Thermal Infrared Anomalies Research Articles

Thermal Infrared Anomalies Associated with Recent Crustal Earthquakes in Gorj County in Romania

Cumulative stress-energy in tectonic active regions associated with ongoing deformation (co-seismic stress) along the main active geologic faults manifests various earthquakes’ precursors. Macro-fracturing processes are preceded by micro-fracturing phenomena which amplify strain field, and geophysical fields’ disturbances like space-time anomalies of Earth’s fracto-emission signals (Thermal; Ionospheric; Electric Field; Acoustic; Radon in air, underground water, and soil; Neutron, etc.) registered months to days before the occurrence of earthquakes. Multispectral and multisensor time series satellite data and space-based geodetic (GPS and GNSS) measurements in synergy with ground-based geophysical/geochemical measurements bring a significant contribution to survey pre-earthquake signals in the tectonic active areas. This study aims to assess the role of seismo-induced thermal infrared (TIR) anomalies characterized by the ground-level air-AT and land surface temperature-LST changes as significant precursors of crustal moderate and strong earthquakes recorded in Gorj County, Oltenia region in Romania. North-West Targu Jiu area is an active tectonic area characterized by two strike-slip faults systems of North-West- South West and East-West orientation, where on 13 February 2023 was recorded a shallow strong earthquake of moment magnitude Mw= 5.2 and 17 km focal depth, followed by 14 February 2023 stronger earthquake of Mw = 5.7 and 6 km focal depth. Several months beyond have been recorded more than 1000 aftershocks of Mw ≤ 4.9. Based on MODIS Terra/Aqua and NOAA AVHRR time series data, some days to weeks before the seismic sequence has detected LST and AT anomalies.

Characterization of thermal infrared medium- and short-term anomaly information from block to fault in mainland China

The relationship between satellite thermal infrared anomalies and earthquakes or fault activity has been studied for more than 30 years. In this study, five strong earthquakes (the MS6.1 earthquake in Biru, Tibet; the MS7.4 earthquake in Madoi, Qinghai; the MS6.0 earthquake in Delingha, Qinghai; the MS6.1 earthquake in Lushan, Sichuan; and the MS6.8 earthquake in Luding, Sichuan) that occurred on the western mainland of China over the past 2 years were studied. Based on monthly MODIS land surface temperature (LST) data and daily NOAA satellite longwave radiation data, the departure algorithm and the Robust Satellite Techniques (RST) algorithm were used to extract and analyze the characteristics of thermal infrared anomaly information for blocks and faults around the earthquake from different temporal and spatial scales. The results showed the following: 1) In the medium-term scale study based on monthly data, blocks near the epicenters of five earthquakes showed temperature increase anomalies of 1–6 months before the earthquakes; the areas of temperature increase anomalies were clearly controlled by the spatial distribution of the blocks, and earthquakes mostly occurred within blocks with frequent temperature increase anomalies. 2) In the short-term, thermal infrared anomaly feature tracking based on daily data meant that obvious thermal anomalies were also found. The thermal anomalies before the five seismic events all appeared within a period of 3 months before the earthquake, and there were multiple consecutive days of anomalies. The significant temperature increases generally occurred a month before the earthquake, and the distribution of the anomalies was mostly in the form of strips, which is basically consistent with the trend of the fault zone. The use of thermal infrared remote sensing data to summarize the dynamic evolution of thermal infrared anomalies of blocks and faults before strong earthquakes can provide a basis for the long-term monitoring of fault activity and seismic monitoring by satellite thermal infrared technology.

Spatially variable model for extracting TIR anomalies before earthquakes: Application to Chinese Mainland

