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Introduction: Forest fires, grassland fires, heap coking, straw burning, and volcanic eruptions are thermal anomalies. They attract attention and are designated as high-temperature targets. They can be retrieved macroscopically and quickly by remote sensing technology. Methods: In temperature inversion, the mid-infrared (MIR, 3∼5 μm) and thermal infrared (TIR, 8∼14 μm) band data are most commonly used for temperature inversion. However, it is difficult to effectively retrieve the temperature of small-area high-temperature targets with them; the SWIR band data can perform this task more effectively. Additionally, inversion methods for short-wave infrared (SWIR, 1.3∼2.5 μm) and TIR band data are different. These differences lie in the mechanisms and models. Therefore, we use SWIR and TIR band data to retrieve heap coking temperature with Landsat 7 and Landsat 8 data. Results: SWIR data obtained the results 496∼651 K and 912 K, and TIR data obtained the results 313∼334 K and 320 K. Conclusion: The SWIR inversion results have higher accuracy than the TIR inversion results. The inversion results are closer to the actual temperature of local coking. For this reason, SWIR is more suitable for temperature inversion of small-area high-temperature targets. [ABSTRACT FROM AUTHOR]

Manam is one of the most frequently active volcanoes in Papua New Guinea and is a top contributor to global volcanic volatile emissions due to its persistent open-vent degassing. Here, we present a multi-year time series (2018–2021) of thermal and SO2 emissions for Manam from satellite remote sensing, which we interpret in the context of open-vent feedback between magma supply, reservoir pressure, and outgassing. We classify the time series into four phases based on the varying SO2 flux and observe a transient, yet substantial, increase in time-averaged SO2 flux from background levels of ~ 0.6 to ~ 4.72 kt day−1 between March and July 2019. We also identify a transition from temporally coupled to decoupled gas and thermal emissions during this period which we explain in the context of a magma recharge event that supplied new, volatile-rich magma to the shallow plumbing system beneath Manam. We infer that the arrival of this recharge magma triggered the series of eruptions between August 2018 and March 2019. These explosive events collectively removed 0.18 km3 of degassed residual magma and signalled the onset of a renewed period of unrest that ultimately culminated in a major eruption on 28 June 2019. We quantify the magnitude of "excess" degassing at Manam after the removal of the inferred residual magma. SO2 emissions reveal that ~ 0.18 km3 of magma was supplied, but only ~ 0.08 km3 was erupted between April 2019 and December 2021. We highlight how multi-parameter remote sensing observations over months to years enable the interpretation of open-vent processes that may be missed by short-duration campaign measurements. [ABSTRACT FROM AUTHOR]

Abstract This study aims to quantify the topography of the Moho boundary, the lower crust and uppermost mantle contact of Egypt, in order to estimate the crustal thickness variation and its link to the distribution of thermal anomalies under Egypt. This is accomplished by modeling satellite gravity, supported by the passive seismic constraints throughout Egypt. However, when estimating the thickness of the crust in Egypt using just seismic data, substantial uncertainty and deviation are produced due to the sparsely dispersed stations. Integrating seismic and gravity data minimizes uncertainty and improves estimate accuracy. The investigation is broken down into four stages, the first involving utilizing the Sentinel-3B satellite to create land surface temperature maps. The subsequent steps consist of gravity and seismic data adjustments, inversion and forward modeling. We used seismically restricted nonlinear inversion to look at Goco06s satellite gravity data to model the Moho’s topographic surface. The data gathered from deep seismic refraction and receiver functions adjusted the analyzed data. The inversion process relies on the adapted Bott's approach and Tikhonov regularization, using the assumption of the sphericity of the Earth planet. Reference values for depth of Moho and density contrast were set at 35 km and 500 kg/m3, respectively. The average statistical difference for Moho depth between gravity-based model and seismic data is − 0.10 km. Through forward gravity modeling, five gravity profiles were chosen and interpreted in 2.5D models. The results indicated that the Moho depth in the south varies from 35 to 39 km and decreases in the north and the Mediterranean. In upper Egypt, the highest Moho depth is 39 km. The depth varies beneath the Sinai Peninsula as it is about 35 km in its south, reaches 30 km in the northern portion, and ranges along the Red Sea’s Rift Margin from 29 to 32 km. Moreover, the final model shows the relation between Moho coincides with the surface temperature anomalies approved by satellite images and hot springs. The model reveals a correlation between Moho discontinuity and surface temperature anomalies, revealing the highest geothermal potential in a rectangular area in central Egypt, between latitudes 25°N and 30°N, based on satellite imagery and hot springs distribution.

This study aims to quantify the topography of the Moho boundary, the lower crust and uppermost mantle contact of Egypt, in order to estimate the crustal thickness variation and its link to the distribution of thermal anomalies under Egypt. This is accomplished by modeling satellite gravity, supported by the passive seismic constraints throughout Egypt. However, when estimating the thickness of the crust in Egypt using just seismic data, substantial uncertainty and deviation are produced due to the sparsely dispersed stations. Integrating seismic and gravity data minimizes uncertainty and improves estimate accuracy. The investigation is broken down into four stages, the first involving utilizing the Sentinel-3B satellite to create land surface temperature maps. The subsequent steps consist of gravity and seismic data adjustments, inversion and forward modeling. We used seismically restricted nonlinear inversion to look at Goco06s satellite gravity data to model the Moho's topographic surface. The data gathered from deep seismic refraction and receiver functions adjusted the analyzed data. The inversion process relies on the adapted Bott's approach and Tikhonov regularization, using the assumption of the sphericity of the Earth planet. Reference values for depth of Moho and density contrast were set at 35 km and 500 kg/m3, respectively. The average statistical difference for Moho depth between gravity-based model and seismic data is − 0.10 km. Through forward gravity modeling, five gravity profiles were chosen and interpreted in 2.5D models. The results indicated that the Moho depth in the south varies from 35 to 39 km and decreases in the north and the Mediterranean. In upper Egypt, the highest Moho depth is 39 km. The depth varies beneath the Sinai Peninsula as it is about 35 km in its south, reaches 30 km in the northern portion, and ranges along the Red Sea's Rift Margin from 29 to 32 km. Moreover, the final model shows the relation between Moho coincides with the surface temperature anomalies approved by satellite images and hot springs. The model reveals a correlation between Moho discontinuity and surface temperature anomalies, revealing the highest geothermal potential in a rectangular area in central Egypt, between latitudes 25°N and 30°N, based on satellite imagery and hot springs distribution. [ABSTRACT FROM AUTHOR]

