Online visualization method and system of paleogeographic maps based on Gplates and Vue

Abstract

The present invention discloses a method and system for online visualization of paleogeographic maps based on Gplates and Vue, belonging to the field of map data processing technology. The method includes the following steps: when a user enters a map browsing interface for each historical period, the base map data for that period is first displayed; layer data and high-level interaction data are preloaded based on the user's device resolution and historical browsing data; dynamic performance optimization is performed using performance evaluation data; and dynamic resource allocation is performed on user cached data based on user information data. When the user zooms in or out during browsing, the dynamically loaded data of the user's interaction operation is used to further determine whether to load detailed areas. The user interaction data is then hierarchically stored based on the operation frequency and historical interaction status, thereby improving the efficiency and fluency of the user's browsing of paleogeographic maps.

Description

Technical Field

[0001] The present invention relates to the technical field of map data processing, and in particular to a paleogeographic map online visualization method and system based on Gplates and Vue. Background Art

[0002] With the advancement of digital cultural heritage preservation, the demand for the preservation, research, and dissemination of ancient maps, as important historical documents, is growing. Simultaneously, the maturity of GIS (Geographic Information System) technology enables the precise matching of ancient maps with modern geographic data, while advances in web technology provide technical support for online interaction.

[0003] The existing online visualization method of ancient maps is to convert them into digital images through high-resolution scanning and digitization, use GIS technology to geo-reference the maps, align them with modern geographic coordinates, and then embed the processed maps into online platforms through Web technology. Users can interact with them through browsers, thus realizing the online visualization and interactive experience of ancient maps.

[0004] For example, the online mapping system based on geographic information disclosed in the patent application with publication number CN118885553A includes: a data collection module, a data processing module, a data comparison module, a map tool service module and a map inspection module; the data collection module includes a Tiandi Map data collection unit, a remote sensing image collection unit and a GIS data collection unit; the data processing module includes a preprocessing unit, a correction unit and an editing unit.

[0005] For example, the online data visualization implementation method, system, device and medium announced in the invention patent with announcement number CN114996374B include: obtaining the target area and area view range information of the geographic information system map, dividing the target area into multiple grids to be rendered according to the preset grid size, determining the grid view position information of each grid to be rendered, and determining the grid geographical location information of each grid to be rendered, determining multiple related stations and related measured data of each related station from multiple preset data collection stations, and then obtaining simulation data of each grid to be rendered, generating a grayscale image through the maximum measured value and each simulation data, and coloring each pixel of the grayscale image according to the grayscale-color mapping relationship to obtain a color image of the target area, thereby realizing online data visualization of the target area.

[0006] However, in the process of implementing the technical solutions of the embodiments of the present application, the present application discovered that the above technology has at least the following technical problems:

[0007] In the existing technology, when users view paleogeographic maps online, paleogeographic maps usually have high resolution and complex details. These factors result in large image files and a large amount of map data. At the same time, users need to perform complex interactive operations such as zooming and viewing details of different layers, which leads to page freezes and long waiting times during the viewing process. Summary of the Invention

[0008] The present invention provides a paleogeographic map online visualization method and system based on Gplates and Vue, which solves the problem in the prior art that when users view paleogeographic maps online, paleogeographic maps usually have high resolution and complex details. These factors lead to large image files and a lot of map data. At the same time, users need to perform complex interactive operations such as zooming and viewing details of different layers, which leads to page freezes and long waiting times during the viewing process. The present invention achieves efficient loading and smooth interaction of online visualization of paleogeographic maps, significantly improving the user experience.

[0009] The present invention provides an online visualization method for paleogeographic maps based on Gplates and Vue, comprising the following steps: classifying paleogeographic maps according to historical periods to obtain maps of each historical period, and then performing secondary classification on the maps of each historical period according to data content to obtain basic map data and layer data of each historical period; when a user enters a map browsing interface of each historical period, first displaying the basic map data of the historical period, preloading layer data and high-level interaction data according to the user device resolution and the user's historical browsing data, performing dynamic performance optimization using performance evaluation data, and dynamically allocating resources to user cache data based on user information data; when the user performs a zoom operation during browsing, further determining whether to load a detail area based on the dynamically loaded data of the user's interaction operation, and performing hierarchical storage based on the operation frequency and historical interaction status of the user interaction data.

[0010] Furthermore, the performance evaluation data includes loading time, update time and response time; the step of using the performance evaluation data to perform dynamic performance optimization includes: obtaining critical loading time, critical update time and critical response time from the ancient map database; performing proportion proximity calculation on the critical loading time, critical update time and critical response time respectively with the loading time, update time and response time, and performing weighted calculation on the results of the proportion proximity calculation and then coupling processing to obtain performance evaluation indicators, and performing performance optimization on the ancient geographical map according to the performance evaluation indicators to obtain optimized performance evaluation indicators, which represent quantitative data on the degree of influence of loading time, update time and response time on the loading performance of the ancient geographical map; comparing and matching the optimized performance evaluation indicators with the map status evaluation thresholds corresponding to each performance evaluation indicator preset in the ancient map database to obtain the map status evaluation thresholds corresponding to the optimized performance evaluation indicators.

[0011] Furthermore, the step of optimizing the performance of the paleogeographic map according to the performance evaluation index includes: obtaining a first performance evaluation threshold and a second performance evaluation threshold from the paleogeographic map database; comparing the performance evaluation index with the first performance evaluation threshold and the second performance evaluation threshold respectively; if the performance evaluation index is less than the first performance evaluation threshold, marking the paleogeographic map as a severely abnormal program and immediately enabling degradation mode; if the performance evaluation index is greater than or equal to the first performance evaluation threshold and less than the second performance evaluation threshold, matching the performance evaluation index with the adjustment multiples corresponding to each performance evaluation index preset in the paleogeographic map database to obtain the adjustment multiples corresponding to the performance evaluation index, and adjusting the performance tuning parameters according to the adjustment multiples; if the performance evaluation index is greater than or equal to the second performance evaluation threshold, no additional operation is performed.

