Gplates and Vue-based palaeographic map online visualization method and system

Abstract

The invention discloses a paleogeographic map online visualization method and system based on Gplates and Vue, and belongs to the technical field of map data processing. The method comprises the following steps: when a user enters a map browsing interface of each historical period, firstly displaying basic map data of the historical period, pre-loading layer data and high-level interaction data according to user equipment resolution and user historical browsing data, performing dynamic performance optimization by utilizing performance evaluation data, and performing dynamic performance optimization by utilizing performance evaluation data; dynamic resource allocation is carried out on the user cache data based on the user information data; when the user carries out the zooming operation in the browsing process, whether the detail area is loaded or not is further judged based on the dynamic loading data of the user interaction operation, hierarchical storage is carried out based on the operation frequency and the historical interaction state of the user interaction data, and the efficiency and the fluency of browsing the paleogeographic map by the user are improved.

Description

Technical Field

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

[0002] With the advancement of the digital protection of cultural heritage, as important historical documents, the preservation, research, and dissemination needs of ancient maps are increasing. At the same time, the maturity of GIS technology (Geographic Information System) enables ancient maps to be precisely matched with modern geographical data, and the progress of Web technology provides technical support for online interaction.

[0003] Existing online visualization methods for ancient maps convert them into digital images through high-resolution scanning and digital processing, use GIS technology to georegister the maps, align them with modern geographical coordinates, and then embed the processed maps into an online platform through Web technology. Users can perform interactive operations through a browser, jointly 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 the 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 Tianditu 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 disclosed in the invention patent announcement with the announcement number: CN114996374B includes: by obtaining the target area and area view range information of a geographic information system map, dividing the target area into multiple grids to be rendered according to a 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 relevant sites and the relevant measured data of each relevant site from multiple preset data collection sites, thereby obtaining the 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 point of the grayscale image according to the grayscale-color mapping relationship to obtain a color image of the target area, realizing the online data visualization of the target area.

[0006] However, in the process of implementing the technical solutions of the present invention in the embodiments of the present application, it is found that the above technologies have at least the following technical problems:

[0007] In the prior art, when a user views a paleogeographic map online, due to the fact that paleogeographic maps usually have high resolution and complex details, these factors result in a large volume of image files and a lot of map data. At the same time, when the user uses it, complex interaction operations such as zooming and viewing details of different layers are required, resulting in problems such as page freezing and long waiting times during the viewing process by the user. Summary of the Invention

[0008] By providing an online visualization method and system for paleogeographic maps based on Gplates and Vue, the present invention solves the problems in the prior art that when a user views a paleogeographic map online, due to the fact that paleogeographic maps usually have high resolution and complex details, these factors result in a large volume of image files and a lot of map data. At the same time, when the user uses it, complex interaction operations such as zooming and viewing details of different layers are required, resulting in problems such as page freezing and long waiting times during the viewing process by the user, and realizes the 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, including 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 according to data content for a second time 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, first display the basic map data of that historical period, preload the layer data and high-level interaction data according to the user device resolution and the user's historical browsing data, perform dynamic performance optimization using performance evaluation data, and perform dynamic resource allocation for the user cache data based on the user information data; when the user performs a zoom operation during the browsing process, further determine whether to load the detail area based on the dynamically loaded data of the user interaction operation, and perform hierarchical storage based on the operation frequency and historical interaction status of the user interaction data.

[0010] Further, the performance evaluation data includes loading time, update time, and response time. The steps of dynamically optimizing performance using the performance evaluation data include: obtaining the critical loading time, critical update time, and critical response time from the ancient map database; performing a ratio approximation operation on the critical loading time, critical update time, and critical response time with the loading time, update time, and response time respectively, and then performing a weighting operation on the results of the ratio approximation operation and coupling them to obtain a performance evaluation index. According to the performance evaluation index, the performance of the ancient geographical map is optimized to obtain an optimized performance evaluation index. The performance evaluation index represents the quantitative data of the degree of influence of the loading time, update time, and response time on the loading performance of the ancient geographical map. Comparing and matching the optimized performance evaluation index with the map state evaluation thresholds corresponding to each performance evaluation index preset in the ancient map database to obtain the map state evaluation threshold corresponding to the optimized performance evaluation index.

[0011] Further, the steps of optimizing the performance of the ancient geographical map according to the performance evaluation index include: obtaining the first performance evaluation threshold and the second performance evaluation threshold from the ancient 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, mark the ancient geographical map as a severely abnormal program and immediately enable the 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, match the performance evaluation index with the adjustment multiples corresponding to each performance evaluation index preset in the ancient map database to obtain the adjustment multiple corresponding to this performance evaluation index, and adjust the performance tuning parameters according to the adjustment multiple. If the performance evaluation index is greater than or equal to the second performance evaluation threshold, no additional operation is performed.