Moore's law states that the performance of computers doubles about every two years. This has dramatic consequences for any modern high development and for satellites. The long development cycles cause these expensive assets to be obsolete before the start of their operations. The advancement also presents challenges to their design, particularly from a thermal perspective, as more heat is dissipated and circuits are more fragile. These challenges mandate that faster spacecraft development methods are found and thermal management technologies are developed. We elaborate on existing development methodologies and present our own lean method. We explore the development of a thermal anomaly-detection payload, extending from conception to in-orbit commissioning, to stimulate discussions on space hardware development approaches. The payload consists of four miniaturized infrared cameras, heating sources in view of the cameras simulating an anomaly, an on-board processor, and peripherals for electrical and communication interfaces. The paper outlines our methodology and its application, showcasing the success of our efforts with the first-light activation of our cameras in orbit. We show our lean method, featuring reference technical and management models, from which we derive further development tools; such details are normally not available in the scientific-engineering literature. Additionally, we address the shortcomings identified during our development, such as the failure of an on-board component and propose improvements for future developments. [ABSTRACT FROM AUTHOR]

IntroductionForest fires, grassland fires, heap coking, straw burning, and volcanic eruptions are thermal anomalies. They attract attention and are designated as high-temperature targets. They can be retrieved macroscopically and quickly by remote sensing technology.MethodsIn temperature inversion, the mid-infrared (MIR, 3∼5 μm) and thermal infrared (TIR, 8∼14 μm) band data are most commonly used for temperature inversion. However, it is difficult to effectively retrieve the temperature of small-area high-temperature targets with them; the SWIR band data can perform this task more effectively. Additionally, inversion methods for short-wave infrared (SWIR, 1.3∼2.5 μm) and TIR band data are different. These differences lie in the mechanisms and models. Therefore, we use SWIR and TIR band data to retrieve heap coking temperature with Landsat 7 and Landsat 8 data.ResultsSWIR data obtained the results 496∼651 K and 912 K, and TIR data obtained the results 313∼334 K and 320 K.ConclusionThe SWIR inversion results have higher accuracy than the TIR inversion results. The inversion results are closer to the actual temperature of local coking. For this reason, SWIR is more suitable for temperature inversion of small-area high-temperature targets.

Urban thermal anomalies profoundly impact human society, affecting daily life, public health, and residential comfort. Prior studies linked thermal anomalies to urban morphology evolution and land use change during urbanization based on multi-indicator quantification of urban morphology and linear regression modeling. However, it remained unclear which urban morphology elements predominantly dominate thermal anomalies and whether their impact is solely linear, and understanding on the diverse mechanisms through how urban morphology influences various thermal anomalies across seasons remains limited. Therefore, this study employed convolutional neural networks and interpretable machine learning (Grad-CAM and SHAP) to explore nonlinear relationships between urban morphology and thermal anomalies, focusing on comparisons between different types of anomaly events across time. The main findings indicated: (1) Grad-CAM's identification of pivotal hotspot pixels and SHAP's interpretability assessment highlighted that crucial urban morphology factors contributing to thermal anomalies include the area of green spaces, water spaces, the number of residential facilities, building floor area ratio, and the count of industrial production facilities. (2) Clear nonlinear relationships were observed between dominant urban morphology factors and the occurrence of thermal anomalies, which confirming the existence of multiple thresholds and activation levels, as demonstrated through SHAP's partial dependency analysis. The dynamic complexity of these associations significantly varied depending on the type of event and the timing of thermal anomalies. These findings offer actionable guidance for urban planners to refine climate-friendly strategies, revealing the heterogeneity of these relationships across time and seasons through multi-scenario analysis and providing tailored insights for climate-sensitive urban planning.

Long-term changes in thermal fields have been studied before and during strong earthquakes with magnitudes from 5.1 to 5.6 that occurred in the region of the Baikal rift zone in 2008–2022. Satellite data are used for these studies. For analysis we use the values of land surface temperature, temperature of the near-surface layer of the atmosphere, outgoing longwave radiation (OLR), and relative humidity (RH) recorded using the AIRS instrument mounted on the Aqua satellite. During the periods of preparation and occurrence of these seismic events, anomalous variations in the parameters of thermal fields registered with satellite are revealed. They exceed the average long-term values: for land surface temperature and temperature of the near-surface layer of the atmosphere by 5–10%, for OLR by 11–15%, and for RH by 6–10%. A strong negative correlation is found between changes in the temperature of the near-surface layer of the atmosphere and RH (correlation coefficient of –0.75), as well as antiphase oscillations between the values of the OLR and RH. The results can be used for studies of the precursor variability of thermal fields during monitoring of seismic hazard zones. [ABSTRACT FROM AUTHOR]

Based on the JRA-55 surface sensible and latent heat flux， reanalysis circulation data provided by Japan Meteorological Agency （JMA）， monthly grid precipitation data provided by the National Meteorological Information Center （NMC） during the period of 1971 -2019.The effects of thermal anomalies over the Iran Plateau and the Qinghai-Xizang Plateau on summer precipitation over the Tarim Basin are analyzed.Results show that the sensible heat over the Iran Plateau and the latent heat over the Qinghai-Xizang Plateau play main roles in summer heating.The singular value decomposition （SVD） analysis has indicated that the surface thermal anomalies over the two plateaus are well related to summer precipitation over the Tarim Basin.Correlations suggest that thermal anomalies in the two plateaus have better relationships with summer precipitation over the Tarim Basin than one in single plateau.When the sensible heat strengthens over the Iran Plateau， and the latent heat strengthen in northern Qinghai-Xizang Plateau and weaken in southern Qinghai-Xizang Plateau， which can cause the middle to upper tropospheric cooling over central Asia.On the one hand， the subtropical westerly jet will shift south over central Asia， and there is an anomalous cyclone over central Asia and an anomalous anticyclone over Mongolian Plateau， which result in anomalous south wind prevailing over the Tarim Basin.On the other hand， the water vapor can be transport to the Tarim Basin by an anomalous anticyclone over the Arabian Sea and an anomalous cyclone over central Asia， meanwhile， the anomalous anticyclone over north China also can transport the water vapor from northwest Pacific to the Tarim Basin.Above both are contributed to more summer precipitation over the Tarim Basin.The single thermal anomalies over the Iran Plateau and the Qinghai-Xizang Plateau both can influence the summer precipitation over the Tarim Basin， but show partial difference related to the source and path of water vapor.The former only can affect water vapor transmission in the tropical Indian Ocean， but the latter can affect water vapor transmission in both the Indian Ocean and northwest Pacific.

