A prediction model drawing system in the environmental protection field
The environmental prediction model mapping system automates the processing of local environmental data and generates contour maps, solving the problems of high workload and low efficiency caused by manual data screening and input in existing technologies, and achieving efficient generation of environmental data distribution maps.
Patent Information
- Application Number
- CN202210063201.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-01-20
- Publication Date
- 2026-05-15
- Estimated Expiration
- 2042-01-20
AI Technical Summary
In existing technologies, generating environmental data distribution maps using Surfer software requires manual screening and input of data that conforms to preset specifications, resulting in a large workload and low efficiency.
This invention provides a mapping system for predictive models in the environmental protection field. Through the environmental impact prediction model mapping tool, it automatically generates a grid point location map based on the latitude and longitude data of local files, constructs a distribution map, and performs triangulation and contour tracing to generate a contour map.
It simplifies the process of generating contour maps, reduces manual workload, improves generation efficiency, and realizes automated production of environmental data distribution maps.
Smart Images
Figure CN114398460B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of chart plotting technology, and more specifically, to a charting system for predictive models in the environmental protection field. Background Technology
[0002] In existing technologies, professional mapping software like Surfer is used to generate distribution maps of the required environmental data. However, environmental data is generally stored in local files, and Surfer software cannot parse local files. Therefore, it is necessary to manually fill the environmental data from the local files into the tables provided by Surfer software. Furthermore, since Surfer software can only recognize environmental data that conforms to preset specifications, it is necessary to manually filter out the environmental data that conforms to the preset specifications from the environmental data in the local files and fill the filtered environmental data that conforms to the preset specifications into the tables provided by Surfer software so that Surfer software can generate distribution maps of the environmental data based on the environmental data that conforms to the preset specifications in the tables. In the above process of generating distribution maps of environmental data, the part that requires manual intervention is quite tedious, which results in a large workload and low efficiency in generating distribution maps of environmental data. Summary of the Invention
[0003] In view of this, embodiments of this application provide a prediction model mapping system for the environmental protection field, so as to reduce manual workload and improve the efficiency of contour map generation.
[0004] This application provides a system for generating maps of prediction models in the environmental protection field. The system includes at least one tool for generating maps of environmental impact prediction models. The environmental impact prediction model generating tool includes:
[0005] In response to the user's selection of a target file, a grid point location map of the specified geographical area is generated based on several latitude and longitude data in the specified geographical area included in the target file; wherein, for each grid point constituting the grid point location map, there is a latitude and longitude data corresponding to that grid point in each of the latitude and longitude data;
[0006] In response to the user's selection of the target interpolation algorithm from among the preset interpolation algorithms for the map data to be generated in the target file, a distribution map of the map data to be generated is constructed in the grid point location map based on the map data to be generated and the target interpolation algorithm; wherein, for each grid point in the distribution map, the value associated with the grid point is used to represent the value of the map data to be generated at the latitude and longitude location point corresponding to the grid point, and the latitude and longitude location point corresponding to the grid point is the geographical location point indicated by the latitude and longitude data corresponding to the grid point;
[0007] The grid points in the distribution map are triangulated to construct a triangular network composed of the grid points in the distribution map;
[0008] Based on the preset contour spacing and contour value range, contour tracing is performed on the triangulation network to obtain the contour map of the data to be mapped in the specified geographical area;
[0009] The environmental impact prediction model mapping tools include: atmospheric prediction model mapping tools, surface water prediction model mapping tools, groundwater prediction model mapping tools, soil prediction model mapping tools, noise prediction model mapping tools, and risk prediction model mapping tools. When the environmental impact prediction model mapping tool is an atmospheric prediction model mapping tool, the data to be mapped is the concentration of air pollutants, and the contour map is a contour map of the concentration of air pollutants. When the environmental impact prediction model mapping tool is a surface water prediction model mapping tool, the data to be mapped is the concentration of surface water pollutants, and the contour map is a contour map of the concentration of surface water pollutants. When the groundwater prediction model mapping tool is used, the data to be mapped is the groundwater pollutant concentration, and the contour map is a contour map of the groundwater pollutant concentration; when the environmental impact prediction model mapping tool is used for soil prediction model mapping, the data to be mapped is the soil pollutant concentration, and the contour map is a contour map of the soil pollutant concentration; when the environmental impact prediction model mapping tool is used for noise prediction model mapping, the data to be mapped is the noise contribution value, and the contour map is a contour map of the noise contribution value; when the environmental impact prediction model mapping tool is used for risk prediction model mapping, the data to be mapped is the toxicity concentration value, and the contour map is a contour map of the toxicity concentration value.