There are several long-term statistical researches using the Molchan diagram (MD) to prove the relation between thermal infrared (TIR) anomalies and earthquakes in different regions, however, these studies are flawed: 1) the original MD is based on the spatially uniform Poisson model, but it will offer wrong evaluations for inhomogenous systems with uneven spatial-temporal distribution of earthquakes; 2) some of these studies have de-clustered earthquake catalogs before applying MD, however, de-clustering will introduce ambiguities to final scores and it may also conceal the potential relation between precursors and the ‘removed’ events. Until now, we have to admit that the long-term statistical evidence for proving the correspondence between earthquake and TIR anomalies is still absent and the power of TIR anomalies for predicting earthquakes is limited. In this study, we use daily nighttime Outgoing Longwave Radiation (OLR) data provided by the National Oceanic and Atmospheric Administration (NOAA) to extract the TIR anomalies of Chinese Mainland (20°-54°N, 73°-135°E). The data from Jan. 2007 to Dec. 2010 is the training dataset to obtain the best parameters for extracting TIR anomalies and the best time-distance-magnitude (TDM) windows for determining the correspondence between earthquakes and TIR anomalies, and the data from Jan. 2011 to Dec. 2017 is the testing dataset. The new 3D Molchan diagram offers a score for each model with different parameters. Unlike the original MD that only deals with the rate of missed events and the size of warning space, the 3D Molchan diagram quantifies the errors including false alarms and missed predictions. We assume that the best parameters and TDM windows are spatially variable for different sub-regions, because the Signal/Noise ratio is spatially variable due to the different geological and meteorological backgrounds. Moreover, we construct a new probability prediction model based on non-seismic binary alarms. Results show that the TIR anomalies is strongly related to normal or reverse earthquakes with magnitude≥ 4.0, and the TIR anomalies caused by earthquakes should be persistent in space and time. Moreover, the spatially variable model is superior to the global invariant one. We succeed in transforming the non-seismic binary alarms into probabilistic predictions based on the TIR anomalies and Relative Intensity index, which is defined as the rate of past earthquakes occurring in each spatial cell. Moreover, our new probabilistic model is superior to the spatially inhomogeneous Poisson model. However, this new probability model is still naïve and weak, and needs to be improved in the future.

Characteristics of Thermal Infrared Anomalies during the Earthquakes in Wenchuan, Lushan in Ya’an and Jiuzhaigou

Satellite thermal infrared observation has advantages over other earthquake observation techniques. With MODIS remote-sensing images from the TERRA satellite, the thermal infrared brightness temperature difference variation rate was used to analyze the observation data prior to three Magnitude-7-and-above earthquakes along the fracture zone of Longmen Mountain, and the result showed that there were thermal infrared brightness temperature anomalies one to two months before these three Magnitude-7-and-above earthquakes, and the earthquakes took place along the boundaries of the area where the anomalies occurred. The observation data show that there have been five times of substantial anomalies in the study area, among which four times were correlated to earthquakes.

Statistical Correlation Analysis Between Thermal Infrared Anomalies Observed From MTSATs and Large Earthquakes Occurred in Japan (2005–2015)

AbstractThe literature often reports space–time relations between the abnormal variations of different kinds of nonseismological (i.e., geophysical, geochemical, and atmospheric) parameters and the occurrence of earthquakes. The integration of such observations with seismological ones could improve the quality of the seismic hazard assessment in the medium‐short term (months to days). Each considered parameter has, in principle, its capabilities to provide useful (and utilizable) information about seismic processes. Therefore, to define a system based on different observations, the first step is to estimate the informative contribution that each considered parameter could provide. In this paper, we will evaluate the potential of Significant Sequence of Thermal Anomalies (SSTAs). In particular, we adopted the broadly used Robust Satellite Techniques (RST) data analysis methodology to identify SSTAs over 11 years (June 2005 to December 2015) of nighttime satellite images acquired by MTSAT satellites over Japan. Aiming at reducing the false‐positive rate, we introduced and tested an innovative configuration of the RST, which is here presented. We executed a correlation analysis between SSTAs and Japanese earthquakes with MJMA ≥ 6 by applying suitable constraints concerning space, time, and magnitude. The analysis highlights (a) the occurrence of just 29 SSTAs in the 11‐year period of observation, (b) 18 SSTAs (i.e., 62%) occur in an apparent space–time relation to earthquakes, and (c) 13 of them occur before the quake. Results of the random test analysis, based on error diagrams, confirm a noncasual correlation between “RST‐based satellite thermal anomalies” and earthquake occurrences. In particular, for MJMA ≥ 6.5 earthquakes, probability gain is up to better than 4.3 as compared with the random guess.

