Two-dimensional map frame rate optimization method under low-performance platform

Abstract

The invention provides a method for optimizing the frame rate of a two-dimensional map under a low-performance platform, and belongs to the technical field of geographic information systems, and the method comprises the steps: building LOD grades: carrying out the two-dimensional display of a map, and building the LOD grades of which the levels are greater than ten levels; setting an element display range: carrying out corresponding display level setting on each type of map elements; processing complex elements: setting different simplification strategies for different types of map elements with edge points exceeding a first preset threshold value, and utilizing a topology maintenance algorithm to ensure topology constraints; and data compression and reading: compressing and reading the original map data based on LOD grading establishment, element display range setting and complex element processing contents. Through the processing scheme provided by the invention, the frame rate stability when the low-performance platform operates the two-dimensional map is improved, the user interaction experience is improved, the equipment energy consumption is reduced, and the overall performance is improved.

Description

Technical Field

[0001] This application relates to the field of geographic information system technology, and in particular to a method for optimizing the frame rate of two-dimensional maps on low-performance platforms. Background Technology

[0002] Modern map clients commonly use either raster tiles or vector features for rendering. Vector maps are widely used due to their customizable styles and ability to achieve multi-level or continuous scaling. To improve the rendering efficiency of vector maps, techniques such as spatial indexing, level of detail (LOD), geometric simplification, vector tile tiling, texture merging, and batch rendering are typically employed. However, on performance-constrained embedded platforms, these techniques still have significant shortcomings, mainly manifested in the following ways: 1. Redundancy in map feature retrieval and loading. When loading by tile / region, a large number of features that are not in the viewport or are not visible are often loaded, wasting real-time performance; 2. Few LOD layers: With few LOD layers, the height changes too much when switching screens, and the map scaling ratio reaches 1:3 or 1:4, resulting in a poor viewing experience; 3. Too many features displayed: The display strategy is not refined according to feature type. Complex features are still fully drawn at high scale levels, and the excessive number of points leads to a serious drop in frame rate. 4. Simplified algorithm is crude: Simplified elements use the same parameters and algorithm, which has poor adaptability at different LOD levels. For example, too many points at high scale levels cause lag, while too few points at low scale levels affect the accuracy of the boundary.

[0003] Therefore, there is an urgent need for an overall solution that can achieve accurate viewport retrieval (based on quadtrees and other schemes) on low-performance platforms, fast map resource reading, hierarchical display of features controlled by LOD, and hierarchical simplification of LOD association, so as to balance rendering smoothness and visual integrity on low-performance devices (such as Jingjia Micro 7200 SOC). Summary of the Invention

[0004] This invention addresses the problems of slow retrieval speed, redundant retrieval content, low frame rate due to excessive rendering elements, and insufficient refinement of simplified elements in vector map rendering on low-performance platforms. It proposes a frame rate optimization method for 2D maps on low-performance platforms, mainly focusing on fast map element retrieval and LOD-related element display and simplification methods for low-performance platforms. It is a high-efficiency and low-energy-consumption map element loading and rendering scheme to solve the problems of excessive element points, redundant data reading leading to a significant drop in frame rate, excessive memory / video memory usage, and unreasonable simplification of complex elements such as rivers, lakes, and administrative boundaries in existing technologies.

[0005] This application provides a method for optimizing the frame rate of two-dimensional maps on a low-performance platform. The method includes: LOD (Level of Distance) grading establishment: Display the map in two dimensions and establish a LOD grading system with more than ten levels; Feature display range settings: Set the corresponding display level for each type of map feature; Complex feature processing: For different types of map features with more than a first preset threshold of edge points, different simplification strategies are set, and topology preservation algorithms are used to ensure topological constraints. Data compression and reading: Based on the LOD hierarchical establishment, feature display range setting, and complex feature processing, the original map data is compressed and read.

[0006] According to one specific implementation of the embodiments of this application, the LOD level range is from ten to fifteen levels.

[0007] According to a specific implementation of this application, the formula for calculating the screen display distance for each level is as follows: L(n) = 3.75 * 2 n , Where the total number of LOD levels is m, then n∈[0,m-1]; L(n) represents the actual screen distance corresponding to level n, in kilometers.