[0010] Optionally, the response to the user's selection of the target interpolation algorithm from among preset interpolation algorithms for the data to be plotted in the target file, and the construction of a distribution map of the data to be plotted in the grid point location map based on the data to be plotted and the target interpolation algorithm, includes:
[0011] In response to the user's selection operation of the data to be mapped in the target file, based on the value of the data to be mapped corresponding to each latitude and longitude data in the target file, the value associated with the first grid point corresponding to the latitude and longitude data in the grid point location map is determined, and the original distribution map of the data to be mapped is obtained.
[0012] In response to the user's selection of a target interpolation algorithm from among the preset interpolation algorithms, at least one second grid point is inserted into the original distribution map according to the target interpolation algorithm, and the value associated with each second grid point is determined to obtain the distribution map of the data to be output.
[0013] Optionally, after obtaining the original distribution map of the data to be mapped, the method further includes:
[0014] The graphical user interface displays an option table containing several preset interpolation algorithms, including: linear interpolation, nearest neighbor sampling, inverse distance multiplication, triangular network interpolation, and custom interpolation algorithms.
[0015] The response to the user's selection of a target interpolation algorithm from among preset interpolation algorithms includes:
[0016] In response to the user's selection of an interpolation algorithm from among several interpolation algorithms included in the option table, the selected interpolation algorithm is used as the target interpolation algorithm.
[0017] Optionally, the environmental protection prediction model mapping system further includes:
[0018] In response to the user's selection of the custom interpolation algorithm in the option table, a preset definition template of the interpolation algorithm is displayed on the graphical user interface;
[0019] In response to the algorithm definition entered by the user in the definition template, a custom interpolation algorithm is generated based on the definition.
[0020] Optionally, after obtaining the contour map of the data to be mapped in the specified geographical area, the method further includes:
[0021] Based on the target values of the data to be mapped set for each contour line in the contour map, the background color of the target area is filled with gradient colors in descending order of the target values to obtain a diffusion map of the data to be mapped in the specified geographical area; wherein, the target area is the area surrounded by the target contour lines in the contour map; the target contour lines are the contour lines corresponding to the smallest target values.
[0022] Optionally, after obtaining the diffusion map of the data to be mapped in the specified geographical area, the method further includes:
[0023] The diffusion map of the data to be plotted is displayed on a graphical user interface; wherein the display format of the diffusion map of the data to be plotted includes: image format file and / or SHP file format.
[0024] Optionally, after obtaining the diffusion map of the data to be mapped in the specified geographical area, the method further includes:
[0025] In response to a user's click on the print control in the environmental prediction model mapping system, the diffusion map of the data to be mapped is printed.
[0026] Optionally, after obtaining the diffusion map of the data to be mapped in the specified geographical area, the method further includes:
[0027] According to the preset target labels, target labels are added to the diffusion map of the data to be generated; wherein, the target labels include at least: plant boundary, north arrow, scale, text description, sensitive area and evaluation area range.
[0028] Optionally, after adding target labels to the diffusion map of the data to be mapped, the method further includes:
[0029] In response to the user's adjustment operation on the diffusion map of the data to be generated, the diffusion map of the data to be generated is adjusted according to the requirements of the adjustment operation; wherein, the adjustment operation includes the adjustment operation of the contour lines in the diffusion map and the adjustment operation of the target labels in the diffusion map.
[0030] Optionally, the environmental protection prediction model mapping system may also include an environmental protection geographic information system (GIS) module.
[0031] Before responding to the user's selection of a target file, the GIS module in the environmental protection field displays an electronic map on the graphical user interface.
[0032] The environmental prediction model mapping system provided in the embodiments of this application may include the following beneficial effects:
[0033] The environmental protection prediction model mapping system provided in this application, after the user selects a target file containing the required environmental data (i.e., the data to be mapped) from a local file, the environmental impact prediction model mapping tool in the system first generates a grid point location map of the specified geographical area based on several latitude and longitude data included in the target file. Then, based on the data to be mapped selected by the user in the target file and the target interpolation algorithm selected from the preset interpolation algorithms, it constructs a distribution map of the data to be mapped on the grid point location map. After obtaining the distribution map of the data to be mapped, the grid points in the distribution map of the data to be mapped are triangulated to construct a triangular network composed of grid points on the distribution map of the data to be mapped. After obtaining the triangular network, according to the preset contour line spacing and contour line value range, contour line tracing is performed on the triangular network to obtain the number of data to be mapped in the specified geographical area. The contour map is generated based on the data. The value corresponding to each contour line on the contour map represents the value of the data to be mapped at the location of that contour line. Therefore, the contour map can intuitively show the distribution of the data to be mapped in a specified geographical area (i.e., it is equivalent to a distribution map of environmental data). In the above mapping process, the data (i.e., environmental data) included in the target file (local file) can be processed directly without having to fill the data in the target file into the table provided by the Surfer software. This simplifies the generation process of the contour map. Moreover, the entire mapping process is automatically completed by the environmental protection prediction model mapping system. The human operator only needs to select the target file required for mapping, select the data to be mapped (data category) in the target file, and select the target interpolation algorithm. The human intervention process is simple, which helps to reduce the workload and improve the generation efficiency of the contour map (i.e., the distribution map of environmental data).
