Quick Compression and Transmission of Meteorological Big Data in Complicated Visualization Systems
The sizes of individual data files have steadily increased along with rising demand for customized services, leading to issues such as low efficiency of web-based geographical information system (WebGIS)-based data compression, transmission, and rendering for rich Internet applications (RIAs) in com...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/6860915 |
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| _version_ | 1850173677663944704 |
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| author | He-Ping Yang Ying-Rui Sun Nan Chen Xiao-Wei Jiang Jing-Hua Chen Ming Yang Qi Wang Zi-Mo Huo Ming-Nong Feng |
| author_facet | He-Ping Yang Ying-Rui Sun Nan Chen Xiao-Wei Jiang Jing-Hua Chen Ming Yang Qi Wang Zi-Mo Huo Ming-Nong Feng |
| author_sort | He-Ping Yang |
| collection | DOAJ |
| description | The sizes of individual data files have steadily increased along with rising demand for customized services, leading to issues such as low efficiency of web-based geographical information system (WebGIS)-based data compression, transmission, and rendering for rich Internet applications (RIAs) in complicated visualization systems. In this article, a WebGIS-based technical solution for the efficient transmission and visualization of meteorological big data is proposed. Based on open-source technology such as HTML5 and Mapbox GL, the proposed scheme considers distributed data compression and transmission on the server side as well as distributed requests and page rendering on the browser side. A high-low 8-bit compression method is developed for compressing a 100 megabyte (MB) file into a megabyte-scale file, with a compression ratio of approximately 90%, and the recovered data are accurate to two decimal places. Another part of the scheme combines pyramid tile cutting, concurrent domain name request processing, and texture rendering. Experimental results indicate that with this scheme, grid files of up to 100 MB can be transferred and displayed in milliseconds, and multiterminal service applications can be supported by building a grid data visualization mode for big data and technology centers, which may serve as a reference for other industries. |
| format | Article |
| id | doaj-art-d444c48b061e44faa6b39295ead73dc5 |
| institution | OA Journals |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-d444c48b061e44faa6b39295ead73dc52025-08-20T02:19:47ZengWileyComplexity1099-05262022-01-01202210.1155/2022/6860915Quick Compression and Transmission of Meteorological Big Data in Complicated Visualization SystemsHe-Ping Yang0Ying-Rui Sun1Nan Chen2Xiao-Wei Jiang3Jing-Hua Chen4Ming Yang5Qi Wang6Zi-Mo Huo7Ming-Nong Feng8National Meteorological Data CenterNational Meteorological Data CenterNational Meteorological Data CenterNational Meteorological Data CenterNational Meteorological Data CenterZhejiang Meteorological Information and Network CenterNational Meteorological Data CenterNational Meteorological Data CenterNational Meteorological Data CenterThe sizes of individual data files have steadily increased along with rising demand for customized services, leading to issues such as low efficiency of web-based geographical information system (WebGIS)-based data compression, transmission, and rendering for rich Internet applications (RIAs) in complicated visualization systems. In this article, a WebGIS-based technical solution for the efficient transmission and visualization of meteorological big data is proposed. Based on open-source technology such as HTML5 and Mapbox GL, the proposed scheme considers distributed data compression and transmission on the server side as well as distributed requests and page rendering on the browser side. A high-low 8-bit compression method is developed for compressing a 100 megabyte (MB) file into a megabyte-scale file, with a compression ratio of approximately 90%, and the recovered data are accurate to two decimal places. Another part of the scheme combines pyramid tile cutting, concurrent domain name request processing, and texture rendering. Experimental results indicate that with this scheme, grid files of up to 100 MB can be transferred and displayed in milliseconds, and multiterminal service applications can be supported by building a grid data visualization mode for big data and technology centers, which may serve as a reference for other industries.http://dx.doi.org/10.1155/2022/6860915 |
| spellingShingle | He-Ping Yang Ying-Rui Sun Nan Chen Xiao-Wei Jiang Jing-Hua Chen Ming Yang Qi Wang Zi-Mo Huo Ming-Nong Feng Quick Compression and Transmission of Meteorological Big Data in Complicated Visualization Systems Complexity |
| title | Quick Compression and Transmission of Meteorological Big Data in Complicated Visualization Systems |
| title_full | Quick Compression and Transmission of Meteorological Big Data in Complicated Visualization Systems |
| title_fullStr | Quick Compression and Transmission of Meteorological Big Data in Complicated Visualization Systems |
| title_full_unstemmed | Quick Compression and Transmission of Meteorological Big Data in Complicated Visualization Systems |
| title_short | Quick Compression and Transmission of Meteorological Big Data in Complicated Visualization Systems |
| title_sort | quick compression and transmission of meteorological big data in complicated visualization systems |
| url | http://dx.doi.org/10.1155/2022/6860915 |
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