Dynamic point tracing method, device and equipment for GIS map and medium

Abstract

The invention relates to a GIS map dynamic point tracing method and device, equipment and a medium. The method comprises the following steps: determining a coordinate system and performing initialization operation on a GIS map; obtaining map data in the GIS map, and constructing association between the map data and corresponding positions on the GIS map; dividing the map data into high-frequency data, intermediate-frequency data and low-frequency data according to the data updating frequency, and carrying out dynamic point tracing on the high-frequency data by adopting a sliding window weighted average algorithm; aiming at the intermediate frequency data, carrying out dynamic point tracing by combining a linear regression algorithm and a moving average algorithm; aiming at low-frequency data, performing dynamic point tracing by adopting a spline interpolation algorithm; and screening the updated data in the original map data, and performing real-time updating on the position of the corresponding tracing point in the GIS map by analyzing and extracting the position change information of the updated data. By adopting the method, accurate, efficient, real-time and flexible dynamic point tracing can be realized.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device, equipment and medium for dynamically drawing points on a GIS map. Background Art

[0002] With the continuous development and application of geographic information system (GIS) technology, GIS maps have become an important tool for displaying and analyzing geographic spatial data. GIS can provide multi-dimensional geographic information support through the collection, storage, processing, analysis, management and display of geographic spatial data, and is widely used in urban planning, environmental monitoring, traffic management, logistics distribution and other fields.

[0003] In the application process of GIS maps, point mapping plays an important role as a basic function. Traditional point mapping technology is mainly used to mark specific locations on GIS maps to help users intuitively view target areas, points of interest (POIs), waypoints and other geographical locations. The point mapping method is usually to fix the specified points on the map through manual input or preset data for further analysis or decision support.

[0004] However, with the widespread application of GIS maps, especially in the context of increasing demand for dynamic and real-time data, static point mapping has certain limitations due to its inability to reflect real-time changes in data, lack of flexibility, and inability to cope with high-frequency data updates. Therefore, how to implement a GIS map point mapping mechanism that can dynamically respond and automatically update to meet the needs of application scenarios such as real-time monitoring, traffic management, and logistics tracking has become a key issue for the further development of GIS technology. Summary of the invention

[0005] Based on this, it is necessary to provide a GIS map dynamic point drawing method, device, equipment and medium to address the above technical problems.

[0006] A GIS map dynamic point drawing method, the method comprising: Determine the coordinate system for GIS map matching and initialize the GIS map; Obtain map data in the GIS map and build associations between the map data and corresponding locations on the GIS map; According to the data update frequency, the map data is divided into high-frequency data, medium-frequency data and low-frequency data. For high-frequency data, the sliding window weighted average algorithm is used for dynamic point drawing; for medium-frequency data, the linear regression algorithm is combined with the moving average algorithm for dynamic point drawing; for low-frequency data, the spline interpolation algorithm is used for dynamic point drawing; By constructing conditional expressions and query statements, the updated data in the original map data is filtered, and the location change information of the updated data is extracted by analysis, and the location of the corresponding points in the GIS map is updated in real time.

[0007] In one embodiment, determining a coordinate system for matching a GIS map and initializing the GIS map includes: Determine the coordinate system that matches the GIS map according to the area of ​​the GIS map; the coordinate system includes the latitude and longitude coordinate system, the Mercator projection coordinate system and the Gauss-Kruger projection coordinate system; Load the GIS map in the pre-selected geographic information system and perform initial configuration operations on the GIS map; the geographic information systems include ArcGIS, QGIS and Leaflet; the initial configuration operations include: Determine the scope and boundaries of the GIS map by entering geographic coordinates or manually drawing polygons; Determine the base map of the GIS map, which includes satellite images, street maps and topographic maps of the area corresponding to the GIS map; Set the zoom level range and initial center point position of the GIS map and set the display and hiding of the GIS map control.

[0008] In one embodiment, obtaining map data in a GIS map and establishing an association between the map data and a corresponding location on the GIS map includes: Obtain map data in the GIS map and perform preprocessing; the map data acquisition method includes: calling the ODBC interface or JDBC interface to connect to the database storing the map data and read the structured map data in the database; using file format parsing to read the map data in the local data file; calling the network service interface based on the RESTful architecture to obtain real-time online map data; According to the attribute information and map elements of the preprocessed map data, spatial indexing and association algorithms are used to build the association between the map data and the corresponding positions on the GIS map; wherein the map elements include points, lines and surfaces of the GIS map.

