Implementation of Robust Satellite Techniques for Volcanoes on ASTER Data under the Google Earth Engine Platform

The RST (Robust Satellite Techniques) approach is a multi-temporal scheme of satellite data analysis widely used to investigate and monitor thermal volcanic activity from space through high temporal resolution data from sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Spinning Enhanced Visible and Infrared Imager (SEVIRI). In this work, we present the results of the preliminary RST algorithm implementation to thermal infrared (TIR) data, at 90 m spatial resolution, from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Results achieved under the Google Earth Engine (GEE) environment, by analyzing 20 years of satellite observations over three active volcanoes (i.e., Etna, Shishaldin and Shinmoedake) located in different geographic areas, show that the RST-based system, hereafter named RASTer, detected a higher (around 25% more) number of thermal anomalies than the well-established ASTER Volcano Archive (AVA). Despite the availability of a less populated dataset than other sensors, the RST implementation on ASTER data guarantees an efficient identification and mapping of volcanic thermal features even of a low-intensity level. To improve the temporal continuity of the active volcanoes monitoring, the possibility of exploiting RASTer is here addressed, in the perspective of an operational multi-satellite observing system. The latter could include mid-high spatial resolution satellite data (e.g., Sentinel-2/MSI, Landsat-8/OLI), as well as those at higher-temporal (lower spatial) resolution (e.g., EOS/MODIS, Suomi-NPP/VIIRS, Sentinel-3/SLSTR), for which RASTer could provide useful algorithm’s validation and training dataset

From visual comparison to robust satellite techniques: 30 years of thermal infrared satellite data analyses for the study of earthquake preparation phases

This review paper reports the main contributions and results achieved after more than 30 years of studies on the possible relationships among space-time variation of Earth’s thermally emitted radiation, measured by satellite sensors operating in the Thermal InfraRed (TIR) spectral range (8-14 m), and earthquake occurrence. Focus will be given on the different existing methods/models to: 1) discriminate a possible pre-seismic TIR anomaly from all the other TIR signal fluctuations; 2) correlate such anomalies with space, time and magnitude of earthquakes; 3) physically justify such a correlation

Optimal Setting of Earthquake-Related Ionospheric TEC (Total Electron Content) Anomalies Detection Methods: Long-Term Validation over the Italian Region

Over the last decade, thanks to the availability of historical satellite observations that have begun to be significantly large and thanks to the exponential growth of artificial intelligence techniques, many advances have been made in the detection of geophysical parameters such as seismic-related anomalies. In this study, the variations of the ionospheric Total Electron Content (TEC), one of the main parameters historically proposed as a seismic-connected indicator, are analyzed. To make a statistically robust analysis of the complex phenomena involved, we propose a completely innovative machine-learning approach developed in the R programming language. Through this approach, an optimal setting of the multitude of methodological inputs currently proposed for the detection of ionospheric anomalies is performed. The setting is optimized by analyzing, for the first time, multi-year—mostly twenty-year—time series of TEC satellite data measured by global navigation satellite systems (GNSS) over the Italian region, matched with the corresponding multi-year time series of seismic events. Seismic events including all the countries of the Mediterranean area, up to Turkey, are involved in the analysis. Tens of thousands of possible combinations of input methodological parameters are simulated and classified according to pre-established criteria. Several inputs examined return clear results. These results combined with each other highlight the presence of anomalous seismic-related sequences that have an extremely low probability of having been detected randomly (up to 2 out of 1 million). The anomalies identified represent the most anomalous behaviors of the TEC recorded during the entire period under investigation (e.g., 20 years). Some of the main conclusions are that, at mid-latitudes, ① the detection of seismic-TEC anomalies can be more efficient looking for punctual rather than persistent phenomena; ② the optimal thresholds for the identification of co-seismic anomalies can assume different values depending on type of anomaly (positive or negative) and type of observation; ③ single GNSS receiver data can be useful for capturing local earthquake-ionospheric effects and Global Ionospheric Maps (GIM) data can be functional in detecting large-scale earthquake-ionospheric effects; ④ earthquakes deeper than 50 km are less likely to affect the ionosphere

