Big Data Analysis for Spatio-Temporal Earthquake Risk-Mapping System in Indonesia with Automatic Clustering
Big Data Analysis for Spatio-Temporal Earthquake Risk-Mapping System in Indonesia with Automatic Clustering
复制标题
印度尼西亚时空地震风险图系统自动聚类大数据分析
DOI：
10.1145/3152723.3152741
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Roy Advandy Aliefyan
中科院分区：
文献类型：
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作者：
Ali Ridho Barakbah;T. Harsono;Amang Sudarsono;Roy Advandy Aliefyan
地震是自然灾害类型之一。印尼几乎所有地区都经常发生震级从小到大的地震。预测和减轻地震灾害是预防大规模地震灾害发生的重要内容之一。预测和处理地震灾民的重要信息之一是提供一个地区（省）的地震风险图信息。这些信息是通过地震分布的大数据处理和地震时空数据的大数据分析提供的。以印尼各省地震密度为基础，对地震风险图系统进行了大数据分析。该系统有4个主要特点：（1）数据采集和预处理，（2）自动聚类使用我们的山谷跟踪算法，（3）密度测量的地震数据分布，（4）风险映射可视化投影到省。对于实验研究，地震数据是从印度尼西亚的高级国家地震系统（ANSS）1963-2016年获得的。我们在安达曼（班卡亚齐）、西苏门答腊和巴布亚的大地震灾区进行了一系列实验。通过对地震分布的大数据处理和地震时空数据的大数据分析，得出地震密度值高对该地区未来一年发生地震的危险性有影响。
Earthquake is one of nature disaster types. Almost all regions in Indonesia are often earthquakes ranging from small magnitude to large. Anticipation and mitigation of earthquake victims is one of the important points in preventing the occurrence of earthquake victims in large numbers. One of the important information in anticipating and handling earthquake victims is to provide information about earthquake risk mapping in a region (province). This information is given by big data processing of the earthquake distribution and big data analytics of spatio-temporal earthquake data. This paperpresented a big data analysis for earthquake risk mapping system based on earthquake density projected to provinces in Indonesia. This system has 4 main features: (1) Data acquisation and preprocessing, (2) Automatic clustering using our Valley Tracing algorithm, (3) Density measurement of earthquake data distribution, and (4) Risk-mapping visualization projected to provinces. For experimental study, earthquake data is obtained from Advanced National Seismic System(ANSS) year 1963-2016 in location of Indonesia. We made a series of experiments in the places hit by big earthquake in Andaman (Banca Aceh), West Sumatra, and Papua. Based on the big data processing of the earthquake distribution and big data analytics of spatio-temporal earthquake data, it performed that the high seismic density value affected the risk of earthquake occurrence in the next year in the area concerned.