[0012] Furthermore, the user information data includes the number of users, the data load amount of each user and the cached data amount of each user; the step of dynamically allocating resources to the user cached data based on the user information data includes: obtaining the critical number of users, the critical data load amount and the critical cached data amount from the ancient map database; performing a coupling process on the data load amount of each user and the cached data amount of each user with the critical data load amount and the critical cached data amount respectively, and then performing a weighted operation on the processing result and the result of the proportion proximity operation of the number of users and the critical number of users, and then performing an inverse proportional operation to obtain a map status evaluation value, the map status evaluation value represents quantitative data on the degree of influence of the number of users, the data load amount of each user and the cached data amount of each user on the usage status of the ancient geographical map; dynamically allocating resources to the user cached data according to the map status evaluation value and the map status evaluation threshold, the dynamic resource allocation is used to dynamically adjust the loaded data and cache to improve the response speed and overall performance of the system.

[0013] Furthermore, the step of dynamically allocating resources to user cached data based on the map state evaluation value and the map state evaluation threshold includes: comparing the map state evaluation value and the map state evaluation threshold: if the map state evaluation value is greater than or equal to the map state evaluation threshold, no additional processing is performed; if the map state evaluation value is less than the map state evaluation threshold, marking the difference between the map state evaluation threshold and the map state evaluation value as a deviation map state evaluation value, and dynamically allocating resources to the user cached data based on the deviation map state evaluation value.

[0014] Furthermore, the step of dynamically allocating resources for user cached data based on the deviation map status evaluation value includes: obtaining a deviation map status evaluation threshold from the ancient map database; comparing the deviation map status evaluation value with the deviation map status evaluation threshold: if the deviation map status evaluation value is less than or equal to the deviation map status evaluation threshold, switching all users to the simplified map mode, and matching the deviation map status evaluation value with the data allowable loading ratio corresponding to each deviation map status evaluation value preset in the ancient map database to obtain the data allowable loading ratio, comparing the total data loading capacity with the number of users, and then obtaining the user data allowable loading amount through multiplication operation of the data allowable loading ratio, and releasing the cached data based on the user data allowable loading amount and the current loading amount of each user; if the deviation map status evaluation value is greater than the deviation map status evaluation threshold, switching all users to the simplified map mode, and releasing all cached data according to the cached data time.

[0015] Furthermore, the dynamically loaded data includes map resolution and user zoom ratio; when the user performs a zoom operation during browsing, the dynamically loaded data based on the user interaction operation is further used to determine whether to load the detail area. The specific steps include: obtaining the critical map resolution, the reference user zoom ratio and the allowable deviation user zoom ratio from the ancient map database; performing a proportion approximation operation on the critical map resolution and the map resolution to obtain a map resolution influencing parameter; performing a deviation conformity operation on the allowable deviation user zoom ratio, the reference user zoom ratio and the user zoom ratio to obtain a user zoom ratio influencing parameter; and then performing a weighted operation on the map resolution influencing parameter and the user zoom ratio influencing parameter and coupling processing to obtain an interactive permission evaluation value. The interactive permission evaluation value represents quantitative data on the degree of influence of the map resolution and the user zoom ratio on the interactive processing capability of the device, and determining whether to load the detail area is based on the interactive permission evaluation value.

[0016] Furthermore, the step of determining whether to load the detail area based on the interaction permission evaluation value includes: matching the user device resolution with the interaction permission evaluation threshold corresponding to each device resolution preset in the ancient map database to obtain the interaction permission evaluation threshold; comparing the interaction permission evaluation value with the interaction permission evaluation threshold; if the interaction permission evaluation value is greater than or equal to the interaction permission evaluation threshold, the interaction operation is allowed, and the interaction status is marked as normal; if the interaction permission evaluation value is less than the interaction permission evaluation threshold, and the user device is in normal operating status, the interaction operation is allowed, the interaction status is marked as normal, and the interaction permission evaluation value is marked as the interaction permission evaluation threshold of the current user device; if the interaction permission evaluation value is less than the interaction permission evaluation threshold, and the user device is in abnormal operating status, the interaction status is marked as abnormal, the interaction data of the map of the current historical period is retained, and all cached data is released.

[0017] Furthermore, the step of performing hierarchical storage based on the operation frequency and historical interaction status of user interaction data includes: obtaining an operation frequency threshold from an ancient map database; marking user interaction data whose operation frequency is greater than or equal to the operation frequency threshold and whose historical interaction status is normal as high-level interaction data; marking user interaction data whose operation frequency is less than the frequency threshold or whose historical interaction status is abnormal as low-level interaction data; storing high-level interaction data in a high-speed storage medium and storing low-level interaction data in a traditional storage medium.

[0018] An embodiment of the present application provides an online visualization system for paleogeographic maps based on Gplates and Vue, including a map classification module, a performance optimization module, a data interaction module and an ancient map database; wherein the map classification module is used to classify paleogeographic maps according to historical periods to obtain maps of each historical period, and then perform secondary classification on the maps of each historical period according to data content to obtain basic map data and layer data of each historical period; the performance optimization module is used to first display the basic map data of each historical period when the user enters the map browsing interface of the historical period, preload layer data and high-level interaction data according to the user device resolution and the user's historical browsing data, use performance evaluation data to perform dynamic performance optimization, and dynamically allocate resources to user cache data based on user information data; the data interaction module is used to further determine whether to load detailed areas based on the dynamic loading data of the user interaction operation when the user performs a zoom operation during the browsing process, and perform hierarchical storage based on the operation frequency and historical interaction status of the user interaction data.

[0019] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0020] 1. The present invention provides an online visualization method and system for paleogeographic maps based on Gplates and Vue, which can perform map classification and data secondary classification according to historical periods, dynamically load and display basic map data and layer data, and thus realize dynamic allocation and hierarchical storage of resources, intelligently optimize loading strategies according to user device performance and historical interaction data, improve user experience and optimize system performance.