Moore’s law states that the performance of computers doubles about every two years. This has dramatic consequences for any modern high development and for satellites. The long development cycles cause these expensive assets to be obsolete before the start of their operations. The advancement also presents challenges to their design, particularly from a thermal perspective, as more heat is dissipated and circuits are more fragile. These challenges mandate that faster spacecraft development methods are found and thermal management technologies are developed. We elaborate on existing development methodologies and present our own lean method. We explore the development of a thermal anomaly-detection payload, extending from conception to in-orbit commissioning, to stimulate discussions on space hardware development approaches. The payload consists of four miniaturized infrared cameras, heating sources in view of the cameras simulating an anomaly, an on-board processor, and peripherals for electrical and communication interfaces. The paper outlines our methodology and its application, showcasing the success of our efforts with the first-light activation of our cameras in orbit. We show our lean method, featuring reference technical and management models, from which we derive further development tools; such details are normally not available in the scientific-engineering literature. Additionally, we address the shortcomings identified during our development, such as the failure of an on-board component and propose improvements for future developments.

Reef corals have been threatened by climate change, with more frequent and intense bleaching events leading to extensive coral mortality and loss of coral cover worldwide. In the face of this, the corals' photosymbiont assemblages have received special attention as a key to better understand the bleaching process and its recovery. To assess the effects of thermal anomalies, the coral Mussismilia harttii and the hydrocoral Millepora alcicornis were monitored through the El Niño 2015/2016 at a Southwestern Atlantic (SWA) coral reef. A severe bleaching event (57% of colonies bleached) was documented, triggered by a < 3 °C-week heatwave, but no mortality was detected. The hydrocoral was more susceptible than the scleractinian, displaying bleaching symptoms earlier and experiencing a longer and more intense bleaching event. The composition of photosymbionts in the M. alcicornis population was affected only at the rare biosphere level (< 5% relative abundance), with the emergence of new symbionts after bleaching. Conversely, a temporary dysbiosis was observed in the M. harttii population, with one of the dominant symbiodiniaceans decreasing in relative abundance at the peak of the bleaching, which negatively affected the total β-diversity. After colonies' complete recovery, symbiodiniaceans' dominances returned to normal levels in both hosts. These results highlight critical differences in how the two coral species cope with bleaching and contribute to the understanding of the role of photosymbionts throughout the bleaching-recovery process. [ABSTRACT FROM AUTHOR]

Scientific progress in the context of seismic precursors reveals a systematic mechanism, namely lithosphere–atmosphere–ionosphere coupling (LAIC), to elaborate the underlying physical processes related to earthquake preparation phases. In this study, a comprehensive analysis was conducted for two earthquakes that occurred on the sea coast through tidal force fluctuation to investigate ocean–lithosphere–atmosphere–ionosphere coupling (OLAIC), based on oceanic parameters (i.e., sea potential temperature and seawater salinity), air temperature and electron density profiles. The interrupted enhancement and diffusion process of thermal anomalies indicate that the intensity of seismic anomalies in the atmosphere is affected by the extent of land near the epicenter. By observing the evolution of the ocean interior, we found that the deep water was lifted and formed upwelling, which then diffused along the direction of plate boundaries with an "intensification-peak-weakening" trend under the action of the accelerated subduction of tectonic plates. Furthermore, the analysis shows that the seismic anomalies have two propagation paths: (i) along active faults, with the surface temperature rising as the initial performance, then the air pressure gradient being generated, and finally the ionosphere being disturbed; (ii) along plate boundaries, upwelling, which is the initial manifestation, leading to changes in the parameters of the upper ocean. The results presented in this study can contribute to understanding the intrinsic characteristics of OLAIC. [ABSTRACT FROM AUTHOR]

The eruption of the Tajogaite volcano in 2021, in the Cumbre Vieja rift zone (La Palma, Canary Islands), is the most recent but also the most damaging and longest-lasting eruption on the island since historical records began. We analyzed geophysical parameters (seismicity, surface deformation, thermal anomalies, and volcanic activity) with the aim of reconstructing the temporal development of the magma plumbing system. The seismic sequence (> 9000 events, mbLg ≤ 5.0) can be grouped into nine distinct phases, which correspond to well-separated spatial clusters and distinct earthquake regimes. A strong premonitory thermal anomaly was calculated on July 2021 in the South of La Palma. The source of the magma was within the upper mantle (40–20 km depth). A second magma budget (< 15 km depth) indicated a short-term stagnation of alkaline magma within the lower crust, near the Moho. The outline of these earthquakes delineates the magma pathway. Just before and immediately after the eruption (phases 2 and 3), the high-frequency seismicity in the mantle disappeared completely, reappearing ten days after the eruption started. The pattern of deformation began before the eruption with a breakpoint around September 11, after which, deformation accelerated sharply, followed by stabilization in phase 3 and a decrease in the following phases. The level of deformation suggested that a shallow magma intrusion was established. Based on the historical eruptive pattern, it is possible to infer two possible hazard-forecast scenarios: (a) the volcano could enter a prolonged phase of tranquility for more than one century or, (b) a new eruption could occur between ca. 2045 and 2065, with a slightly shorter duration than this recent one. Therefore, if the more pessimistic scenario is assumed, appropriate territorial planning is required. [ABSTRACT FROM AUTHOR]

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The earthquakes prediction based on LST anomalies remain a contradicting debate due to limited and short-term data around the earthquake's epicenter. The results are varying in different case studies, only few research matches with pre seismic LST anomalies while many are not found to be significant for earthquakes predication. This study assessed temperature anomalies in different earthquakes events of Mw ≥ 6.0 in Pakistan from 2000 to 2020. The present study uses Moderate Resolution Imaging Spectroradiometer (MODIS) satellite thermal imagery data over the epicenter region to analyze thermal anomaly associated and earthquake prediction. The surface temperature growth before the earthquake event is estimated using the satellite thermal infrared images carrying valuable earthquake precursory information. The study area Pakistan is prone to active seismicity due to Northern Head-on Collision of Indian-and Eurasian plate; Southern Makran Subduction Zone of Indian and Arabian plate and the regional Chaman transform boundary. The results show pre seismic temperature variation range between 30 °C − 54 °C, which seems to be a good prospect for linking thermal anomalies to earthquake prediction. [ABSTRACT FROM AUTHOR]

