地理时空大数据协同计算技术

Collaborative Computing Technology of Geographical Big Data

大数据时代,地理时空数据的迅猛增长给应用理念、技术框架和服务形式带来挑战。本文在阐述地理时空大数据概念的基础上,首先分析了地理时空大数据计算面临的挑战,从数据协同、技术协同、服务协同和生产协同4个层次阐述了地理时空大数据协同计算方法;然后,根据平台化服务的需求设计了地理时空大数据协同计算框架,从遥感数据综合预处理、地理时空数据的组织与管理、地理时空大数据高效计算、地理时空大数据可视化4个方面论述了地理时空大数据协同计算实现的关键技术;最后,以遥感大数据综合处理系统作为案例说明了地理时空大数据协同计算与服务的实现方法,并对地理时空大数据的应用模式进行了展望。

In the era of big data, the rapid growth of geographic spatial temporal data has challenged the conventional application concepts, technical framework and service modes. In this paper, the concept and features of geographic spatial temporal big data is elaborated firstly. Then, the characteristics and challenges of the geographic spatial temporal big data computation are analyzed. Particularly, the theory of collaborative computing and service for the geographic spatial temporal big data is developed, which includes four levels of collaboration： data collaboration, technology collaboration, service collaboration and producing collaboration.According to the demand of the market-oriented operation and platform-based service, the technical frameworks of the geographic spatial temporal big data collaborative computing are designed. Furthermore, four common key technologies are discussed, including the remote sensing data preprocessing, the geographic spatial temporal data storage and management, the high performance computing and the visualization of geographic spatial temporal big data. Next, the remote sensing data processing system is developed, and is taken as a case to illustrate the implementation of collaborative computing and service of geographic spatial temporal big data. At last, this paper forecasts the future application mode of geographic spatial temporal big data.