Long-term statistical evidence proving the correspondence between tir anomalies and earthquakes is still absent

Recently, researchers have conducted long-term statistical studies to prove the correspondence between earthquakes and thermal infrared (TIR) anomalies. Upon obtaining relatively high true positive rates (TPR), it was concluded that TIR anomalies are closely related to earthquakes. However, the temporal-spatial clustering of earthquakes and overly large temporal-spatial windows will also contribute to high TPRs, and it is improper to correlate TIR anomalies with earthquakes without excluding these influences. In this paper, relevant studies will be tested according to the prior probability, random earthquake catalogs and Molchan diagram weighted by the Relative Intensity (RI) index. Our results show that the high TPR in the previous studies were caused by overly large determining windows, and the result was close to random guessing, which means that the extracted TIR anomalies make no contributions to predicting the timing, epicenter and magnitude of earthquakes. By comparing the original Molchan diagram and the Molchan diagram weighted by the RI index, we found that simply taking the fraction of space-time occupied by alarm may give a wrong evaluation for alarm. Moreover, long-term statistical evidence proving the correspondence between earthquakes and TIR anomalies in Greece and Taiwan are still absent.

Infrared Emission from rocks in the Thermal Infrared (TIR) window

Satellite data provide ground surface temperatures based on the intensity of the thermal infrared (TIR) emission. TIR anomalies that appear to be related to impending earthquake activity were first reported more than 25 years ago. They can reach 10–15 K. To account for such temperature anomalies, it has been widely assumed that, prior to major earthquakes, warm gases or radon are emanating from the ground around the future epicenter. Here a radically different explanation is presented based on the growing evidence that rocks in the Earth's crust contain peroxy defects in their constituent mineral grains. Peroxy defects consist of pairs of tightly coupled O− such as in O3Si-OO-SiO3. Upon application of stress the electrically inactive peroxy defects can break up, releasing highly mobile electronic charge carriers: defect electrons in the O2-sublattice, called positive holes, symbolized by h•. The h• are the electronic wave function associated with O− in a matrix of O2−. They have the remarkable ability to flow out of the stressed rock volume, spreading fast and far. At the Earth's surface the h• become trapped, preferentially at topographic highs. As they recombine, returning to the peroxy state, IR photons of specific energies are emitted in the Thermal Infrared (TIR) window. In laboratory and field experiments rocks were subjected to stress either by loading one end of a rectangular chunk of a black quartz-bearing diorite via a hydraulic press or by stressing granite boulders from the inside out via expanding BUSTAR cement in boreholes. The TIR emission was recording during the build-up of stress up to failure of the rocks. Principal components analysis and a novel application of fluctuation spectroscopy identified several previously unknown phenomena, in particular a series of TIR emission bands that are consistent with the radiative de-excitation of vibrationally “hot” states of peroxy bonds forming at the rock surface and to pink noise suggestive of electron/hole trapping like in semiconductors.

Atmospheric and ionospheric coupling phenomena associated with large earthquakes

This paper explores multi-instrument space-borne observations in order to validate physical concepts of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) in relation to a selection of major seismic events. In this study we apply some validated techniques to observations in order to identify atmospheric and ionospheric precursors associated with some of recent most destructive earthquakes: M8.6 of March 28, 2005 and M8.5 of Sept. 12, 2007 in Sumatra, and M7.9 of May 12, 2008 in Wenchuan, China. New investigations are also presented concerning these three earthquakes and for the M7.2 of March 2008 in the Xinjiang-Xizang border region, China (the Yutian earthquake). It concerns the ionospheric density, the Global Ionospheric Maps (GIM) of the Total Electron Content (TEC), the Thermal Infra-Red (TIR) anomalies, and the Outgoing Longwave Radiation (OLR) data. It is shown that all these anomalies are identified as short-term precursors, which can be explained by the LAIC concept proposed in [S. Pulinets, D. Ouzounov, J. Asian Earth Sci. 41, 371 (2011)].

Toward the development of a multi parametric system for a short-term assessment of the seismic hazard in Italy

With the aim to develop a multi-parametric system devote to improving our present capability to assess seismic hazard particularly in the short-medium term, the preliminary step is to identify those parameters that have demonstrated their non-casual relation with earthquake occurrences and whose anomalous variations can be associated to the complex seismic process. Since 80, fluctuations of Earth thermally emitted radiation, measured by satellite sensors in the Thermal InfraRed (TIR) spectral region, have been reported by several authors in some connection with the occurrence of earthquakes; they and can be considered as one of the possible parameters to include within a multi-parametric system. In this paper, the Robust Satellite Techniques (RST) approach has been exploited to highlight Significant Sequences of TIR Anomalies (SSTAs) possibly related to seismic events happened in Italy in the period June 2004 - December 2014. In particular, we evaluated the level of correlation between occurrence of earthquakes with M≥4 and RST-based TIR anomalies using two different spatial resolutions of MSG-SEVIRI (Meteosat Second Generation -Spinning Enhanced Visible and Infrared Imager) images. Results of the two RST analyses show that the 82% of the identified SSTAs does not disappear when downscaled spatial resolution SEVIRI TIR records were used. For both analyses, more than 60% of SSTAs is apparently in connection with the occurrence of M≥4 earthquakes; more than the 80% of them has tendency to anticipate the occurrence of earthquakes. Although about the 40% of SSTAs is not apparently related to documented seismic activity (false positives), results of random tests (i.e. Molchan’s error diagrams) indicate a non-casual correlation between SSTAs and earthquake occurrences. These results confirm that the parameter “RST-based satellite TIR anomalies” is one of the possible candidates to be included in a multi-parametric system for time-Dependent Assessment of Seismic Hazard (t-DASH).