[0009] In one embodiment, for high-frequency data, a sliding window weighted average algorithm is used to perform dynamic point plotting, including: High-frequency data is updated in seconds or minutes; For high-frequency data, a sliding window of high-frequency data is set, and a weight is assigned to each data point of high-frequency data newly entering the sliding window, and the weighted average of all data points in the sliding window is used as the plotting value of the high-frequency data; wherein, the data points in the sliding window are arranged in order of entry, and the earlier the data point enters, the later the arrangement position is. The weight value of the data point that enters the sliding window the latest is the highest, and as the position of the data point in the sliding window becomes later, the weight value gradually decreases; Furthermore, an exponential smoothing algorithm is used to smooth the plotting values ​​of the high-frequency data; specifically, a high weight is assigned to the plotting value of the latest acquired high-frequency data, and the weight of the plotting value of the historically acquired high-frequency data is gradually reduced, and the final plotting value of the high-frequency data is obtained by weighted summing up all the plotting values ​​of the high-frequency data.

[0010] In one embodiment, for the intermediate frequency data, a linear regression algorithm and a moving average algorithm are combined to perform dynamic plotting, including: Medium frequency data is updated on an hourly basis; For the intermediate frequency data, linear regression analysis is performed on the historical data corresponding to the intermediate frequency data to obtain the straight line equation that reflects the changing trend of the intermediate frequency data. The moving average algorithm is used to calculate the moving average of several recent data points of the intermediate frequency data. The predicted value of the straight line equation and the moving average are weighted summed to obtain the plotted point value of the intermediate frequency data.

[0011] In one embodiment, for low-frequency data, a spline interpolation algorithm is applied to dynamically plot points, including: Low-frequency data is updated at daily or weekly intervals; For low-frequency data, the discrete data points of the low-frequency data are fitted by the spline interpolation algorithm to obtain a fitting curve that reflects the changing trend of the low-frequency data, and the predicted value of the fitting curve is used as the plotting point value of the low-frequency data.

[0012] In one embodiment, by constructing conditional expressions and query statements, the updated data in the original map data is filtered, and the location change information of the updated data is extracted by analysis, and the location of the corresponding plotted point in the GIS map is updated in real time, including: Filter the updated data in the original map data by constructing conditional expressions and query statements based on numerical ranges, geographic location ranges, or time ranges; Analyze and extract the position change information in the update data, and perform format conversion and standardization on the position change information; According to the processed location change information, the API interface of the geographic information platform where the GIS map is located is called to update the location of the corresponding point in the GIS map in real time.

[0013] A GIS map dynamic point drawing device, the device comprising: The initialization module is used to determine the coordinate system of the GIS map and perform initialization operations on the GIS map; A data acquisition module is used to acquire map data in a GIS map and to establish associations between the map data and corresponding locations on the GIS map; The dynamic point drawing module is used to divide the map data into high-frequency data, medium-frequency data and low-frequency data according to the data update frequency. For high-frequency data, the sliding window weighted average algorithm is used for dynamic point drawing; for medium-frequency data, the linear regression algorithm is combined with the moving average algorithm for dynamic point drawing; for low-frequency data, the spline interpolation algorithm is used for dynamic point drawing; The point update module is used to filter the updated data in the original map data by constructing conditional expressions and query statements, and to update the positions of the corresponding points in the GIS map in real time by analyzing and extracting the position change information of the updated data.

[0014] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented: Determine the coordinate system for GIS map matching and initialize the GIS map; Obtain map data in the GIS map and build associations between the map data and corresponding locations on the GIS map; According to the data update frequency, the map data is divided into high-frequency data, medium-frequency data and low-frequency data. For high-frequency data, the sliding window weighted average algorithm is used for dynamic point drawing; for medium-frequency data, the linear regression algorithm is combined with the moving average algorithm for dynamic point drawing; for low-frequency data, the spline interpolation algorithm is used for dynamic point drawing; By constructing conditional expressions and query statements, the updated data in the original map data is filtered, and the location change information of the updated data is extracted by analysis, and the location of the corresponding points in the GIS map is updated in real time.

