分布式环境下遥感影像数据存储方法  

Research on Remote Sensing Image Data Storage in Distributed Environment

作　　者：王卓琳 高心丹[1] WANG Zhuolin;GAO Xindan(College of Information and Computer Engineering,Northeast Forestry University,Harbin 150000,China)

机构地区：[1]东北林业大学信息与计算机工程学院,哈尔滨150000

出　　处：《实验室研究与探索》2018年第10期129-135,145,共8页Research and Exploration In Laboratory

基　　金：国家自然科学基金面上项目(31770768);中央高校基本科研业务费专项资助基金E类(2572017EB09)

摘　　要：为了对遥感影像数据进行高效地存储与管理,解决传统的存储与查询效率不高的问题。设计一种基于猫群算法的遥感影像并行存储算法,采用线性四叉树对地理空间进行划分和编码,利用MapReduce并行计算框架和猫群优化算法来构建金字塔,把地物标识码、四叉树索引ID两种信息作为行键,采用HBase分布式数据库对影像数据进行存储。实验表明,该方法在金字塔构建的过程中有效的提高了遥感影像的存储效率且保证了数据的完整性。在查询方面,改进的行键不仅达到了筛选数据的目的而且提高了读取效率。研究成果可满足对海量影像高效存储、管理的需求,具有很好的可行性和可扩展性。In order to store and manage the remote sensing image data efficiently,to solve the problem that the traditional storage and query efficiency is not high,a parallel storage algorithm for remote sensing images based on cat swarm algorithm was designed.First,the linear quadtree was used to divide and code the geographic space.Then,the MapReduce parallel computing framework and the cat swarm optimization algorithm were used to build pyramid.Finally,HBase distributed database was used to store the image data by using the landmark identification code and the quadtree index ID as the Rowkeys.The experiment showed that the method can effectively improve the storage efficiency of remote sensing image and ensure the integrity of the data in the process of building Pyramid.In query,the improved row key not only achieved the purpose of filtering the data,but also improved the reading efficiency.The research results could meet the needs of high efficient storage and management of massive images,and had good feasibility and scalability.

关 键 词：分布式存储 四叉树 猫群算法 影像金字塔 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]