A Data Warehouse for earthquakes signal precursors analysis

P. Biagi, C. Guaragnella, A. Guerriero, C. Pasquale, F. Ragni
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引用次数: 4

Abstract

Earthquake analysis and monitoring requires complex processing of raw data acquired from several kind of sensors or extracted from data repositories. Management and processing of huge amount of data produced by different sources, i.e. remote sensing and measurement stations of ground and atmospheric physical parameters, the complexity of the environmental models adopted to understand observed phenomena, the necessary distributed collaboration among scientists, results sharing and validation, require specific middleware and applications. A number of researches propose to transform acquired data into assessments of current ecosystem conditions and its evolution trends in time and space; many algorithms, protocols, and applications have been presented to collect, process and analyze ground precursors representing changes in the physical and chemical state of the Earth. These projects deal with data obtained i.e. from satellite, VLF signal and INGV database, integrated with meteorological data and stored in ad hoc repositories. No work deals with a general and flexible approach to integrate and manage different kind of data. In this paper we present a data warehouse to analyze earthquake signal precursors, whose goal is to fuse and exploit efficiently different kind of data and share/display the processing results. The proposed platform allows users/researches: to access data collected by different sources, to record data for future use, to normalize and visualize data for exploring and analyzing complex structure and relationships, and to process data using distributed computing resources and web applications. A case study related to data fusion of INGV data, magnetic field variations acquired by a network of VLF radio stations, MODIS data to evaluate modification in the ground temperature by satellite and geo-located sensor data of weather and climatic parameters is presented.
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地震前兆分析的数据仓库
地震分析和监测需要对从几种传感器获取的原始数据或从数据存储库中提取的原始数据进行复杂的处理。管理和处理来自不同来源的大量数据,如地面和大气物理参数的遥感和测量站,用于理解观测现象的环境模型的复杂性,科学家之间必要的分布式协作,结果共享和验证,都需要特定的中间件和应用程序。一些研究建议将获取的数据转化为对当前生态系统状况及其时空演变趋势的评估;已经提出了许多算法、协议和应用程序来收集、处理和分析代表地球物理和化学状态变化的地面前体。这些项目处理从卫星、VLF信号和INGV数据库获得的数据,这些数据与气象数据相结合并存储在临时存储库中。没有工作涉及集成和管理不同类型数据的通用且灵活的方法。本文提出了一种用于地震前兆分析的数据仓库,其目标是有效地融合和利用不同类型的数据,并共享/显示处理结果。该平台允许用户/研究人员访问不同来源收集的数据,记录数据以备将来使用,对数据进行规范化和可视化,以探索和分析复杂的结构和关系,并使用分布式计算资源和web应用程序处理数据。介绍了INGV数据、VLF无线电台网络获取的磁场变化数据、用于评估卫星地温变化的MODIS数据和地理位置传感器的天气和气候参数数据的数据融合的案例研究。
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