[0034] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description
[0035] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0036] Figure 1 A flowchart illustrating a method for generating contour maps of data to be mapped, provided in an embodiment of this application, is shown.
[0037] Figure 2This illustration shows an example diagram of a method for constructing a distribution map of data to be plotted, as provided in an embodiment of this application.
[0038] Figure 3 An example diagram of an option table provided in an embodiment of this application is shown;
[0039] Figure 4 An example diagram of a gradient color filling method provided in an embodiment of this application is shown. Detailed Implementation
[0040] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.
[0041] This application provides a system for generating prediction models in the environmental protection field, which will be described below through embodiments.
[0042] Example
[0043] This application provides a prediction model mapping system for the environmental protection field, which includes at least one environmental impact prediction model mapping tool. Figure 1 This document illustrates a flowchart of a method for generating contour maps from data to be mapped, as provided in an embodiment of this application. Figure 1 As shown, the environmental impact prediction model mapping tool can generate contour maps through the following steps S101 to S104:
[0044] Step S101: In response to the user's selection operation of the target file, generate a grid point location map of the specified geographical area based on several latitude and longitude data in the specified geographical area included in the target file; wherein, for each grid point constituting the grid point location map, there is a latitude and longitude data corresponding to the grid point in each of the latitude and longitude data.
[0045] Specifically, when conducting environmental statistics, different environmental data (i.e., natural resource data) collected from different geographical regions are generally written to different local files (i.e., local files). These files can be in formats such as txt (text file), plt, csv (Comma-Separated Values), xlsx, or xls (spreadsheet). For example, air pollutant concentration data is written to a plt file, while noise contribution data is written to a txt file. No specific limitations are made here. When a user wants to access specific environmental data within a geographical region (i.e., a designated geographical area), they need to select a target file (a local file) containing that environmental data from the stored files. This target file includes: several latitude and longitude coordinates within the designated geographical area, pollutant concentration data corresponding to each latitude and longitude coordinate, altitude data corresponding to each latitude and longitude coordinate, and the data acquisition time corresponding to each latitude and longitude coordinate. No specific limitations are made here.
[0046] It should be noted that the above selection operation can be set according to the actual situation. For example, it can be a click operation on the target file displayed in the user's graphical interface, or an input operation on the file name of the target file. There are no specific limitations here.
[0047] It should be noted again that in the target file, different categories of environmental data can be distinguished using different columns. For example, longitude data in latitude and longitude data is in the first column, latitude data in latitude and longitude data is in the second column, pollutant concentration data corresponding to latitude and longitude data is in the third column, and altitude data corresponding to latitude and longitude data is in the fourth column, etc. Based on this, after the user selects the target file, the environmental impact prediction model mapping tool retrieves several latitude and longitude data points located in the first and second columns of the target file.
[0048] In practice, after obtaining a number of latitude and longitude data points in a specified geographical area, a grid point location map of the specified geographical area is constructed based on each latitude and longitude data point. This grid point location map consists of a number of grid points, with each grid point corresponding to one latitude and longitude data point. Therefore, the number of grid points in the grid point location map is the same as the number of latitude and longitude data points obtained. In addition, the border of the grid point location map is marked with longitude and latitude labels (used to indicate the latitude and longitude of each geographical location in the geographical area). Therefore, the position of each grid point in the grid point location map is determined based on the latitude and longitude data corresponding to that grid point. That is, the latitude and longitude values corresponding to the grid point in the grid point location map are the same as the latitude and longitude values of the latitude and longitude data corresponding to the grid point.
[0049] It should be noted again that the environmental data in the aforementioned target files include actual environmental data and / or predicted environmental data.
[0050] Step S102: In response to the user's operation on the data to be mapped in the target file and the selection of the target interpolation algorithm among the preset interpolation algorithms, construct a distribution map of the data to be mapped in the grid point location map according to the data to be mapped and the target interpolation algorithm; wherein, for each grid point in the distribution map, the value associated with the grid point is used to represent the value of the data to be mapped at the latitude and longitude location point corresponding to the grid point, and the latitude and longitude location point corresponding to the grid point is the geographical location point indicated by the latitude and longitude data corresponding to the grid point.