[0012] Further, the user information data includes the number of users, the data loading amount of each user, and the cache data amount of each user. The steps of dynamically allocating resources for the user cache data based on the user information data include: obtaining the critical number of users, the critical data loading amount, and the critical cache data amount from the ancient map database; performing a ratio approximation operation on the data loading amount of each user and the cache data amount of each user with the critical data loading amount and the critical cache data amount respectively, then coupling the processed results, and then performing a weighting operation on the processed results and the ratio approximation operation result of the number of users and the critical number of users, and then performing an inverse ratio operation to obtain a map state evaluation value. The map state evaluation value represents the quantitative data of the degree of influence of the number of users, the data loading amount of each user, and the cache data amount of each user on the usage state of the ancient geographical map. Dynamically allocate resources for the user cache data according to the map state evaluation value and the map state evaluation threshold. The dynamic resource allocation is used to dynamically adjust the loaded data and the cache to improve the response speed and overall performance of the system.

[0013] Further, the steps of dynamically allocating resources for user cache data according to the map status evaluation value and the map status evaluation threshold include: comparing the map status evaluation value with the map status evaluation threshold: if the map status evaluation value is greater than or equal to the map status evaluation threshold, no additional processing is performed; if the map status evaluation value is less than the map status evaluation threshold, the difference between the map status evaluation threshold and the map status evaluation value is marked as the deviation map status evaluation value, and dynamic resource allocation is performed on the user cache data according to the deviation map status evaluation value.

[0014] Further, the steps of dynamically allocating resources for user cache data according to the deviation map status evaluation value include: obtaining the 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, all users are switched to the simplified map mode, and the deviation map status evaluation value is matched with the data allowable loading ratio corresponding to each preset deviation map status evaluation value in the ancient map database to obtain the data allowable loading ratio. The total data loading capacity is divided by the number of users, and then the user data allowable loading amount is obtained through the product operation of the data allowable loading ratio. Cache data is released 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, all users are switched to the simplified map mode, and at the same time, all cache data is released according to the cache data time.

[0015] Further, the dynamically loaded data includes the map resolution and the user zoom ratio; when the user performs a zoom operation during browsing, it is further determined whether to load the detailed area based on the dynamically loaded data of the user interaction operation. 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 ratio approximation operation on the critical map resolution and the map resolution to obtain the map resolution influence parameter, performing a deviation compliance operation on the allowable deviation user zoom ratio, the reference user zoom ratio, and the user zoom ratio to obtain the user zoom ratio influence parameter, and then performing a weighted operation and coupling process on the map resolution influence parameter and the user zoom ratio influence parameter to obtain the interaction allowable evaluation value. The interaction allowable evaluation value represents the quantitative data of the combined influence of the map resolution and the user zoom ratio on the device interaction processing ability. It is determined whether to load the detailed area according to the interaction allowable evaluation value.

[0016] Further, the steps of determining whether to load the detailed area according to the interaction permission evaluation value include: matching the user device resolution with the interaction permission evaluation thresholds corresponding to the preset device resolutions 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 current interaction status is marked as normal; if the interaction permission evaluation value is less than the interaction permission evaluation threshold and the user device operating status is normal, the interaction operation is allowed, the current 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 operating status is abnormal, the current interaction status is marked as abnormal, the interaction data of the map in the current historical period is retained, and all cached data is released.

[0017] Further, the steps of hierarchical storage based on the operation frequency of user interaction data and the historical interaction status include: obtaining the operation frequency threshold from the ancient map database; marking the 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; marking the user interaction data with an operation frequency less than the frequency threshold or an abnormal historical interaction status as low-level interaction data; storing the high-level interaction data in a high-speed storage medium and the low-level interaction data in a traditional storage medium.

[0018] The embodiment of the present application provides an online visualization system for ancient geographical 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 the ancient geographical maps according to historical periods to obtain maps of each historical period, and then classify the maps of each historical period according to data content to obtain the basic map data and layer data of each historical period; the performance optimization module is used to, when the user enters the map browsing interface of each historical period, first display the basic map data of that historical period, preload the layer data and high-level interaction data according to the user device resolution and the user's historical browsing data, perform dynamic performance optimization using the performance evaluation data, and perform dynamic resource allocation on the user's cached data based on the user information data; the data interaction module is used to, when the user performs a zoom operation during the browsing process, further determine whether to load the detailed area based on the dynamically loaded data of the user interaction operation, and perform hierarchical storage based on the operation frequency of the user interaction data and the historical interaction status.

[0019] One or more technical solutions provided in the embodiments of the present 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 classify maps and reclassify data according to historical periods, dynamically load and display basic map data and layer data, thus realizing dynamic resource allocation and hierarchical storage. It intelligently optimizes the loading strategy based on the user device performance and historical interaction data, improving the user experience while optimizing the system performance.

[0021] 2. The present invention dynamically allocates resources for user cache data based on user information data, can intelligently allocate resources according to the user's historical browsing and interaction status, avoid unnecessary resource waste, further improve the system performance and optimize the user experience, and thus realizes efficient resource management and dynamic optimization, ensuring a smooth map browsing experience in different device and network environments.

[0022] 3. The present invention further determines whether to load the detailed area through dynamically loading data based on user interaction operations, and performs hierarchical storage in combination with the operation frequency and historical interaction status of user interaction data, so as to accurately judge the user's needs, avoid unnecessary data loading, improve the utilization efficiency of system resources, and thus realize a smoother map browsing experience.

[0023] 4. The present invention obtains performance evaluation indicators through comprehensive analysis of the loading time, update time, and response time, thereby quantifying the influence degree of the loading time, update time, and response time on the loading performance of the paleogeographic map, and then realizes performance optimization of the paleogeographic map according to the optimized performance evaluation indicators, improves the loading efficiency and interactive response speed, and finally enhances the user's browsing experience and the overall performance of the system.

