湖北农业科学 ›› 2023, Vol. 62 ›› Issue (1): 182-187.doi: 10.14088/j.cnki.issn0439-8114.2023.01.032

• 农业工程 • 上一篇    下一篇

基于DataV的气象可视化数据平台设计与实现

邱忠洋, 蒋骏, 雷正翠, 黄文彦   

  1. 常州市气象局,江苏 常州 213022
  • 收稿日期:2021-06-02 出版日期:2023-01-25 发布日期:2023-03-07
  • 作者简介:邱忠洋(1990-),男,江苏盐城人,硕士,主要从事计算机软件、地理信息系统研究,(电话)13382864466(电子信箱)1011349606@qq.com。
  • 基金资助:
    中国气象局专项项目(CMAYBY2019-043); 江苏省预报员专项项目(JSYBY201809); 江苏省常州市气象局重点项目(CZQX2002)

Design and implementation of meteorological data visualization platform based on DataV

QIU Zhong-yang, JIANG Jun, LEI Zheng-cui, HUANG Wen-yan   

  1. Changzhou Meteorological Bureau, Changzhou 213022,Jiangsu,China
  • Received:2021-06-02 Online:2023-01-25 Published:2023-03-07

摘要: 综合分析了传统气象数据展示的缺陷,针对气象数据量大、展示直观度低、分析研判少、智能演示弱等问题,提出将DataV技术引入可视化展示平台的解决方案,结合气象业务现状,将气象预警、预报、站点、服务产品等海量信息分析后集中展示,给决策机构提供可靠的数据展示;平台总体框架设计过程中,引入数据中台技术,使用了多线程B/S架构录入数据,后台采用了MySQL数据库存储服务,数据接口使用了Mybatis框架,前端使用DataV平台进行演示;阐述了系统各项技术设计方案,并给出具体设计方法。实际运行效果表明,该技术方案可以直观反映气象大数据分析的结果,极大地提高了气象数据的交互性、实时性、灵活性,更清晰地辅助于决策。

关键词: DataV, 气象数据, 数据中台, B/S模式, Mybatis框架

Abstract: The defects of the traditional meteorological data display were analyzed comprehensively by the paper. Aiming at the problems of large amounts of meteorological data, low visualization, less analysis, research and judgment, and weak intelligent demonstration, the solution of introducing DataV technology into the visual display platform was proposed. Massive information, such as meteorological early warning, forecast, stations and service products, had been intensively displayed after analysis to provide reliable data display for decision-making bodies. In the design process of the platform, the data middle platform technology was introduced, the multithreaded B/S architecture was used to input data, the MySQL database storage service was used in the background, the Mybatis framework was used in the data interface processing, and the DataV platform was used in the fore-end of the display. The technical design scheme of the system was described, and the specific design method was given. The results of meteorological big data analysis could be reflected directly by this technical scheme. The interactivity, real-time performance and flexibility of meteorological data were improved greatly, and decision-making would become easier.

Key words: DataV, meteorological data, data center, B/S mode, Mybatis framework

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