Current-day volcanic activity in the Azores archipelago is characterized by seismic events and secondary manifestations of volcanism. Remote sensing techniques have been widely employed to monitor deformation in volcanic systems, map lava flows, or detect high-temperature gas emissions. However, using satellite imagery, it is still challenging to identify low-magnitude thermal changes in a volcanic system. In 2010, after drilling a well for geothermal exploration on the northern flank of Fogo Volcano on São Miguel Island, a new degassing and thermal area emerged with maximum temperatures of 100 °C. In the present paper, using the ASTER sensor, we observed changes in the near-infrared signals (15 m spatial resolution) six months after the anomaly emerged. In contrast, the thermal signal (90 m spatial resolution) only changed its threshold value one and a half years after the anomaly was recognized. The results show that wavelength and spatial resolution can influence the response time in detecting changes in a system. This paper reiterates the importance of using thermal imaging and high spatial resolution images to monitor and map thermal anomalies in hydrothermal systems such as those found in the Azores. [ABSTRACT FROM AUTHOR]

Climate change is affecting rocky reef ecosystems in a multitude of ways at global scale. During summer 2018, the rocky reef communities of Portofino Marine Protected Area (MPA) (NW Mediterranean) were affected by thermal anomalies, a mucilaginous event, and the seasonal expansion of Caulerpa cylindracea. Moreover, a severe storm occurred on 29 October. The effects of these pressures on the rocky reef communities were analysed at different depths (10 m, 20 m, 30 m, and 40 m) and at three times (June, October, December) to evaluate change at short temporal scale. Portofino MPA's communities have significantly changed: thermal anomalies mostly affected the biota living above the summer thermocline (ca 20 m depth); mucilaginoius aggregates first impacted the communities in shallow waters and only later those in deep waters, where they typically fall in late summer; the greatest impact by Caulerpa cylindracea was detected at 20 m depth; the storm directly impacted communities in shallow and intermediate waters by uprooting algal species, while it had indirect effects at greater depths through sediment redistribution. Disentangling the effects of multiple pressures on coastal ecosystems is one of the most pressing goals in marine ecology and biodiversity conservation. This study represents an attempt in this direction as applied to the short-term dynamics of rocky reef communities under a climate change scenario. [ABSTRACT FROM AUTHOR]

Coral reefs of Vietnam are highly threatened by a combination of anthropogenic impacts and natural disturbances. As a result, preservation of the remaining reefs is a major governmental concern. Con Dao Islands, located in the coastal area of southern Vietnam in the South China Sea, still possess diverse and healthy coral communities. Coral surveys conducted in 2017–2020 on six sites within the marine protected area of Con Dao National Park revealed extensive coral cover (62.8–95.5%) and diversity (168 stony coral species). Coral communities were mostly dominated by Acroporidae followed by Poritidae and Fungiidae. Temporal dynamics over a 3-year period exhibited no significant decrease in the cover of dominant coral taxa, despite the severe thermal anomaly in 2019 and subsequent moderate coral bleaching, suggesting that the local corals may be successfully acclimating to the current level of thermal stress, although further study of coral adaptation in this region is warranted. High diversity and coral cover, together with the potential of resistance and resilience to repeated thermal stress in coral communities of the Con Dao Archipelago, highlights the need for authorities to pay special attention to this area and to expand conservational efforts to preserve this unique natural site. [ABSTRACT FROM AUTHOR]

On the basis of satellite monitoring data, the features of large natural fires and the volumes of CO, CO2, and PM2.5 emissions caused by them on the territory of Russian Federation and in its individual regions from April to October 2001–2021 have been studied. It has been found that, in July and August 2021, the average monthly values of the areas covered by fire throughout Russia exceeded by 25 000 and 24 500 km2 similar values recorded in these months for the period from 2001 to 2020. Excess values of the areas covered by fire in the territory of large regions in 2021 compared to 2020 were revealed: in April in the European part of Russia (by 2100 km2), in May in the Ural Federal District (by 6700 km2), in the Siberian Federal District (by 8400 km2), and in July and August in the Far Eastern Federal District (by 18 400 and 27 000 km2, respectively). It has been found that, in certain months of 2021, an increase in the contribution of emissions caused by natural fires in the territories of these regions to the total emissions in the country reached 44.9% when compared to 2020. Using satellite data, an analysis was carried out of changes in the gas composition of the atmosphere during the period of strong fires in the Republic of Sakha (Yakutia) in July 2021, which revealed areas of anomalously high CO and CH4 concentrations and an increase in the aerosol index (AI) from 1.4 to 3.7. [ABSTRACT FROM AUTHOR]

In this study, we demonstrate the strong potential of combining Unmanned Aerial Vehicle (UAV)-based thermal infrared (IR) and magnetic measurements to image the thermal state of volcanic edifices, as well as the distribution of active volcano-tectonic features at depth. Since magnetization is strongly dependent on temperature and alteration, thermally active structures are also associated with a decrease in magnetization. Based on the analysis of recent combined magnetic and infrared acquisitions, we focus on the recent evolution of the summit activity at Piton de la Fournaise. The comparison clearly highlights zones of major thermal activity, alteration and high permeability, and potentially areas of low mechanical resistance. Those observations provide information on preferential pathways for future activity, and also provide constraints on fluid transfer, diffusion, and cooling processes occurring within the volcano subsurface. Through reiterations, such combined UAV measurements are therefore particularly relevant in monitoring volcanic hazards before, during and after eruptions.

Thermal anomalies detected by Earth observation satellites have been widely used to identify active fires, even though there has been a high percentage of misclassified fire pixels. A total of about 75,000 Fire Radiative Power (FRP) pixels have been spatially and temporally combined with the EFFIS Burned Areas Database, distributed under the Copernicus Emergency Management Service, in order to identify thermal anomaly hotspots misclassified as fire pixels. The proposed approach uses a cluster analysis to partition the FRP pixels dataset into discrete subsets, based on defined distance measures like the spatial distance of the pixel centroids and the temporal frequencies. Later, zonal statistics were performed in order to evaluate fractional land cover within each identified hotspot. Results demonstrate that misclassified large surfaces, like industrial areas, can be identified from both spatial and temporal patterns, while other FRP false alarms are smaller in size.

