Study On Seismic Thermal Infrared Algorithm And Characteristics Based On Satellite Remote Sensing Retrieval

China is one of the countries with most serious earthquake disasters,and the death toll of the earthquake disasters accounted for 54%of the total number of natural disasters since the founding of the People's Republic of China.Seismic activity of China has the characteristics of wide distribution,high frequency,high intensity,shallow source and heavy disaster.It is of great significance to strengthen the research of earthquake monitoring and forecasting.Satellite observation has merits of wide range and unlimited with natural conditions,which makes up for the lack of ground observation,and has important research significance in obtaining seismic anomaly information.Ground heat anomalies before strong earthquakes have been concerned by seismologists for long time.Especially the former Soviet Union scholar found thermal infrared anomalies before the earthquakes in Asia and the Eastern Mediterranean region using NOAA satellite brightness temperature data in the 1980s.Then the domestic and foreign scholars have studied thermal infrared anomalies of earthquake by satellite parameters,which are brightness temperature,longwave radiation,surface temperature,latent heat flux and NCEP data etc.In order to maximize the extraction of thermal infrared anomaly information,more and more exception extraction algorithms are proposed.The research of thermal infrared satellite in earthquake has gradually developed into one of the promising technologies in earthquake prediction research field.The key of the prediction of earthquakes using thermal infrared remote sensing is to obtain the precursory anomalies and their temporal and spatial evolution characteristics related to earthquakes.However,the influence factors of thermal infrared radiation are numerous and complex,and the thermal changes caused by various factors are difficult to be separated.In order to detect the thermal anomaly caused by seismic activity,it is necessary to study the non-seismic factors which affect the surface thermal infrared radiation.The main factors of thermal infrared radiation were summarized on the basis of analysis of previous studies in this paper.These factors include topography,ground type,meteorological change,geothermal heat and gas change,etc.then which were quantitatively analyzed.Especially,the effects on infrared radiation of three kinds of gases,water vapor,carbon dioxide and methane,are simulated by using MODTRAN,radiative transfer simulation software.It is considered that the terrain is the basic factor to control the spatial distribution of surface temperature in a region,mainly including elevation and aspect,and terrain factor is relatively stable.The terrain of a region usually does not change over a period of time.Meteorology is the most complex factor of infrared radiation,and its change is almost random.For gas factors,water vapor has a greater influence on infrared radiance,and CO₂ and CH₄ have less influence on infrared radiance.The vorticity algorithm was improved and a new anomaly exponential algorithm was proposed for different types of data sources after analyzing and summarizing the current thermal infrared anomaly extraction algorithm based on the study of the influencing factors of infrared radiation.?1?For the surface temperature data,the basic idea of the improved vorticity algorithm is as follows:firstly,the RST anomaly information extraction is carried out on the surface temperature data?LST?,mainly focusing on the use of background information,and then the vorticity algorithm operated using the obtained results by RST in order to obtain the surface temperature anomaly highlight the geographical location of information;?2?For the long-wave radiation data,the basic idea of the anomaly index algorithm is as follows:firstly,The RST anomaly information extraction operation is carried out based on the mean and standard deviation on same location using long time data,focusing on background information extraction in this process;then the data before and after the earthquake for a period of time were calculated using the vorticity algorithm,paying attention to extract the relative temperature of different locations at the same time in this step;Finally,the value obtained from RST abnormal algorithm is multiplied with the value got from vorticity algorithm,the new value was defined the abnormal index to represent the infrared anomaly.Based on the MODIS surface temperature,the improved vorticity algorithm was used to analyze the seismic thermal infrared anomaly of 40 earthquakes above M5.5 in China and surrounding areas between 2007 and 2015.The results showed that 18 cases had obvious anomalies before the earthquakes,accounting for 45%,6 cases had anomalies after the earthquakes,accounting for 15%,no obvious abnormal information were detected before and after the earthquakes the rest 40%cases.The infrared anomaly proportion of surface temperature is different for different magnitudes earthquakes;therefore,it is believed that the surface temperature anomalies before earthquakes are related to the magnitude of earthquakes.At the same time,it is found that the proportion of abnormal surface temperature in different regions is different,especially more surface temperature anomalies were found in Sichuan and Yunnan.It is indicated that the application of surface temperature to thermal infrared monitoring before earthquake has certain regional applicability.The proportion of surface temperature anomaly of earthquake is different for different earthquake focal mechanism;it is considered that thermal infrared anomalies are related to the mechanism of earthquakes.The probability of surface temperature anomalies before earthquakes is relatively high for strike slip faults and reverse faults.In order to verify the applicability of surface temperature anomaly,we used improved vorticity algorithm to study temperature characteristic of 40 assumed earthquakes by changing occurrence year of earthquakes on same location and date.The results showed that eight earthquakes occurring surface temperature anomalies accounting for 20%.And we study Nepal and the Wenchuan earthquake infrared characteristics between 2007 with 2015,three year anomalies were found for all two earthquakes,and one of these corresponds to the real earthquake.Taking the Nepal earthquake in 2015 as an example,the proposed anomaly index algorithm is used to preferably extract the infrared anomalies several days before the earthquake.We analyzed the temporal and spatial variations of outgoing long wave radiation?OLR?obtained from satellite observations around the occurrence time of the two earthquakes using RST and anomaly index algorithms.The Meteorological satellite data we used include night-time data?once dilly?from the polar orbit NOAA/AVHRR and three hours data?8 times dilly?of the Chinese geostationary satellite FY-2D.The results show that RST algorithm provides no anomalous solutions around the epicenter of two earthquakes.In comparison the infrared anomaly index algorithm did provide anomaly detection,and specifically we found an increase of emitted infrared radiation in west region of the M_S8.1 earthquake epicenter on April 15th 2015.The thermal anomaly derived from NOAA data reached the maximum value on April 24 at 100kilometers west of the M_S8.1 earthquake epicenter,and then disappeared gradually.In addition another thermal anomaly was detected on May 10 at 200 kilometers east of the M_S7.5 earthquake epicenter.Based on three-hour data analysis from FY-2D,we found on April 24 a dynamic evolution in the anomalous process,the same day when the NOAA data thermal anomaly reaches the maxim.In this case FY-2D satellite data provided complimentary data to the initial detection based on low temporal/spatial resolution obtained from NOAA and does improve overall the final solution in the location of the anomaly.Our initial results suggest that systematic use of multi-orbit satellite observation can provide reference to monitor the pre-earthquake changes of thermal radiation.At the same time,the improved vorticity algorithm is used to identify the infrared anomalies before the Nepal earthquake.The vorticity and improved vorticity algorithm were used to analyze the change of the surface temperature characteristics for M_S 8.1 and M_S 7.5 Nepal earthquake in2015 based on 5.6km surface temperature retrieval from the polar orbiting MODIS satellite.Then the results of vorticity algorithm and the improved vorticity algorithm are compared and analyzed.The improved vorticity algorithm can preferably identify the infrared anomaly near the earthquake epicenter prior to the earthquake.The thermal anomaly derived from MODIS LST data reached the maximum on April 27 at 100 kilometers northwest of the M_S8.1 earthquake epicenter,and then disappeared gradually.In addition another thermal anomaly was detected on May 12 at 100kilometers southwest of the M_S7.5 earthquake epicenter.The location of the two anomalies is about 100km from the epicenter;it shows that the improved vorticity algorithm has a certain indication for the location of strong earthquakes.