[0021] 2. The present invention dynamically allocates resources to user cache data based on user information data, and can intelligently allocate resources according to the user's historical browsing and interaction status to avoid unnecessary resource waste, thereby further improving system performance and optimizing user experience, thereby achieving efficient resource management and dynamic optimization, ensuring a smooth map browsing experience under different devices and network environments.

[0022] 3. The present invention further determines whether to load detail areas by dynamically loading data based on user interaction operations, and performs hierarchical storage based on the operation frequency and historical interaction status of user interaction data, thereby accurately judging user needs, avoiding unnecessary data loading, improving the utilization efficiency of system resources, and achieving a smoother map browsing experience.

[0023] 4. The present invention obtains performance evaluation indicators through comprehensive analysis of loading time, update time and response time, thereby quantifying the impact of loading time, update time and response time on the loading performance of paleogeographic maps, and then realizes performance optimization of paleogeographic maps according to the optimized performance evaluation indicators, thereby improving loading efficiency and interactive response speed, and ultimately enhancing the user's browsing experience and the overall performance of the system.

[0024] 5. The present invention obtains a map status evaluation value through a comprehensive analysis of the number of users, the amount of data loaded by each user, and the amount of cached data of each user, thereby quantifying the degree of influence of the number of users, the amount of data loaded by each user, and the amount of cached data of each user on the usage status of the paleogeographic map. This further realizes dynamic resource allocation of user cached data according to the map status evaluation value, optimizes the allocation method of loaded data and cache, improves the response speed and overall performance of the system, and enhances the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 Flowchart of the online visualization method of paleogeographic maps based on Gplates and Vue provided in the embodiment of this application.

[0026] Figure 2 A graph showing changes in performance evaluation indicators based on the online visualization method for paleogeographic maps provided in an embodiment of the present application.

[0027] Figure 3This is a schematic diagram of the structure of the online paleogeographic map visualization system based on Gplates and Vue provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The embodiment of the present application solves the problem in the prior art that when users view paleogeographic maps online, paleogeographic maps usually have high resolution and complex details. These factors lead to large image files and a lot of map data. At the same time, users need to perform complex interactive operations such as zooming and viewing details of different layers, which leads to page freezes and long waiting times during the viewing process. By classifying paleogeographic maps according to historical periods, maps of each historical period are obtained, and then the maps of each historical period are secondary classified according to data content to obtain basic information of each historical period. Basic map data and layer data of each historical period; when the user enters the map browsing interface of each historical period, the basic map data of the historical period is displayed first, and the layer data and high-level interaction data are preloaded according to the user's device resolution and the user's historical browsing data. Dynamic performance optimization is performed using performance evaluation data, and dynamic resource allocation is performed on user cache data based on user information data; when the user zooms in and out during browsing, the dynamic loading data based on the user's interactive operation further determines whether to load the detailed area, and hierarchical storage is performed based on the operation frequency and historical interaction status of the user interaction data, thereby improving the efficiency and fluency of users browsing paleogeographic maps.

[0029] The technical solution in the embodiments of the present application is to solve the above-mentioned problems when users view paleogeographic maps online. Because paleogeographic maps usually have high resolution and complex details, these factors lead to large image files and a large amount of map data. At the same time, users need to perform complex interactive operations such as zooming in and out and viewing details of different layers, which may cause page freezes and long waiting times during the viewing process. The overall concept is as follows:

[0030] By classifying paleogeographic maps according to historical periods and performing secondary classification on maps of each historical period, we obtain basic map data and layer data. When users enter the map browsing interface of each historical period, basic map data is displayed first, and layer data and high-level interactive data are preloaded based on the user's device resolution and historical browsing data. At the same time, dynamic performance optimization is performed through performance evaluation data, and cached data is dynamically allocated resources based on user information data to ensure efficient utilization of system performance. When the user zooms in or out, the dynamically loaded data further determines whether to load detailed areas based on the user's interactive operation, and is stored in a hierarchical manner according to the user's operation frequency and historical interaction status, achieving efficient display and smooth browsing of maps from different historical periods.

[0031] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0032] like Figure 1 As shown, it is a flow chart of the online visualization method of paleogeographic maps based on Gplates and Vue provided by an embodiment of the present application. The method is applied to the online visualization device of paleogeographic maps based on Gplates and Vue, and the method includes the following steps: classifying the paleogeographic maps according to historical periods to obtain maps of each historical period, and then classifying the maps of each historical period for a second time according to the data content to obtain the basic map data of each historical period and the layer data of each historical period; when the user enters the map browsing interface of each historical period, the basic map data of the historical period is first displayed, and the layer data and high-level interaction data are preloaded according to the user device resolution and the user's historical browsing data, dynamic performance optimization is performed using performance evaluation data, and dynamic resource allocation is performed on the user cache data based on user information data; when the user performs a zoom operation during the browsing process, the dynamic loading data of the user interaction operation is further determined based on the dynamic loading data of the user interaction operation, and hierarchical storage is performed based on the operation frequency and historical interaction status of the user interaction data.

[0033] In this embodiment, the present application is a way to dynamically and interactively display paleogeographic data (such as plate tectonics, paleoclimate, etc.) through modern Web technology, through the powerful earth historical data visualization function provided by Gplates and the interactive front-end framework provided by Vue.js, combined with WebGL and other related technologies, to help users better understand the earth's historical geographical information and conduct real-time geographic data analysis. Basic map data refers to the core content that constitutes the map, including geographic boundary information, terrain information, geographic coordinate system, basic road information, basic city points, etc. Layer data is the data of different levels displayed in the map, including historical population data, cultural relics of various historical periods, geographic data of wars or important events, historical buildings or heritage sites, etc. Map data is divided into basic map data and layer data for separate management, which can avoid slow loading caused by excessively large data; according to the user's device resolution, the layer data allowed by the device resolution is loaded to avoid wasting bandwidth and memory, and at the same time, the user's area of ​​interest is inferred based on the user's historical browsing data, and relevant data is loaded in advance to improve user experience; the present invention dynamically adjusts resource allocation based on real-time performance evaluation to avoid slow loading caused by poor user device performance or network instability, and dynamically adjusts cache content based on user historical data and current data loading information, reduces unnecessary caching and data preloading, and improves storage space utilization; when the user zooms, the present invention dynamically loads data according to the operation. When the user uses the system to view paleogeographic maps, the present invention can further load detailed layer data under the condition that the user device and the system are operating normally, so that the map content viewed by the user is more detailed, fast and effective.