[0024] 5. The present invention obtains a map status evaluation value through comprehensive analysis of the number of users, the data loading volume of each user, and the cache data volume of each user, thereby quantifying the influence degree of the number of users, the data loading volume of each user, and the cache data volume of each user on the usage status of the paleogeographic map, and then realizes dynamic resource allocation for user cache 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 It is a flowchart of the online visualization method for paleogeographic maps based on Gplates and Vue provided by an embodiment of the present application.

[0026] Figure 2 It is a graph of the change of performance evaluation indicators for the online visualization method of paleogeographic maps provided by an embodiment of the present application.

[0027] Figure 3Schematic diagram of the structure of the online visualization system for paleogeographic maps based on Gplates and Vue provided by the embodiments of the present application. Detailed implementation manners

[0028] In the embodiments of the present application, by providing a method and system for online visualization of paleogeographic maps based on Gplates and Vue, the problems in the prior art are solved. When a user views a paleogeographic map online, since the paleogeographic map usually has a high resolution and complex details, these factors lead to a large volume of the image file and a large amount of map data. At the same time, when the user uses it, complex interaction operations such as zooming and viewing details of different layers are required, resulting in problems such as page freezing and long waiting time during the user's viewing process. By classifying the paleogeographic map according to historical periods to obtain maps of each historical period, and then classifying the maps of each historical period according to data content, the basic map data and layer data of each historical period are obtained; when the user enters the map browsing interface of each historical period, the basic map data of that historical period is first displayed, and the layer data and high-level interaction data are pre-loaded according to the user device resolution and user historical browsing data, dynamic performance optimization is carried out using performance evaluation data, and dynamic resource allocation is carried out on the user cache data based on user information data; when the user performs a zoom operation during the browsing process, it is further determined whether to load the detailed area based on the dynamically loaded data of the user interaction operation, and hierarchical storage is carried out based on the operation frequency and historical interaction status of the user interaction data, realizing the improvement of the efficiency and fluency of the user in viewing the paleogeographic map.

[0029] The technical solutions in the embodiments of the present application are to solve the above problems that when a user views a paleogeographic map online, since the paleogeographic map usually has a high resolution and complex details, these factors lead to a large volume of the image file and a large amount of map data. At the same time, when the user uses it, complex interaction operations such as zooming and viewing details of different layers are required, resulting in problems such as page freezing and long waiting time during the user's viewing process. The general idea is as follows:

[0030] By classifying the paleogeographic map according to historical periods and performing secondary classification on the maps of each historical period, the basic map data and layer data are obtained respectively. When the user enters the map browsing interface of each historical period, the basic map data is preferentially displayed, and the layer data and high-level interaction data are pre-loaded in combination with the user device resolution and historical browsing data. At the same time, dynamic performance optimization is carried out using performance evaluation data, and dynamic resource allocation is carried out on the cache data based on user information data to ensure the efficient utilization of system performance. When the user performs a zoom operation, the dynamically loaded data further determines whether to load the detailed area according to the user interaction operation, and hierarchical storage is carried out according to the operation frequency and historical interaction status of the user, achieving the efficient display and smooth browsing of maps of different historical periods.

[0031] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments.

[0032] As Figure 1 shown, it is a flowchart of an online visualization method for paleogeographic maps based on Gplates and Vue provided by an embodiment of the present application. This method is applied to an online visualization device for paleogeographic maps based on Gplates and Vue, and this method includes the following steps: Classify the paleogeographic maps according to historical periods to obtain maps of each historical period, and then classify the maps of each historical period according to 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, first display the basic map data of this historical period, preload the layer data and high-level interaction data according to the user device resolution and user historical browsing data, perform dynamic performance optimization using performance evaluation data, and perform dynamic resource allocation on the user cache data based on the user information data; When the user performs a zoom operation during the browsing process, further determine whether to load the detailed area based on the dynamically loaded data of the user interaction operation, and perform hierarchical storage based on the operation frequency and historical interaction status of the user interaction data.

[0033] In this embodiment, the present application dynamically and interactively displays paleogeographic data (such as plate tectonics, paleoclimate, etc.) through modern Web technologies. By using the powerful earth history data visualization function provided by Gplates and the interactive front-end framework provided by Vue.js, combined with WebGL and other related technologies, it helps users better understand the historical geographic information of the earth and perform real-time geographic data analysis. The base map data refers to the core content of the map, including geographic boundary information, terrain information, geographic coordinate system, basic road information, basic city points, etc. The layer data is the data of different levels displayed in the map, including historical population data, cultural relic sites in various historical periods, geographic data of wars or important events, historical buildings or heritage sites, etc. The map data is divided into base map data and layer data for separate management, which can avoid slow loading caused by overly large data; according to the device resolution of the user, load the layer data that the device resolution allows to load, avoiding waste of bandwidth and memory. At the same time, infer the user's interest area based on the user's historical browsing data and pre-load relevant data in advance to improve the user experience; the present invention dynamically adjusts resource allocation according to real-time performance evaluation, avoiding slow loading caused by poor performance of the user's device or unstable network. Based on the user's historical data and current data loading information, dynamically adjust the content of the cache, reduce unnecessary caching and data pre-loading, and improve the utilization rate of storage space; when the user zooms in or out, load data dynamically according to the operation. The present invention can further load detailed layer data when the user views the paleogeographic map using the system, provided that the user's device and the system are operating normally, so that the map content seen by the user is more refined, fast and effective.