[0015] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps: Determine the coordinate system for GIS map matching and initialize the GIS map; Obtain map data in the GIS map and build associations between the map data and corresponding locations on the GIS map; According to the data update frequency, the map data is divided into high-frequency data, medium-frequency data and low-frequency data. For high-frequency data, the sliding window weighted average algorithm is used for dynamic point drawing; for medium-frequency data, the linear regression algorithm is combined with the moving average algorithm for dynamic point drawing; for low-frequency data, the spline interpolation algorithm is used for dynamic point drawing; By constructing conditional expressions and query statements, the updated data in the original map data is filtered, and the location change information of the updated data is extracted by analysis, and the location of the corresponding points in the GIS map is updated in real time.

[0016] The above-mentioned GIS map dynamic point drawing method, device, equipment and medium have the following beneficial effects compared with the traditional static point drawing method: 1. This application adopts different dynamic point mapping algorithms for map data of different frequencies, which has high adaptability and flexibility, can meet the dynamic point mapping needs in various application scenarios, and improve the accuracy and real-time performance of dynamic point mapping of GIS maps. Among them, the sliding window weighted average algorithm can timely reflect the latest changes in high-frequency data while smoothing some instantaneous extreme fluctuations; the linear regression algorithm and the moving average algorithm can more accurately capture the changes in medium-term data through trend prediction and trend adjustment based on new data; the spline interpolation algorithm maintains the long-term stability of low-frequency data through smooth interpolation.

[0017] 2. By constructing conditional expressions and query statements to set up precise screening mechanisms, we ensure that only updated data in the original map data can enter subsequent processing, which improves the accuracy of data processing and effectively reduces the load pressure during map rendering, ensuring the efficiency and response speed of map point updates. Especially when processing large-scale data and high-concurrency access, it can still maintain a smooth operation state, providing users with a stable and reliable service experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic diagram of a process of a GIS map dynamic point drawing method in one embodiment; Figure 2 A structural block diagram of a GIS map dynamic point drawing device in one embodiment; Figure 3 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0020] In one embodiment, Figure 1 As shown, a GIS map dynamic point drawing method is provided, comprising the following steps: Step S1, determine the coordinate system for GIS map matching and initialize the GIS map.

[0021] Wherein, step S1 specifically includes the following steps: First, determine the coordinate system that matches the GIS map based on the area of ​​the GIS map; the coordinate system includes the latitude and longitude coordinate system, the Mercator projection coordinate system, and the Gauss-Krüger projection coordinate system. Specifically, for different application scenarios and map requirements, it is necessary to weigh the advantages and limitations of various coordinate systems. For example, the latitude and longitude coordinate system is universal on a global scale, but it may be deformed when displayed on a large-area map; the Mercator projection coordinate system has equiangular characteristics in small-scale maps, which is suitable for fields such as marine navigation.

[0022] Then, load the GIS map into the pre-selected GIS and perform initial configuration operations on the GIS map; the GIS includes ArcGIS, which has excellent performance and powerful spatial analysis and data processing capabilities; QGIS, which is feature-rich and provides open source and highly customizable solutions; Leaflet, which is lightweight and flexible and suitable for building lightweight Web map applications. When choosing a GIS, you need to consider project scale, technical requirements, development costs and other factors to make a wise choice.

[0023] Among them, the initialization configuration operations of the GIS map include: determining the scope and boundaries of the GIS map by entering geographic coordinates or manually drawing polygons to ensure that the area displayed on the map meets user needs; determining the base map of the GIS map, which includes satellite images, street maps and topographic maps of the area corresponding to the GIS map; setting the zoom level range of the GIS map, the initial center point position, and setting details such as the display and hiding of GIS map controls.

[0024] Step S2, obtaining map data in the GIS map, and establishing an association between the map data and corresponding locations on the GIS map.

[0025] Wherein, step S2 specifically includes the following steps: First, obtain the map data in the GIS map and preprocess it. The methods of obtaining map data include: calling the ODBC (Open Database Connectivity) interface or the JDBC (Java Database Connectivity) interface to connect to the database (such as MySQL, Oracle) that stores the map data, and reading the structured map data in the database; using file formats (such as CSV, JSON, XML) to parse and read the map data in the local data file; calling the network service interface based on the RESTful (Representational State Transfer) architecture to obtain real-time online map data. At the same time, in order to ensure the legitimacy, accuracy and integrity of the data source, it is also necessary to perform necessary preprocessing operations such as data cleaning and data standardization after obtaining the map data.

