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Article

Evaluation of Pre-Earthquake Anomalies of Borehole Strain Network by Using Receiver Operating Characteristic Curve

1
Key Laboratory of Geo-Exploration Instrumentation, Ministry of Education, Jilin University, Changchun 130061, China
2
The College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130061, China
3
Graduate School of Science, Chiba University, Inage, Chiba 263-8522, Japan
4
Center for Environmental Remote Sensing, Chiba University, Inage, Chiba 263-8522, Japan
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Istituto Nazionale di Geofisica e Vulcanologia, Via di Vigna Murata, 605, 00143 Rome, Italy
6
School of Information Science and Technology, Hainan Normal University, Haikou 571158, China
*
Author to whom correspondence should be addressed.
Academic Editor: Salvarore Stramondo
Remote Sens. 2021, 13(3), 515; https://doi.org/10.3390/rs13030515
Received: 2 December 2020 / Revised: 24 January 2021 / Accepted: 29 January 2021 / Published: 1 February 2021
In order to monitor temporal and spatial crustal activities associated with earthquakes, ground- and satellite-based monitoring systems have been installed in China since the 1990s. In recent years, the correlation between monitoring strain anomalies and local major earthquakes has been verified. In this study, we further evaluate the possibility of strain anomalies containing earthquake precursors by using Receiver Operating Characteristic (ROC) prediction. First, strain network anomalies were extracted in the borehole strain data recorded in Western China during 2010–2017. Then, we proposed a new prediction strategy characterized by the number of network anomalies in an anomaly window, Nano, and the length of alarm window, Talm. We assumed that clusters of network anomalies indicate a probability increase of an impending earthquake, and consequently, the alarm window would be the duration during which a possible earthquake would occur. The Area Under the ROC Curve (AUC) between true predicted rate, tpr, and false alarm rate, fpr, is measured to evaluate the efficiency of the prediction strategies. We found that the optimal strategy of short-term forecasts was established by setting the number of anomalies greater than 7 within 14 days and the alarm window at one day. The results further show the prediction strategy performs significantly better when there are frequent enhanced network anomalies prior to the larger earthquakes surrounding the strain network region. The ROC detection indicates that strain data possibly contain the precursory information associated with major earthquakes and highlights the potential for short-term earthquake forecasting. View Full-Text
Keywords: receiver operating characteristic; a new prediction strategy; frequent network anomalies; prediction efficiency; short-term earthquake forecasting receiver operating characteristic; a new prediction strategy; frequent network anomalies; prediction efficiency; short-term earthquake forecasting
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MDPI and ACS Style

Yu, Z.; Hattori, K.; Zhu, K.; Fan, M.; Marchetti, D.; He, X.; Chi, C. Evaluation of Pre-Earthquake Anomalies of Borehole Strain Network by Using Receiver Operating Characteristic Curve. Remote Sens. 2021, 13, 515. https://doi.org/10.3390/rs13030515

AMA Style

Yu Z, Hattori K, Zhu K, Fan M, Marchetti D, He X, Chi C. Evaluation of Pre-Earthquake Anomalies of Borehole Strain Network by Using Receiver Operating Characteristic Curve. Remote Sensing. 2021; 13(3):515. https://doi.org/10.3390/rs13030515

Chicago/Turabian Style

Yu, Zining, Katsumi Hattori, Kaiguang Zhu, Mengxuan Fan, Dedalo Marchetti, Xiaodan He, and Chengquan Chi. 2021. "Evaluation of Pre-Earthquake Anomalies of Borehole Strain Network by Using Receiver Operating Characteristic Curve" Remote Sensing 13, no. 3: 515. https://doi.org/10.3390/rs13030515

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