{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T22:04:55Z","timestamp":1766181895661,"version":"build-2065373602"},"reference-count":26,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,6,16]],"date-time":"2022-06-16T00:00:00Z","timestamp":1655337600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2019YFC1509205","41874019","ZDJ2019-12"],"award-info":[{"award-number":["2019YFC1509205","41874019","ZDJ2019-12"]}]},{"name":"National Nature Science Foundation of China","award":["2019YFC1509205","41874019","ZDJ2019-12"],"award-info":[{"award-number":["2019YFC1509205","41874019","ZDJ2019-12"]}]},{"name":"National Institute of Natural Hazards, Ministry of Emergency Management of China","award":["2019YFC1509205","41874019","ZDJ2019-12"],"award-info":[{"award-number":["2019YFC1509205","41874019","ZDJ2019-12"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>How to estimate an earthquake\u2019s magnitude rapidly and accurately is a challenge for any earthquake early warning system. In order to reach a balance between accuracy and timeliness, a synchronous magnitude estimation method with P-wave phases\u2019 detection is proposed. In this method, the P-wave phases are detected by the changes of the signal-to-noise ratio (SNR) of the seismic records, where the SNRs are calculated by the short-term power and long-term power ratio (STP\/LTP). Meanwhile, the variations of the SNR are applied to estimate the magnitude of the earthquake. By the statistics of some earthquake cases, a synchronous magnitude estimation model of the variation of the P-wave phases\u2019 SNR, the earthquake magnitude, and the hypocentral distance was built. Compared with some other magnitude estimation methods, the suggested method inherits the robustness of the STP\/LTP method and is more accurate and rapid than the peak displacement (Pd) method.<\/jats:p>","DOI":"10.3390\/s22124534","type":"journal-article","created":{"date-parts":[[2022,6,16]],"date-time":"2022-06-16T03:01:22Z","timestamp":1655348482000},"page":"4534","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Synchronous Magnitude Estimation with P-Wave Phases\u2019 Detection Used in Earthquake Early Warning System"],"prefix":"10.3390","volume":"22","author":[{"given":"Dingwen","family":"Zhang","sequence":"first","affiliation":[{"name":"National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8024-1610","authenticated-orcid":false,"given":"Jihua","family":"Fu","sequence":"additional","affiliation":[{"name":"National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China"},{"name":"Institute of Disaster Prevention, Sanhe 065201, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhitao","family":"Li","sequence":"additional","affiliation":[{"name":"National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Linyue","family":"Wang","sequence":"additional","affiliation":[{"name":"National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiale","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Disaster Prevention, Sanhe 065201, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianjun","family":"Wang","sequence":"additional","affiliation":[{"name":"National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,16]]},"reference":[{"key":"ref_1","first-page":"673","article-title":"On the Urgent Earthquake Detection and Alarm System (UrEDAS)","volume":"2","author":"Nakamura","year":"1988","journal-title":"Proc. Ninth World Conf. Earthq. Eng."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1785\/0120030133","article-title":"An Automatic Processing System for Broadcasting Earthquake Alarms","volume":"95","author":"Shigeki","year":"2005","journal-title":"Bull. Seismol. Soc. Am."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1126\/science.1080912","article-title":"The Potential for Earthquake Early Warning in Southern California","volume":"300","author":"Allen","year":"2003","journal-title":"Science"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1253","DOI":"10.1016\/S0074-6142(03)80190-0","article-title":"76\u2014The Seismic Alert System of Mexico City","volume":"81","year":"2003","journal-title":"Int. Geophys."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"719","DOI":"10.3319\/TAO.1999.10.4.719(T)","article-title":"Development of an Integrated Earthquake Early Warning System in Taiwan-Case for the Hualien Area Earthquakes","volume":"10","author":"Wu","year":"1999","journal-title":"Terr. Atmos. Ocean. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1023\/A:1024813612271","article-title":"Istanbul Earthquake Early Warning and Rapid Response System","volume":"1","author":"Erdik","year":"2003","journal-title":"Bull. Earthq. Eng."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Fu, J., Li, Z., Meng, H., Wang, J., and Shan, X. (2019). Performance Evaluation of Low-Cost Seismic Sensors for Dense Earthquake Early Warning: 2018\u20132019 Field Testing in Southwest China. Sensors, 19.","DOI":"10.3390\/s19091999"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1146\/annurev.earth.33.092203.122626","article-title":"Real-Time seismology and earthquake damage mitigation","volume":"33","author":"Kanamori","year":"2005","journal-title":"Annu. Rev. Earth Planet. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1111\/j.1365-246X.2007.03430.x","article-title":"Determination of earthquake early warning parameters, \u03c4c and Pd, for southern California","volume":"170","author":"Wu","year":"2007","journal-title":"Geophys. J. Int."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2739","DOI":"10.1785\/0120080144","article-title":"Limitation of the Predominant-Period Estimator for Earthquake Early Warning and the Initial Rupture of Earthquakes","volume":"98","author":"Yamada","year":"2008","journal-title":"Bull. Seismol. Soc. Am."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1254","DOI":"10.1785\/BSSA0880051254","article-title":"Quick and Reliable Determination of Magnitude for Seismic Early Warning","volume":"88","author":"Wu","year":"1998","journal-title":"Bull. Seismol. Soc. Am."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1785\/0120040097","article-title":"Experiment on an Onsite Early Warning Method for the Taiwan Early Warning System","volume":"95","author":"Wu","year":"2005","journal-title":"Bull. Seismol. Soc. Am."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1029\/2006GL026871","article-title":"Magnitude estimation using the first three seconds P-wave amplitude in earthquake early warning","volume":"33","author":"Wu","year":"2006","journal-title":"Geophys. Res. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"B12302","DOI":"10.1029\/2007JB005386","article-title":"A Bayesian approach to the real-time estimation of magnitude from the early P and S wave displacement peaks","volume":"113","author":"Lancieri","year":"2008","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_15","first-page":"123","article-title":"Research on earthquake early warning parameters and rapid magnitude estimation based events in Yunnan region in 2014","volume":"34","author":"Li","year":"2018","journal-title":"World Inf. Earthq. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1007\/s10950-020-09981-w","article-title":"Magnitude-scaling relationships based on initial P-wave information in the Xinjiang region, China","volume":"25","author":"Wang","year":"2021","journal-title":"J. Seismol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"L00B05","DOI":"10.1029\/2008GL036659","article-title":"A study on warning algorithms for Istanbul earthquake early warning system","volume":"36","author":"Alcik","year":"2009","journal-title":"Geophys. Res. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"653226","DOI":"10.3389\/feart.2021.653226","article-title":"Magnitude Estimation for Earthquake Early Warning Using a Deep Convolutional Neural Network","volume":"9","author":"Zhu","year":"2021","journal-title":"Front. Earth Sci."},{"key":"ref_19","first-page":"e2019GL085976","article-title":"A Machine-Learning Approach for Earthquake Magnitude Estimation","volume":"41","author":"Mousavi","year":"2019","journal-title":"Geophys. Res. Lett."},{"key":"ref_20","first-page":"2617","article-title":"Application of machine learning to magnitude estimation in earthquake emergency prediction system","volume":"63","author":"Hu","year":"2020","journal-title":"Chin. J. Geophys."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1785\/0220190043","article-title":"Automatic Phase-Picking Method for Detecting Earthquakes Based on the Signal-to-Noise-Ratio Concept","volume":"91","author":"Fu","year":"2019","journal-title":"Seismol. Res. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1126\/science.268.5212.851","article-title":"Seismic evidence for an earthquake nucleation phase","volume":"268","author":"Ellsworth","year":"1995","journal-title":"Science"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1002\/2017GL076118","article-title":"Real-Time Detection of Rupture Development: Earthquake Early Warning Using P Waves From Growing Ruptures","volume":"45","author":"Kodera","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"L23312","DOI":"10.1029\/2006GL027795","article-title":"Earthquake magnitude estimation from peak amplitudes of very early seismic signals on strong motion records","volume":"33","author":"Zollo","year":"2006","journal-title":"Geophys. Res. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1007\/BF02479833","article-title":"Markovian representation of stochastic processes and its application to analysis of autoregressive moving average processes","volume":"26","author":"Akaike","year":"1974","journal-title":"Ann. Inst. Stat. Math."},{"key":"ref_26","first-page":"261","article-title":"PhaseNet: A deep-neural-network-based seismic arrival-time picking method","volume":"216","author":"Zhu","year":"2018","journal-title":"Geophys. J. Int."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/12\/4534\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:32:36Z","timestamp":1760139156000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/12\/4534"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,16]]},"references-count":26,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2022,6]]}},"alternative-id":["s22124534"],"URL":"https:\/\/doi.org\/10.3390\/s22124534","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2022,6,16]]}}}