## 2 Data and Methods
### Method  
It is widely known that the ionospheric environment is easily influenced by a geomagnetic storm that mainly originates from solar activity. Thus, the relatively weak seismic precursors could be submerged by such powerful space weather disturbances [18,21]. Therefore, it is necessary to check the space weather conditions before looking for eventual seismic information. The satellite data recorded under the geomagnetic indexes Kp exceeded 3 or the Dst index lower than \(-30\) nT were carefully examined to minimize the anomalous interference likely excited by strong geomagnetic activity. Moreover, the observation results affected by the satellite control experiments were also excluded, according to the satellite platform's data quality flags and information.  
Based on previous studies [23], the orbits from the CSES-01 flying over the epicenters \(\pm 10^{\circ}\) in longitude and latitude were chosen about 30 days before the EQs occurrence in these cases, as presented in Figure 3. Among these data, only those from ascending orbits (the satellite passed through the study areas around LT 2:00 a.m.) were used in this research, considering that the ionospheric environment of descending orbits (in the daytime) was strongly affected by the variations of the solar radiation [18].  
Figure 2: The space weather index from August to October 2018. From top to bottom: (**a**) the space weather index for August 2018, (**b**) the space weather index for September 2018, and (**c**) the space weather index for October 2018. The red vertical lines represent the times of four strong EQs.  
According to long-term data processing and previous analysis results, plasma values vary significantly in different regions, while the disturbance caused by the EQ is relatively small [20]. In addition, considering there is only one satellite, its observation ability is limited in spatial and time resolutions, considering the distance between adjacent tracks in one day is about 2600 km. Therefore, it is not recommended to analyze the seismo-ionospheric disturbances in large areas, which may mix with other disturbance phenomena induced by other factors. In this research, we have monitored the critical areas for a long time, checked the relative abnormal changes of multiple plasma parameters through the revisiting orbit quartile analysis method, and then extracted the seismic anomalies.  
Furthermore, considering that there are numerical deviations in the absolute values of \(No^{+}\) and \(V_{z}\) and their relative variations were reliable, we did not use their absolute values directly in the analysis in Section 3, but normalized them, i.e., firstly, we calculated the maximum values of \(No^{+}\) and \(V_{z}\) in the region of the latitude range shown in the figures, and then divided the observations by the maximum values in order to obtain their relative change states. In this way, we will focus on their relative variations during the seismic anomaly analysis process rather than their absolute values. Moreover, we compared the simultaneous variations of multiple parameters, such as \(No^{+}\), \(V_{z}\), \(Ne\), \(Te\), and electric field waveform, to ensure the accuracy of seismic anomaly information extraction.