The Advanced Himawari Imager (AHI) and Advanced Baseline Imager (ABI), respectively aboard Himawari-8 and GOES-R geostationary satellites, are two important instruments for the near-real time monitoring of active volcanoes in the Eastern Asia/Western Pacific region and the Pacific Ring of Fire. In this work, we use for the first time AHI and ABI data, at 10 min temporal resolution, to assess the behavior of a Normalized Hotspot Index (NHI) in presence of active lava flows/lakes, at Krakatau (Indonesia), Ambrym (Vanuatu) and Kilauea (HI, USA) volcanoes. Results show that the index, which is used operationally to map hot targets through the Multispectral Instrument (MSI) and the Operational Land Imager (OLI), is sensitive to high-temperature features even when short-wave infrared (SWIR) data at 2 km spatial resolution are analyzed. On the other hand, thresholds should be tailored to those data to better discriminate thermal anomalies from the background in daylight conditions. In this context, the multi-temporal analysis of NHI may enable an efficient identification of high-temperature targets without using fixed thresholds. This approach could be exported to SWIR data from the Flexible Combined Imager (FCI) instrument aboard the next Meteosat Third Generation (MTG) satellites. [ABSTRACT FROM AUTHOR]

Peat fires differ from other wildfires by significant carbon loss, the emission of greenhouse gases and other combustion products as well as by serious environmental consequences. Not only biomass but also peat is burnt. A possibility of detecting peat fires from satellite and ground-based data is considered for the fires in the Moscow region in 2010. The peat fire detection technique was tested by superimposing data on thermal anomalies from Terra/Aqua MODIS satellite data on the peatland contours, as well as by analyzing the vegetation cover changes before fires and the next year using the Landsat satellite multispectral data. Threshold values were found for the fire duration, maximum temperature, and maximum fire radiative power that characterize peat fires and can be used to discriminate between fires on peat lands and peat fires themselves for taking into account emissions not only from biomass burning but also from soil carbon loss. [ABSTRACT FROM AUTHOR]

Italy boasts a long history of hydrocarbon exploration. The Po Basin, in particular, has been extensively explored due to its peculiar geological setting, arising from the convergence of the Southern Alps and Northern Apennines. Because of this, substantial subsurface data have been collected and made publicly available. Today, data from past oil and gas exploration campaigns can find new life in decarbonization programs, especially for geothermal exploration. Geothermal data on the Po Basin, including bottom hole temperature (BHT) and drill stem test (DST) records, play a crucial role in understanding the thermal state of the subsurface, and can therefore be employed in the exploration of geothermal resources. This study presents a 3D model of the thermal regime in the Po Basin based on the analysis of legacy hydrocarbon wells. Geostatistical models of subsurface temperatures are produced via direct sequential simulations that consider: (i) the overall geothermal gradient across the region, (ii) anisotropy in the temperature field revealed by variogram analysis, and (iii) temperature data in the surrounding geological volumes. A base-case model of expected temperature values and associated conditional variance are thus generated from which depth-to-the-isotherm maps were extracted for temperatures in the low-enthalpy range (<100 °C). The study confirms that promising thermal anomalies are mapped in the Ferrara Arc and the buried Southern Alps. These areas offer opportunities for new developments and the repurposing of depleted oil wells for district heating. Additionally, the findings highlight other areas in the Po Plain (e.g., Emilian Arc) where there exists more subtle geothermal potential for further exploration and development. • The 3D temperature distribution of sedimentary basins can be predicted by using geostatistical methods from corrected BHT data • The model predicts the depths at which it is possible to find certain temperatures at any given point in the Po Plain • The model predicts several thermal anomalies associated with different geological structures • Anomalies are found in existing O&G fields that can be repurposed for geothermal production after depletion of the reservoirs [ABSTRACT FROM AUTHOR]

Vulcano belongs to the seven volcanic islands forming the Aeolian archipelago (Italy) and has the privilege to define an eruptive style as "Vulcanian". It has to be considered as an active volcano as its most recent activity demonstrated. Starting by late spring 2021, the thermal state of the Vulcano summit area changed and the gas emission increased. During the summer and, in particular, starting from September, geophysical and geochemical signals, precisely those linked to the activity of the hydrothermal system that feeds the fumaroles of the Fossa crater, varied. The temperature of the gases emitted by the fumaroles on the crater rim has increased and the composition of the gases has showed an increase in CO2 and SO2 (carbon dioxide and sulfur dioxide) concentration. For such reasons, the authors decided to follow this event by analyzing the remotely sensed available data suitable for detecting changes in thermal state. By processing the TIRS (Landsat 8) and ASTER time series, two long-term surface temperature logs were obtained and, therefore, by adopting a statistical approach, an analysis in both space and time domains has emphasized a thermal signature since mid-September 2021. [ABSTRACT FROM AUTHOR]

The Spratly Islands are a remote group of more than 150 coral reefs and islands scattered in the south‐central South China Sea and representing a biodiversity hotspot in the region. An integrative anthropogenic impact and increased frequency of thermal anomalies have increasingly been threatening these unique reef ecosystems over the last three decades. The repetitive surveys conducted on four coral reef sites within the Spratly Islands in 2018–2019 and in 2021 revealed a significant decrease of coral cover, particularly of acroporids, a decrease of species diversity and an outbreak of crown‐of‐thorns starfish (COTS) Acanthaster planci (the variation of starfish abundance was 1–18 starfish/100 m2). Moreover, one of two additional sites, located within the same study reefs, revealed a coral‐killing photoautotrophic cyanosponge Terpios hoshinota, covering 56.9% of all dead scleractinian colonies on the reef slope of this site. Analysis of sea surface temperature dynamics during the last 4 years (2018–2021) in the Spratly area allowed suggesting the concurrent negative effect of the COTS outbreak and the thermal anomaly of 2020 on local coral communities. This effect may have contributed to the general trends in coral reef decline in the area of the Spratly archipelago under the condition of repetitive thermal stress and increasing anthropogenic impact. [ABSTRACT FROM AUTHOR]

Nowadays, there has been a growing interest in understanding earthquake forerunners, i.e., anomalous variations that are possibly associated with the complex process of earthquake evolution. In this context, the Robust Satellite Technique was coupled with 10 years (2012–2021) of daily night-time MODIS-Land Surface Temperature remote sensing data to detect thermal anomalies likely related to the 27 September 2021, strong onshore earthquake of magnitude Mw6.0 occurring near the Arkalochori village in Central Crete, Greece. Eight intense (signal-to-noise ratio > 3) and infrequent, quite extensive, and temporally persistent thermal signal transients were detected and characterized as pre-seismic anomalies, while one thermal signal transient was identified as a co-seismic effect on the day of the main tectonic event. The thermal anomalies dataset was combined with tectonic parameters of Central Crete, such as active faults and fault density, seismogenic zones and ground displacement maps produced using Sentinel-1 satellite imagery and the Interferometric Synthetic Aperture Radar technique. Regarding the thermal anomaly of 27 September, its greatest portion was observed over the footwall part of the fault where a significant subsidence up to 20 cm exists. We suggest that the thermal anomalies are possibly connected with gas release which happens due to stress changes and is controlled by the existence of tectonic lines and the density of the faults, even if alternative explanations could not be excluded. [ABSTRACT FROM AUTHOR]