Thermal Infrared and Ionospheric Anomalies of the 2017 Mw6.5 Jiuzhaigou Earthquake

Taking the 2017 Mw6.5 Jiuzhaigou earthquake as a case study, ionospheric disturbances (i.e., total electron content and TEC) and thermal infrared (TIR) anomalies were simultaneously investigated. The characteristics of the temperature of brightness blackbody (TBB), medium-wave infrared brightness (MIB), and outgoing longwave radiation (OLR) were extracted and compared with the characteristics of ionospheric TEC. We observed different relationships among the three types of TIR radiation according to seismic or aseismic conditions. A wide range of positive TEC anomalies occurred southern to the epicenter. The area to the south of the Huarong mountain fracture, which contained the maximum TEC anomaly amplitudes, overlapped one of the regions with notable TIR anomalies. We observed three stages of increasing TIR radiation, with ionospheric TEC anomalies appearing after each stage, for the first time. There was also high spatial correspondence between both TIR and TEC anomalies and the regional geological structure. Together with the time series data, these results suggest that TEC anomaly genesis might be related to increasing TIR.

A statistical analysis of TIR anomalies extracted by RSTs in relation to an earthquake in the Sichuan area using MODIS LST data

Abstract. Research in the field of earthquake prediction has a long history, but the inadequacies of traditional approaches to the study of seismic threats have become increasingly evident. Remote sensing and Earth observation technology, an emerging method that can rapidly capture information concerning anomalies associated with seismic activity across a wide geographic area, has for some time been believed to be the key to overcoming the bottleneck in earthquake prediction studies. However, a multi-parametric method appears to be the most promising approach for increasing the reliability and precision of short-term seismic hazard forecasting, and thermal infrared (TIR) anomalies are important earthquake precursors. While several studies have investigated the correlation among TIR anomalies identified by the robust satellite techniques (RSTs) methodology and single earthquakes, few studies have extracted TIR anomalies over a long period within a large study area. Moreover, statistical analyses are required to determine whether TIR anomalies are precursors to earthquakes. In this paper, RST data analysis and the Robust Estimator of TIR Anomalies (RETIRA) index were used to extract the TIR anomalies from 2002 to 2018 in the Sichuan region using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data, while the earthquake catalog was used to ascertain the correlation between TIR anomalies and earthquake occurrences. Most TIR anomalies corresponded to earthquakes, and statistical methods were used to verify the correlation between the extracted TIR anomalies and earthquakes. This is the first time that the ability to predict earthquakes has been evaluated based on the positive predictive value (PPV), false discovery rate (FDR), true-positive rate (TPR), and false-negative rate (FNR). The statistical results indicate that the prediction potential of RSTs with use of MODIS is limited with regard to the Sichuan region.

A New Algorithm for the Characterization of Thermal Infrared Anomalies in Tectonic Activities

