VEVCC program for concatenation of volcanic events based on cross-correlation analysis
Volcanic eruptions pose a significant risk to communities located near active volcanoes. Disaster mitigation and risk reduction efforts rely on detecting and monitoring volcanic activity as early as possible. This article introduces VEVCC, a MATLAB-based application designed to precisely identify an...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2023-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/105/e3sconf_icstugm2023_01006.pdf |
| _version_ | 1797344986826539008 |
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| author | Dairoh Dairoh Fauzi Masykuri Anas Setyo Yuliatmoko Rahmat Rakhman Afif Saroji Sudarmaji Ashari Ahmad Suryanto Wiwit |
| author_facet | Dairoh Dairoh Fauzi Masykuri Anas Setyo Yuliatmoko Rahmat Rakhman Afif Saroji Sudarmaji Ashari Ahmad Suryanto Wiwit |
| author_sort | Dairoh Dairoh |
| collection | DOAJ |
| description | Volcanic eruptions pose a significant risk to communities located near active volcanoes. Disaster mitigation and risk reduction efforts rely on detecting and monitoring volcanic activity as early as possible. This article introduces VEVCC, a MATLAB-based application designed to precisely identify and extract volcanic seismic events from continuous data streams. VEVCC's primary objective is to facilitate the creation of an Excel file containing the arrival times of detected events, which can then be used for various purposes, such as early warning disaster mitigation and automated event identification via machine learning techniques. VEVCC utilizes cross-correlation algorithms to identify volcanic seismic events. It separates these events from background noise and other sources of seismicity, allowing for the construction of a clean and informative dataset. The extracted data is a valuable resource for estimating the frequency of volcanic events and evaluating patterns of volcanic activity. VEVCC's time-stamped event data is indispensable for improving early warning systems, real-time surveillance, and automated event identification. We tested the program on the Merapi volcano datasets during a 1998 campaign for a broadband experiment with the capability to extract the events automatically. Further machine-learning models and algorithms enhance the automatic recognition of volcanic events. |
| first_indexed | 2024-03-08T11:10:56Z |
| format | Article |
| id | doaj.art-ee6bbb2f6bec46c39d0452beae2dc294 |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-03-08T11:10:56Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-ee6bbb2f6bec46c39d0452beae2dc2942024-01-26T10:44:48ZengEDP SciencesE3S Web of Conferences2267-12422023-01-014680100610.1051/e3sconf/202346801006e3sconf_icstugm2023_01006VEVCC program for concatenation of volcanic events based on cross-correlation analysisDairoh Dairoh0Fauzi Masykuri Anas1Setyo Yuliatmoko Rahmat2Rakhman Afif3Saroji Sudarmaji4Ashari Ahmad5Suryanto Wiwit6Doctoral Program of Physics, Department of Physics, FMIPA, Universitas Gadjah MadaDoctoral Program of Physics, Department of Physics, FMIPA, Universitas Gadjah MadaDoctoral Program of Physics, Department of Physics, FMIPA, Universitas Gadjah MadaGeophysical Laboratory, Department of Physics, FMIPA, Universitas Gadjah MadaGeophysical Laboratory, Department of Physics, FMIPA, Universitas Gadjah MadaDepartment of Computer Science and Electronics, FMIPA, Universitas Gadjah MadaGeophysical Laboratory, Department of Physics, FMIPA, Universitas Gadjah MadaVolcanic eruptions pose a significant risk to communities located near active volcanoes. Disaster mitigation and risk reduction efforts rely on detecting and monitoring volcanic activity as early as possible. This article introduces VEVCC, a MATLAB-based application designed to precisely identify and extract volcanic seismic events from continuous data streams. VEVCC's primary objective is to facilitate the creation of an Excel file containing the arrival times of detected events, which can then be used for various purposes, such as early warning disaster mitigation and automated event identification via machine learning techniques. VEVCC utilizes cross-correlation algorithms to identify volcanic seismic events. It separates these events from background noise and other sources of seismicity, allowing for the construction of a clean and informative dataset. The extracted data is a valuable resource for estimating the frequency of volcanic events and evaluating patterns of volcanic activity. VEVCC's time-stamped event data is indispensable for improving early warning systems, real-time surveillance, and automated event identification. We tested the program on the Merapi volcano datasets during a 1998 campaign for a broadband experiment with the capability to extract the events automatically. Further machine-learning models and algorithms enhance the automatic recognition of volcanic events.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/105/e3sconf_icstugm2023_01006.pdf |
| spellingShingle | Dairoh Dairoh Fauzi Masykuri Anas Setyo Yuliatmoko Rahmat Rakhman Afif Saroji Sudarmaji Ashari Ahmad Suryanto Wiwit VEVCC program for concatenation of volcanic events based on cross-correlation analysis E3S Web of Conferences |
| title | VEVCC program for concatenation of volcanic events based on cross-correlation analysis |
| title_full | VEVCC program for concatenation of volcanic events based on cross-correlation analysis |
| title_fullStr | VEVCC program for concatenation of volcanic events based on cross-correlation analysis |
| title_full_unstemmed | VEVCC program for concatenation of volcanic events based on cross-correlation analysis |
| title_short | VEVCC program for concatenation of volcanic events based on cross-correlation analysis |
| title_sort | vevcc program for concatenation of volcanic events based on cross correlation analysis |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/105/e3sconf_icstugm2023_01006.pdf |
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