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

[0035] Further, the performance evaluation data includes loading time, update time, and response time; the step of dynamically optimizing performance using the performance evaluation data includes: obtaining the critical loading time, critical update time, and critical response time from the ancient map database; performing a ratio approach operation on the critical loading time, critical update time, and critical response time with the loading time, update time, and response time respectively, and performing a weighting operation on the results of the ratio approach operation and then coupling them to obtain a performance evaluation index, and optimizing the performance of the ancient geographical map according to the performance evaluation index to obtain an optimized performance evaluation index, where the performance evaluation index represents the quantification data of the degree of influence of the loading time, update time, and response time on the loading performance of the ancient geographical map; comparing and matching the optimized performance evaluation index with the map state evaluation threshold corresponding to each performance evaluation index preset in the ancient map database to obtain the map state evaluation threshold corresponding to the optimized performance evaluation index.

[0036] Among them, the acquisition method of the performance evaluation index is as follows:

[0037]

[0038] In the formula, PE represents the performance evaluation index, α1 represents the performance evaluation index influence factor corresponding to the loading time, α2 represents the performance evaluation index influence factor corresponding to the update time, α3 represents the performance evaluation index influence 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 influencing factors corresponding to the preset loading time, update time and response time in the ancient map database, which respectively represent the numerical values ​​of the influence degree of loading time, update time and response time on the performance evaluation index, and can be directly obtained from the ancient map database when used. These relationships are organized into a "mapping set", that is, a lookup table or corresponding rules. When the value of a certain performance evaluation data is actually monitored, the value can be found according to the corresponding mapping set, and then the corresponding performance evaluation index influencing factor can be obtained. This influencing factor is a number between 0 and 1, which represents the evaluation result of the influence degree of the current performance evaluation data on the performance evaluation index. For example, for loading time, there are loading time and the performance evaluation index influencing factors corresponding to loading time as a mapping set. By inputting the value of loading time, the performance evaluation index influencing factors corresponding to loading time can be obtained; for update time, there are update time and the performance evaluation index influencing factors corresponding to update time as a mapping set. By inputting the value of update time, the performance evaluation index influencing factors corresponding to update time can be obtained; for response time, there are response time and the performance evaluation index influencing factors corresponding to response time as a mapping set. By inputting the value of response time, the performance evaluation index influencing factors corresponding to response time can be obtained. These mapping relationships can be many-to-one or one-to-one.

[0040] In this embodiment, the loading time indicates the time from when the user initiates a request to when 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 indicates the time required for the page content to update and display new data after the user interacts (such as zooming, switching layers). The longer the update time, the lower the performance evaluation index; the response time indicates the time from when the user operates (such as clicking, dragging) to when the system gives feedback (such as when the image starts to move or zoom). The longer the response time, the lower the performance evaluation index. The three are interrelated. For example, the longer the loading time, the longer the subsequent update time and response time may become. The performance evaluation index obtained by comprehensive analysis can measure the efficiency and user experience of the system during actual operation. Optimizing the performance of the paleogeographic map according to the performance evaluation index can not only help users access and operate historical geographic information more quickly, but also ensure that the system is still stable and reliable under large-scale use, and ultimately improve the platform's usage rate and user stickiness.

[0041] Set the impact factor of the performance evaluation index corresponding to the loading time to 0.4, the impact factor of the performance evaluation index corresponding to the update time to 0.2, the impact factor of the performance evaluation index corresponding to the response time to 0.4, the loading time to 0.2 s, the critical loading time to 0.1 s, the update time to 0.05 s, the critical update time to 0.05 s, and the critical response time to 0.05 s. Calculate the performance evaluation index when the response time is increasing continuously. As shown in Table 1, the data table of the performance evaluation index of the online visualization method based on the paleogeographic map.

[0042] Table 1 Data table of the performance evaluation index of the online visualization method based on the paleogeographic map

[0043]

[0044]

[0045] As Figure 2 shown, it is the change diagram of the performance evaluation index of the online visualization method based on the paleogeographic map provided by the embodiment of the present application. As shown in Table 1 and Figure 2 it can be seen that when the impact factor of the performance evaluation index corresponding to the loading time, the impact factor of the performance evaluation index corresponding to the update time, the impact factor of the performance evaluation index corresponding to the response time, the loading time, the critical loading time, the update time, the critical update time, and the critical response time remain unchanged and the response time is increasing continuously, the performance evaluation index is continuously decreasing.

