Seismic monitoring is a very important and challenging task. The continuous development of remote sensing technology has strengthened our ability to monitor the Earth’s surface on a macro scale. Research shows that an abnormal rise in surface temperature usually occurs before an earthquake, so a variety of anomaly extraction algorithms have been applied to the study of seismic thermal anomalies. Among them, the extraction method based on background field is widely used because of its strong mechanism interpretation. However, the previous anomaly methods based on the background field mainly limit the background field to a certain fixed threshold value, and ignore the small range of normal LST fluctuations caused by external factors(non-seismic). Therefore, a method of constructing a seismothermal infrared background field based on GPR-LSTM is proposed in this paper. The main idea of the method is that the LST background field is obtained by adding the established annual variable reference field and the fluctuation range of normal LST. First, the LST exhibits a range of fluctuations due to non-seismic factors such as solar radiation, weather, and human activities. Therefore, it is not reasonable to take a fixed value of the LST background field but it should have a certain fluctuation range. Therefore, the dynamic fluctuation characteristics of the background field should be reflected in the construction process of the background field in this study. Secondly, the reason why this method uses the LSTM model to predict the annual variable reference field of the earthquake period based on the annual variable reference field of the non-earthquake period is that on the one hand, the LSTM model can predict the law of long time series data, so it can better learn the annual variation law of LST in the non-earthquake year. At the same time, the LST trend of increasing or decreasing year by year caused by climate change can be predicted, which is conducive to more truly describing the LST trend of the real background field in the year of the earthquake period.
The method includes two parts: the establishment of the annual variable reference field, the calculation of the residual fluctuation range of the actual LST and the construction of the background field. Based on the MODIS surface temperature product, the precursory thermal anomaly information of the 2008 Wenchuan earthquake in Sichuan Province and the Yutian earthquake in Xinjiang Province was extracted and analyzed by using the proposed method. Based on the MODIS surface temperature data of the 2008 Wenchuan earthquake in Sichuan Province and the Yutian earthquake in Xinjiang Province, the proposed method is used to detect and analyze the thermal anomalies before the earthquake. The following conclusions are drawn:
(1)The established LST background field on the Qinghai-Xizang Plateau is consistent with the actual variation law of LST and is relatively stable on the whole. In the time dimension, the background field of LST shows the annual variation of high summer and low winter. In terms of spatial dimension, the established LST background field is generally high in the south, low in the middle and low in the north, and the temperature value of the background field is the lowest at the highest altitude of the Qinghai-Xizang Plateau.
(2)The thermal anomalies obtained based on the new algorithm are usually distributed along the fault zone of the Qinghai-Xizang Plateau, and the anomaly evolution law is obvious. For the Yutian earthquake in Xinjiang, the trend of thermal anomalies is consistent with that of the fault zone in most cases, and the thermal anomalies are mainly distributed in the northern margin of the fault zone. For the Wenchuan earthquake in Sichuan Province, with the onset time approaching, the thermal anomalies gradually moved southward along the Longmenshan fault zone from the north margin, filled the entire fault zone before the earthquake, and disappeared after the earthquake. This proves the validity of the proposed background field construction method.
(3)Compared with non-seismic years, the spatial characteristics of thermal anomalies along faults are more obvious in seismic years, and the duration and amplitude of the anomalies are longer. This indicates that the tectonic activity in seismic years is more active than that in non-seismic years, resulting in more significant abnormal warming of surface temperature.
(4)The evolution law of thermal anomalies of earthquakes with magnitude 7 or above on the Qinghai-Tibet Plateau can be summarized as incubation—disappearance—accumulation—disappearance—earthquake occurrence, and the strength of thermal anomalies appears in the way of repeated changes. This indicates that the thermal anomaly is not continuously enhanced or weakened before the earthquake but shows the characteristics of repeated fluctuations between strong and weak until the earthquake eruption thermal anomaly disappears.
In conclusion, the proposed method can not only ensure that the established background field is not affected by tectonic factors but also fully consider the small range of normal fluctuation of surface temperature caused by non-tectonic factors, which makes the extraction of thermal infrared anomaly information more accurate. This provides new technical means and ideas for the extraction of earthquake anomaly information and is helpful for the further development of earthquake monitoring.