[0034] In addition, the ancient map database is used to store relevant data of the online visualization method of paleogeographic maps based on Gplates and Vue, including: the influencing factor of the performance evaluation index corresponding to the loading time, the critical loading time, the critical update time, the critical response time, the first threshold of performance evaluation and the adjustment multiples corresponding to each performance evaluation index, etc. The data in the ancient map database can be obtained directly through the Gplates database, or through cooperation with geological information agencies or relevant academic institutions.

[0035] Furthermore, the performance evaluation data includes loading time, update time and response time; the step of using the performance evaluation data to perform dynamic performance optimization includes: obtaining critical loading time, critical update time and critical response time from the ancient map database; performing proportion proximity calculation on the critical loading time, critical update time and critical response time respectively with the loading time, update time and response time, and performing weighted calculation on the results of the proportion proximity calculation and then coupling processing to obtain performance evaluation indicators, and performing performance optimization on the ancient geographical map according to the performance evaluation indicators to obtain optimized performance evaluation indicators, which represent quantitative data on the degree of influence of loading time, update time and response time on the loading performance of the ancient geographical map; comparing and matching the optimized performance evaluation indicators with the map status evaluation thresholds corresponding to each performance evaluation indicator preset in the ancient map database to obtain the map status evaluation thresholds corresponding to the optimized performance evaluation indicators.

[0036] The performance evaluation index is obtained as follows:

[0037]

[0038] Where PE represents the performance evaluation index, α1 represents the performance evaluation index impact factor corresponding to the loading time, α2 represents the performance evaluation index impact factor corresponding to the update time, α3 represents the performance evaluation index impact factor corresponding to the response time, LT1 represents the loading time, LT0 represents the critical loading time, UT1 represents the update time, UT0 represents the critical update time, RT1 represents the response time, and RT0 represents the critical response time.

[0039] α1, α2, and α3 are the performance evaluation index impact factors corresponding to load time, update time, and response time, respectively, preset in the ancient map database. These values ​​represent the degree of impact of load time, update time, and response time on the performance evaluation index, and can be directly retrieved from the ancient map database. These relationships are organized into a "mapping set," a lookup table or corresponding rules. When a performance evaluation data value is actually monitored, the corresponding performance evaluation index impact factor can be found by searching the corresponding mapping set. This impact factor is a number between 0 and 1, representing the impact of the current performance evaluation data on the performance evaluation index. For example, for load time, there is a mapping set of load time and performance evaluation index impact factors corresponding to load time. Entering the load time value yields the performance evaluation index impact factor corresponding to load time. For update time, there is a mapping set of update time and performance evaluation index impact factors corresponding to update time. Entering the update time value yields the performance evaluation index impact factor corresponding to update time. For response time, there is a mapping set of response time and performance evaluation index impact factors corresponding to response time. Entering the response time value yields the performance evaluation index impact factor corresponding to response time. These mapping relationships can be many-to-one or one-to-one.

[0040] In this embodiment, the loading time represents the time from the user initiating a request to the time the paleogeographic map is fully loaded and displayed on the page. The longer the loading time, the lower the performance evaluation index; the update time represents the time required for the page content to update and display new data after the user performs an interactive operation (such as zooming, switching layers). The longer the update time, the lower the performance evaluation index; the response time represents the time from the user's operation (such as clicking, dragging) to the system's feedback (such as the image starts to move or zoom). The longer the response time, the lower the performance evaluation index. The three are interrelated. For example, a longer loading time may lead to longer subsequent update time and response time. The performance evaluation indicators obtained through comprehensive analysis can measure the efficiency and user experience of the system during actual operation. Optimizing the performance of paleogeographic maps based on performance evaluation indicators can not only help users access and operate historical geographic information more quickly, but also ensure that the system remains stable and reliable under large-scale use, ultimately improving the platform's usage rate and user stickiness.

[0041] The performance evaluation index impact factor for load time was set to 0.4, the performance evaluation index impact factor for update time was set to 0.2, and the performance evaluation index impact factor for response time was set to 0.4. The load time was set to 0.2s, the critical load time was set to 0.1s, the update time was set to 0.05s, the critical update time was set to 0.05s, and the critical response time was set to 0.05s. Performance evaluation indicators were calculated under the condition of increasing response time. Table 1 shows the performance evaluation index data based on the online visualization method of paleogeographic maps.

[0042] Table 1 Performance evaluation index data table based on online visualization method of paleogeographic map

[0043]

[0044]

[0045] like Figure 2 As shown in Table 1 and Figure 2 It can be seen that while the performance evaluation index impact factor corresponding to loading time, the performance evaluation index impact factor corresponding to update time, the performance evaluation index impact factor corresponding to response time, loading time, critical loading time, update time, critical update time and critical response time remain unchanged, and the response time continues to increase, the performance evaluation index continues to decrease.

[0046] Furthermore, the step of optimizing the performance of the paleogeographic map according to the performance evaluation index includes: obtaining a first performance evaluation threshold and a second performance evaluation threshold from the paleogeographic map database; comparing the performance evaluation index with the first performance evaluation threshold and the second performance evaluation threshold respectively; if the performance evaluation index is less than the first performance evaluation threshold, marking the paleogeographic map as a severely abnormal program and immediately enabling degradation mode; if the performance evaluation index is greater than or equal to the first performance evaluation threshold and less than the second performance evaluation threshold, matching the performance evaluation index with the adjustment multiples corresponding to each performance evaluation index preset in the paleogeographic map database to obtain the adjustment multiples corresponding to the performance evaluation index, and adjusting the performance tuning parameters according to the adjustment multiples; if the performance evaluation index is greater than or equal to the second performance evaluation threshold, no additional operation is performed.

