With the development of remote sensing technology,there is a remarkable increase in the kind of remote sensing data and reso-lution of remote sensing image data,the traditional data storage and processing cannot meet the requirements of remote data management, which is a challenge for the traditional remote sensing data management mode. Based on digital earth project,in order to manage the mas-sive remote sensing data effectively,firstly introduce a physical storage structure and design the data structure and coding mode. With the purpose to improve query efficiency,propose a index based on binary tree and minimum bounding box,which is more simple,better bal-anced,more effective than the other index. The experimental results illustrate the proposed data storage structure and index is suitable for managing massive remote sensing data,which can meet the requirements of data input,index building and data query.%随着遥感技术的发展,遥感数据的种类不断增加,遥感影像分辨率不断提高,遥感数据的量级呈现不断增加的趋势,大数据时代的遥感数据存储和处理都面临着严峻的挑战,传统的数据存储和处理已不能满足遥感数据管理的需求.以数字地球项目为背景,为有效地管理项目中的海量遥感数据,首先对遥感数据物理存储结构进行设计,从底层数据存储层对数据结构和编码方式进行了规划;其次为了提高数据的检索效率,在现有四叉树索引的技术上,提出了一种基于二叉树的最小包围盒索引结构,相比于其他索引结构具有设计简单、树结构平衡、检索效率高的特点.实验结果表明,提出的数据存储结构和索引结构可以满足数据入库、索引构建和数据查询的要求,适合于支持海量遥感数据的存储和管理.
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