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随着我国空间技术科学的发展,遥感数据正以指数级增长,由于遥感数据的地理信息特征,海量遥感数据的存储和处理成了近年的研究热点,本文采用在商业上取得出色成绩的hadoop云计算平台来对海量遥感数据进行并行化处理,完成了系统并行性能测试与分析,结果表明利用hadoop对海量遥感数据的并行化处理的可行性,并且还能满足海量遥感数据并行处理效率要求和高可用性。
With the development of China’s space science and technology, remote sensing data are exponentially increasing. Due to the geographic information features of remote sensing data, the storage and processing of massive remote sensing data has become a research hotspot in recent years. In this paper, the Hadoop cloud Computing platform to parallelize the mass remote sensing data, completed the system parallel performance testing and analysis, the results show that the use of hadoop parallel processing of remote sensing data is feasible and can meet the mass remote sensing data parallel processing efficiency requirements and high Usability.