通过增强机载传感器的灵活性,打破大数据壁垒

P. Baumann, A. Dumitru, Vlad Merticariu, D. Misev, M. Rusu
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引用次数: 2

摘要

现代传感器,如高光谱相机,可以提供大量的数据。在卫星上,在立交桥期间,高容量与低带宽和部分可用性相匹配。这导致了当今遥感中众所周知的可用性问题和瓶颈。我们通过基于Array Analytics引擎rasdaman的灵活过滤和处理能力来增强车载系统,从而解决了这一挑战。然后,用户可以确定请求,这可以大大减少数据流量。我们的项目已经被接受为立方体卫星任务,rasdaman现在已经准备好了。为此,我们介绍了为rasdaman所做的项目设置和核心扩展。
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Breaking the big data barrier by enhancing on-board sensor flexibility
Modern sensors, such as hyperspectral cameras, deliver massive amounts of data. On board of satellites, the high volume is paired with low bandwidth and part-time availability, during overpasses. This leads to well-known availability problems and bottlenecks in today's remote sensing. We address this challenge by enhancing the on-board system with flexible filtering and processing capabilities based on the Array Analytics engine, rasdaman. Users then can exact request, which can lead to substantially decreased data traffic. Our project has been accepted for a CubeSat mission for which rasdaman now has been prepared. We present the project setup and core extensions done to rasdaman to this end.
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