[0026] Then, based on the attribute information of the pre-processed map data (such as geographic location fields, time fields, etc.) and map elements (such as points, lines, and surfaces on GIS maps), spatial indexing and association algorithms are used to build associations between map data and corresponding locations on GIS maps, achieving accurate matching and fusion of data and maps. For example, weather station data containing longitude and latitude information is associated with corresponding locations on GIS maps to intuitively display the spatial distribution of weather data.

[0027] Step S3, according to the data update frequency, the map data is divided into high-frequency data, medium-frequency data and low-frequency data. For high-frequency data, a sliding window weighted average algorithm is used for dynamic point plotting; for medium-frequency data, a linear regression algorithm is combined with a moving average algorithm for dynamic point plotting; for low-frequency data, a spline interpolation algorithm is used for dynamic point plotting.

[0028] Wherein, in the application scenario of mechanical cloud identifying excavator data, step S3 includes the following steps: High-frequency data is updated in seconds or minutes, such as the real-time position changes of the excavator's working trajectory and the frequent changes of the excavator's specific points. Medium-frequency data is updated in hours, such as the phased changes in the connection between the excavator and the construction personnel. Low-frequency data is updated in days or weeks, such as the daily or weekly summary data of the excavator's working trajectory in a specific area. This type of data focuses more on presenting long-term trends and laws, providing reference for construction planning and resource allocation.

[0029] For high-frequency data, a sliding window of high-frequency data is set, and a weight is assigned to each data point of high-frequency data newly entering the sliding window, and the weighted average of all data points in the sliding window is used as the plotting value of the high-frequency data; wherein, the data points in the sliding window are arranged in order of entry, and the earlier the data point enters, the later the arrangement position is, and the weight value of the data point that enters the sliding window the latest is the highest, and as the position of the data point in the sliding window becomes later, the weight value gradually decreases. In this way, while reflecting the latest changes in high-frequency data, some instantaneous extreme fluctuations can be smoothed out, avoiding excessive jumps in the plotting position due to instantaneous data fluctuations, and improving the accuracy of dynamic plotting of high-frequency data.

[0030] For example, if the sliding window of high-frequency data is set to 50 data points, and the data points in the sliding window are arranged in sequence as [10, 15, 20, 25, 30, …], and the weights are [0.5, 0.4, 0.3, 0.2, 0.1, …], then the weighted average = (10×0.5+15×0.4+20×0.3+25×0.2+30×0.1) / (0.5+0.4+0.3+0.2+0.1).

[0031] Furthermore, an exponential smoothing algorithm is used to smooth the plotting values ​​of high-frequency data. Through smoothing, the latest data points can get more attention each time they are updated, ensuring that the plotting values ​​always fit the current trend of change, while maintaining a certain influence on historical data, avoiding excessive interference of sudden changes or drastic changes on the system. Specifically, a high weight is given to the plotting values ​​of the latest high-frequency data, and the weight of the plotting values ​​of the historically acquired high-frequency data is gradually reduced. The final plotting value of the high-frequency data is obtained by weighted summing all the plotting values ​​of the high-frequency data. For example, the current weighted average value (i.e., the plotting value) of the high-frequency data is 20, and the last plotting value is 18. Assuming the weight (or smoothing) coefficient is 0.7, the new smoothed plotting value = 0.7×20+0.3×18.

[0032] For the intermediate frequency data, linear regression analysis is performed on the historical data corresponding to the intermediate frequency data to obtain the straight line equation that reflects the changing trend of the intermediate frequency data. The moving average algorithm is used to calculate the moving average of several recent data points of the intermediate frequency data. The predicted value of the straight line equation and the moving average are weighted summed to obtain the plotted point value of the intermediate frequency data.

[0033] For example, suppose the equation of the line obtained by linear regression is y = 5x + 10, and the moving average of the last 10 data points is 25. The weights are set to 0.6 and 0.4 respectively, then the plot point value of the intermediate frequency data = 0.6 × (5 × current time + 10) + 0.4 × 25.