[0047] In this embodiment, the degradation mode includes shutting down non-critical functions (such as user personalization settings, social functions, and advertising display, etc.), loading only data within the current view range, and notifying maintenance personnel to perform repairs, which can ensure that the system automatically switches to safe mode when performance degrades extremely, avoiding system crashes or instability due to overload or performance problems; performance tuning parameters include rendering resolution, interception time, and cache existence time. When adjusting the performance tuning parameters according to the adjustment multiples, the ancient map database forms a mapping relationship table by corresponding performance evaluation indicators and adjustment multiples one by one. The table records each performance evaluation indicator and its corresponding adjustment multiple. These relationships can be one-to-one or many-to-one. When obtaining the adjustment multiple, you only need to enter the performance evaluation indicator into the mapping relationship table. The ancient map database can quickly locate and return the adjustment multiple corresponding to the performance evaluation indicator, and multiply the adjustment multiple by the performance tuning parameter to obtain the adjusted performance tuning parameter, and adjust the performance tuning parameter to the numerical value of the adjusted performance tuning parameter. By comparing the performance evaluation indicators with the first performance evaluation threshold and the second performance evaluation threshold respectively, the performance can be monitored in real time during system operation, and whether optimization measures need to be taken can be automatically determined based on the comparison results.

[0048] Furthermore, the user information data includes the number of users, the data load amount of each user and the cached data amount of each user; the step of dynamically allocating resources to the user cached data based on the user information data includes: obtaining the critical number of users, the critical data load amount and the critical cached data amount from the ancient map database; performing a coupling process on the data load amount of each user and the cached data amount of each user with the critical data load amount and the critical cached data amount respectively, and then performing a weighted operation on the processing result and the result of the proportion proximity operation of the number of users and the critical number of users, and then performing an inverse proportional operation to obtain a map status evaluation value, the map status evaluation value represents quantitative data on the degree of influence of the number of users, the data load amount of each user and the cached data amount of each user on the usage status of the ancient geographical map; dynamically allocating resources to the user cached data according to the map status evaluation value and the map status evaluation threshold, the dynamic resource allocation is used to dynamically adjust the loaded data and cache to improve the response speed and overall performance of the system.

[0049] The map status evaluation value is obtained as follows:

[0050]

[0051] Where MS represents the map state evaluation value, α4 represents the map state evaluation impact factor corresponding to the number of users, α5 represents the map state evaluation impact factor corresponding to the amount of data, SN1 represents the number of users, SN0 represents the critical number of users, and DL 1irepresents the data load of the i-th user, DL0 represents the critical data load, DC 1i represents the amount of data cached by the i-th user, DC0 represents the critical amount of data cached, where i is the user number, i=1, 2, 3, ..., SN1.

[0052] α4 and α5 are map status assessment impact factors corresponding to the number of users and data volume, respectively, preset in the ancient map database. These factors represent the degree of influence of the number of users and data volume on the map status assessment value, respectively, and can be directly retrieved from the ancient map database. These relationships are organized into "mapping sets," or lookup tables or corresponding rules. When a user's information data value is actually monitored, that value can be searched in the corresponding mapping set to obtain the corresponding map status assessment impact factor. This impact factor is a number between 0 and 1 that represents the impact of the current user's information data on the map status assessment value. For example, for the number of users, there is a mapping set of user numbers and corresponding map status assessment impact factors. By inputting the value of the number of users, the corresponding map status assessment impact factor is obtained. For the data volume, there is a mapping set of data volume and corresponding map status assessment impact factors. By inputting the value of the data volume, the corresponding map status assessment impact factor is obtained. These mapping relationships can be many-to-one or one-to-one.

[0053] In this embodiment, the number of users refers to the total number of users currently using the map system. The greater the number of users, the smaller the map status evaluation value. The data load of each user refers to the amount of data loaded on the device when each user accesses the map. The larger the data load of each user, the smaller the map status evaluation value. The cached data volume of each user refers to the amount of data cached in each user's device. The larger the cached data volume of each user, the smaller the map status evaluation value. All three can be directly obtained from the cache management records of the map system. The map status evaluation value obtained through comprehensive analysis can accurately assess the current system performance and resource usage, and optimize and adjust the system to ensure that the map service provides a smooth and efficient user experience under different loads.

[0054] Furthermore, the step of dynamically allocating resources to user cached data based on the map state evaluation value and the map state evaluation threshold includes: comparing the map state evaluation value and the map state evaluation threshold: if the map state evaluation value is greater than or equal to the map state evaluation threshold, no additional processing is performed; if the map state evaluation value is less than the map state evaluation threshold, marking the difference between the map state evaluation threshold and the map state evaluation value as a deviation map state evaluation value, and dynamically allocating resources to the user cached data based on the deviation map state evaluation value.

[0055] In this embodiment, the deviation map state evaluation value reflects the difference between the current state of the system and the expected target, and thus can provide guidance on how to optimize resource allocation, whether it is necessary to increase cache capacity or allocate more computing resources to compensate for performance deficiencies, and dynamically adjust resource allocation to ensure that when the map state evaluation value is lower than the set threshold, resources are adjusted according to the deviation value to adjust cache allocation, thereby avoiding resource waste or over-concentration, enabling efficient use of resources, avoiding performance degradation or system overload caused by improper resource allocation, and ensuring that the system always operates in the best state.

