2026-04-13T07:36:22Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/3911352026-01-21T06:07:00Zcom_2072_1033col_2072_452950

00925njm 22002777a 4500 dc Boudriki Semlali, Badr Eddine author Molina Ordóñez, Carlos author Hyuk, Park author Camps Carmona, Adriano José author 2023-02-17 Every year, earthquakes cause thousands of casualties and high economic losses. For example, in the time frame from 1998 to 2018, the total number of casualties due to earthquakes was larger than 846 thousand people, and the recorded economic losses were about USD 661 billion. At present, there are no earthquake precursors that can be used to trigger a warning. However, some studies have analyzed land surface temperature (LST) anomalies as a potential earthquake precursor. In this study, a large database of global LST data from the Geostationary Operational Environmental Satellite (GOES) and AQUA satellites during the whole year 2020 has been used to study the LST anomalies in the areas affected by earthquakes. A total of 1350 earthquakes with a magnitude larger than M4 were analyzed. Two methods widely used in the literature have been used to detect LST anomalies in the detrended LST time series: the interquartile (IQT) method and the standard deviation (STD). To the authors’ knowledge, it is the first time that the confusion matrix (CM), the receiver operating characteristic curve (ROC), and some other figures of merit (FoM) are used to assess and optimize the performance of the methods, and to select the optimum combination that could be used as a proxy for their occurrence. A positive anomaly was found a few days before the studied earthquakes, followed by the LST decrease after the event. Further studies over larger regions and more extended periods will be needed to consolidate these encouraging results. This work was sponsored by project “GENESIS: GNSS Environmental and Societal Missions—Subproject UPC”, Grant PID2021-126436OB-C21, sponsored by MCIN/AEI/10.13039/501100011033/ and EU ERDF “A way to do Europe”. Badr-Eddine Boudriki Semlali received support in the form of an FI grant: 2021 FI_B 00471 from Generalitat de Catalunya—FI AGAUR 2021. Peer Reviewed Postprint (published version) Àrees temàtiques de la UPC::Enginyeria de la telecomunicació Earthquakes Deep learning Big data LST Time series Anomalies Earthquake precursors Big data analysis Terratrèmols Aprenentatge profund Dades massives First results on the systematic search of land surface temperature anomalies as earthquakes precursors