The monitoring of earthquake events is a very important and challenging task. Remote sensing technology has been found to strengthen the monitoring abilities of the Earth’s surface at a macroscopic scale. Therefore, it has proven to be very helpful in the exploration of some important anomalies, which cannot be seen in a small scope. Previously, thermal infrared (TIR) anomalies have been widely regarded as indications of early warnings for earthquake events. At the present time, some classic algorithms exist, which have been developed to extract TIR anomaly signals before the onset of large earthquakes. In this research study, with the aim of addressing some of the deficiencies of the classic algorithm, which is currently used for noise filtering during the process of extracting tectonic TIR anomalies signals, a novel TTIA (tectonic thermal infrared anomalies) algorithm was proposed to characterize earthquake TIR anomalies using the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature dataset (MOD11A2). Then, for the purpose of determining the rule of the TIR anomalies prior to large earthquake events, the Qinghai-Tibet Plateau in China was chosen as the study area. It is known that tectonic movements are very active in the study area, and major earthquakes often occur. The following conclusions were obtained from the experimental results of this study: (1) The TIR anomalies extracted using the proposed TTIA method showed a very obvious spatial distribution characteristic along the tectonic faults, which indicated that the proposed algorithm had distinctive advantages in removing or weakening the disturbances of the atectonic TIR anomalies signals; (2) The seismogenic zone was observed to be a more effective observation scale for assisting in the deeper understanding and investigations of the mid- and short-term seismogenic and crust stress change processes; (3) The movement trace of the centroids of the TIR anomalies on the Tibetan Plateau three years prior to earthquake events contributed to improved judgments of dangerous regions where major earthquakes may occur in the future.

The impact of satellite sensor viewing geometry on time-series analysis of volcanic emissions

Abstract Time-series analysis techniques are being increasingly used to process satellite observations of volcanic gas emissions and heat flux, with the aim of identifying cyclic behaviour that could inform hazard assessment or elucidate volcanic processes. However, it can be difficult to distinguish cyclic variations due to geophysical processes from those that are artefacts of the observation technique. Here, we conduct a comprehensive investigation into the origin of cyclicity in volcanic observations by analysing daily, global satellite measurements of volcanic SO2 loading by the Ozone Monitoring Instrument (OMI) and thermal infrared anomalies detected by the Moderate Resolution Imaging Spectroradiometer (MODIS). We use a fast Fourier Transform (FFT) multi-taper method (MTM) to analyse multiple phases of activity at 32 target volcanoes, utilising measurements obtained from three NASA satellite instruments (Aura – OMI, Aqua – MODIS and Terra – MODIS), and identify a common cycle (period of ~ 2.3 days), which is not considered to be of volcanic origin. Based on the presence of this cycle in multiple satellite datasets, we attribute it to variations in viewing angle during the 16-day orbit repeat cycle of sun-synchronous satellites maintained in Low Earth Orbit (LEO). A 5-point averaging correction procedure is tested on satellite observations from Kilauea volcano, Hawaii, and is found to reduce the impact of higher frequency cycles and reveal the presence of longer-period geophysical signals. In addition to the identification of a signal common to different measurement techniques, an underlying cyclical pattern was found in the OMI SO2 observations (periods of ~ 7.9 and 3.2 days) generated by the OMI Row Anomaly (ORA). We conclude that identification of the presence and magnitude of non-geophysical cyclic behaviour, which can suppress natural cycles in time-series data, and implementation of appropriate corrections, is crucial for accurate interpretation of satellite observations. The use of data averaging to suppress non-geophysical cycles imposes limits on the length of natural cycles that can be confidently identified in moderate resolution satellite observations from polar-orbiting spacecraft.

Identification and quantification of diffuse fresh submarine groundwater discharge via airborne thermal infrared remote sensing

Abstract Airborne thermal infrared (TIR) overflights were combined with shoreline radionuclide surveys to investigate submarine groundwater discharge (SGD) along the north shore of Long Island, NY between June 2013 and September 2014. Regression equations developed for three distinct geomorphological environments suggest a positive linear relationship between the rate of diffuse SGD and the spatial extent of the observed coastal TIR anomalies; such a relationship provides quantitative evidence of the ability to use TIR remote sensing as a tool to remotely identify and measure SGD. Landsat TIR scenes were unable to resolve any of the 18 TIR anomalies identified during the various airborne overflights. Two locations were studied in greater detail via 222 Rn time series and manual seepage meters in order to understand why specific shoreline segments did not exhibit a TIR anomaly. SGD at the first site, located within a large, diffuse TIR anomaly, was composed of a mixture of fresh groundwater and circulated seawater with elevated levels of nitrate. In contrast, SGD at the second site, where no coastal TIR anomaly was observed, was composed of circulated seawater with negligible nitrate. Despite the compositional differences in seepage, both sites were similar in discharge magnitude, with average time series 222 Rn derived SGD rates equal to 18 and 8 cm d − 1 for the TIR site and non-TIR site, respectively. Results suggest that TIR remote sensing has the ability to identify locations of a mixture between diffuse fresh and circulated seawater SGD. If TIR anomalies can be demonstrated to represent a mixture between fresh and circulated seawater SGD, then the cumulative area of the TIR anomalies may be used to estimate the fresh fraction of SGD relative to the cumulative area of the seepage face, and thus allows for improved SGD derived nutrient flux calculations on a regional scale.