[0051] Specifically, the data to be mapped is any type of data (i.e., a data category) selected by the user from the data included in the target file, excluding latitude and longitude data. For example, it could be pollutant concentration data. There must be at least one such data set, and each data set must have a corresponding latitude and longitude coordinate in the target file. The environmental impact prediction model mapping system has several pre-set interpolation algorithms, allowing the user to select the desired algorithm. After the user selects the data to be mapped from the target file and the desired interpolation algorithm, the environmental impact prediction model mapping tool generates the map based on the selected latitude and longitude data. The data and the interpolation algorithm are used to construct a distribution map of the data to be mapped in the above grid point location map. The distribution map of the data to be mapped is used to show the values of the data to be mapped at several geographical locations in a specified geographical area. These several geographical locations are several grid points in the distribution map of the data to be mapped. Therefore, the values of the data to be mapped at several geographical locations can be represented by the values associated with each grid point in the distribution map. That is, the values associated with the grid point are used to represent the values of the data to be mapped at the latitude and longitude location points corresponding to the grid point. The latitude and longitude location points corresponding to the grid point are the geographical locations indicated by the latitude and longitude data corresponding to the grid point.
[0052] It should be noted that the representation of each grid point in the distribution map of the data to be plotted can be set according to the actual situation. Grid points can be represented by small circles in the distribution map, or by special markers (such as exclamation marks). There is no specific limitation here. In addition, the representation of the values associated with the grid points can also be set according to the actual situation. It can be in the form of annotation boxes near the grid points (with values written in the annotation boxes), or it can be in the form of pixel values of the pixels at the grid points (different pixel values correspond to different numerical values). There is no specific limitation here.
[0053] Step S103: Triangulate the grid points in the distribution map to construct a triangular network composed of the grid points in the distribution map.
[0054] Specifically, after obtaining the distribution map of the data to be mapped, the distribution map contains several grid points. Each grid point is equivalent to a point on the planar map. All the grid points on the distribution map of the data to be mapped constitute the point set on the planar map. The point set on the planar map is triangulated according to the Delaunay triangulation algorithm to construct a triangular network on the planar map. That is, the grid points in the distribution map of the data to be mapped are triangulated to construct a triangular network composed of each grid point in the distribution map of the data to be mapped.
[0055] Step S104: Based on the preset contour line spacing and contour line value range, perform contour line tracing on the triangular network to obtain the contour map of the data to be mapped in the specified geographical area.
[0056] Specifically, since each grid point of the triangular network is associated with a numerical value that represents the specific value of the data to be mapped, contour tracing can be performed on the triangular network according to the preset contour spacing (the difference between the values corresponding to adjacent contour lines) and contour value range (the limited range of the values corresponding to the contour lines) to obtain a contour map. This contour map contains at least one contour line. For each of the at least one contour line, the numerical value marked on that contour line (i.e., the value corresponding to the contour line) represents the specific value of the data to be mapped at the geographical location covered by that contour line. Therefore, this contour map can represent the distribution of the data to be mapped in the specified geographical area, that is, this contour map is a contour map of the data to be mapped in the specified geographical area.
[0057] It should be noted that the contour map above is the distribution map of the data to be mapped in the specified geographical area.
[0058] The environmental impact prediction model mapping tools include: atmospheric prediction model mapping tools, surface water prediction model mapping tools, groundwater prediction model mapping tools, soil prediction model mapping tools, noise prediction model mapping tools, and risk prediction model mapping tools. When the environmental impact prediction model mapping tool is an atmospheric prediction model mapping tool, the data to be mapped is the concentration of air pollutants, and the contour map is a contour map of the concentration of air pollutants. When the environmental impact prediction model mapping tool is a surface water prediction model mapping tool, the data to be mapped is the concentration of surface water pollutants, and the contour map is a contour map of the concentration of surface water pollutants. When the environmental impact prediction model mapping tool is a groundwater prediction model mapping tool... When the environmental impact prediction model mapping tool is a soil prediction model mapping tool, the data to be mapped is the groundwater pollutant concentration, and the contour map is a contour map of the groundwater pollutant concentration; when the environmental impact prediction model mapping tool is a noise prediction model mapping tool, the data to be mapped is the noise contribution value, and the contour map is a contour map of the noise contribution value (i.e., isoacoustic map); when the environmental impact prediction model mapping tool is a risk prediction model mapping tool, the data to be mapped is the toxicity concentration value, and the contour map is a contour map of the toxicity concentration value (i.e., toxicity corridor map).
[0059] It should be noted again that the method for generating contour lines of the above-mentioned data to be mapped can also be the nearest neighbor difference method, the B-spline method, or the Kriging interpolation method; no specific limitation is made here.
