processor 1522 may be configured to execute the computer program to perform the aforementioned method for generating an air quality model.

[0123] Additionally, the electronic device 1500 may also include a power supply component 1526 and a communication component 1550. The power supply component 1526 can be configured to perform power management of the electronic device 1500, and the communication component 1550 can be configured to enable communication of the electronic device 1500, such as wired or wireless communication. Furthermore, the electronic device 1500 may also include an input / output (I / O) interface 1558. The electronic device 1500 can operate on an operating system stored in the memory 1532.

[0124] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the air quality model generation method described above. For example, the computer-readable storage medium may be the memory 1532 including the program instructions described above, which may be executed by the processor 1522 of the electronic device 1500 to complete the air quality model generation method described above.

[0125] In another exemplary embodiment, a computer program product is also provided, which includes a computer program executable by a processor, which, when executed by the processor, implements the steps of the above-described method for generating an air quality model.

[0126] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.

[0127] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0128] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

Claims

1. A method for generating an air quality model, characterized in that, include: Obtain the geographic information of the three-dimensional air quality query area and the grid data of the three-dimensional grid of the air quality query area; The air quality query area includes a three-dimensional air environment layer and a geographic layer from top to bottom. The air environment layer is divided into multiple three-dimensional grids, and the grid data includes at least one of meteorological data and pollutant concentrations. For each of the three-dimensional grids, the visualized air environment characteristics of the three-dimensional grids are obtained based on the meteorological data of the three-dimensional grids and at least one of the pollutant concentrations. The visualized air environment features are used to characterize the visualization effect of the air environment in the air quality query area; The grid data is rendered into the 3D grid corresponding to the grid data in the air environment layer, and the geographic information is rendered into the geographic layer to generate and display an air quality model that reflects the air environment conditions of the air quality query area.

2. The method according to claim 1, characterized in that, For each of the three-dimensional grids, based on the meteorological data of the three-dimensional grid and the pollutant concentration, the visualized air environment characteristics of the three-dimensional grid are obtained, including: For each of the three-dimensional grids, a visual pollution level feature corresponding to the pollutant concentration of the three-dimensional grid is queried from the pollutant mapping table, and a visual wind speed feature of the three-dimensional grid is obtained based on the meteorological data of the three-dimensional grid; wherein, the visual air environment feature includes the visual pollution level feature and the visual wind speed feature, the visual pollution level feature is used to characterize the pollution level of the pollutant concentration, and the visual wind speed feature is used to characterize the atmospheric flow trajectory of the three-dimensional grid. Rendering the mesh data into the atmospheric environment layer corresponding to the 3D mesh data includes: For each of the three-dimensional grids, the visualized pollution level features and the visualized wind speed features of the three-dimensional grids are rendered on the three-dimensional grids.

3. The method according to claim 1, characterized in that, For each of the three-dimensional grids, based on the meteorological data of the three-dimensional grid, the visualized air environment characteristics of the three-dimensional grid are obtained, including: For each of the three-dimensional grids, the visualized wind speed characteristics and visualized non-wind speed characteristics of the three-dimensional grids are obtained based on the meteorological data of the three-dimensional grids; wherein, the visualized air environment characteristics include the visualized wind speed characteristics and the visualized non-wind speed characteristics, the visualized wind speed characteristics are used to characterize the atmospheric flow trajectory of the three-dimensional grids, and the visualized non-wind speed characteristics are used to characterize the visualization effect of the intensity of the non-wind speed data of the three-dimensional grids. Rendering the mesh data into the atmospheric environment layer corresponding to the 3D mesh data includes: For each of the three-dimensional grids, the visualized wind speed features and the visualized non-wind speed features of the three-dimensional grids are rendered on the three-dimensional grids.

4. The method according to claim 2, characterized in that, For each of the three-dimensional grids, the visual pollution level feature corresponding to the pollutant concentration of the three-dimensional grid is queried from the pollutant mapping table, including: The pollutant concentration corresponding to the pollutant concentration in the 3D grid is retrieved from the pollutant mapping table; the visualized pollution level features include the pollution color and transparency, and the color depth of the pollution color is positively correlated with the transparency. For each of the three-dimensional grids, the visualized pollution level features and the visualized wind speed features of the three-dimensional grids are rendered on the three-dimensional grids, including: The pollutant concentration corresponding to the pollutant color and transparency, along with the visualized wind speed features, are rendered onto the 3D grid.

5. The method according to claim 1, characterized in that, Obtain the grid data of the 3D grid of the air quality query area, including: In response to a query operation on the air quality query area, the pollutant concentrations of the air quality query area at different time points are filtered from multiple areas. In response to a query operation on the air quality status of the air quality query area at a specified time point, the pollutant concentration of the air quality query area at the specified time point is filtered from the pollutant concentrations at different time points; In response to a query operation on the air quality status of a specified pollutant in the air quality query area, the pollutant concentration of the specified pollutant is filtered out from the pollutant concentration at a specified time point.

6. The method according to claim 1, characterized in that, After generating and displaying an air quality model reflecting the air environment conditions of the air quality query area, the method further includes: In response to a sectioning operation on at least one side of the air quality model, a specified three-dimensional region is segmented from the air quality model, and the air environment conditions and geographical information of the three-dimensional region are displayed.

7. The method according to claim 1, characterized in that, Obtaining the grid data of the three-dimensional grid of the air quality query area includes: obtaining the grid data of the three-dimensional grid of the air quality query area at different time points; Rendering the grid data into the three-dimensional grid corresponding to the grid data in the air environment layer includes: in response to a playback operation of the air quality status of the air quality query area, dynamically rendering the grid data at different time points to the three-dimensional grid corresponding to the grid data in chronological order, so as to play the evolution process of the air quality status of the air quality query area over time.

8. The method according to claim 7, characterized in that, The method further includes: When playing the evolution of air quality status in the air quality query area over time, in response to an air quality query operation at any specified time point on the progress bar, the grid data of the specified time point is rendered onto the 3D grid to display the air quality status of the air quality query area at the specified time point; wherein, the progress bar is the playback progress displayed during the playback of the air quality status of the air quality query area.

9. The method according to claim 1, characterized in that, The method further includes: In response to a touch operation on the 3D grid, the grid data is displayed around the 3D grid.

10. An electronic device, characterized in that, include: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method according to any one of claims 1 to 9.

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