[0056] Furthermore, the step of dynamically allocating resources for user cached data based on the deviation map state evaluation value includes: obtaining a deviation map state evaluation threshold from the ancient map database; comparing the deviation map state evaluation value with the deviation map state evaluation threshold: if the deviation map state evaluation value is less than or equal to the deviation map state evaluation threshold, switching all users to a simplified map mode, and matching the deviation map state evaluation value with the data allowable loading ratio corresponding to each deviation map state evaluation value preset in the ancient map database to obtain the data allowable loading ratio, comparing the total data loading capacity with the number of users, and then obtaining the user data allowable loading amount through multiplication operation of the data allowable loading ratio, releasing cached data that exceeds the user data allowable loading amount based on the user data allowable loading amount and the current loading amount of each user; if the deviation map state evaluation value is greater than the deviation map state evaluation threshold, switching all users to a simplified map mode, and releasing all cached data starting from the earliest cached data according to the chronological order of the cached data time.

[0057] In this embodiment, when in simplified map mode, the system removes unnecessary visual details, such as geographic landmarks, buildings, or other non-critical map information, while reducing the complexity of dynamic rendering, reducing the amount of data displayed and loaded, and simplifying the map presentation content, allowing users to quickly load and browse. When releasing cached data, the cached data is sorted from large to small according to its existence time, and the cached data is cleaned up according to the sorting, thereby releasing more resources. Dynamically adjusting the user's cached data based on the deviation map state assessment threshold can ensure that each user can load an appropriate amount of data, avoiding memory overflow or system crashes due to excessive cached data. At the same time, when resources are limited, users can continue to experience smooth map services, thereby enhancing user satisfaction.

[0058] Furthermore, the dynamically loaded data includes map resolution and user zoom ratio; when the user performs a zoom operation during browsing, the dynamically loaded data based on the user interaction operation is further used to determine whether to load the detail area. The specific steps include: obtaining the critical map resolution, the reference user zoom ratio and the allowable deviation user zoom ratio from the ancient map database; performing a proportion approximation operation on the critical map resolution and the map resolution to obtain a map resolution influencing parameter; performing a deviation conformity operation on the allowable deviation user zoom ratio, the reference user zoom ratio and the user zoom ratio to obtain a user zoom ratio influencing parameter; and then performing a weighted operation on the map resolution influencing parameter and the user zoom ratio influencing parameter and coupling processing to obtain an interactive permission evaluation value. The interactive permission evaluation value represents quantitative data on the degree of influence of the map resolution and the user zoom ratio on the interactive processing capability of the device, and determining whether to load the detail area is based on the interactive permission evaluation value.

[0059] The interaction permission evaluation value is obtained as follows:

[0060]

[0061] Where IA represents the interaction allowable evaluation value, α6 represents the interaction allowable evaluation impact factor corresponding to the map resolution, α7 represents the interaction allowable evaluation impact factor corresponding to the user zoom ratio, MR1 represents the map resolution, MR0 represents the critical map resolution, ZR1 represents the user zoom ratio, ZR0 represents the reference user zoom ratio, and ZR2 represents the allowable deviation user zoom ratio.

[0062] α6 and α7 are the interaction permissibility evaluation factors corresponding to map resolution and user zoom ratio, respectively, preset in the ancient map database. These factors represent the degree of influence of map resolution and user zoom ratio on the interaction permissibility evaluation value, respectively. These values ​​can be directly retrieved from the ancient map database. These relationships are organized into a "mapping set," a lookup table or corresponding rules. When a dynamically loaded data value is actually monitored, the corresponding interaction permissibility evaluation factor can be retrieved based on the mapping set. This factor is a number between 0 and 1, representing the impact of the dynamically loaded data on the interaction permissibility evaluation value. For example, for map resolution, a mapping set exists between map resolution and interaction permissibility evaluation factors. By inputting a map resolution value, the interaction permissibility evaluation factor corresponding to the map resolution is retrieved. For user zoom ratio, a mapping set exists between user zoom ratio and interaction permissibility evaluation factors corresponding to the user zoom ratio. By inputting a user zoom ratio value, the interaction permissibility evaluation factor corresponding to the user zoom ratio is retrieved. These mappings can be many-to-one or one-to-one.

[0063] In this embodiment, map resolution refers to the level of detail of the map image. The larger the map resolution, the more details the map displays, the higher the requirements for the device, and the smaller the interaction allowance evaluation value. The user zoom ratio refers to the ratio when the user zooms in and out of the map through interaction (such as mouse wheel, finger sliding, etc.). The larger the user zoom ratio, the more details the map has, and the smaller the interaction allowance evaluation value. The two are interrelated. When the zoom ratio decreases, the map resolution will decrease, the displayed area will be wider, but the details will be reduced. The interaction allowance evaluation value obtained through comprehensive analysis is used to judge the smoothness of the current map display and whether further optimization of data loading is needed. It can accurately evaluate the current map status, optimize the interactive experience, dynamically load appropriate map data, and improve the response speed and performance of the system.

[0064] Furthermore, the step of determining whether to load the detail area according to the interaction permission evaluation value includes: matching the user device resolution with the interaction permission evaluation threshold corresponding to each device resolution preset in the ancient map database to obtain the interaction permission evaluation threshold; comparing the interaction permission evaluation value with the interaction permission evaluation threshold; if the interaction permission evaluation value is greater than or equal to the interaction permission evaluation threshold, the interaction operation is allowed, and the interaction status is marked as normal; if the interaction permission evaluation value is less than the interaction permission evaluation threshold, and the user device operation status is normal (the user device CPU usage rate does not reach the preset ratio), the interaction operation is allowed, the interaction status is marked as normal, and the interaction permission evaluation value is marked as the interaction permission evaluation threshold of the current user device; if the interaction permission evaluation value is less than the interaction permission evaluation threshold, and the user device operation status is abnormal (the user device CPU usage rate reaches the preset ratio), the interaction status is marked as abnormal, the interaction data of the map of the current historical period is retained, and all cached data is released.