[0060] The environmental protection prediction model mapping system provided in this application, after the user selects a target file containing the required environmental data (i.e., the data to be mapped) from a local file, the environmental impact prediction model mapping tool in the system first generates a grid point location map of the specified geographical area based on several latitude and longitude data included in the target file. Then, based on the data to be mapped selected by the user in the target file and the target interpolation algorithm selected from the preset interpolation algorithms, it constructs a distribution map of the data to be mapped on the grid point location map. After obtaining the distribution map of the data to be mapped, the grid points in the distribution map of the data to be mapped are triangulated to construct a triangular network composed of grid points on the distribution map of the data to be mapped. After obtaining the triangular network, according to the preset contour line spacing and contour line value range, contour line tracing is performed on the triangular network to obtain the number of data to be mapped in the specified geographical area. The contour map is generated based on the data. The value corresponding to each contour line on the contour map represents the value of the data to be mapped at the location of that contour line. Therefore, the contour map can intuitively show the distribution of the data to be mapped in a specified geographical area (i.e., it is equivalent to a distribution map of environmental data). In the above mapping process, the data (i.e., environmental data) included in the target file (local file) can be processed directly without having to fill the data in the target file into the table provided by the Surfer software. This simplifies the generation process of the contour map. Moreover, the entire mapping process is automatically completed by the environmental protection prediction model mapping system. The human operator only needs to select the target file required for mapping, select the data to be mapped (data category) in the target file, and select the target interpolation algorithm. The human intervention process is simple, which helps to reduce the workload and improve the generation efficiency of the contour map (i.e., the distribution map of environmental data).
[0061] In one feasible implementation, step S102 described above can be performed through the following steps:
[0062] Step S201: In response to the user's selection operation of the map data to be generated in the target file, based on the value of the map data to be generated corresponding to each latitude and longitude data in the target file, determine the value associated with the first grid point corresponding to the latitude and longitude data in the grid point location map, and obtain the original distribution map of the map data to be generated.
[0063] Specifically, after the user selects the data to be mapped (a column of data) in the target file, for each data point in that column, there are corresponding latitude and longitude coordinates in the target file. For each latitude and longitude coordinate in the target file, there is a corresponding first grid point in the grid point location map. In other words, in the grid point location map, one first grid point corresponds to one data point. Therefore, for each first grid point, a value associated with that first grid point can be set based on the value of the data point to be mapped, where the value associated with the first grid point is the same as the value of the data point to be mapped. After setting the values associated with all the first grid points in the grid point location map, this grid point location map is used as the original distribution map of the data to be mapped.
[0064] Step S202: In response to the user's selection of a target interpolation algorithm from the preset interpolation algorithms, insert at least one second grid point into the original distribution map according to the target interpolation algorithm, and determine the value associated with each second grid point to obtain the distribution map of the data to be output.
[0065] Specifically, in the environmental protection field, the prediction model mapping system pre-sets several interpolation algorithms, allowing users to select the desired target interpolation algorithm. To ensure the original distribution map of the data to be mapped more accurately represents the distribution of the data in a specified geographical area, at least one second grid point is inserted into the original distribution map of the data to be mapped, based on the target interpolation algorithm selected by the user. The number of inserted second grid points is determined based on the number of first grid points in the original distribution map and the target interpolation algorithm used. After inserting the second grid point, the associated value needs to be determined, based on the associated value of the first grid point in the original distribution map and the target interpolation algorithm used. After completing the insertion process for each second grid point in the original distribution map and the determination process for the associated value of each second grid point, the resulting original distribution map is used as the distribution map of the aforementioned data to be mapped.
[0066] It should be noted that the aforementioned interpolation algorithms include a series of algorithms capable of performing grid point interpolation operations, such as linear interpolation, nearest neighbor sampling, inverse distance multiplication, and triangular network interpolation.
[0067] It should be noted again that the explanation of the above-mentioned target interpolation algorithm selection operation is the same as the explanation of the target file selection operation above, and will not be repeated here.
[0068] For example, Figure 2This illustration shows an example diagram of a distribution map construction method for data to be mapped, as provided in an embodiment of this application. Figure 2 As shown, the area above the arrow is the original distribution map 200 of the data to be mapped. The vertical bars on the border of the original distribution map 200 are marked latitude and longitude separators (equivalent to step sizes on the coordinate axes). The original distribution map 200 includes three first grid points (one dot represents one first grid point), and each first grid point is associated with a first value. If the target interpolation method is linear interpolation, according to the linear interpolation method, a second grid point (one triangle represents one second grid point) is inserted at the midpoint of the line connecting every two first grid points (dashed line) in the original distribution map 200. For each second grid point, the value associated with the second grid point (the triangle on the dashed line) is determined to be the average of the values associated with the two first grid points. These two first grid points are the first grid points (dots) at both ends of the dashed line where the second grid point is located. Through the above process, the distribution map 201 of the data to be mapped is obtained.
[0069] In one feasible implementation, after obtaining the original distribution map of the data to be plotted, an option table containing several preset interpolation algorithms is displayed on the graphical user interface. The several interpolation algorithms include: linear interpolation, nearest neighbor sampling, inverse distance multiplication, triangular network interpolation, and custom interpolation algorithms.
