基于云计算的遥感影像存储组织模型研究

发布时间：2018-06-15 11:06

本文选题：遥感影像数据 + 云计算　；参考：《河南大学》2013年硕士论文

【摘要】：随着自然科学的发展和人类历史的进步，人类获取遥感影像数据的手段日益多样化，获取到的遥感影像数据的类型日益丰富，遥感影像数据量爆炸性增长，形成了GB级、TB级、PB级的发展趋势。如此海量的数据给影像的高效存储、科学管理和低平台数据共享等各个方面带来了很大的困难，在数据的存储和使用方面都存在着较为突出的问题。本课题就是在这种背景下提出的，目的在于整合和管理现有的高分辨率遥感影像数据以及在分布式环境下为高分辨率影像共享服务以及高性能应用服务提供技术支撑。本文采用先进的云计算技术与遥感影像数据相结合的方式为解决海量多源异构影像数据的管理提供了一种新的方法，该方法区别于其他方式的数据管理模型，，在数据管理和检索效率上具有较为明显的优势。论文首先研究了与研究核心内容密切相关的三个方面背景知识，主要包括遥感影像数据、金字塔剖分模型和云计算的相关知识。从涉及到的每一方面要素的特点和功能出发提出了本文的核心内容——一种支持云计算的遥感影像数据组织模型（RemoteSensing Data Organization Model Based on Cloud Computing，RSC-DOM）。在深入分析目前遥感影像数据管理现状的基础上，详细剖析了云计算环境下遥感影像数据组织模型的各个关键性要素，涉及了支持扩展的分布式存储模式、存储站点结构以及虚拟磁盘空间结构等内容，构建了基于云计算的分布式存储模型架构。最后将该模型应用于海量多源异构空间数据存储和管理平台中的云存储子平台中，解决了分布式环境下的海量空间数据和模型方法等信息的快速存取。实验结果表明，所提出的存储模型在实际应用中具有较为明显的优势。
[Abstract]:With the development of natural science and the progress of human history, the means of obtaining remote sensing image data are becoming more and more diverse, the types of remote sensing image data are becoming more and more abundant, and the amount of remote sensing image data is increasing explosively. The development trend of GB grade TB grade and PB grade is formed. Such a huge amount of data has brought great difficulties to the efficient storage of images, scientific management and low platform data sharing, and there are some outstanding problems in the storage and use of data. The purpose of this paper is to integrate and manage the existing high resolution remote sensing image data and to provide technical support for the high resolution image sharing service and the high performance application service in the distributed environment. In this paper, the combination of advanced cloud computing technology and remote sensing image data provides a new method for the management of massive multi-source and heterogeneous image data, which is different from other data management models. It has obvious advantages in data management and retrieval efficiency. Firstly, three aspects of background knowledge, including remote sensing image data, pyramid subdivision model and cloud computing knowledge, which are closely related to the core contents of the research, are studied in this paper. Based on the characteristics and functions of each element involved, this paper presents the core content of this paper, a remote sensing data Organization model based on cloud computing and RSC-DOMN, which supports cloud computing. Based on the in-depth analysis of the current situation of remote sensing image data management, the key elements of remote sensing image data organization model in cloud computing environment are analyzed in detail, and the distributed storage model supporting extended storage is involved. The distributed storage model architecture based on cloud computing is constructed by storage site structure and virtual disk space structure. Finally, the model is applied to the cloud storage sub-platform of the massive multi-source heterogeneous spatial data storage and management platform, which solves the fast access of the massive spatial data and the model method in the distributed environment. Experimental results show that the proposed storage model has obvious advantages in practical applications.
【学位授予单位】：河南大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP333;TP79

【参考文献】