[0046] Furthermore, the steps for optimizing the performance of the paleogeographic map according to the performance evaluation index include: obtaining the first performance evaluation threshold and the second performance evaluation threshold from the ancient 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, mark the paleogeographic map as a seriously abnormal program and immediately enable the 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, match the performance evaluation index with the adjustment multiples corresponding to each performance evaluation index preset in the ancient map database to obtain the adjustment multiple corresponding to the performance evaluation index, and adjust the performance tuning parameters according to the adjustment multiple; 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 turning off non-critical functions (such as user personalization settings, social functions, and advertisement display, etc.), only loading the data within the current view range, and notifying the maintenance personnel for repair, which can ensure that the system automatically switches to the safe mode when the performance drops extremely, avoiding system crashes or instability caused by overload or performance issues; the performance tuning parameters include rendering resolution, retention time, and cache existence time. When adjusting the performance tuning parameters according to the adjustment multiple, in the ancient map database, a mapping relationship table is formed by corresponding the performance evaluation indicators with the adjustment multiple one by one. The table records each performance evaluation indicator and its corresponding adjustment multiple, and these relationships can be one-to-one or many-to-one. When obtaining the adjustment multiple, just input the performance evaluation indicator into the mapping relationship table, and the ancient map database can quickly locate and return the adjustment multiple corresponding to this performance evaluation indicator, and multiply the adjustment multiple by the performance tuning parameter to obtain the adjusted performance tuning parameter, and adjust the value of the performance tuning parameter to the 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 the system operation, and whether optimization measures need to be taken can be automatically determined according to the comparison results.

[0048] Further, the user information data includes the number of users, the data loading amount of each user, and the cache data amount of each user; the steps of dynamically allocating resources for the user cache data based on the user information data include: obtaining the critical number of users, the critical data loading amount, and the critical cache data amount from the ancient map database; performing a ratio approximation operation on the data loading amount of each user and the cache data amount of each user with the critical data loading amount and the critical cache data amount respectively, then performing a coupling process, and then performing a weighted operation and an inverse ratio operation on the processing result and the ratio approximation operation result of the number of users and the critical number of users to obtain a map state evaluation value, where the map state evaluation value represents the quantitative data of the influence degree of the number of users, the data loading amount of each user, and the cache data amount of each user on the usage state of the ancient geographical map; dynamically allocating resources for the user cache data according to the map state evaluation value and the map state evaluation threshold, where the dynamic resource allocation is used to dynamically adjust the loaded data and the cache, improving the response speed and overall performance of the system.

[0049] Among them, the obtaining method of the map state evaluation value is as follows:

[0050]

[0051] In the formula, MS represents the map state evaluation value, α4 represents the map state evaluation influence factor corresponding to the number of users, α5 represents the map state evaluation influence factor corresponding to the data volume, SN1 represents the number of users, SN0 represents the critical number of users, DL 1iIndicates the data loading volume of the i-th user, DL0 represents the critical data loading volume, and DC 1i Indicates the cached data volume of the i-th user, DC0 represents the critical cached data volume, where i is the number of each user, i = 1, 2, 3,..., SN1.

[0052] α4 and α5 are respectively the map state evaluation influence factors corresponding to the preset number of users and data volume in the ancient map database, representing the numerical values of the influence degrees of the number of users and data volume on the map state evaluation value, which can be directly obtained from the ancient map database when used. These relationships are organized into a "mapping set", that is, a lookup table or corresponding rule. When the value of a certain user information data is actually monitored, this value can be found according to the corresponding mapping set, and then the corresponding map state evaluation influence factor can be obtained. This influence factor is a number between 0 and 1, which represents the evaluation result of the influence degree of the current user information data on the map state evaluation value. For example, for the number of users, there is a mapping set of the number of users and the map state evaluation influence factor corresponding to the number of users. By inputting the value of the number of users, the map state evaluation influence factor corresponding to the number of users can be obtained; for the data volume, there is a mapping set of the data volume and the map state evaluation influence factor corresponding to the data volume. By inputting the value of the data volume, the map state evaluation influence factor corresponding to the data volume can be obtained. Among them, 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 more the number of users, the smaller the map state evaluation value. The data loading volume of each user refers to the data volume that has been loaded by the device when each user accesses the map. The larger the data loading volume of each user, the smaller the map state evaluation value. The cached data volume of each user refers to the data volume cached by each user in their device. The more the cached data volume of each user, the smaller the map state evaluation value. All three can be directly obtained from the cache management record of the map system. The map state evaluation value obtained through comprehensive analysis can accurately evaluate the performance and resource usage of the current system, and optimize and adjust the system to ensure that the map service can provide a stable and efficient user experience under different loads.

[0054] Furthermore, the steps of dynamically allocating resources for user cached data according to the map state evaluation value and the map state evaluation threshold include: 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, the difference between the map state evaluation threshold and the map state evaluation value is marked as the deviation map state evaluation value, and dynamic resource allocation is performed for the user cached data according to 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 goal. Therefore, it can guide how to optimize resource allocation, whether it is necessary to increase the cache capacity or allocate more computing resources to make up for performance deficiencies. By dynamically adjusting resource allocation, when the deviation map state evaluation value is lower than the set threshold, the resources adjust the cache allocation according to the deviation value, avoiding resource waste or over-concentration, being able to efficiently utilize 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 steps of dynamically allocating resources for user cached data according to the deviation map state evaluation value include: obtaining the 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, switch all users to the simplified map mode, and match the deviation map state evaluation value with the data allowable loading ratio corresponding to each preset deviation map state evaluation value in the ancient map database to obtain the data allowable loading ratio. Divide the total data loading capacity by the number of users, and then obtain the user data allowable loading amount through the product operation of the data allowable loading ratio. Release the 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, switch all users to the simplified map mode, and at the same time, starting from the earliest cached data according to the chronological order of the cached data time, release all the cached data.

