An analyst-created, high-resolution seismic arrival time dataset for evaluating machine learning phase detectors

This data set contains phase arrival times and phase labels for one hour of continuous seismic data recorded at the three-component broadband station WY.YNR on 2014 30 March from 13:00:00 to 14:00:00 UTC. This hour of data follows a M_w 4.8 occurring at 12:34 UTC in the Yellowstone region and contains many small events close together in space and time. All 687 picks (404 P and 283 S) were made by a seismic analyst trained at the University of Utah Seismograph Stations. The goal was to pick as many reasonable arrivals as possible for evaluating the performance of machine-learning-based phase detectors on continuous data during high seismicity rates. Phase picks were made using the Seismic Analysis Code (SAC; Goldstein and Snoke, 2005) and Pyrocko (Heimann <em>et al</em>., 2017). In general, a 1 to 17 Hz bandpass filter was used. The csv file contains the pick id, phase arrival time in UTC and Unix epoch formats, and the phase labels (P or S).本数据集包含2014年3月30日协调世界时（UTC）13:00:00至14:00:00期间，三分量宽频台站WY.YNR记录的1小时连续地震数据的震相到时及时相标签。该时段数据采集于协调世界时12:34黄石地区发生M_w 4.8级地震之后，记录了诸多时空分布密集的小型地震事件。本次共标注687个震相到时（其中P波到时404个，S波到时283个），均由犹他大学地震台站培训的地震分析师完成。本数据集的标注目标为尽可能多地标记可靠震相到时，用于评估高地震活动率场景下，基于机器学习的震相检测算法在连续地震数据中的表现。震相到时标注采用地震分析代码（Seismic Analysis Code, SAC; Goldstein和Snoke, 2005）以及Pyrocko（Heimann等人, 2017）完成。整体而言，数据处理时采用了1至17 Hz的带通滤波器。本数据集的CSV文件包含标注ID、协调世界时与Unix时间戳格式的震相到时，以及震相标签（P波或S波）。