[0070] The response to the user's selection of a target interpolation algorithm from among the preset interpolation algorithms includes: responding to the interpolation algorithm selected by the user from among the several interpolation algorithms included in the option table, and using the selected interpolation algorithm as the target interpolation algorithm.
[0071] Specifically, to facilitate users in selecting the desired target interpolation algorithm from among various interpolation algorithms, after obtaining the original distribution map of the data to be mapped, an option table is displayed on the graphical user interface of the environmental protection prediction model mapping system. This option table displays all preset interpolation algorithms, and users can select the desired interpolation algorithm from among the displayed interpolation algorithms. After the user selects the desired interpolation algorithm, the selected interpolation algorithm is used as the aforementioned target interpolation algorithm.
[0072] It should be noted that the preset interpolation algorithms (i.e., the aforementioned interpolation algorithms) include at least linear interpolation, nearest neighbor sampling, inverse distance multiplication, triangular network interpolation, and custom interpolation algorithms. These interpolation algorithms are listed in descending order of interpolation accuracy as follows: linear interpolation, nearest neighbor sampling, inverse distance multiplication, triangular network interpolation, and custom interpolation algorithm. It should also be noted that higher interpolation accuracy results in a longer interpolation time when using that algorithm.
[0073] Figure 3An example diagram of an option table provided in an embodiment of this application is shown, such as... Figure 3 As shown, option table 300 displays text and option boxes for linear interpolation, nearest neighbor sampling, inverse distance multiplication, triangular network interpolation, and custom interpolation algorithms. In addition, there are controls for confirming the options. When the user wants to select linear interpolation, they need to click the selection box before the text "linear interpolation" and then click the "OK" control at the bottom of the option box to complete the selection operation of linear interpolation.
[0074] In one feasible implementation, in response to the user's selection of the custom interpolation algorithm in the option table, a preset definition template for the interpolation algorithm is displayed on the graphical user interface; in response to the user's input of the algorithm definition in the definition template, a custom interpolation algorithm is generated according to the definition.
[0075] Specifically, if the user does not have a preferred interpolation algorithm among the pre-set options, the user can select a custom interpolation algorithm from the options table. When the user selects a custom interpolation algorithm, a pre-defined template for the interpolation algorithm is displayed on the graphical user interface, allowing the user to edit the required interpolation algorithm independently. That is, the user enters the definition of the required interpolation algorithm in the definition template. After the user completes the input, a custom interpolation algorithm that can be used for interpolation is generated based on the user's definition of the required interpolation algorithm, such as a cube fitting algorithm.
[0076] In one feasible implementation, after obtaining the contour map of the data to be mapped in the specified geographical area, according to the target values of the data to be mapped set for each contour line in the contour map, the background color of the target area is filled with a gradient color in descending order of the target values to obtain a diffusion map of the data to be mapped in the specified geographical area; wherein, the target area is the area surrounded by the target contour lines in the contour map; and the target contour lines are the contour lines corresponding to the smallest target values.
[0077] Specifically, in a contour map, the target value of the data to be mapped is set for each contour line, which is the value marked on each contour line. To more clearly show the distribution of the data to be mapped in a specified geographical area, after obtaining the contour map, according to the target values set for each contour line in the contour map from high to low, the background color of the target area in the contour map is filled with a gradient color. The target area is the area enclosed by the target contour line with the smallest corresponding target value, and the area enclosed by the target contour line is the largest among the areas enclosed by all contour lines.
[0078] It should be noted that, for each pixel in the target area on the contour map, the background color of different pixels (i.e., the pixel value of the pixel) is used to represent the numerical value of the map data to be generated at the corresponding geographical location of the pixel.
[0079] Figure 4 An example diagram of a gradient color filling method provided in an embodiment of this application is shown, such as... Figure 4 As shown, in contour map 400, there are 5 contour lines. According to the order of the area enclosed by the contour lines from largest to smallest, the target values (the values annotated next to each contour line) are 7.5, 15, 22, 30, and 60, respectively. Therefore, the target contour line is the contour line corresponding to the target value of 7.5. The area enclosed by this target contour line in contour map 400 is the target area. In the target area, a gradient color is filled according to the direction of the arrow (from the outside to the inside).
[0080] It should be noted that after filling the background color of the target area with gradient colors, for each color in the gradient, an annotation is added to indicate the numerical range of the data to be plotted that the color represents.
[0081] It should be noted again that the diffusion map of the data to be mapped in the specified geographical area mentioned above is also a distribution map of the data to be mapped.
[0082] In one feasible implementation, after obtaining the diffusion map of the data to be mapped in the specified geographical area, the diffusion map of the data to be mapped is displayed on a graphical user interface; wherein, the display format of the diffusion map of the data to be mapped includes: image format file and / or SHP file format.
[0083] Specifically, in order to facilitate users' analysis of the distribution of the data to be mapped in a specified geographical area, after obtaining the diffusion map of the data to be mapped, the diffusion map is displayed on the graphical user interface of the preset drawing platform.