The energy-intensive industrial sector (EIIS) occupies a majority of global CO2 emissions, but spatially monitoring the spatiotemporal dynamics of these emissions remains challenging. In this study, we used the Chinese province with the largest carbon emissions, Shandong Province, as an example to investigate the capacity of remotely sensed thermal anomaly products to identify annual industrial heat source (IHS) patterns at a 1 km resolution and estimated the carbon emissions of these sources using auxiliary datasets and the boosting regression tree (BRT) model. The IHS identification accuracy was evaluated based on two IHS references and further attributed according to corporate inventory data. We followed a bottom-up approach to estimate carbon emissions for each IHS object and conducted model fitting using the explanatory strength of the annual population density, nighttime light (NTL), and relevant thermal characteristic information derived from the Visible Infrared Imaging Radiometer Suite (VIIRS). We generated a time series of IHS distributions from 2012 to 2020 containing a total of over 3700 IHS pixels exhibiting better alignment with the reference data than that obtained in previous work. The results indicated that the identified IHSs mostly belonged to the EIIS, such as energy-related industries (e.g., thermal power plants) and heavy manufacturing industries (e.g., chemistry and cement plants), that primarily use coal and coke as fuel sources. The BRT model exhibited a good performance, explaining 61.9% of the variance in the inventory-based carbon emissions and possessing an index of agreement (IOA) of 0.83, suggesting a feasible goodness of fit of the model when simulating carbon emissions. Explanatory variables such as the population density, thermal power radiation, NTL, and remotely sensed thermal anomaly durations were found to be important factors for improving carbon emissions modeling. The method proposed in this study is useful to aid management agencies and policymakers in tracking the carbon footprint of the EIIS and regulating high-emission corporations to achieve carbon neutrality. [ABSTRACT FROM AUTHOR]

The harsh environment of high-latitude areas with large amounts of snow and ice cover makes it difficult to carry out full geological field surveys. Uranium resources are abundant within the Ilimaussaq Complex in the Narsaq region of Greenland, where the uranium ore body is strictly controlled by the Lujavrite formation, which is the main ore-bearing rock in the complex rock mass. Further, large aggregations of radioactive minerals appear as thermal anomalies on remote sensing thermal infrared imagery, which is indicative of deposits of highly radioactive elements. Using a weight-of-evidence analysis method that combines machine-learned lithological classification information with information on surface temperature thermal anomalies, the prediction of radioactive element-bearing deposits at high latitudes was carried out. Through the use of Worldview-2 (WV-2) remote sensing images, support vector machine algorithms based on texture features and topographic features were used to identify Lujavrite. In addition, the distribution of thermal anomalies associated with radioactive elements was inverted using Landsat 8 TIRS thermal infrared data. From the results, it was found that the overall accuracy of the SVM algorithm-based lithology mapping was 89.57%. The surface temperature thermal anomaly had a Spearman correlation coefficient of 0.63 with the total airborne measured uranium gamma radiation. The lithological classification information was integrated with surface temperature thermal anomalies and other multi-source remote sensing mineralization elements to calculate mineralization-favorable areas through a weight-of-evidence model, with high-value mineralization probability areas being spatially consistent with known mineralization areas. In conclusion, a multifaceted remote sensing information finding method, focusing on surface temperature thermal anomalies in high-latitude areas, provides guidance and has reference value for the exploration of potential mineralization areas for deposits containing radioactive elements. [ABSTRACT FROM AUTHOR]

The recent advances in satellite-based earthquakes (EQs) precursors provide an opportunity to correlate the seismic variation on lithosphere with atmosphere during the EQ preparation period through a rigorous atmospheric monitoring system. In the present study, seismic-induced thermal anomalies from cloud-free satellite thermal images of Moderate Resolution Imaging Spectroradiometer-Land Surface Temperature (MODIS-LST) are analyzed within a time interval of three months (precedent two months and succeeding one month to each EQ day) of 13 $\text{M}_{w} \ge6.0$ terrestrial EQs during 2000–2019. All these EQs occur in low vegetation and no snow cover regions except $\text{M}_{w}~6.7$ , Siberia Russia event. Remote sensing data show evidence of significant perturbation with reference to confidence bounds in LST within 5–20 time window upon the antecedent and the descendant of EQ day. The studied thermal anomalies are obtained from LST values over the epicenter region. This work endorses the performance of MODIS-LST for detecting EQ-induced thermal anomalies in terrestrial regions with no vegetation and snow cover and also assisting to the development of lithosphere-atmosphere hypothesis over the epicenter region. [ABSTRACT FROM AUTHOR]

A time series of the occurrence of thermal anomalies, aerosol optical-depth anomalies, and total electron content of the ionosphere during the preparation of strong earthquakes with magnitudes of M = 5.2–6.6 in Central Italy in 2016–2017 is revealed based on the joint analysis of various geophysical fields recorded from space. The values of temperatures of the surface, the near-surface layer of the atmosphere, and the outgoing longwave radiation detected by the AIRS instrument (Aqua satellite) are used to analyze thermal fields. Changes in the aerosol optical-depth values are investigated using the MCD19A2 product (Terra and Aqua satellites). Global ionospheric maps obtained from data of global satellite navigation systems and ground-based GPS stations located within a radius of 100 km from earthquake epicenters are used to study anomalies in the ionosphere. It is found that the first precursory changes in geophysical fields occurred in areas with radii of 200 km, the centers of which coincided with the centers of high earthquake risk zones, and were detected 11–15 days before the main seismic shocks. [ABSTRACT FROM AUTHOR]

