Analysis Of Seismic Thermal Anomaly Based On Multi-Source Remote Sensing Data At Different Spatial And Temporal Scales

China is one of the countries with the most serious earthquake disasters in the world.Earthquake prevention and disaster reduction is an important cause in China.It is very important to strengthen earthquake scientific research.Satellite infrared remote sensing technology has many advantages,such as continuous data,all-weather,large coverage,and so on.To a great extent,it makes up for the lack of conventional ground observation.In recent years,the research on the theory and method of seismic stereoscopic observation and prediction based on satellite remote sensing has become the development frontier in the field of international observation,and has attracted extensive attention at home and abroad.A large number of studies have proved that thermal infrared remote sensing is a promising earthquake prediction method.Many achievements have been made in earthquake monitoring and prediction based on satellite thermal infrared remote sensing technology.Seismic infrared remote sensing has formed a multi parameter,multi method,multi space-time research system,but there are still a lot of problems to be further studied.At present,thermal infrared research mainly involves brightness temperature,land surface temperature,outgoing longwave radiation,etc.in addition to these infrared parameters,atmospheric temperature,latent heat flux and other parameters can also be used to study seismic thermal anomalies,and good research results have been achieved.The physical meanings of various parameters are different,and the time and space scales are different.The thermal infrared anomalies extracted by different parameters have different characteristics,and the anomaly characteristics also have certain correlation.In order to effectively extract the thermal infrared anomaly information related to earthquakes,more and more anomaly extraction algorithms have been proposed according to different thermal infrared Parameters and different mathematical and physical methods.There are mainly anomaly extraction algorithms based on difference analysis,background field analysis and signal analysis.The anomaly information reflected by different algorithms is different.This paper selects typical strong earthquakes in Chinese Mainland in recent 20 years,uses MODIS land surface temperature data,NOAA outgoing long wave radiation data and satellite remote sensing data,and uses RST algorithm,vorticity background field algorithm,diathermy index and anomaly value to extract seismic thermal infrared anomalies from different time scales,and extract surface thermal information related to tectonic activities.Different algorithms are suitable for different data and time scales.The seismic thermal infrared anomalies extracted by different algorithms are compared and analyzed.The extracted anomaly features are systematically combed and evaluated,and the applicable data and time scales of each algorithm are summarized.Select the appropriate algorithm and use the remote sensing data of different spacetime scales to extract the thermal anomaly comprehensively.Carry out the application in the demonstration area,analyze the thermal infrared anomalies extracted from the demonstration area,and summarize the regularity of anomalies from different data sources at different time and space scales.Combined with the previous research on seismic infrared remote sensing,the anomaly discrimination methods are summarized and applied in the demonstration area.Through the inspection,44 anomalies were detected in the southern Xinjiang and Sichuan Yunnan demonstration areas,of which31 were corresponding to earthquakes above M ? 5.0,13 were false alarms,and 15 were missed.There were a large number of corresponding earthquakes,with an accuracy rate of 70%,and the inspection effect was good.The retrospective test results in Sichuan and Yunnan regions show that the number of abnormal intervals extracted from multi-source remote sensing data is reduced by 8 and the false alarm rate is reduced by 24% compared with single data.The research results of this paper enrich the methods of extracting seismic anomaly information,provide support for the discrimination of seismic thermal infrared anomaly at multi-temporal and spatial scales,and have certain significance for the monitoring of seismic thermal infrared anomaly.