Satellite remote sensing in earthquake prediction. A review

Abstract

Sudden, violent movement of the earth's surface resulted of the release of energy into the atmosphere can destroy cities and claim lives. With the recent advances in space-borne data collecting methods which have made it possible monitoring the earth surface with different sensors, scientists are now able to better study the causes and signs of Earthquakes. Current researches are moving in the direction of pre-earthquake deformation detection. In order to make successful prediction all the related data must be collected from different space-borne sensors and ground-based stations. Past earthquakes should also be investigated for any phenomena that can occur before an earthquake. Surface deformation data are provided by GPS and SAR imaging, land surface temperature changes by ASTER, Landsat TM and ETM, different types of cloud studies using MODIS and Seawifs data, electromagnetic and ionosphere anomalies by ground passive stations and radon gas emissions in the faults areas by solid on the ground detectors. In this paper we tried to gather complete and helpful information of earthquake precursors which have been studied until now.

Application of Artificial Intelligence in Predicting Earthquakes: State-of-the-Art and Future Challenges

“…Content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2020.3029859, IEEE Access [9] reviewed earthquake researches till 1997 2007 [10] criticized different seismo-electromagnetic precursor-based researches for scientific value 2009 [11] reviewed short-term earthquake prediction researches based on seismo-electromagnetic signals 2009 [12] reviewed earthquake precursor -based researches and the satellites monitoring these precursors 2009 [13] reviewed researches focusing animal behavior before earthquake 2011 [14] reviewed earthquake prediction researches based on space & ground-based sensors 2012 [15] reviewed 19 journals focusing earthquake prediction using NN & data mining approaches 2014 [16] presented a brief review of earthquake prediction studies based on NN, Fuzzy logic, & bio-inspired algorithms 2015 [17] reviewed radon gas concentration-based researches 2017 [18] reviewed earthquake precursor-based researches in China 2018 [19] reviewed data mining techniques-based studies for natural disasters 2019 [20] reviewed ML trends in earthquake 2019 [21] reviewed DL-based researches & future trends 2019 [22] reviewed NN & DNN-based earthquake prediction studies II, the works related to this study are discussed. Section III discusses the working principle of the most common AI algorithms.…”

“…They pointed out that this electric signal should not be considered as earthquake precursors. Alvan and Azad [14] reviewed earthquake prediction researches based on space-based and ground-based sensors covering most of the earthquake precursors. They divided the studies based on the different precursors like earth's crust, temperature, strange cloud formation, humidity, and Radon gas concentration.…”

Assessment of Building Damage in Raqqa during the Syrian Civil War Using Time-Series of Radar Satellite Imagery

“…Remote sensing has proven to be a valuable source of information for the mapping of natural hazards and disasters (Joyce et al, 2009). Applications include the aftermath of single events, such as floods (Klemas, 2015), landslides (Scaioni et al, 2014) or earthquakes (Tronin, 2006), and the long-term monitoring of continuous phenomena, such as tectonic or geomorphologic movement (Alvan & Azad, 2011), air pollution (Martin, 2008) or ecosystem degradation (Xie et al, 2008) The possibility of accessing large image archives is especially helpful for the assessment of changes over long time periods. In this context, the temporal resolution of a sensor can become more important than its spatial resolution, because it allows both the clear identification of the date of occurrence of an event and the detailed monitoring of subtle changes (Lazecky et al, 2017;Gernhardt & Bamler, 2012) Earth observation (EO) using multi-spectral imagery is often constrained by cloud cover and shadows (Wulder et al, 2008;Giles, 2001;Pearce, 1985).…”

Estación de Sensado para Emisiones de Campo Magnético a Frecuencias Extremadamente Bajas y su Aplicación en la Predicción de Sismos

“…[2] [3]. Algunas hipótesis sugieren vincular estos fenómenos con la trituración de rocas cristalinas [4] [5], ya que podría considerarse cierto tipo de efecto piezoeléctrico generado por el desplazamiento o intensas presiones entre las rocas, principalmente aquellas con altos contenidos de cuarzo.…”