本文選題：遙感影像數(shù)據(jù) + 云計算��； 參考：《河南大學》2013年碩士論文

【摘要】：隨著自然科學的發(fā)展和人類歷史的進步，人類獲取遙感影像數(shù)據(jù)的手段日益多樣化，獲取到的遙感影像數(shù)據(jù)的類型日益豐富，遙感影像數(shù)據(jù)量爆炸性增長，形成了GB級、TB級、PB級的發(fā)展趨勢。如此海量的數(shù)據(jù)給影像的高效存儲、科學管理和低平臺數(shù)據(jù)共享等各個方面帶來了很大的困難，在數(shù)據(jù)的存儲和使用方面都存在著較為突出的問題。本課題就是在這種背景下提出的，目的在于整合和管理現(xiàn)有的高分辨率遙感影像數(shù)據(jù)以及在分布式環(huán)境下為高分辨率影像共享服務(wù)以及高性能應(yīng)用服務(wù)提供技術(shù)支撐。本文采用先進的云計算技術(shù)與遙感影像數(shù)據(jù)相結(jié)合的方式為解決海量多源異構(gòu)影像數(shù)據(jù)的管理提供了一種新的方法，該方法區(qū)別于其他方式的數(shù)據(jù)管理模型，，在數(shù)據(jù)管理和檢索效率上具有較為明顯的優(yōu)勢。 論文首先研究了與研究核心內(nèi)容密切相關(guān)的三個方面背景知識，主要包括遙感影像數(shù)據(jù)、金字塔剖分模型和云計算的相關(guān)知識。從涉及到的每一方面要素的特點和功能出發(fā)提出了本文的核心內(nèi)容——一種支持云計算的遙感影像數(shù)據(jù)組織模型（RemoteSensing Data Organization Model Based on Cloud Computing，RSC-DOM）。 在深入分析目前遙感影像數(shù)據(jù)管理現(xiàn)狀的基礎(chǔ)上，詳細剖析了云計算環(huán)境下遙感影像數(shù)據(jù)組織模型的各個關(guān)鍵性要素，涉及了支持擴展的分布式存儲模式、存儲站點結(jié)構(gòu)以及虛擬磁盤空間結(jié)構(gòu)等內(nèi)容，構(gòu)建了基于云計算的分布式存儲模型架構(gòu)。 最后將該模型應(yīng)用于海量多源異構(gòu)空間數(shù)據(jù)存儲和管理平臺中的云存儲子平臺中，解決了分布式環(huán)境下的海量空間數(shù)據(jù)和模型方法等信息的快速存取。實驗結(jié)果表明，所提出的存儲模型在實際應(yīng)用中具有較為明顯的優(yōu)勢。
[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.
【學位授予單位】：河南大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP333;TP79

【參考文獻】

相關(guān)期刊論文 前3條

1 程承旗;宋樹華;濮國梁;萬元嵬;董芳;;空間信息全球惟一編碼GeoID模型初探[J];測繪科學;2010年06期

2 呂雪鋒;程承旗;龔健雅;關(guān)麗;;海量遙感數(shù)據(jù)存儲管理技術(shù)綜述[J];中國科學:技術(shù)科學;2011年12期

3 李建鋒;彭艦;;云計算環(huán)境下基于改進遺傳算法的任務(wù)調(diào)度算法[J];計算機應(yīng)用;2011年01期

本文編號：2021797