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Towards Building a Distributed Data Management Architecture to Integrate Multi-Sources Remote Sensing Big Data

机译:致力于构建分布式数据管理体系结构以集成多源遥感大数据

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摘要

Recent advances in sensor technologies have led to the significant growth of remote sensing data in terms of its volume, velocity, and variety. Remote sensing data are recognized as the big data, which pose the urgent need for new technologies to integrate and manage heterogeneous remote sensing big data. In this paper, a scalable, efficient, distributed data management system is proposed for heterogeneous remote sensing big data integration and management across the distributed environment. In the system, the remote sensing data are stored as NetCDF files. Meanwhile, the corresponding remote sensing metadata are standardized according to the ISO 19115-2:2009 based metadata template. In this way, a unified view of heterogeneous remote sensing data is formed. Two organization models are designed to store massive remote sensing data and its metadata in HDFS and HBase, respectively. Besides, an Elasticsearch-based secondary index is built for HBase to provide users with query ability of metadata contents.
机译:传感器技术的最新进展已使遥感数据的数量,速度和种类大大增加。遥感数据被认为是大数据,迫切需要集成和管理异构遥感大数据的新技术。本文提出了一种可扩展,高效,分布式的数据管理系统,用于跨分布式环境的异构遥感大数据集成和管理。在系统中,遥感数据存储为NetCDF文件。同时,根据基于ISO 19115-2:2009的元数据模板对相应的遥感元数据进行了标准化。这样,形成了异构遥感数据的统一视图。设计了两种组织模型,分别在HDFS和HBase中存储海量遥感数据及其元数据。此外,为HBase构建了基于Elasticsearch的二级索引,为用户提供元数据内容的查询功能。

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