halilugur/eqn_2020_analysis

Analysis of EQN detections between 2017-12-15 and 2020-01-31, particularly in Chile, USA and Italy

EQN detections between 2017-12-15 and 2020-01-31

Introduction

The 'Earthquake Network’ (EQN) is an app which detects earthquakes by creating an ad-hoc network of smartphones' accelerometer sensors and provides early warnings for earthquakes via the same smartphone app. Detections are not due to individual smartphone measurements but due to near-simultaneous trigger signals from clusters of smartphones running the app.

This analysis was conducted on detections by the EQN system between 2017-12-15 and 2020-01-31 in order to test it's performance and whether EQN detections are fast enough to provide early warnings of earthquakes to its users.

This dataset and analysis is a supplement to the article Bossu et al. "Shaking in 5 seconds!" A Voluntary Smartphone-based Earthquake Early Warning System (2021)

D1 - eqn_article_D1_usa_chl_ita.csv

This dataset contains the 550 detections made by EQN between 2017-12-15 and 2020-01-31 in Chile, USA and Italy. Each detection was associated with an earthquake from the parameter catalogue of each countries foremost seismic insitute (CSN for Chile, USGS for USA and INGV for Italy) wherever possible (initially automatically and also checked manually).

The csv file uses ',' separators and its first row contains the field headers. A description of each field is found in the table below.

D2 - eqn_article_D2_mag_gt_4.5.csv

This dataset contains 134 detections from around the world that could be associated to earthquakes (in the USGS earthquake parameter catalogue) with magnitude ≥ M5 or magnitude ≥ M4.5 in Italy and the USA. There are 68 detections that are common to the D1 dataset.

The csv file uses ',' separators and its first row contains the field headers. A description of each field is found in the table below. Note that this dataset doesn't have the final 16 fields described in that table

dataset description

Field	Description
peakid	Each EQN detection has a random 7 digit numeric id associated.
det_lat	Latitude where EQN detection occurred (degrees).
det_lon	Longitude where EQN detection occurred (degrees).
country	Country iso3166 code, one of {‘chl’,’usa’,’ita’}.
detectiontime	Date and time of EQN detection (Iso8166 format) (UTC time zone).
detectiontime_local	Localised date and time of EQN detection.
pytz	Time zone of EQN detection.
nighttime	Did EQN detection occur between 23h and 7h local time? (Boolean)
signals	The number of signals that caused the EQN detection to trigger.
actives	The number of active EQN apps within 30 km of the detection location.
felt_reports_green	Number of felt reports collected indicating 'green' within 3 min from detection and within a radius of 300 km.
felt_reports_yellow	Number of felt reports collected indicating 'yellow' within 3 min from detection and within a radius of 300 km.
felt_reports_red	Number of felt reports collected indicating 'red' within 3 min from detection and within a radius of 300 km.
notification_time	When the notification based on felt reports was sent to the Firebase notification service.
notification_delay_from_detection	Delay between detection and the notification.
Intensity_strong	If 1, a second alert for strong earthquakes was sent. The time of this second alert is the same of notification_time since it is based on the felt reports.
cat	Seismic catalogue used for earthquake parameters.
num_eq_matches	Number of potentially associated earthquakes in catalogue.
origintime	Date and time of associated earthquake in catalogue (UTC).
magtype	Type of magnitude for associated earthquake.
magnitude	Magnitude of associated earthquake in catalogue.
eq_lat	Latitude of associated earthquake in catalogue (deg).
eq_lon	Longitude of associated earthquake in catalogue (deg).
depth	Depth of associated earthquake in catalogue (km).
separation	Separation of EQN detection from epicentre of associated parameters.
detectiondelay	Delay between origintime and EQN detection (s).
P_at_surface_delay	Delay for P wave to reach the Earth’s surface (s).
offshore	Was earthquake offshore? (Boolean).
dist_shore	Distance from epicentre to closest point on the shore (km).
closest_land_lat	Latitude of point of coast closest to the epicentre (deg).
closest_land_lon	Longitude of point of coast closest to the epicentre (deg).
P_at_coast_delay	Delay for P wave to reach the closest point on the coastline (and at the surface) (s).
P_on_land_surface_delay	Delay for the P wave to read the surface (or the coast if applicable) (s).
detectiondelay_wrt_P	Delay between the P wave arriving at the EQN detection location and the detection time (s).
detectiondelay_wrt_S	Delay between the S wave arriving at the EQN detection location and the detection time (s).
causal_phase	Whether the EQN detection was estimated to have been caused by the P wave or the S wave.
intensity_at_0ld	The predicted intensity of the earthquake for the location of the S wave at the moment of the EQN detection.
intensity_at_5ld	The predicted intensity of the earthquake at locations with a lead time of 5 s with respect to the S wave at the moment of the EQN detection.
intensity_at_10ld	The predicted intensity of the earthquake at locations with a lead time of 10 s with respect to the S wave at the moment of the EQN detection.
intensity_at_15ld	The predicted intensity of the earthquake at locations with a lead time of 15 s with respect to the S wave at the moment of the EQN detection.
sm_net	The seismic network if strong motion accelerometer data was found nearby.
sm_sta	The station name if strong motion accelerometer data was found nearby.
sm_loc	The separation between the strong motion station and the EQN station (km).
sm_unit	One of {‘acc’,’vel’,’disp’} where acc is acceleration (m/s/s), vel is velocity (m/s) and disp is displacement (m).
sm_sta_lat	Latitude of strong motion station (deg).
sm_sta_lon	Longitude of strong motion station (deg).
sm_sta_elv	Elevation of strong motion station (m).
sm_sep_eqn_sta	Separation between EQN detection and strong motion station (km).
sm_strongest_motion	Strongest value recorded by station.
sm_strong_motion_time	Time of strongest motion (this already accounts for sm_dt_correction).
sm_strongest_motion_eqn_delay	Delay between strong motion and EQN detection (this already accounts for sm_dt_correction).
sm_dt_correction	Time correction (s) due to difference in distances of station and EQN detection from the epicentre. A velocity of 8 km/s is used to convert between distance and time.