[0008] According to a specific implementation of an embodiment of this application, the step of setting a corresponding display hierarchy for each type of map element includes: For map features of the city boundary type, the display level is L2~L3; For map elements of the district / county boundary type, the display level is L4-L5; For river-type map features, the display hierarchy is L5-Lm; For map features of the lake and reservoir type, the display level is L5-Lm; For forest-type map features, the display hierarchy is L5-Lm; For map features of the railway type, the display hierarchy is L5-L8; For map features of the types of expressways, national highways, and provincial highways, the display level is L6-L8; For map features of the township and island types, the display level is L6-Lm; For map features of park, institution, school and village types, the display level is L7-Lm; For map features of the types of expressways, county roads, and village roads, the display level is L8-Lm; For other unmentioned map elements, the display hierarchy is L0-Lm.

[0009] According to a specific implementation of an embodiment of this application, the step of setting different simplification strategies for different types of map features with more than a first preset threshold number of edge points, and using a topology preservation algorithm to ensure topological constraints, includes: For map features of rivers with more than the first preset threshold of edge points, the Visvalingam-Whyatt algorithm is used for simplification, with the tolerance parameter set to 50-200 m according to the scale; the minimum number of vertices to be retained is 2-5, and the maximum offset distance is 1.2 times the tolerance to 2.0 times the tolerance. For map features of lakes and reservoirs with more than the first preset threshold of edge points, the Zhou-Jones algorithm is used for simplification, with the tolerance parameter set to 100-500 m according to the scale; the maximum angular deviation is 10°-20°. For map features representing administrative boundaries with more than a first preset threshold of edge points, the Douglas-Peucker algorithm is used for simplification. The tolerance parameter is set to 30-150 m according to the scale; the convexity weight is 0.5-0.9; and the minimum effective area is π / 2 * tolerance. 2 -2π*tolerance 2 ; For map features of forests and parks with more than the first preset threshold of edge points, the Wang-Muller algorithm is used for simplification, with the tolerance parameter set to 80-300 m according to the complexity; the bend recognition threshold is 1.5 * tolerance - 3.0 * tolerance, and the smoothing iteration count is 1-3 times.

[0010] According to a specific implementation of an embodiment of this application, the compression and reading of the original map data includes: Preprocess the raw map data; Initialize and load the preprocessed data; Dynamically loaded when displaying in real time; Perform graphical rendering on the loaded data.

[0011] According to a specific implementation of an embodiment of this application, the preprocessing of the original map data includes: The original map data is read and preprocessed in a unified manner, and a quadtree index structure based on LOD hierarchy is constructed. The preprocessed data is pre-compiled into binary format. During the compilation process, data is stored separately, with background data and vector data stored as independent files. The background data is terrain information tile data, and the vector data is information tile data of each element.

[0012] According to a specific implementation of an embodiment of this application, the initial loading of the preprocessed data includes: When the system starts, a minimum loading mechanism is used, loading only the background data of the highest level in the LOD hierarchy.

[0013] According to a specific implementation of an embodiment of this application, the real-time display is dynamically loaded, including: During real-time display, the system dynamically calculates the bounding box range based on the current viewpoint position, and then determines the LOD level that needs to be read based on the viewing height. By using a quadtree traversal algorithm, background data and vector data within the spatial bounding box are selectively read to ensure that only map data within the current viewpoint is updated.

[0014] According to a specific implementation of an embodiment of this application, the step of performing graphical rendering processing on the loaded data includes: The rendering pipeline clears the screen buffer and renders the loaded terrain background data to the screen; Based on the OpenGL ES graphics library, vector data vertices are submitted according to the preset priority order of feature types to complete the drawing of map features in each layer and screen updates.

