Interactive Visualization of Geographic Vector Big Data Based on Viewport Generalization Model
The visualization of geographic vector data is an important premise for spatial analysis and spatial cognition. Traditional geographic vector data visualization methods are data-driven, and their computational costs have increased rapidly with the growth of the scale of data used. Even if the distri...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/15/7710 |
| _version_ | 1797432966462308352 |
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| author | Luo Chen Zebang Liu Mengyu Ma |
| author_facet | Luo Chen Zebang Liu Mengyu Ma |
| author_sort | Luo Chen |
| collection | DOAJ |
| description | The visualization of geographic vector data is an important premise for spatial analysis and spatial cognition. Traditional geographic vector data visualization methods are data-driven, and their computational costs have increased rapidly with the growth of the scale of data used. Even if the distributed parallel strategy is used, it is still difficult to achieve a real-time response when dealing with big geographic vector data (BGVD). To solve this problem, this paper proposes a viewport generalization model and a visualization method for the online interactive visualization of BGVD. The method takes the viewport display pixel as the analysis unit and synthesizes the existence or quantity results of geographic vector data in the corresponding spatial range of each viewport display pixel into the display value of this display pixel; thus, it converts traditional computational complexity, dependent on the data scale, into computational complexity dependent on the number of pixels in the viewport. When the number of pixels in the viewport is much smaller than that of the geographic vector data, the visualization efficiency is greatly improved. In order to realize the above conversion, the pixel quadtree index (VPQ) structure and the real-time visualization algorithm of geographic vector data based on VPQ are proposed. Experiments show that the proposed method can achieve the near-real-time interactive visualization of BGVD, and provides more than a tenfold performance improvement over the best existing methods. |
| first_indexed | 2024-03-09T10:09:21Z |
| format | Article |
| id | doaj.art-4c4d00a63de04e8980748e2298119a1c |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T10:09:21Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-4c4d00a63de04e8980748e2298119a1c2023-12-01T22:50:42ZengMDPI AGApplied Sciences2076-34172022-07-011215771010.3390/app12157710Interactive Visualization of Geographic Vector Big Data Based on Viewport Generalization ModelLuo Chen0Zebang Liu1Mengyu Ma2College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaThe visualization of geographic vector data is an important premise for spatial analysis and spatial cognition. Traditional geographic vector data visualization methods are data-driven, and their computational costs have increased rapidly with the growth of the scale of data used. Even if the distributed parallel strategy is used, it is still difficult to achieve a real-time response when dealing with big geographic vector data (BGVD). To solve this problem, this paper proposes a viewport generalization model and a visualization method for the online interactive visualization of BGVD. The method takes the viewport display pixel as the analysis unit and synthesizes the existence or quantity results of geographic vector data in the corresponding spatial range of each viewport display pixel into the display value of this display pixel; thus, it converts traditional computational complexity, dependent on the data scale, into computational complexity dependent on the number of pixels in the viewport. When the number of pixels in the viewport is much smaller than that of the geographic vector data, the visualization efficiency is greatly improved. In order to realize the above conversion, the pixel quadtree index (VPQ) structure and the real-time visualization algorithm of geographic vector data based on VPQ are proposed. Experiments show that the proposed method can achieve the near-real-time interactive visualization of BGVD, and provides more than a tenfold performance improvement over the best existing methods.https://www.mdpi.com/2076-3417/12/15/7710geographic data visualizationgeospatial big dataviewport generalizationparallel computinginteractive visualization |
| spellingShingle | Luo Chen Zebang Liu Mengyu Ma Interactive Visualization of Geographic Vector Big Data Based on Viewport Generalization Model Applied Sciences geographic data visualization geospatial big data viewport generalization parallel computing interactive visualization |
| title | Interactive Visualization of Geographic Vector Big Data Based on Viewport Generalization Model |
| title_full | Interactive Visualization of Geographic Vector Big Data Based on Viewport Generalization Model |
| title_fullStr | Interactive Visualization of Geographic Vector Big Data Based on Viewport Generalization Model |
| title_full_unstemmed | Interactive Visualization of Geographic Vector Big Data Based on Viewport Generalization Model |
| title_short | Interactive Visualization of Geographic Vector Big Data Based on Viewport Generalization Model |
| title_sort | interactive visualization of geographic vector big data based on viewport generalization model |
| topic | geographic data visualization geospatial big data viewport generalization parallel computing interactive visualization |
| url | https://www.mdpi.com/2076-3417/12/15/7710 |
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