Traditional fluxgate sensors used in geomagnetic field observations are large, costly, power-consuming and often limited in their use. Although the size of the micro-fluxgate sensors has been significantly reduced, their performance, including indicators such as accuracy and signal-to-noise, does not meet observational requirements. To address these problems, a new race-track type probe is designed based on a magnetic core made of a Co-based amorphous ribbon. The size of this single-component probe is only Φ10 mm × 30 mm. The signal processing circuit is also optimized. The whole size of the sensor integrated with probes and data acquisition module is Φ70 mm × 100 mm. Compared with traditional fluxgate and micro-fluxgate sensors, the designed sensor is compact and provides excellent performance equal to traditional fluxgate sensors with good linearity and RMS noise of less than 0.1 nT. From operational tests, the results are in good agreement with those from a standard fluxgate magnetometer. Being more suitable for modern dense deployment of geomagnetic observations, this small-size fluxgate sensor offers promising research applications at lower costs.

Extracting weak seismic-magnetic signals from strong electromagnetic backgrounds has always been an important part of seismic-electromagnetic research. Based on the data of D/H/Z components measured through a three-axis ring-core-type fluxgate magnetometer in GLM (Geermu), JYG (Jiayuguan), and KSH (Kashi) observatories, we analyzed geomagnetic signals as precursors to some earthquakes in China using the polarization method. The most effective main frequency of seismic-electromagnetic emission was determined according to the skin effect. The results showed that only 5 out of 37 earthquakes were found to have probable signals of seismomagnetic anomalies before them. Further research revealed that the significant enhancements of polarization ratios of Y_ZH and Y_ZG (Y_ZH, the spectral power ratio of Z to H and Y_ZG, the spectral power ratio of Z to G) occurred five days prior to the Jinta earthquake (M_s 5.4) and continued for about two months. The polarization ratio of Y_ZH reached an abnormally high value about one month before some earthquakes (M_s 7.4, M_s 6.7, M_s 6.7) near the KSH station and lasted for about one week to half a month, then returned to the normal value. Similarly, some enhancements of polarization ratios of Y_ZH and Y_ZG occurred two months before the Haixi earthquake (M_s 5.0) and lasted for about one month. Analysis results showed that the enhancements prior to earthquake events may be closely related to the Jinta earthquake and a series of earthquakes near the KSH station; however, the high value of Y_ZH and Y_ZG in GLM station had nothing to do with the Haixi earthquake.

Studying the temporal and spatial evolution trends in earthquakes in an area is beneficial for determining the earthquake risk of the area so that local governments can make the correct decisions for disaster prevention and reduction. In this paper, we propose a new method for analyzing the temporal and spatial evolution trends in earthquakes based on earthquakes of magnitude 3.0 or above from 1980 to 2019 in California and Nevada. The experiment’s results show that (1) the frequency of earthquake events of magnitude 4.5 or above present a relatively regular change trend of decreasing–rising in this area; (2) by using the weighted average center method to analyze the spatial concentration of earthquake events of magnitude 3.0 or above in this region, we find that the weighted average center of the earthquake events in this area shows a conch-type movement law, where it moves closer to the center from all sides; (3) the direction of the spatial distribution of earthquake events in this area shows a NW–SE pattern when the standard deviational ellipse (SDE) method is used, which is basically consistent with the direction of the San Andreas Fault Zone across the north and south of California; and (4) the spatial distribution pattern of the earthquake events in this region is found to be clustered using the global spatial autocorrelation analysis method. This study provides a new perspective for the exploration of the temporal and spatial evolution trends in earthquakes and understanding the earthquake risk in an area.