Thermal-field anomalies recorded during the preparation and occurrence of strong earthquakes on March 8, 2010 (M = 6.1), and January 24, 2020 (M = 6.7), in Turkey, are studied using satellite data. Temperatures of the surface and atmospheric near-surface layer, as well as outgoing longwave radiation registered by the AIRS sensor of the Aqua satellite, are used for the analysis. The processing results have allowed us to establish that positive variations in surface and atmosphere temperatures appeared 7–12 days before the studied seismic events with M = 6.1 and M = 6.7, and these variations marked the onset of formation of the outgoing longwave radiation anomalies registered over the North and East Anatolian tectonic faults. The thermal-field anomalies detected during the preparation of the earthquakes in Turkey confirm the presence of heat generation effects between the surface and the upper cloud edge. These effects can be used as short-term remotely registered precursors of strong seismic events. [ABSTRACT FROM AUTHOR]

Passive microwave remote sensing technology is an effective means to identify the thermal anomalies associated with earthquakes due to its penetrating capability through clouds compared with infrared sensors. However, observed microwave brightness temperature is strongly influenced by soil moisture and other surface parameters. In the present article, the segmented threshold method has been proposed to detect anomalous microwave brightness temperature associated with the strong earthquakes occurred in Sichuan province, China, an earthquake-prone area with high soil moisture. The index of microwave radiation anomaly (IMRA) computed by the proposed method is found to enhance prior to the three strong earthquakes, 2008 Wenchuan (M = 7.8), 2013 Lushan (M = 6.6), and 2017 Jiuzhaigou (M = 6.5), occurred during 2008-2018 using the Defense Meteorological Space Program Special Sensor Microwave Imager/Sounder F17 satellite data. Our results show that the microwave brightness temperature anomalies appeared about two months prior to the three strong earthquakes. For the Wenchuan and Lushan earthquakes, the enhanced IMRA distributed along the main fault, which is consistent with the variations of our earlier studies of the 1997 Manyi (M = 7.5) and the 2001 Kokoxili (M = 7.8) earthquakes in the region with low soil moisture. For the Jiuzhaigou earthquake, the anomalies distributed around the epicenter and do not indicate the seismogenic structure, which could be due to the presence of a blind fault. It should be noted that quantitative evaluation of IMRA is limited due to infrequent occurrence of earthquakes.

Earthquakes occur because of increase of stress and rock fracture. Prior to impending earthquake, physical and chemical interactions in the earth's crust lead to anomalous variations of air temperature (AT). Satellite based remote sensing method allows to determine earthquake precursors over a large tectonic area. Buildup of stresses in a seismically active area manifests as thermal anomaly. In the present study, variations in AT prior to eastern Turkey, Bella Bella (Canada) and Pocito (Argentina) earthquakes were studied by utilizing multi-year background data. The analysis shows strong anomalous variations of AT prior to the seismic events with the highest AT values recorded before the earthquakes. Anomaly plots show that the release of energy was concentrated in the region along epicenter. Descriptive statistics of AT for the earthquakes show significant changes prior to the seismic event. Degassing of gases occur during rock micro-fracturing, which results in air ionization, thereby resulting in AT precursory anomalies. [ABSTRACT FROM AUTHOR]

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The potential to map geothermal anomalies using remote sensing information has attracted recently much research, reflecting thus the increasing interest for renewable energy resources. Aim of the present work is to highlight areas with geothermal anomalies, as demonstrated by increased Land Surface Temperature (LST) values, that could potentially indicate possible locations for geothermal field development. We hypothesized that an area with increased geothermal potential can possibly have a surface expression through increased LST, that discriminates it from other areas of low geothermal interest. LST is known to be affected by increased heat flow but also from other parameters such as altitude, land cover and meteorological conditions. Therefore, there is need to develop a methodology capable to extract LST signals corresponding to the geothermal component. To delineate areas with constantly higher LST values from surrounding locations, we analyzed Landsat 8 derived LST time series, and accounted for different land cover types and altitudes. To test our hypothesis, we used a well-known geothermal field in Aristino-Alexandroupolis, NE Greece, where it was shown that spatial means of winter LST were significantly greater within geothermal zones. Furthermore, our results indicated that areas within geothermal fields demonstrate winter LST values greater than a certain threshold value for each different land cover type. Therefore, we developed a logical operator algorithm and applied our methodology to Thrace basin – NE Greece. The produced geothermal potential map depicted correctly spot areas, which make part of the known geothermal fields in Eastern Macedonia and Thrace Tertiary sedimentary basins, but also indicated other possible sites with increased potential for future research.

Multiple parameters (brightness temperature, soil moisture, surface latent heat flux, surface air temperature and carbon monoxide) before and after the 2015 Nepal M7.8 Gorkha main earthquake and M7.3 Dolakha aftershock were analysed using satellite observation data. The thermal anomalies from optical and microwave data appear about two months prior to the 2015 Gorkha earthquake. Some of the parameters show anomalous changes at different altitudes about 20 days prior to the main earthquake event and 10 days prior to the strong aftershock. Our results show that pre-earthquake anomalous signals propagate from the in situ to the top of atmosphere, and the anomalies in the atmosphere often observed prior to an impending earthquake. The changes on the land surface and corresponding changes in meteorological and atmospheric parameters show existence of strong coupling during the seismogenic period, although the transfer mechanism of seismic/electromagnetic is still has to be investigated and understood.

Pre-seismic thermal anomalies have been widely reported, however, there is still no unified understanding of their causes or physical mechanisms. To clarify whether subsurface fluid convection and rock deformation directly related to seismic fault stress release can form thermal anomalies before an earthquake, we carried out thermo-hydro-mechanical (THM) coupled modeling of the Wenchuan earthquake, and considered the influence of maximum horizontal principal stress direction (MPSD) and fault dip. The results show that convective thermal flux (CT) anomalies of subsurface fluid and the deformation induced thermal flux (DT) of the rock mass caused by stress release of the seismic fault can explain the observed thermal anomalies along the fault. The calculated and observed thermal anomalies are comparable in spatial distribution, evolution, and magnitude. Specifically, for the Wenchuan earthquake, seismic fault stress release-induced CT and DT anomalies occur in the fault zone and in the adjacent hanging wall area. In the fault zone, CT and DT induced thermal anomalies were comparable, and superposition of the two was characterized by strong initial warming, followed by weaker warming and then short-term cooling. However, outside of the fault zone, CT induced thermal anomalies had much higher intensities than those induced by DT, and were characterized by band-like warming along the hanging wall of the fault. In addition, variations in the MPSD and fault dip cause the segmentation of thermal anomalies along the Wenchuan earthquake fault. From the southern to the northern segments of the fault, the intensity of thermal anomalies is significantly weakened with rotation of MPSD and an increase in fault dip. Our study provides evidence that seismic fault stress release is the cause of pre-seismic thermal anomalies; furthermore, the results indicate the CT and DT could be important physical mechanisms of pre-seismic thermal anomalies. [ABSTRACT FROM AUTHOR]