[0034] It can be understood that by performing linear regression on the historical data of the medium-frequency data, the long-term trend of the medium-frequency data can be extracted. This trend analysis helps to predict the direction and speed of change of the medium-frequency data, ensuring that the dynamic plotting not only reflects the current data points, but also accurately captures the overall trend of the medium-frequency data changes. For example, in the scenario of traffic flow or temperature changes, linear regression can help predict future trends and improve the forward-looking nature of dynamic plotting. By calculating the moving average of the most recent data points of the medium-frequency data, short-term fluctuations can be effectively smoothed and the sharp fluctuations in the plotting value caused by local changes or noise can be reduced. This has a good smoothing effect on periodic or accidental fluctuations in the medium-frequency data (for example, daytime fluctuations in temperature, short-term changes in traffic volume, etc.).

[0035] Furthermore, in order to more accurately capture the changing trends in the medium term, the linear regression analysis can be re-performed periodically and the trend line can be adjusted according to the new intermediate frequency data.

[0036] For low-frequency data, the spline interpolation algorithm is used to fit the discrete data points of the low-frequency data to obtain a fitting curve that reflects the changing trend of the low-frequency data, and the predicted value of the fitting curve is used as the plotting value of the low-frequency data. The spline interpolation algorithm can provide high-quality continuous fitting between data points, especially for low-frequency data. It can effectively reflect the long-term changing trend of the data while maintaining the stability of the data. The fitting result will be a smooth and natural curve, rather than a straight line formed by connecting discrete points, avoiding rough jumps or mutations.

[0037] For example, for the working positions of the excavator in a specific area within a week, the cubic spline interpolation algorithm is used to fit the curve, which can clearly reflect whether the excavator's activity range in the area is gradually concentrated or expanded, and whether there are obvious repeated work areas.

[0038] In order to analyze low-frequency data more deeply, we can further combine statistical analysis methods, such as calculating the coverage area and average distance of the work trajectory, to provide a quantitative basis for construction efficiency evaluation and resource planning. In addition, by comparing low-frequency data with historical data of the same period, we can find improvements or potential problems in the construction mode and provide decision support for optimizing the construction process.

[0039] Step S4, by constructing conditional expressions and query statements, the updated data in the original map data is filtered, and the position change information of the updated data is extracted by analysis, and the position of the corresponding plotted point in the GIS map is updated in real time.

[0040] Wherein, step S4 specifically includes the following steps: First, we filter the updated data in the original map data by constructing conditional expressions and query statements based on numerical ranges, geographic location ranges, or time ranges. The numerical ranges include temperature above 30 degrees, wind speed below 5 meters per second, etc.; the geographic location ranges include within a specific city, within a specific latitude and longitude area; and the time ranges include within a certain time period, data from the last week, etc. By constructing conditional expressions and query statements, we can accurately filter the updated data.

[0041] Then, the position change information in the updated data is analyzed and extracted, and the position change information is formatted and standardized. Specifically, by using statistical analysis methods (such as mean, median, standard deviation), cluster analysis, classification algorithms, etc., the position change information in the updated data that is closely related to the map point position can be analyzed and extracted, such as changes in longitude and latitude coordinates or changes in altitude. At the same time, in order to meet the needs of map point drawing, the position change information needs to be further formatted and standardized.

[0042] Finally, based on the processed location change information, the API interface (application programming interface) of the geographic information platform where the GIS map is located is called to update the location of the corresponding points in the GIS map in real time to ensure the real-time and accuracy of the map information. Furthermore, the API interface can also be called to handle possible concurrent updates and data conflicts to ensure the stability and consistency of the map display.

[0043] Through the above-mentioned GIS map dynamic point drawing method, it is possible to quickly and sensitively respond to changes in the state of geographic space, and automatically realize accurate, efficient, real-time and flexible dynamic point drawing on the GIS map, thereby effectively enhancing the real-time and interactivity of the GIS system, significantly improving the effectiveness of data visualization, and effectively improving the ability of decision support, which can meet the specific needs of various application scenarios. For example, in the traffic flow monitoring scenario, this method can accurately reflect the instantaneous changes of road congestion points in a blink of an eye, providing drivers with a key basis for quickly adjusting routes, greatly improving travel efficiency and planning flexibility. In the field of agricultural irrigation, this method can accurately and accurately mark the subtle changes in soil moisture in each piece of farmland, providing strong support for the goal of achieving precision irrigation, and effectively improving the utilization efficiency of agricultural resources and the growth quality of crops. In application scenarios with extremely high real-time requirements such as emergency response and traffic monitoring, this method can provide decision makers with instant and accurate geographic information references, thereby greatly enhancing the ability and efficiency of responding to emergencies.

