Pre-Seismic Anomaly Detection from Multichannel Infrared Images of FY-4A Satellite

Abstract

Research of seismic infrared remote sensing has been undertaken for several decades, but there is no stable and effective earthquake prediction method. A new algorithm combining the long short-term memory and the density-based spatial clustering of applications with noise models is proposed to extract the anomalies from the multichannel infrared remote sensing images of the Fengyun-4 satellites. A statistical analysis is used to validate the correlation between the anomalies and earthquakes. The results show that the correlation rate is 64.29%, the hit rate is 68.75%, and the probability gain is about 1.91. In the Madoi and YangBi earthquake cases, the infrared anomaly detected in this paper is correlated with the TEC anomaly found in the previous research. This indicates that it is feasible to combine multi-source data to improve the accuracy of earthquake prediction in future studies.

Early Detection of Earthquakes Using IoT and Cloud Infrastructure: A Survey

“…Radio-frequency identification, satellite systems, the Internet of Things (IoT), network functions virtualization (NFV), 5G, software-defined networks (SDN), data networks, and a variety of other technologies have all been the focus of significant research in recent years in an effort to lessen the damage that earthquakes cause [26][27][28][29][30][31][32][33][34]. For instance, satellite systems have been used to track earthquake movements, and IoT sensors have been used to detect earthquakes and provide early warnings.…”