[0065] In this embodiment, a mapping relationship table is formed in the ancient map database by corresponding each device resolution to the interaction allowed evaluation threshold. The table records each device resolution and its corresponding interaction allowed evaluation threshold. These relationships can be one-to-one or many-to-one. When obtaining the interaction allowed evaluation threshold, it is only necessary to input the user device resolution into the mapping relationship table, and the ancient map database can quickly locate and return the interaction allowed evaluation threshold corresponding to the device resolution. By setting different interaction evaluation thresholds according to the resolution of the device, the present invention can ensure that each device operates within its capabilities and avoid freezes or crashes caused by performance overload; by detecting the device status and adopting different strategies (such as releasing cache, marking anomalies, etc.), the system's fault tolerance for abnormal situations is improved, and the occurrence of crashes or freezes is reduced. At the same time, in the event of device abnormalities, important historical data is retained and the cache is released to ensure that data is not lost, while avoiding the impact of excessive cache on system stability.

[0066] Furthermore, the step of performing hierarchical storage based on the operation frequency and historical interaction status of user interaction data includes: obtaining an operation frequency threshold from an ancient map database; marking user interaction data whose operation frequency is greater than or equal to the operation frequency threshold and whose historical interaction status is normal as high-level interaction data; marking user interaction data whose operation frequency is less than the frequency threshold or whose historical interaction status is abnormal as low-level interaction data; storing high-level interaction data in a high-speed storage medium and storing low-level interaction data in a traditional storage medium.

[0067] In this embodiment, high-speed storage media refers to storage devices that provide fast data read and write speeds, typically with low latency and high throughput, and include solid-state drives (SSDs) and memory. Traditional storage media refers to devices with slower read speeds but lower costs and larger storage capacities, including mechanical hard drives and tape storage. Through tiered storage, the system can better utilize storage resources while improving system efficiency. Fast access to high-frequency interactive data ensures a smooth user experience during high-frequency operations, while slower access to low-frequency data does not affect regular operations.

[0068] like Figure 3 As shown, it is a structural schematic diagram of the paleogeographic map online visualization system based on Gplates and Vue provided in an embodiment of the present application. The paleogeographic map online visualization system based on Gplates and Vue provided in an embodiment of the present application includes: a map classification module, a performance optimization module, a data interaction module and a paleomap database; wherein, the map classification module is used to classify the paleogeographic map according to historical periods to obtain maps of each historical period, and then perform secondary classification on the maps of each historical period according to the data content to obtain basic map data and layer data of each historical period; the performance optimization module is used to first display the basic map data of each historical period when the user enters the map browsing interface of each historical period, preload layer data and high-level interaction data according to the user device resolution and user historical browsing data, use performance evaluation data to perform dynamic performance optimization, and dynamically allocate resources to user cache data based on user information data; the data interaction module is used to further determine whether to load detailed areas based on the dynamic loading data of the user interaction operation when the user performs a zoom operation during the browsing process, and perform hierarchical storage based on the operation frequency and historical interaction status of the user interaction data.

[0069] In summary, the embodiment of the present application classifies paleogeographic maps according to historical periods and performs secondary classification on maps of each historical period to obtain basic map data and layer data respectively. When the user enters the map browsing interface of each historical period, the basic map data is displayed first, and the layer data and high-level interactive data are preloaded in combination with the user device resolution and historical browsing data. At the same time, dynamic performance optimization is performed through performance evaluation data, and dynamic resource allocation is performed on cached data based on user information data to ensure efficient utilization of system performance. When the user performs a zoom operation, the dynamically loaded data further determines whether to load the detailed area based on the user's interactive operation, and performs hierarchical storage based on the user's operation frequency and historical interaction status, thereby achieving efficient display and smooth browsing of maps of different historical periods.

[0070] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0071] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0072] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0073] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0074] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0075] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. The online visualization method of paleogeographic map based on Gplates and Vue is characterized by: The following steps are involved: Classify the paleogeographic maps according to historical periods to obtain maps of each historical period, and then perform secondary classification on the maps of each historical period according to data content to obtain basic map data and layer data of each historical period; When the user enters the map browsing interface of each historical period, the basic map data of the historical period is first displayed, and the layer data and high-level interaction data are preloaded according to the user device resolution and the user's historical browsing data. The performance evaluation data is used to perform dynamic performance optimization, and the user cache data is dynamically allocated resources based on the user information data; wherein, the user information data includes the number of users, the data loading amount of each user and the cached data amount of each user; the step of dynamically allocating resources to the user cache data based on the user information data includes: obtaining the critical number of users, the critical data loading amount and the critical cached data amount from the ancient map database; performing a proportion approach calculation on the data loading amount of each user and the cached data amount of each user, respectively, and then coupling the calculation; then performing a weighted calculation on the processing result and the proportion approach calculation result of the number of users and the critical number of users, and then performing an inverse proportional calculation to obtain the map. A map state evaluation value, wherein the map state evaluation value represents quantitative data on the degree of influence of the number of users, the amount of data loaded by each user, and the amount of cached data of each user on the usage status of the paleogeographic map; dynamic resource allocation is performed on the user cached data according to the map state evaluation value and the map state evaluation threshold, and the dynamic resource allocation is used to dynamically adjust the loaded data and cache to improve the response speed and overall performance of the system; wherein the step of dynamically allocating resources to the user cached data according to the map state evaluation value and the map state evaluation threshold comprises: comparing the map state evaluation value with the map state evaluation threshold: if the map state evaluation value is greater than or equal to the map state evaluation threshold, no additional processing is performed; if the map state evaluation value is less than the map state evaluation threshold, marking the difference between the map state evaluation threshold and the map state evaluation value as a deviation map state evaluation value, and dynamically allocating resources to the user cached data according to the deviation map state evaluation value; When the user performs a zooming operation during browsing, the dynamic loading data based on the user interaction operation is further determined to determine whether to load the detail area, and the user interaction data is hierarchically stored based on the operation frequency and historical interaction status.

