遥感大数据的基础设施:集成、管理与按需服务

发布时间：2018-05-17 00:41

本文选题：数据基础设施 + 遥感大数据　；参考：《计算机研究与发展》2017年02期

【摘要】：随着遥感技术的不断进步,遥感数据的数据量越来越大,种类越来越多,分布越来越分散,遥感应用的复杂程度和个性化程度也不断提高,遥感正在走向大数据时代.而目前遥感数据基础设施在容量、可扩展性、易用性和性能等方面都难以满足遥感应用的需求,成为了遥感科学与工程从获取到最终产品这个流程中的瓶颈.为此,首先从遥感数据的本质出发,讨论了遥感数据基础设施应当具备的分布、异构、时空连续和按需数据处理等特性,并依据遥感数据基础设施的基本服务单元、分布性、时空连续性和按需处理支持能力将遥感数据基础设施分成6类.其次,针对这6类遥感数据基础设施展现出的特性,设计了实现这些基础设施可以采用的体系结构,并指出了其中实现的技术难点和解决思路.最后,就遥感数据基础设施设计和实现过程中涉及到的数据收集与整合、数据组织与管理、数据服务接口、按需数据处理等方面的技术方案进行了深入的讨论.在这些技术的支持下,遥感数据基础设施能够做到分布化、智能化和平台化,支持遥感科学的合作研究和工程上的协同应用.
[Abstract]:With the development of remote sensing technology, the amount of remote sensing data is becoming larger and larger, more and more kinds of remote sensing data are distributed, and the complexity and individuation of remote sensing applications are also increasing. Remote sensing is moving towards the era of big data. At present, remote sensing data infrastructure is difficult to meet the requirements of remote sensing applications in terms of capacity, scalability, ease of use and performance, which has become the bottleneck in the process of remote sensing science and engineering from obtaining to final product. Therefore, starting from the essence of remote sensing data, this paper discusses the characteristics of remote sensing data infrastructure, such as distribution, heterogeneity, spatio-temporal continuity and on-demand data processing, and according to the basic service unit of remote sensing data infrastructure, distribution. Spatial and temporal continuity and on-demand processing support can divide remote sensing data infrastructure into six categories. Secondly, according to the characteristics of the six kinds of remote sensing data infrastructure, the architecture that can be used to implement these infrastructure is designed, and the technical difficulties and solutions are pointed out. Finally, the data collection and integration, data organization and management, data service interface, on-demand data processing and so on, which are involved in the design and implementation of remote sensing data infrastructure, are discussed in depth. With the support of these technologies, remote sensing data infrastructure can be distributed, intelligent and platform, and support cooperative research and engineering application of remote sensing science.
【作者单位】：中国科学院遥感与数字地球研究所;清华大学计算机科学与技术系;
【基金】：国家重点研发计划项目(2016YFB0501504) 海南省重大科技计划项目(ZDKJ2016021)~~
【分类号】：TP79

【相似文献】