[0044] In one embodiment, Figure 2 As shown, a GIS map dynamic point drawing device is provided, comprising: The initialization module 201 is used to determine the coordinate system for GIS map matching and perform initialization operations on the GIS map.

[0045] The data acquisition module 202 is used to acquire map data in the GIS map and to establish an association between the map data and corresponding locations on the GIS map.

[0046] The dynamic point drawing module 203 is used to divide the map data into high-frequency data, medium-frequency data and low-frequency data according to the data update frequency. For high-frequency data, a sliding window weighted average algorithm is used for dynamic point drawing; for medium-frequency data, a linear regression algorithm is combined with a moving average algorithm to perform dynamic point drawing; for low-frequency data, a spline interpolation algorithm is used for dynamic point drawing.

[0047] The plot point update module 204 is used to filter the update data in the original map data by constructing conditional expressions and query statements, and to update the positions of the corresponding plot points in the GIS map in real time by analyzing and extracting the position change information of the update data.

[0048] The specific definition of a GIS map dynamic point drawing device can be found in the above definition of a GIS map dynamic point drawing method, which will not be repeated here. Each module in the above-mentioned GIS map dynamic point drawing device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0049] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a GIS map dynamic point drawing method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0050] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0051] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented: Determine the coordinate system for GIS map matching and initialize the GIS map; Obtain map data in the GIS map and build associations between the map data and corresponding locations on the GIS map; According to the data update frequency, the map data is divided into high-frequency data, medium-frequency data and low-frequency data. For high-frequency data, the sliding window weighted average algorithm is used for dynamic point drawing; for medium-frequency data, the linear regression algorithm is combined with the moving average algorithm for dynamic point drawing; for low-frequency data, the spline interpolation algorithm is used for dynamic point drawing; By constructing conditional expressions and query statements, the updated data in the original map data is filtered, and the location change information of the updated data is extracted by analysis, and the location of the corresponding points in the GIS map is updated in real time.

[0052] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Determine the coordinate system for GIS map matching and initialize the GIS map; Obtain map data in the GIS map and build associations between the map data and corresponding locations on the GIS map; According to the data update frequency, the map data is divided into high-frequency data, medium-frequency data and low-frequency data. For high-frequency data, the sliding window weighted average algorithm is used for dynamic point drawing; for medium-frequency data, the linear regression algorithm is combined with the moving average algorithm for dynamic point drawing; for low-frequency data, the spline interpolation algorithm is used for dynamic point drawing; By constructing conditional expressions and query statements, the updated data in the original map data is filtered, and the location change information of the updated data is extracted by analysis, and the location of the corresponding points in the GIS map is updated in real time.

[0053] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0054] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0055] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A GIS map dynamic point drawing method, characterized in that: The method comprises: Determine the coordinate system for GIS map matching and perform initialization operations on the GIS map; Acquire map data in the GIS map, and establish an association between the map data and corresponding locations on the GIS map; According to the data update frequency, the map data is divided into high-frequency data, medium-frequency data and low-frequency data. For the high-frequency data, the sliding window weighted average algorithm is used for dynamic point plotting; for the medium-frequency data, the linear regression algorithm is combined with the moving average algorithm for dynamic point plotting; for the low-frequency data, the spline interpolation algorithm is used for dynamic point plotting; By constructing conditional expressions and query statements, the updated data in the original map data is filtered, and the position change information of the updated data is extracted by analysis, so as to update the position of the corresponding plotted points in the GIS map in real time.

2. The method according to claim 1, characterized in that Determine the coordinate system for GIS map matching and perform initialization operations on the GIS map, including: Determining a coordinate system matching the GIS map according to the area of ​​the GIS map; wherein the coordinate system includes a latitude and longitude coordinate system, a Mercator projection coordinate system, and a Gauss-Krüger projection coordinate system; The GIS map is loaded into a pre-selected geographic information system, and an initial configuration operation is performed on the GIS map; wherein the geographic information system includes ArcGIS, QGIS and Leaflet; and the initial configuration operation includes: Determine the scope and boundaries of the GIS map by entering geographic coordinates or manually drawing polygons; Determine a base map of the GIS map, wherein the base map includes a satellite image map, a street map, and a topographic map of the area corresponding to the GIS map; Set the zoom level range and initial center point position of the GIS map and set the display and hiding of the GIS map control.