2. The online visualization method for paleogeographic maps based on Gplates and Vue as claimed in claim 1, characterized in that: The performance evaluation data includes loading time, update time and response time; The step of using the performance evaluation data to perform dynamic performance optimization includes: Obtain critical loading time, critical update time, and critical response time from the ancient map database; The critical loading time, critical update time, and critical response time are respectively subjected to a proportion approximation operation with the loading time, update time, and response time, and the results of the proportion approximation operation are respectively weighted and coupled to obtain a performance evaluation index. The paleogeographic map is performance optimized based on the performance evaluation index to obtain an optimized performance evaluation index, which represents quantitative data on the degree of influence of the loading time, update time, and response time on the loading performance of the paleogeographic map; The optimized performance evaluation index is compared and matched with the map state evaluation thresholds corresponding to each performance evaluation index preset in the ancient map database to obtain the map state evaluation thresholds corresponding to the optimized performance evaluation index.

3. The online visualization method for paleogeographic maps based on Gplates and Vue as claimed in claim 2, characterized in that: The step of optimizing the performance of the paleogeographic map according to the performance evaluation index comprises: Obtaining a first performance evaluation threshold and a second performance evaluation threshold from an ancient map database; Compare the performance evaluation index with the first performance evaluation threshold and the second performance evaluation threshold respectively. If the performance evaluation index is less than the first performance evaluation threshold, the paleogeographic map is marked as a serious abnormal program and the degradation mode is immediately activated; If the performance evaluation index is greater than or equal to the first performance evaluation threshold and less than the second performance evaluation threshold, the performance evaluation index is matched with the adjustment multiples corresponding to each performance evaluation index preset in the ancient map database to obtain the adjustment multiples corresponding to the performance evaluation index, and the performance tuning parameters are adjusted according to the adjustment multiples; If the performance evaluation index is greater than or equal to the second performance evaluation threshold, no additional operation is performed.

4. The online visualization method for paleogeographic maps based on Gplates and Vue as claimed in claim 1, characterized in that: The step of dynamically allocating resources to user cache data according to the deviation map state evaluation value includes: Obtaining deviation map status assessment thresholds from paleomap databases; Compare the deviation map state evaluation value with the deviation map state evaluation threshold: If the deviation map state evaluation value is less than or equal to the deviation map state evaluation threshold, all users will be switched to the simplified map mode, and the deviation map state evaluation value will be matched with the data allowable loading ratio corresponding to each deviation map state evaluation value preset in the ancient map database to obtain the data allowable loading ratio. The total data loading capacity will be compared with the number of users, and then the user data allowable loading capacity will be obtained by multiplying the data allowable loading ratio. The cached data will be released based on the user data allowable loading capacity and the current loading capacity of each user. If the deviation map state evaluation value is greater than the deviation map state evaluation threshold, all users will be switched to the simplified map mode, and all cached data will be released according to the cached data time.

5. The online visualization method for paleogeographic maps based on Gplates and Vue as claimed in claim 1, characterized in that: The dynamically loaded data includes map resolution and user zoom ratio; When the user performs a zooming operation during browsing, the dynamic loading data based on the user interaction operation is further determined whether to load the detail area. The specific steps include: Obtain critical map resolution, reference user scaling, and allowable deviation user scaling from the paleomap database; A proportion approximation operation is performed on the critical map resolution and the map resolution to obtain the map resolution influencing parameter. A deviation conformity operation is performed on the allowed deviation user zoom ratio, the reference user zoom ratio and the user zoom ratio to obtain the user zoom ratio influencing parameter. The map resolution influencing parameter and the user zoom ratio influencing parameter are weighted and coupled to obtain an interaction permission evaluation value. The interaction permission evaluation value represents quantitative data on the degree of influence of the map resolution and the user zoom ratio on the device's interaction processing capability. Whether to load the detail area is determined based on the interaction permission evaluation value.

6. The online visualization method for paleogeographic maps based on Gplates and Vue as claimed in claim 5, characterized in that: The step of determining whether to load the detail area according to the interaction permission evaluation value includes: Matching the user device resolution with the interaction permission evaluation threshold corresponding to each device resolution preset in the ancient map database to obtain the interaction permission evaluation threshold; The interaction permission evaluation value is compared with the interaction permission evaluation threshold. If the interaction permission evaluation value is greater than or equal to the interaction permission evaluation threshold, the interaction operation is allowed and the interaction status is marked as normal. If the interaction permission evaluation value is less than the interaction permission evaluation threshold and the user device is in normal operation, the interaction operation is allowed, the interaction state is marked as normal, and the interaction permission evaluation value is marked as the interaction permission evaluation threshold of the current user device; If the interaction allowance evaluation value is less than the interaction allowance evaluation threshold and the user device is operating in an abnormal state, the interaction state is marked as abnormal, the interaction data of the map in the current historical period is retained, and all cached data is released.

7. The online visualization method for paleogeographic maps based on Gplates and Vue as claimed in claim 1, characterized in that: The step of hierarchically storing the user interaction data based on the operation frequency and historical interaction status includes: Obtaining the operation frequency threshold from the ancient map database; Mark user interaction data with an operation frequency greater than or equal to the operation frequency threshold and a normal historical interaction status as high-level interaction data; Mark user interaction data with an operation frequency lower than a frequency threshold or abnormal historical interaction status as low-level interaction data; High-level interaction data is stored in high-speed storage media, and low-level interaction data is stored in traditional storage media.

8. A paleogeographic map online visualization system based on Gplates and Vue, applying the paleogeographic map online visualization method based on Gplates and Vue as claimed in any one of claims 1 to 7, characterized in that: Including map classification module, performance optimization module, data interaction module and ancient map database; The map classification module is used to classify paleogeographic maps according to historical periods to obtain maps of each historical period, and then perform secondary classification on the maps of each historical period according to data content to obtain basic map data and layer data of each historical period; The performance optimization module is used to first display the basic map data of each historical period when the user enters the map browsing interface of each historical period, preload layer data and high-level interactive data according to the user's device resolution and the user's historical browsing data, perform dynamic performance optimization using performance evaluation data, and dynamically allocate resources for user cache data based on user information data; The data interaction module is used to further determine whether to load the detail area based on the dynamic loading data of the user interaction operation when the user performs a zoom operation during browsing, and to perform hierarchical storage based on the operation frequency and historical interaction status of the user interaction data.

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