[0057] In this embodiment, when in the simplified map mode, the system will remove unnecessary visual details, such as geographical landmarks, buildings, or other unimportant map information, and at the same time reduce the dynamic rendering complexity, reduce the amount of data displayed and loaded, simplify the presented content of the map, so that users can quickly load and browse. When releasing the cached data, sort the cached data according to the existence time from large to small, and clean the cached data according to the sorting, so as to release more resources. Dynamically adjusting the cached data of users according to the deviation map state evaluation threshold can ensure that each user can load an appropriate amount of data, avoid memory overflow or system crash caused by excessive cached data, and at the same time, when resources are limited, users can still continue to experience smooth map services, enhancing user satisfaction.

[0058] Further, the dynamically loaded data includes the map resolution and the 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 detailed area. The specific steps include: obtaining the critical map resolution from the ancient map database, referring to the user zoom ratio and the allowable deviation user zoom ratio; performing a ratio approximation operation on the critical map resolution and the map resolution to obtain a map resolution influence parameter, performing a deviation compliance operation on the allowable deviation user zoom ratio, the reference user zoom ratio, and the user zoom ratio to obtain a user zoom ratio influence parameter, and then performing a weighted operation and coupling process on the map resolution influence parameter and the user zoom ratio influence parameter to obtain an interaction allowance evaluation value. The interaction allowance evaluation value represents the quantitative data of the combined influence of the map resolution and the user zoom ratio on the device interaction processing ability. Whether to load the detailed area is determined according to the interaction allowance evaluation value.

[0059] Among them, the interaction allowance evaluation value is obtained as follows:

[0060]

[0061] In the formula, IA represents the interaction allowance evaluation value, α6 represents the interaction allowance evaluation influence factor corresponding to the map resolution, α7 represents the interaction allowance evaluation influence 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 respectively the interaction allowance evaluation influence factors corresponding to the map resolution and the user zoom ratio preset in the ancient map database, and respectively represent the numerical values of the influence degrees of the map resolution and the user zoom ratio on the interaction allowance evaluation value. They can be directly obtained from the ancient map database when used. These relationships are organized into a "mapping set", that is, a lookup table or a corresponding rule. When the value of a certain dynamically loaded data is actually monitored, this value can be found according to the corresponding mapping set, and then the corresponding interaction allowance evaluation influence factor can be obtained. This influence factor is a number between 0 and 1, which represents the evaluation result of the influence degree of the current dynamically loaded data on the interaction allowance evaluation value. For example, for the map resolution, there is a mapping set of the map resolution and the interaction allowance evaluation influence factor corresponding to the map resolution. By inputting the value of the map resolution, the interaction allowance evaluation influence factor corresponding to the map resolution can be obtained; for the user zoom ratio, there is a mapping set of the user zoom ratio and the interaction allowance evaluation influence factor corresponding to the user zoom ratio. By inputting the value of the user zoom ratio, the interaction allowance evaluation influence factor corresponding to the user zoom ratio can be obtained. Among them, these mapping relationships can be many-to-one or one-to-one.

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

[0064] Further, the steps for determining whether to load the detailed area according to the allowable interaction evaluation value include: matching the user device resolution with the allowable interaction evaluation thresholds corresponding to each device resolution preset in the ancient map database to obtain the allowable interaction evaluation threshold; comparing the allowable interaction evaluation value with the allowable interaction evaluation threshold. If the allowable interaction evaluation value is greater than or equal to the allowable interaction evaluation threshold, the interaction operation is allowed, and the current interaction state is marked as normal; if the allowable interaction evaluation value is less than the allowable interaction evaluation threshold and the user device operating state is normal (the CPU usage rate of the user device does not reach the preset ratio), the interaction operation is allowed, the current interaction state is marked as normal, and the allowable interaction evaluation value is marked as the allowable interaction evaluation threshold of the current user device; if the allowable interaction evaluation value is less than the allowable interaction evaluation threshold and the user device operating state is abnormal (the CPU usage rate of the user device reaches the preset ratio), the current interaction state is marked as abnormal, the interaction data of the map in the current historical period is retained, and all cache data is released.

[0065] In this embodiment, in the ancient map database, a mapping relationship table is formed by corresponding each device resolution with the allowable interaction evaluation threshold one by one. The table records each device resolution and its corresponding allowable interaction evaluation threshold. These relationships can be one-to-one or many-to-one. When obtaining the allowable interaction evaluation threshold, only the user device resolution needs to be input into the mapping relationship table, and the ancient map database can quickly locate and return the allowable interaction 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, avoiding lags or crashes caused by performance overload; by detecting the device state and adopting different strategies (such as releasing the cache, marking abnormalities, etc.), the fault tolerance of the system to abnormal situations is improved, reducing the occurrence of crashes or lags. At the same time, in the case of device abnormalities, important historical data is retained, and the cache is released to ensure that the data is not lost and to avoid affecting the system stability due to excessive cache.

[0066] Further, the steps of hierarchical storage based on the operation frequency and historical interaction status of user interaction data include: obtaining an operation frequency threshold from the ancient map database; marking 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; marking user interaction data with an operation frequency less than the frequency threshold or an abnormal historical interaction status as low-level interaction data; storing the high-level interaction data in a high-speed storage medium and the low-level interaction data in a traditional storage medium.