[0015] Beneficial effects: The 2D map frame rate optimization method for low-performance platforms described in this application has the following technical effects on low-performance embedded platforms: 1. Reduce hierarchical jumps: By using more than ten levels of LOD hierarchy, layered display of features, and hierarchical simplification, the visual continuity of zooming operations is improved, and the visual topological integrity is maintained. 2. Streamlined element display hierarchy, significantly improving the layer frame rate at large scales; 3. Specific simplification methods are adopted for multiple elements to reduce the number of points drawn while preserving topological features and improving the map display frame rate; 4. Preprocessing map data is separated from map operation, reducing device load and improving display performance; 5. Compressed map data reduces memory usage, decreases data reading volume, increases speed, lowers LOD switching latency, and increases average frame rate. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of a method for optimizing the frame rate of a two-dimensional map on a low-performance platform according to an embodiment of the present invention. Detailed Implementation

[0018] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0019] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this application, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0021] It should also be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The illustrations only show the components related to this application and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0022] Furthermore, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.

[0023] This application provides a method for optimizing the performance of 2D maps on low-performance embedded platforms (such as the Jingjia Micro JM7200 SOC platform). It addresses the shortcomings of traditional 2D map displays, such as limited LOD levels, large data volume, slow reading speed, excessive feature display, and lack of specific feature simplification methods. By significantly increasing the number of LOD levels, specifying features displayed at different levels, performing specific simplification and topology maintenance on complex features, compressing data to improve reading speed, and reading specific tiles based on the viewpoint, the frame rate of 2D maps on low-performance platforms is guaranteed.

[0024] In one embodiment, a method for optimizing the frame rate of two-dimensional maps on a low-performance platform is provided, referring to... Figure 1 The method includes: LOD (Level of Distance) grading establishment: Display the map in two dimensions and establish a LOD grading system with more than ten levels; Feature display range settings: Set the corresponding display level for each type of map feature; Complex feature processing: For different types of map features with more than a first preset threshold of edge points, different simplification strategies are set, and topology preservation algorithms are used to ensure topological constraints. Data compression and reading: Based on the LOD hierarchical establishment, feature display range setting, and complex feature processing, the original map data is compressed and read.

[0025] Furthermore, the LOD grading ranges from ten to fifteen levels.

[0026] In this implementation, a refined 10-15 level LOD classification replaces the traditional 4-6 level LOD division, reducing the actual distance difference between levels to a factor of 1, thus replacing the existing 2-3x scaling scheme. This effectively avoids the visual jump issues caused by excessive height changes when switching traditional LOD levels. When the map scaling ratio is controlled within the range of 1:1.5 to 1:2, the smoothness of the map viewing experience is significantly improved, effectively reducing the visual disjointedness during zooming operations.

[0027] Furthermore, the formula for calculating the screen display distance for each level is as follows: L(n) = 3.75 * 2 n , Where the total number of LOD levels is m, then n∈[0,m-1]; L(n) represents the actual screen distance corresponding to level n, in kilometers.

[0028] In practice, L(0) represents the detail view, with a scale of 1:18,450 for a screen with a resolution of 1024*768 and a resolution of 96 DPI; L(9) represents the panoramic view, with a scale of 1:9,446,400 for a screen with a resolution of 1024*768 and a resolution of 96 DPI; and L(14) represents the maximum view, with a scale of 1:302,284,800 for a screen with a resolution of 1024*768 and a resolution of 96 DPI.

[0029] Furthermore, the step of setting the corresponding display level for each type of map feature (Lm represents the current maximum level) includes: For map features of the city boundary type, the display level is L2~L3; For map elements of the district / county boundary type, the display level is L4-L5; For river-type map features, the display hierarchy is L5-Lm; For map features of the lake and reservoir type, the display level is L5-Lm; For forest-type map features, the display hierarchy is L5-Lm; For map features of the railway type, the display hierarchy is L5-L8; For map features of the types of expressways, national highways, and provincial highways, the display level is L6-L8; For map features of the township and island types, the display level is L6-Lm; For map features of park, institution, school and village types, the display level is L7-Lm; For map features of the types of expressways, county roads, and village roads, the display level is L8-Lm; For other unmentioned map elements, the display hierarchy is L0-Lm.