[0084] It should be noted that when the diffusion map of the data to be generated is an SHP (shape, SHP sip) file, the diffusion map of the data to be generated will be displayed in the form of an SHP file on a GIS (Geographic Information System) electronic map. When the diffusion map of the data to be generated is an image, the diffusion map of the data to be generated will be displayed in the form of an image file.
[0085] In one feasible implementation, after obtaining the diffusion map of the data to be mapped in the specified geographical area, the diffusion map of the data to be mapped is printed in response to the user's click operation on the print control in the environmental protection prediction model mapping system.
[0086] In one feasible implementation, after obtaining the diffusion map of the data to be mapped in the specified geographical area, target labels are added to the diffusion map of the data to be mapped according to preset target labels; wherein, the target labels include at least: factory boundary, compass, scale, text description, sensitive area and evaluation area range.
[0087] In one feasible implementation, after adding target labels to the diffusion map of the data to be mapped, in response to the user's adjustment operation on the diffusion map of the data to be mapped, the diffusion map of the data to be mapped is adjusted according to the requirements of the adjustment operation; wherein, the adjustment operation includes the adjustment operation of the contour lines in the diffusion map and the adjustment operation of the target labels in the diffusion map.
[0088] Specifically, the adjustments to contour lines in the diffusion map include at least: adjusting contour line spacing, adjusting contour line numerical range, adjusting contour line width, and adjusting contour line color; the adjustments to target annotations in the diffusion map include at least: adjusting line width, adjusting text descriptions, adjusting fill color, and adjusting the display format of sensitive areas in the diffusion map; the line width includes at least: the width of lines annotated in the diffusion chart, the width of the border of the annotated area, and the width of the border of the annotated icon; the fill color includes at least: the fill color of lines annotated in the diffusion chart, the fill color of the border of the annotated area, the fill color of the annotated area, the fill color of the border of the annotated icon, the fill color of the annotated icon, and the fill color of the text description; the adjustments to the display format of sensitive areas in the diffusion map include at least: adjusting the display order (top and bottom of the layer) of sensitive areas and adjusting the transparency of sensitive areas.
[0089] In one feasible implementation, the environmental protection prediction model mapping system further includes an environmental protection geographic information system (GIS) module; the environmental protection GIS module displays an electronic map on a graphical user interface before responding to the user's selection of the target file.
[0090] Specifically, after a user opens a prediction model mapping system for the environmental protection field, the environmental protection GIS module displays an electronic map on the graphical user interface. This electronic map can be an electronic map of a specified area or an electronic map of the geographical area described in the specified area.
[0091] In another feasible implementation, after the electronic map is displayed, a specified marker (user-specified marker) can be added to the electronic map, such as: adding the pollution source of the pollutant (pollution source location point), or selecting the factory boundary area, or selecting environmentally sensitive areas (such as the area where the river is located, the area where the ecological function zone is located, the area where the drinking water source protection area is located, the area where the nature reserve is located, the area where the forest park is located, the area where the school is located, the area where the hospital is located, etc.).
[0092] In another feasible implementation, after obtaining the diffusion map of the data to be mapped in the specified geographical area, the diffusion map is stored.
[0093] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.
[0094] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0095] In addition, the functional units in the embodiments provided in this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.
[0096] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0097] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0098] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.
Claims
1. A system for generating graphs from predictive models in the environmental protection field, characterized in that, The environmental protection prediction model mapping system includes at least one environmental impact prediction model mapping tool; the environmental impact prediction model mapping tool: In response to the user's selection of a target file, a grid point location map of the specified geographical area is generated based on several latitude and longitude data in the specified geographical area included in the target file; wherein, for each grid point constituting the grid point location map, there is a latitude and longitude data corresponding to that grid point in each of the latitude and longitude data; In response to the user's selection of the target interpolation algorithm from among the preset interpolation algorithms for the map data to be generated in the target file, a distribution map of the map data to be generated is constructed in the grid point location map based on the map data to be generated and the target interpolation algorithm; wherein, for each grid point in the distribution map, the value associated with the grid point is used to represent the value of the map data to be generated at the latitude and longitude location point corresponding to the grid point, and the latitude and longitude location point corresponding to the grid point is the geographical location point indicated by the latitude and longitude data corresponding to the grid point; The grid points in the distribution map are triangulated to construct a triangular network composed of the grid points in the distribution map; Based on the preset contour spacing and contour value range, contour tracing is performed on the triangulation network to obtain the contour map of the data to be mapped in the specified geographical area; The environmental impact prediction model mapping tools include: atmospheric prediction model mapping tools, surface water prediction model mapping tools, groundwater prediction model mapping tools, soil prediction model mapping tools, noise prediction model mapping tools, and risk prediction model mapping tools. When the environmental