3. The method according to claim 1, characterized in that: Obtaining map data in a GIS map and establishing an association between the map data and a corresponding location on the GIS map, including: Obtaining map data in a GIS map and preprocessing it; wherein the map data acquisition method includes: calling an ODBC interface or a JDBC interface to connect to a database storing map data and reading structured map data in the database; using file format parsing to read map data in a local data file; calling a network service interface based on a RESTful architecture to obtain real-time online map data; According to the attribute information and map elements of the preprocessed map data, a spatial index and association algorithm is used to construct an association between the map data and the corresponding positions on the GIS map; wherein the map elements include points, lines and surfaces of the GIS map.

4. The method according to claim 1, characterized in that: For the high-frequency data, a sliding window weighted average algorithm is used to perform dynamic point plotting, including: High-frequency data is updated in seconds or minutes; For the high-frequency data, a sliding window of high-frequency data is set, a weight is assigned to each data point of the high-frequency data newly entering the sliding window, and the weighted average of all data points in the sliding window is used as the plotting value of the high-frequency data; wherein the data points in the sliding window are arranged in sequence according to the order of entry, the earlier the data point enters, the later the arrangement position, the weight value of the data point that enters the sliding window the latest is the highest, and as the position of the data point in the sliding window becomes later, the weight value gradually decreases; Furthermore, an exponential smoothing algorithm is used to smooth the plotting values ​​of the high-frequency data; specifically, a high weight is assigned to the plotting value of the latest acquired high-frequency data, and the weight of the plotting value of the historically acquired high-frequency data is gradually reduced, and the final plotting value of the high-frequency data is obtained by weighted summing up all the plotting values ​​of the high-frequency data.

5. The method according to claim 1, characterized in that For the intermediate frequency data, dynamic plotting is performed by combining a linear regression algorithm with a moving average algorithm, including: Medium frequency data is updated on an hourly basis; For the intermediate frequency data, a linear regression analysis is performed on the historical data corresponding to the intermediate frequency data to obtain a straight line equation reflecting the changing trend of the intermediate frequency data, and a moving average algorithm is used to calculate and obtain the moving average value of several recent data points of the intermediate frequency data. The predicted value of the straight line equation and the moving average value are weightedly summed to obtain the plotted point value of the intermediate frequency data.

6. The method according to claim 1, characterized in that For the low-frequency data, a spline interpolation algorithm is applied to dynamically plot points, including: Low-frequency data is updated at daily or weekly intervals; For the low-frequency data, the discrete data points of the low-frequency data are fitted by a spline interpolation algorithm to obtain a fitting curve reflecting the changing trend of the low-frequency data, and the predicted value of the fitting curve is used as the plotting point value of the low-frequency data.

7. The method according to claim 1, characterized in that By constructing conditional expressions and query statements, the updated data in the original map data is filtered, and the position change information of the updated data is extracted by analysis, and the position of the corresponding plotted point in the GIS map is updated in real time, including: Filter the updated data in the original map data by constructing conditional expressions and query statements based on numerical ranges, geographic location ranges, or time ranges; Analyzing and extracting the position change information in the update data, and performing format conversion and standardization processing on the position change information; According to the processed position change information, the API interface of the geographic information platform where the GIS map is located is called to update the position of the corresponding point in the GIS map in real time.

8. A GIS map dynamic point drawing device, characterized in that: The device comprises: An initialization module is used to determine the coordinate system of the GIS map and perform initialization operations on the GIS map; A data acquisition module, used to acquire map data in a GIS map and to establish an association between the map data and corresponding locations on the GIS map; The dynamic point drawing module is used to divide the map data into high-frequency data, medium-frequency data and low-frequency data according to the data update frequency. For the high-frequency data, the sliding window weighted average algorithm is used for dynamic point drawing; for the medium-frequency data, the linear regression algorithm and the moving average algorithm are combined to perform dynamic point drawing; for the low-frequency data, the spline interpolation algorithm is used for dynamic point drawing; The point update module is used to filter the update data in the original map data by constructing conditional expressions and query statements, and to extract the position change information of the update data by analyzing and updating the position of the corresponding points in the GIS map in real time.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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