[0067] In this embodiment, the high-speed storage medium refers to a storage device that can provide fast data reading and writing speeds, usually with low latency and high throughput, including solid-state drives, memory, etc. The traditional storage medium refers to a device with a slower reading speed, lower cost, and larger storage capacity, including mechanical hard drives, tape storage, etc. Through hierarchical storage, the system can make better use of storage resources and improve the operating efficiency of the system at the same time. The fast access of high-frequency interaction data ensures a smooth experience for users during high-frequency operations, while the slow access of low-frequency data does not affect normal operations.

[0068] As Figure 3 shown, it is a schematic structural diagram of an online visualization system of ancient geographical maps based on Gplates and Vue provided by an embodiment of the present application. The online visualization system of ancient geographical maps based on Gplates and Vue provided by an embodiment of the present application includes: 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 ancient geographical maps according to historical periods to obtain maps of each historical period, and then classify the maps of each historical period according to data content to obtain the basic map data and layer data of each historical period; the performance optimization module is used to, when the user enters the map browsing interface of each historical period, first display the basic map data of that historical period, preload the layer data and high-level interaction data according to the user device resolution and user historical browsing data, perform dynamic performance optimization using performance evaluation data, and perform dynamic resource allocation on the user cache data based on user information data; the data interaction module is used to, when the user performs a zoom operation during browsing, further determine whether to load the detailed area based on the dynamically loaded data of the user interaction operation, and perform hierarchical storage based on the operation frequency and historical interaction status of the user interaction data.

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

[0070] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0071] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows 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 the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices produce means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0072] These computer program instructions can 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, such that the instructions stored in the computer-readable memory produce a manufactured article including an instruction device that implements the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

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

[0074] Although the preferred embodiments of the present invention have been described, additional changes and modifications can be made by those skilled in the art once they learn of the basic inventive concept. Therefore, the appended claims are intended to be construed to cover the preferred embodiments as well as all changes and modifications that fall within the scope of the present invention.

[0075] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. An online visualization method of paleogeographic maps based on Gplates and Vue, characterized in that It includes the following steps: Classify the paleogeographic maps according to historical periods to obtain maps of each historical period, and then classify the maps of each historical period according to data content to obtain the basic map data and layer data of each historical period; When the user enters the map browsing interface of each historical period, first display the basic map data of that historical period, preload the layer data and high-level interaction data according to the user device resolution and user historical browsing data, perform dynamic performance optimization using performance evaluation data, and perform dynamic resource allocation on the user cache data based on the user information data; When the user performs a zoom operation during browsing, further determine whether to load the detail area based on the dynamically loaded data of the user interaction operation, and perform hierarchical storage based on the operation frequency and historical interaction status of the user interaction data.

2. The online visualization method of paleogeographic maps based on Gplates and Vue according to claim 1, characterized in that: The performance evaluation data includes loading time, update time, and response time; The steps of performing dynamic performance optimization using performance evaluation data include: Obtain the critical loading time, critical update time, and critical response time from the ancient map database; Perform ratio approximation operations on the critical loading time, critical update time, and critical response time with the loading time, update time, and response time respectively, and perform weighted operations on the results of the ratio approximation operations and then perform coupling processing to obtain performance evaluation indicators, and perform performance optimization on the paleogeographic maps according to the performance evaluation indicators to obtain optimized performance evaluation indicators. The performance evaluation indicators represent the quantification data of the influence degree of the loading time, update time, and response time on the loading performance of the paleogeographic maps; Compare and match the optimized performance evaluation indicators with the map state evaluation thresholds corresponding to the preset performance evaluation indicators in the ancient map database to obtain the map state evaluation thresholds corresponding to the optimized performance evaluation indicators.

3. The online visualization method of paleogeographic maps based on Gplates and Vue according to claim 2, characterized in that: The steps of performing performance optimization on the paleogeographic maps according to the performance evaluation indicators include: Obtain the first performance evaluation threshold and the second performance evaluation threshold from the ancient map database; Compare the performance evaluation indicators with the first performance evaluation threshold and the second performance evaluation threshold respectively. If the performance evaluation indicator is less than the first performance evaluation threshold, mark the paleogeographic map as a seriously abnormal program and immediately enable the downgrade mode; If the performance evaluation indicator is greater than or equal to the first performance evaluation threshold and less than the second performance evaluation threshold, match the performance evaluation indicator with the adjustment multiples corresponding to the preset performance evaluation indicators in the ancient map database to obtain the adjustment multiple corresponding to the performance evaluation indicator, and adjust the performance tuning parameters according to the adjustment multiple; If the performance evaluation indicator is greater than or equal to the second performance evaluation threshold, no additional operation is performed.