[0030] In this embodiment, different display ranges are defined for map features based on their type, and independent display layer thresholds are set for different feature types. This ensures that complex polygons such as roads, parks, forests, rivers, lakes, and administrative boundaries are not drawn at appropriate lower layers (i.e., when the scale is small), thereby reducing the number of rendered vertices and improving the frame rate. This layered display strategy significantly reduces the number of graphics instructions that low-performance platforms need to process per unit time in large-scale scenes, thereby increasing the layered frame rate by more than 30% and effectively solving the frame rate fluctuation problem caused by indiscriminate loading of features in traditional methods.

[0031] Furthermore, for different types of map features with more than a first preset threshold of edge points, different simplification strategies are set, and a topology preservation algorithm is used to ensure topological constraints, including: For map features of rivers with more than the first preset threshold of edge points, the Visvalingam-Whyatt algorithm is used for simplification, with the tolerance parameter set to 50-200 m according to the scale; the minimum number of vertices to be retained is 2-5, and the maximum offset distance is 1.2 times the tolerance to 2.0 times the tolerance. For map features of lakes and reservoirs with more than the first preset threshold of edge points, the Zhou-Jones algorithm is used for simplification, with the tolerance parameter set to 100-500 m according to the scale; the maximum angular deviation is 10°-20°. For map features representing administrative boundaries with more than a first preset threshold of edge points, the Douglas-Peucker algorithm is used for simplification. The tolerance parameter is set to 30-150 m according to the scale; the convexity weight is 0.5-0.9; and the minimum effective area is π / 2 * tolerance. 2 -2π*tolerance 2 ; For map features of forests and parks with more than the first preset threshold of edge points, the Wang-Muller algorithm is used for simplification, with the tolerance parameter set to 80-300 m according to the complexity; the bend recognition threshold is 1.5 * tolerance - 3.0 * tolerance, and the smoothing iteration count is 1-3 times.

[0032] Preferably, for map features of rivers with more than a first preset threshold number of edge points, the minimum number of vertices to be retained is 3, and the maximum offset distance is 1.5 * tolerance. For map features of lakes and reservoirs with more than the first preset threshold number of edge points, the maximum angle deviation is 15°. For map features on administrative boundaries where the number of edge points exceeds a first preset threshold, the convexity weight is 0.7, and the minimum effective area is π * tolerance. 2 ; For map features of forests and parks with more than the first preset threshold number of edge points, the bend recognition threshold is 2.0 * tolerance, and the smoothing iteration count is 1.

[0033] In this embodiment, a hierarchical simplification strategy related to Level of Detail (LOD) is proposed for elements such as lakes, rivers, administrative boundaries, and forests. The simplification threshold for complex elements is dynamically adjusted according to the LOD level (more simplification for smaller scales and less simplification for larger scales), significantly reducing the number of element points. While ensuring visual continuity, the topological connectivity and consistency of adjacent boundaries of elements are maintained, avoiding breaks or topological errors caused by simplification.

[0034] In one embodiment, the compression and reading of the original map data includes: Preprocess the raw map data; Initialize and load the preprocessed data; Dynamically loaded when displaying in real time; Perform graphical rendering on the loaded data.

[0035] Furthermore, the preprocessing of the original map data includes: The original map data (.shp) is read and preprocessed in a unified manner, and a quadtree index structure based on LOD hierarchy is constructed. The preprocessed data is pre-compiled into binary format (.bin). During the compilation process, data is stored separately, with background data and vector data stored as independent files. The background data is terrain information tile data, and the vector data is information tile data of each feature.

[0036] In this embodiment, by constructing a quadtree index structure based on LOD hierarchy, the required map data tiles within the current viewport range can be quickly located, improving data retrieval efficiency. Preprocessed data is pre-compiled into binary format, which significantly reduces data volume and speeds up file read / write compared to traditional text format. Furthermore, binary data requires no format conversion during parsing and can be directly recognized by the graphics rendering engine, further reducing CPU processing overhead. A data separation storage strategy is adopted, storing terrain information tile data and feature information tile data independently. This allows the system to accurately read the corresponding data type based on current display requirements during dynamic loading, avoiding the loading of invalid data that consumes memory resources. Especially on low-performance platforms, this data organization method effectively alleviates memory pressure and improves data loading response speed.

