## 1 Introduction  
Earthquake prediction is a complex and challenging theme. Since scientists discovered pre-seismic infrared abnormal phenomena in the 1980s [1], scholars around the world have undertaken various relevant research. [PERSON] et al. put forward a relatively reasonable theoretical mechanism, which indicates that the main causes of the abnormal temperature increase before the earthquake are gases released from the earth's crust and the change of the electric field, based on various observations and experiments [2]. The change of water content in the earth's surface soils is also able to cause infrared anomalies before earthquakes [3]. Some experiments proved that the infrared radiation of the rock changes when it is pressed by stress [4]. Their studies provide theoretical support for the development of earthquake prediction using infrared radiation data. Infrared remote sensing images have a definite advantage of wide-field and continuous observation over ground-based observation and are widely applied to earthquake prediction [5, 6, 7, 8]. Most researchers only analyzed single-type data, mainly using long-wave infrared radiation or its products, such as land surface temperature (LST) and outgoing long-wave radiation (OLR) [9, 10, 11]. In some case studies, the pre-seismic infrared anomaly is discovered from remote sensing images as a common phenomenon [12, 13, 14]. There are only a few studies about the middle-wave infrared anomalies before earthquakes, whose trend is similar to the anomalies in the long-wave channel [5, 15]. Other earthquake case studies found that there are abnormal changes in water vapor content in the atmosphere before and after the event [16, 17]. Most infrared data used to predict earthquakes are from NOAA satellites, Terra/Aqua satellites and Fengyun satellites [18; 19]. [PERSON] et al. found the infrared anomalies before the Ms8.0 earthquake in Sichuan, China, using single-channel images from the FY-2C satellite [20]. [PERSON] et al. found the anomalies before several strong earthquakes in Xinjiang, China, using OLR data from NOAA satellites and the FY-2D satellite [21]. [PERSON] et al. found the infrared anomaly associated with the 2017 M6.5 Jiuzhaigou earthquake from the data of two Fengyun satellites (FY-2E and FY-2G) [22]. Researchers have proposed different methods that were successfully used to extract pre-seismic anomalies, such as robust satellite techniques [23], interquartile, wavelet transform, Kalman filter methods [24], power spectrum [25] and some artificial intelligent methods [26]. Although abundant remote sensing data and advanced information processing technologies are used to predict earthquakes, there has not been any stable and valid algorithm to eliminate the influence of non-seismic factors, such as seasonal changes, weather conditions and human activities [18]. This is because of the complexity and variability of the earth system and the space environment. As a result, most methods merely work well in a few cases, lacking statistical evidence. Some statistical results in a small region show that there is an infrared anomaly before most earthquakes, but they did not analyze the proportion of the anomalies followed by an earthquake. In a study of 20 earthquakes in the Tibet region, the anomalies of the brightness temperature appeared before 17 earthquakes, and that of long-wave radiation appeared before 16 earthquakes [27]. The accuracy of earthquake prediction is unable to be estimated without PPV. Some statistical studies show a low positive predictive value (PPV). The statistical results based on the robust satellite techniques indicate the true positive rate (TPR) is high but the PPV of pre-seismic infrared anomalies, which is 25.9% in Sichuan province, is too low to put into practice [28]. The accuracy of earthquake prediction in the statistics by [PERSON] and [PERSON] is 6.01% [29]. The PPV calculated by [PERSON] et al. is 7.61% [23]. This means that most prediction results are wrong.