impact prediction model mapping tool is an atmospheric prediction model mapping tool, the data to be mapped is the concentration of air pollutants, and the contour map is a contour map of the concentration of air pollutants. When the environmental impact prediction model mapping tool is a surface water prediction model mapping tool, the data to be mapped is the concentration of surface water pollutants, and the contour map is a contour map of the concentration of surface water pollutants. When the groundwater prediction model mapping tool is used, the data to be mapped is the groundwater pollutant concentration, and the contour map is a contour map of the groundwater pollutant concentration; when the environmental impact prediction model mapping tool is used for soil prediction model mapping, the data to be mapped is the soil pollutant concentration, and the contour map is a contour map of the soil pollutant concentration; when the environmental impact prediction model mapping tool is used for noise prediction model mapping, the data to be mapped is the noise contribution value, and the contour map is a contour map of the noise contribution value; when the environmental impact prediction model mapping tool is used for risk prediction model mapping, the data to be mapped is the toxicity concentration value, and the contour map is a contour map of the toxicity concentration value. The response to the user's input on the data to be plotted in the target file and the selection of a target interpolation algorithm from among preset interpolation algorithms, and the construction of a distribution map of the data to be plotted in the grid point location map based on the data to be plotted and the target interpolation algorithm, includes: In response to the user's selection operation of the data to be mapped in the target file, based on the value of the data to be mapped corresponding to each latitude and longitude data in the target file, the value associated with the first grid point corresponding to the latitude and longitude data in the grid point location map is determined, and the original distribution map of the data to be mapped is obtained. In response to the user's selection of a target interpolation algorithm from among the preset interpolation algorithms, at least one second grid point is inserted into the original distribution map according to the target interpolation algorithm, and the value associated with each second grid point is determined to obtain the distribution map of the data to be output.
2. The environmental protection prediction model mapping system as described in claim 1, characterized in that, After obtaining the original distribution map of the data to be plotted, the process further includes: The graphical user interface displays an option table containing several preset interpolation algorithms, including: linear interpolation, nearest neighbor sampling, inverse distance multiplication, triangular network interpolation, and custom interpolation algorithms. The response to the user's selection of a target interpolation algorithm from among preset interpolation algorithms includes: In response to the user's selection of an interpolation algorithm from among several interpolation algorithms included in the option table, the selected interpolation algorithm is used as the target interpolation algorithm.
3. The environmental protection prediction model plotting system as described in claim 2, characterized in that, Also includes: In response to the user's selection of the custom interpolation algorithm in the option table, a preset definition template of the interpolation algorithm is displayed on the graphical user interface; In response to the algorithm definition entered by the user in the definition template, a custom interpolation algorithm is generated based on the definition.
4. The environmental protection prediction model plotting system as described in claim 1, characterized in that, After obtaining the contour map of the data to be mapped in the specified geographical area, the method further includes: Based on the target values of the data to be mapped set for each contour line in the contour map, the background color of the target area is filled with gradient colors in descending order of the target values to obtain a diffusion map of the data to be mapped in the specified geographical area; wherein, the target area is the area surrounded by the target contour lines in the contour map; the target contour lines are the contour lines corresponding to the smallest target values.
5. The environmental protection prediction model plotting system as described in claim 4, characterized in that, After obtaining the diffusion map of the data to be mapped in the specified geographical area, the method further includes: The diffusion map of the data to be plotted is displayed on a graphical user interface; wherein the display format of the diffusion map of the data to be plotted includes: image format file and / or SHP file format.
6. The environmental protection prediction model mapping system as described in claim 4, characterized in that, After obtaining the diffusion map of the data to be mapped in the specified geographical area, the method further includes: In response to a user's click on the print control in the environmental prediction model mapping system, the diffusion map of the data to be mapped is printed.
7. The environmental protection prediction model plotting system as described in claim 4, characterized in that, After obtaining the diffusion map of the data to be mapped in the specified geographical area, the method further includes: According to the preset target labels, target labels are added to the diffusion map of the data to be generated; wherein, the target labels include at least: plant boundary, north arrow, scale, text description, sensitive area and evaluation area range.
8. The environmental protection prediction model plotting system as described in claim 7, characterized in that, After adding target labels to the diffusion map of the data to be mapped, the process also includes: In response to the user's adjustment operation on the diffusion map of the data to be generated, the diffusion map of the data to be generated is adjusted according to the requirements of the adjustment operation; wherein, the adjustment operation includes the adjustment operation of the contour lines in the diffusion map and the adjustment operation of the target labels in the diffusion map.
9. The environmental protection prediction model plotting system as described in claim 1, characterized in that, The environmental protection prediction model mapping system also includes an environmental protection geographic information system (GIS) module. Before responding to the user's selection of a target file, the GIS module in the environmental protection field displays an electronic map on the graphical user interface.