[0037] Furthermore, the initial loading of the preprocessed data includes: When the system starts, it loads the pre-compiled binary file into memory, using a minimal loading mechanism, loading only the background data of the highest level in the LOD hierarchy.

[0038] In this embodiment, this loading method can minimize the resource consumption during the system startup phase. On low-performance embedded platforms, the initial loading time can be shortened to less than 1 / 5 of the traditional full loading method, while the initial memory usage is reduced by more than 70%. This avoids system lag or response delay caused by loading a large amount of data during startup, ensuring that the application can quickly enter a usable state.

[0039] Furthermore, the real-time display dynamically loads data, including: During real-time display, the system dynamically calculates the bounding box range based on the current viewpoint position, and then determines the LOD level that needs to be read based on the viewing height. By using a quadtree traversal algorithm, background data and vector data within the spatial bounding box are selectively read to ensure that only map data within the current viewpoint is updated.

[0040] In this embodiment, vector features are merged into a binary file based on a quadtree spatial index during the preprocessing stage. At runtime, feature data within the viewport is read directly from the quadtree based on the viewport bounding box, reducing unnecessary data loading and rendering. Precise control of data loading is achieved by dynamically calculating the matching relationship between the spatial bounding box and the LOD level. When the user pans or zooms on the map, the system can respond in real time to changes in the current viewpoint, loading only the map tiles of the required level within the viewport, avoiding redundant calculations caused by loading data from the entire area in traditional methods.

[0041] Furthermore, the graphical rendering processing of the loaded data includes: The rendering pipeline clears the screen buffer and renders the loaded terrain background data to the screen; Based on the OpenGL ES graphics library, vector data vertices are submitted according to the preset priority order of feature types to complete the drawing of map features in each layer and screen updates.

[0042] In practice, when displaying a two-dimensional map, the following steps are included: a) Load the pre-compiled binary file into memory; b) When the map starts, only the background data at the Lm level is loaded. When displaying the map, the current bounding box is calculated based on the current viewpoint height, then the tiles in the current bounding box are calculated, and finally the background quadtree and vector quadtree are read, updating only the necessary map data; c) Use a quadtree to traverse the background tiles and vector tiles within the bounding box and load them into the OpenGL buffer; d) Clear the screen and update the background of the buffer to the screen; e) Based on the OpenGL ES function library, submit vertex data, draw elements onto the screen in sequence, and perform drawing updates.

[0043] The embodiments provided by this invention relate to a method for spatial index retrieval, simplification, and hierarchical display of vector map features on a low-performance embedded platform, specifically applicable to low-performance, low-power SOC processor platforms (such as Jingjia Micro 7200 SOC). While ensuring map visual coherence and feature accuracy, it significantly improves the rendering calculation speed and frame rate of low-performance platforms, achieving an increased average frame rate on conventional map datasets, enhancing user interaction experience, reducing device power consumption, and improving overall performance.

[0044] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for optimizing frame rate of a two-dimensional map under a low-performance platform, characterized in that, The method includes: LOD (Level of Distance) grading establishment: Display the map in two dimensions and establish a LOD grading system with more than ten levels; Feature display range settings: Set the corresponding display level for each type of map feature; Complex feature processing: For different types of map features with more than a first preset threshold of edge points, different simplification strategies are set, and topology preservation algorithms are used to ensure topological constraints. Data compression and reading: Based on the LOD hierarchical establishment, feature display range setting, and complex feature processing, the original map data is compressed and read.

2. The low-performance platform under two-dimensional map frame rate optimization method of claim 1, wherein, The LOD (Level of Observation) classification ranges from level ten to level fifteen.

3. The low performance platform under two-dimensional map frame rate optimization method of claim 1, wherein, The formula for calculating the screen display distance for each level is: L(n) = 3.75 * 2 n , Where the total number of LOD levels is m, then n∈[0,m-1]; L(n) represents the actual screen distance corresponding to level n, in kilometers.