Robust Satellite Techniques (RST) for monitoring earthquake prone areas by satellite TIR observations: The case of 1999 Chi-Chi earthquake (Taiwan)

For more than 13years a multi-temporal data-analysis method, named Robust Satellite Techniques (RST), has been being applied to satellite Thermal InfraRed (TIR) monitoring of seismically active regions. It gives a clear definition of a TIR anomaly within a validation/confutation scheme devoted to verify if detected anomalies can be associated or not to the time and location of the occurrence of major earthquakes. In this scheme, the confutation part (i.e. verifying if similar anomalies do not occur in the absence of a significant seismic activity) assumes a role even much important than the usual validation component devoted to verify the presence of anomalous signal transients before (or in association with) specific seismic events. Since 2001, RST approach has been being used to study tens of earthquakes with a wide range of magnitudes (from 4.0 to 7.9) occurred in different continents and in various geo-tectonic settings.In this paper such a long term experience is exploited in order to give a quantitative definition of a significant sequence of TIR anomalies (SSTA) in terms of the required space–time continuity constraints (persistence), identifying also the different typologies of known spurious sequences of TIR anomalies that have to be excluded from the following validation steps. On the same basis, taking also into account for the physical models proposed for justifying the existence of a correlation between TIR anomalies and earthquakes occurrence, specific validation rules (in line with the ones used by the Collaboratory for the Study of Earthquake Predictability – CSEP – Project) have been defined to drive the validation process. In this work, such an approach is applied for the first time to a long-term dataset of night-time GMS-5/VISSR (Geostationary Meteorological Satellite/Visible and Infrared Spin-Scan Radiometer) TIR measurements, comparing SSTAs and earthquakes with M>4 which occurred in a wide area around Taiwan, in the month of September of different years (from 1995 to 2002). In this dataset the Chi-Chi earthquake (MW=7.6) which occurred on September 20, 1999 represents the major, but not unique, event. The analysis shows that all identified SSTAs occur in the pre-fixed space–time window around (in terms of time and location) earthquakes with M>4. The false positive rate remains zero even if only earthquakes with M>4.5 are considered. In the case of the Chi-Chi earthquake, 3 SSTAs were identified (all within the established space–time correlation window), one of them appearing about 2weeks before and very close to the epicentre of the earthquake just along the associated tectonic lineaments. The wide considered space–time window, together with the high seismicity of the considered area, surely positively conditioned the achieved results, so that further analyses should be carried out by using longer datasets and different geographic areas. However, also considering the coincidence with other (possible) precursor phenomena, independently reported (particularly within the iSTEP project) at the time of the Chi Chi earthquake, achieved results seem already sufficient (at least) to qualify TIR anomalies (identified by RST) among the parameters to be considered in the framework of a multi-parametric approach to a time-Dependent Assessment of Seismic Hazard (t-DASH).

Geology, tectonics and topography underlined by L'Aquila earthquake TIR precursors

Abstract Anomalous thermal infrared (TIR) emissions have widely been detected by satellite sensors before the major earthquakes. A recent processing technique for geostationary thermal data, developed for the case of the 2009 April 6, magnitude 6.3 L'Aquila earthquake, makes it possible to identify areas of enhanced TIR emissions around the epicentral region at a mean distance of less than 50 km but inside a radius of about 100 km. The index, called Night Thermal Gradient (NTG), derived from 4-D time-series data (two spatial and two temporal coordinates), identifies TIR anomalies by following the temperature trend during night, when the surface of the Earth is expected to cool. Leading up to the L'Aquila earthquake, an anomalous warming trend was observed. In this study, the anomalous NTG pattern is compared to the expected normal trend, taking into account the seismogenic faults, the overall tectonic setting, lithological spatial features, the orography and world stress map near the epicentral region. Main results are that a certain lithological selectivity can be recognized and that the known main stress field and seismogenic faults seem to be less important than certain tectonic lineaments, which are classified as non-seismogenic. The strong correlation between the topography and the TIR anomalies is in agreement with proposed physical mechanism for the generation of TIR anomalies. This relation is, in turn, present mainly in correspondence to two tectonic lineaments which in particular are thrusts: therefore, strong compressive states seem to be a positive condition for the generation of TIR anomalies. The temporary modification of these stress fields have triggered the Paganica Fault to its normal rupture mechanism. It is important to note that the distances, over which the TIR anomalies occurred, are an order of magnitude larger than the estimated length of the main fault rupture. Pixel-by-pixel time-series comparisons between the maximum TIR anomaly area and the epicentre of the main shock show that the increase in radiative emission occurred in the areas of maximum TIR anomalies and did not start by spreading outward from the epicentral region.

