Viper: Interactive Exploration of Large Satellite Data✱✱
Viper: Interactive Exploration of Large Satellite Data✱✱
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DOI：
10.1145/3609956.3609966
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发表时间：
2023-08
期刊：
影响因子：
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通讯作者：
Zhuocheng Shang;Ahmed Eldawy
中科院分区：
文献类型：
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作者：
Zhuocheng Shang;Ahmed Eldawy
高分辨率卫星数据的显著增加需要更有效的分析方法，以使数据科学家受益。交互式探索对生产力至关重要，因为它通过提供快速响应来保持用户参与。本文讨论了渐进式分区统计问题，给定大卫星数据，聚合函数，和一组查询多边形，分区统计计算聚合函数为每个查询多边形在栅格数据。高效查询复杂多边形、阅读高分辨率像素和同时处理多个多边形是三个主要挑战。这项工作介绍了毒蛇，一个互动的勘探管道，以克服这些挑战，并实现要求。Viper使用光栅矢量索引来引导答案，在短时间内获得准确的结果。然后，它使用优先级处理算法逐步细化答案，以产生最终答案。在大规模真实的数据上的实验表明，Viper可以达到90%或更高的准确率，比基线算法快两个数量级。
Significant increase in high-resolution satellite data requires more productive analysis methods to benefit data scientists. Interactive exploration is essential to productivity since it keeps the user engaged by providing quick responses. This paper addresses the progressive zonal statistics problem that given big satellite data, an aggregate function, and a set of query polygons, zonal statistics computes the aggregate function for each query polygon over raster data. Efficiently querying complex polygons, reading high resolution pixels and process multiple polygons simultaneously are three main challenges. This work introduces Viper, an interactive exploration pipeline to overcome these challenges and achieve requirements. Viper uses a raster-vector index to bootstrap the answer with an accurate result in a short time. Then, it progressively refines the answer using a priority processing algorithm to produce the final answer. Experiments on large-scale real data show that Viper can reach 90% accuracy or higher up-to two orders of magnitude faster than baseline algorithms.