4. The method for optimizing the frame rate of two-dimensional maps on a low-performance platform according to claim 3, characterized in that, The step of setting the corresponding display hierarchy for each type of map feature includes: For map features of the city boundary type, the display level is L2~L3; For map elements of the district / county boundary type, the display level is L4-L5; For river-type map features, the display hierarchy is L5-Lm; For map features of the lake and reservoir type, the display level is L5-Lm; For forest-type map features, the display hierarchy is L5-Lm; For map features of the railway type, the display hierarchy is L5-L8; For map features of the types of expressways, national highways, and provincial highways, the display level is L6-L8; For map features of the township and island types, the display level is L6-Lm; For map features of park, institution, school and village types, the display level is L7-Lm; For map features of the types of expressways, county roads, and village roads, the display level is L8-Lm; For other unmentioned map elements, the display hierarchy is L0-Lm.

5. The method for optimizing the frame rate of two-dimensional maps on a low-performance platform according to claim 4, characterized in that, For different types of map features with more than a first preset threshold of edge points, different simplification strategies are set, and a topology preservation algorithm is used to ensure topological constraints, including: For map features of rivers with more than the first preset threshold of edge points, the Visvalingam-Whyatt algorithm is used for simplification, with the tolerance parameter set to 50-200 m according to the scale; the minimum number of vertices to be retained is 2-5, and the maximum offset distance is 1.2 times the tolerance to 2.0 times the tolerance. For map features of lakes and reservoirs with more than the first preset threshold of edge points, the Zhou-Jones algorithm is used for simplification, with the tolerance parameter set to 100-500 m according to the scale; the maximum angular deviation is 10°-20°. For the administrative boundary map elements with edge point number exceeding the first preset threshold, simplification is performed using the Douglas-Peucker algorithm, the tolerance parameter is set to 30-150 m according to the scale, the convexity weight is 0.5-0.9, and the minimum effective area is π / 2*tolerance 2 -2π*tolerance 2 ​ For map features of forests and parks with more than the first preset threshold of edge points, the Wang-Muller algorithm is used for simplification, with the tolerance parameter set to 80-300 m according to the complexity; the bend recognition threshold is 1.5 * tolerance - 3.0 * tolerance, and the smoothing iteration count is 1-3 times.

6. The method for optimizing the frame rate of two-dimensional maps on a low-performance platform according to claim 1, characterized in that, The compression and reading of the original map data includes: Preprocess the raw map data; Initialize and load the preprocessed data; Dynamically loaded when displaying in real time; Perform graphical rendering on the loaded data.

7. The method for optimizing the frame rate of two-dimensional maps on a low-performance platform according to claim 6, characterized in that, The preprocessing of the original map data includes: The original map data is read and preprocessed in a unified manner, and a quadtree index structure based on LOD hierarchy is constructed. The preprocessed data is pre-compiled into binary format. During the compilation process, data is stored separately, with background data and vector data stored as independent files. The background data is terrain information tile data, and the vector data is information tile data of each element.

8. The method for optimizing the frame rate of two-dimensional maps on a low-performance platform according to claim 7, characterized in that, The initial loading of the preprocessed data includes: When the system starts, a minimum loading mechanism is used, loading only the background data of the highest level in the LOD hierarchy.

9. The method for optimizing the frame rate of two-dimensional maps on a low-performance platform according to claim 8, characterized in that, The real-time display is dynamically loaded, including: During real-time display, the system dynamically calculates the bounding box range based on the current viewpoint position, and then determines the LOD level that needs to be read based on the viewing height. By using a quadtree traversal algorithm, background data and vector data within the spatial bounding box are selectively read to ensure that only map data within the current viewpoint is updated.

10. The method for optimizing the frame rate of two-dimensional maps on a low-performance platform according to claim 1, characterized in that, The graphical rendering process of the loaded data includes: The rendering pipeline clears the screen buffer and renders the loaded terrain background data to the screen; Based on the OpenGL ES graphics library, vector data vertices are submitted according to the preset priority order of feature types to complete the drawing of map features in each layer and screen updates.

Images