Detecting seismic IR anomalies in bi-angular Advanced Along-Track Scanning Radiometer data

Abstract. This paper presents a validation and confutation analysis using the methods of the robust satellite data analysis technique (RST) to detect seismic anomalies within the bi-angular Advanced Along-Track Scanning Radiometer (AATSR) data based on spatial/temporal continuity analysis. The distinguishing feature of our method is that we carried out a comparative analysis of seismic anomalies from bi-directional observation, which could help understanding seismic thermal infrared (TIR) anomalies. The proposed method has been applied to analyse bi-angular AATSR gridded brightness temperature data with longitude from 5 to 25° E and latitude from 35 to 50° N associated with the earthquake that occurred in Abruzzo, Italy, on 6 April 2009, and a full data set of 7 yr data from 2003 to 2009 during the months of March and April has been analysed for validation purposes. Unperturbed periods (March–April 2008) have been considered for confutation analysis. Combining with the tectonic explanation of spatial and temporal continuity of the abnormal phenomena, along with the analysed results, a number of anomalies could be associated with possible seismic activities, which follow the same time and space. Therefore, we conclude that the anomalies observed from 29 March 2009 to 5 April 2009, about eight days before the Abruzzo earthquake, could be earthquake anomalies.

Thermal Infrared Anomalies of Several Strong Earthquakes

In the history of earthquake thermal infrared research, it is undeniable that before and after strong earthquakes there are significant thermal infrared anomalies which have been interpreted as preseismic precursor in earthquake prediction and forecasting. In this paper, we studied the characteristics of thermal radiation observed before and after the 8 great earthquakes with magnitude up to Ms7.0 by using the satellite infrared remote sensing information. We used new types of data and method to extract the useful anomaly information. Based on the analyses of 8 earthquakes, we got the results as follows. (1) There are significant thermal radiation anomalies before and after earthquakes for all cases. The overall performance of anomalies includes two main stages: expanding first and narrowing later. We easily extracted and identified such seismic anomalies by method of “time-frequency relative power spectrum.” (2) There exist evident and different characteristic periods and magnitudes of thermal abnormal radiation for each case. (3) Thermal radiation anomalies are closely related to the geological structure. (4) Thermal radiation has obvious characteristics in abnormal duration, range, and morphology. In summary, we should be sure that earthquake thermal infrared anomalies as useful earthquake precursor can be used in earthquake prediction and forecasting.

Characteristics of Seismic Thermal Radiation of the Japan MS9.0 and Myanmar MS7.2 Earthquake

AbstractUsing the satellite thermal infrared brightness temperature data from Chinese geostationary meteorological satellite, we got their relative power spectra and analyzed this information in the wide range and full‐time. The results show that there are significant changes in brightness temperature before the Japan Ms9.0 and Myanmar Ms7.2 earthquake. The thermal‐infrared anomalies appeared about six months before the earthquakes. The change amplitude is more than 10 times than the normal relative amplitude. There are significant differences between the two earthquakes in the size of the abnormal regions and the time curves. Such differences may be associated with geological and climatic conditions.

Variation Characteristics of OLR for the Wenchuan Earthquake

AbstractBased on the outgoing long‐wave radiation data of geostationary satellite and their variation characteristics, this paper proposes a method for extracting earthquake thermal infrared anomaly, namely, the relative variance rate of power spectrum estimation. The proposed method is applied to analyze OLR for the Wenchuan earthquake and other five Ms ≥ 6.5 earthquakes in Mainland China. The results indicate that the power spectrum amplitude of OLR increased to different degrees before the great earthquakes. The characteristic period and characteristic amplitude are short and small in moist (low altitude) areas respectively, while the period and amplitude are long and big in arid (high altitude) areas respectively. The characteristics of observed thermal infrared anomalies are easy to be recognized. The method is very effective for extracting useful information and can be used to the extraction and analysis of earthquake‐related information.