4. The online visualization method of paleogeographic maps based on Gplates and Vue according to claim 1, wherein: The user information data includes the number of users, the data loading amount of each user, and the cache data amount of each user; The steps of performing dynamic resource allocation on the user cache data based on the user information data include: Obtain the critical number of users, critical data loading amount, and critical cache data amount from the ancient map database; The ratio approach degrees of each user's data loading volume and each user's cached data volume to the critical data loading volume and the critical cached data volume are respectively calculated and then coupled. Then, the weighted operation is performed on the processing result and the ratio approach degree operation result of the number of users to the critical number of users, and the inverse proportion operation is carried out to obtain the map state evaluation value. The map state evaluation value represents the quantitative data of the influence degree of the number of users, each user's data loading volume, and each user's cached data volume on the usage state of the paleogeographic map. Based on the map state evaluation value and the map state evaluation threshold, dynamic resource allocation is performed on the user's cached data. The dynamic resource allocation is used to dynamically adjust the loaded data and the cache, improving the response speed and overall performance of the system.

5. The online visualization method of paleogeographic maps based on Gplates and Vue according to claim 4, characterized in that: The step of performing dynamic resource allocation on the user's cached data according to the map state evaluation value and the map state evaluation threshold includes: 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, the difference between the map state evaluation threshold and the map state evaluation value is marked as the deviation map state evaluation value, and dynamic resource allocation is performed on the user's cached data according to the deviation map state evaluation value.

6. The online visualization method of paleogeographic maps based on Gplates and Vue according to claim 5, characterized in that: The step of performing dynamic resource allocation on the user's cached data according to the deviation map state evaluation value includes: Obtaining the deviation map state evaluation threshold from the paleomap 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, all users are switched to the simplified map mode, and the deviation map state evaluation value is matched with the corresponding data allowable loading ratio of each preset deviation map state evaluation value in the paleomap database to obtain the data allowable loading ratio. The total data loading capacity is divided by the number of users, and then the user data allowable loading amount is obtained through the product operation of the data allowable loading ratio. The cached data is released based on the user data allowable loading amount and each user's current loading amount. If the deviation map state evaluation value is greater than the deviation map state evaluation threshold, all users are switched to the simplified map mode, and all cached data is released according to the cache data time.

7. The online visualization method of paleogeographic maps based on Gplates and Vue according to claim 1, wherein: The dynamically loaded data includes the map resolution and the user zoom ratio. When the user performs a zoom operation during the browsing process, it is further determined whether to load the detailed area based on the dynamically loaded data of the user interaction operation. The specific steps include: Obtaining the critical map resolution, referring to the user zoom ratio, and the allowable deviation user zoom ratio from the paleomap database. Perform a ratio approximation operation on the critical map resolution and the map resolution to obtain a map resolution influence parameter. Perform a deviation compliance operation on the allowable deviation user scaling ratio, the reference user scaling ratio, and the user scaling ratio to obtain a user scaling ratio influence parameter. Then, perform a weighted operation on the map resolution influence parameter and the user scaling ratio influence parameter and perform a coupling process to obtain an interaction allowable evaluation value. The interaction allowable evaluation value represents the quantitative data of the influence degree of the map resolution and the user scaling ratio on the device interaction processing ability. Determine whether to load the detailed area according to the interaction allowable evaluation value.

8. The online visualization method of paleogeographic maps based on Gplates and Vue according to claim 7, characterized in that: The step of determining whether to load the detailed area according to the interaction allowable evaluation value includes: Match the user device resolution with the interaction allowable evaluation threshold corresponding to each preset device resolution in the ancient map database to obtain the interaction allowable evaluation threshold; Compare the interaction allowable evaluation value with the interaction allowable evaluation threshold. If the interaction allowable evaluation value is greater than or equal to the interaction allowable evaluation threshold, allow the interaction operation and mark the current interaction status as normal; If the interaction allowable evaluation value is less than the interaction allowable evaluation threshold and the user device running status is normal, allow the interaction operation, mark the current interaction status as normal, and mark the interaction allowable evaluation value as the interaction allowable evaluation threshold of the current user device; If the interaction allowable evaluation value is less than the interaction allowable evaluation threshold and the user device running status is abnormal, mark the current interaction status as abnormal, retain the interaction data of the map in the current historical period, and release all cache data.

9. The online visualization method of paleogeographic maps based on Gplates and Vue according to claim 1, characterized in that: The step of performing hierarchical storage based on the operation frequency of the user interaction data and the historical interaction status includes: Obtain the operation frequency threshold from the ancient map database; Mark the user interaction data with an operation frequency greater than or equal to the operation frequency threshold and a historical interaction status of normal as high-level interaction data; Mark the user interaction data with an operation frequency less than the frequency threshold or a historical interaction status of abnormal as low-level interaction data; Store the high-level interaction data in a high-speed storage medium and store the low-level interaction data in a traditional storage medium.

10. An online visualization system for paleogeographic maps based on Gplates and Vue, characterized in that, Include a map classification module, a performance optimization module, a data interaction module, and an ancient map database; Among them, the map classification module is used to classify the ancient geographical 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 the basic map data of each historical period and the layer data of each historical period; The performance optimization module is used to, when the user enters the map browsing interface of each historical period, first display the basic map data of that historical period, preload the layer data and high-level interaction data according to the user device resolution and the user historical browsing data, perform dynamic performance optimization using the performance evaluation data, and perform dynamic resource allocation on the user cache data based on the user information data; The data interaction module is used to, when the user performs a zoom operation during the browsing process, further determine whether to load the detailed area based on the dynamically loaded data of the user interaction operation, and perform hierarchical storage based on the operation frequency of the user interaction data and the historical interaction status.

Images