• Energy yield analysis on string level has been combined with infrared thermography. • The average effect of thermal anomalies on the performance of strings is quantified. • This amounts to a loss of 1.16% per module substring containing a thermal anomaly. • No observed correlation between loss on string level and hot-spot temperature. • No obvious correlations between loss on string level and thermal signature category. Methods for quick and accurate detection and diagnosis of defects in PV systems are increasingly important as the global photovoltaic (PV) capacity continues to grow at a rapid pace. Two of the most used methods for defect detection involve aerial infrared thermography and data analysis of production data. In this work, we combine the two methods to analyze two utility scale PV plants, providing new understanding about the two methods. We report on the percentage and distribution of thermal anomalies of different categories and quantify their relationship with performance on string level. We find that the most important parameter for determining production losses on string level is the number of module substrings containing thermal anomalies. Due to the large variability of the effect of different thermal signatures, as well as uncertainties in the estimate of the string performance, we find no clear correlation between performance and thermal signature category or temperature. However, a whole hot cell is the thermal signature that on average has the smallest impact on the power output on string level. Finally, in our data, the performance of a string of 20 modules with 3 bypass diodes is on average reduced by 1.16 ± 0.12% per module substring containing thermal anomalies. [ABSTRACT FROM AUTHOR]

Satellite-derived land surface temperature (LST) has been widely used to understand surface energy exchange and surface radiation budget and is a critical input of earth system models for carbon and water cycles studies at regional to global scales. Spatially and temporally consistent thermal measurements with long historical records are in a high demand to understand the biophysical changes of Earth surfaces. The current monthly LST products' spatial resolutions are relatively coarse and the temporal and spatial consistency could be interrupted by the presence of clouds and satellite orbit limitations. This study develops a diurnal temperature cycle (DTC) model-based approach from MODIS observations that are suitable for constructing the long-term and near-global coverage of monthly LSTs at 1 km to fill these data gaps. The new approach allows us to estimate temporally representative 24-hr mean and maximum temperatures in a diurnal cycle of each month. We performed an inter-comparison among satellite-based data, including DTC-based MODIS estimates, the simple composite of four MODIS overpasses, and the hourly geostationary observations (GEO), and also assessed the satellite-based LST against in-situ LSTs from FLUXNET globally. Our proposed DTC-based mean LSTs outperformed the other two satellite estimates from the simple composite and GEO, showing a mean difference of 0.3 °C and an RMSE of 2.2 °C relative to the in-situ measurements. Moreover, we illustrate an application that explores the relationship between the DTC-based monthly LSTs and the soil moisture anomalies across the United States. The monthly maximum LSTs estimated from DTC scheme show higher sensitivity to droughts than the monthly mean. In sum, the improved monthly LST dataset using DTC scheme can enhance our understanding of the thermal dynamics resulting from land–atmosphere interaction across the local, regional, and global scales. [ABSTRACT FROM AUTHOR]

Multiple parameters (brightness temperature, soil moisture, surface latent heat flux, surface air temperature and carbon monoxide) before and after the 2015 Nepal M7.8 Gorkha main earthquake and M7.3 Dolakha aftershock were analysed using satellite observation data. The thermal anomalies from optical and microwave data appear about two months prior to the 2015 Gorkha earthquake. Some of the parameters show anomalous changes at different altitudes about 20 days prior to the main earthquake event and 10 days prior to the strong aftershock. Our results show that pre-earthquake anomalous signals propagate from the in situ to the top of atmosphere, and the anomalies in the atmosphere often observed prior to an impending earthquake. The changes on the land surface and corresponding changes in meteorological and atmospheric parameters show existence of strong coupling during the seismogenic period, although the transfer mechanism of seismic/electromagnetic is still has to be investigated and understood. [ABSTRACT FROM AUTHOR]

Climate-induced warming events increasingly threaten coral reefs, heightening the need for accurate quantification of baseline temperatures and thermal stress in these ecosystems. To assess the strengths and weaknesses of NOAA satellite sea surface temperature and in situ measurements, we compared 5 yr of these data on Kiritimati atoll, in the central equatorial Pacific. We find that (1) satellite measurements were similar to in situ measurements (~ 10 m depth), albeit slightly warmer, with measurements converging once above Kiritimati's maximum monthly mean; (2) in situ loggers detected subsurface cooling events missed by satellites; (3) thermal baselines and anomalies were consistent around the island; and (4) in situ degree heating week (DHW) calculations were most comparable to NOAA DHWs when calculated using NOAA's climatology. These results suggest that NOAA's satellite products accurately reflect conditions on central Pacific reefs, but that in situ measurements can identify localized events, such as subsurface upwelling, that may be ecologically relevant for corals. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Thermal anomaly, as an earthquake precursory, is widely confirmed. • To characterize the thermal anomalies, Robust Satellite Technique was applied. • The results confirmed the existence of thermal anomalies related to the earthquake. • The RST is a sensitive approach to detect the Earth's thermal anomalies. Abstract Employing an efficient and robust prediction system along with early warnings is useful to reduce the effects of devastating earthquakes. Thermal anomaly, as an earthquake precursory, is widely confirmed. In this study, to characterize the thermal anomalies within a 10-year specific observation interval of Land Surface Temperature (LST), satellite data products obtained from MODIS-Aqua (March 16th to May 16th, every year from 2004 to 2013) were analyzed using Robust Satellite Technique (RST) method. The Saravan earthquake (April 16th, 2013, M W = 7.8, Iran) were used for validation phase, and the year 2012, as a relatively seismically unperturbed year (no earthquakes with Mw > 3.5 regarding target time and region), was taken for confutation phase. For the first time, to reduce the effects of the topography with respect to vegetation cover, using unsupervised classification, the study area was divided into the low and high elevation regions. The results of the present study showed the Significant Sequences of LST Anomalies (SSLAs) from several days before and immediately after the Saravan earthquake appeared in the north, south, and center of the study area. However, no anomalies were observed in a seismically unperturbed year (2012). Therefore, the results confirmed the existence of space-time thermal anomalies related to destructive earthquakes and revealed that the RST method is a reliable approach to detect disturbances of the Earth's thermal emission. [ABSTRACT FROM AUTHOR]