RST Analysis of Anomalous TIR Sequences in Relation with Earthquakes Occurred in Turkey in the Period 2004–2015

first_pagesettings Open AccessArticle RST Analysis of Anomalous TIR Sequences in Relation with Earthquakes Occurred in Turkey in the Period 2004–2015 by Carolina Filizzola 1ORCID,Angelo Corrado 2,Nicola Genzano 2ORCID,Mariano Lisi 1ORCID,Nicola Pergola 1ORCID,Roberto Colonna 2 andValerio Tramutoli 2,*ORCID 1 Institute of Methodologies for Environmental Analysis, National Research Council, 85050 Potenza, Italy 2 School of Engineering, University of Basilicata, 85100 Potenza, Italy * Author to whom correspondence should be addressed. Academic Editor: Stephan Havemann Remote Sens. 2022, 14(2), 381; https://doi.org/10.3390/rs14020381 Received: 12 November 2021 / Revised: 8 January 2022 / Accepted: 11 January 2022 / Published: 14 January 2022 (This article belongs to the Special Issue Advances in Remote Sensing Systems for Disaster Management and Risk Mitigation) Download PDF Browse Figures Citation Export Abstract The paper provides, for the first time, a long-term (>10 years) analysis of anomalous transients in Earth’s emitted radiation over Turkey and neighbouring regions. The RST (Robust Satellite Techniques) approach is used to identify Significant Sequences of Thermal Anomalies (SSTAs) over about 12 years (May 2004 to October 2015) of night-time MSG-SEVIRI satellite images. The correlation analysis is performed with earthquakes with M ≥ 4, which occurred in the investigated period/region within a pre-defined space-time volume around SSTA occurrences. It confirms, also for Turkey, the possibility to qualify SSTAs among the candidate parameters of a multi-parametric system for time-Dependent Assessment of Seismic Hazard (t-DASH). After analysing about 4000 images (about 400 million of single satellite records), just 155 SSTAs (about 4 every 100 images) were isolated; 115 (74% out of the total) resulted in earthquake-related (false-positive rate 26%). Results of the error diagram confirms a non-casual correlation between RST-based SSTAs and earthquake occurrences, with probability gain values up to 2.2 in comparison with the random guess. The analysis, separately performed on Turkish areas characterized by different faults and earthquakes densities, demonstrates the SSTA correlation with a dynamic seismicity more than with static tectonic settings

Landslides Detection and Mapping with an Advanced Multi-Temporal Satellite Optical Technique

Landslides are catastrophic natural phenomena occurring as a consequence of climatic, tectonic, and human activities, sometimes combined among them. Mostly due to climate change effects, the frequency of occurrence of these events has quickly grown in recent years, with a consequent increase in related damage, both in terms of loss of human life and effects on the involved infrastructures. Therefore, implementing properly actions to mitigate consequences from slope instability is fundamental to reduce their impact on society. Satellite systems, thanks to the advantages offered by their global view and sampling repetition capability, have proven to be valid tools to be used for these activities in addition to traditional techniques based on in situ measurements. In this work, we propose an advanced multitemporal technique aimed at identifying and mapping landslides using satellite-derived land cover information. Data acquired by the Multispectral Instrument (MSI) sensor aboard the Copernicus Sentinel-2 platforms were used to investigate a landslide affecting Pomarico city (southern Italy) in January 2019. Results achieved indicate the capability of the proposed methodology in identifying, with a good trade-off between reliability and sensitivity, the area affected by the landslide not just immediately after the event, but also a few months later. The technique was implemented within the Google Earth Engine Platform, so that it is completely automatic and could be applied everywhere. Therefore, its potential for supporting mitigation activities of landslide risks is evident

Mt. Etna Paroxysms of February–April 2021 Monitored and Quantified through a Multi-Platform Satellite Observing System

On 16 February 2021, an eruptive paroxysm took place at Mt. Etna (Sicily, Italy), after continuous Strombolian activity recorded at summit craters, which intensified in December 2020. This was the first of 17 short, but violent, eruptive events occurring during February–April 2021, mostly at a time interval of about 2–3 days between each other. The paroxysms produced lava fountains (up to 1000 m high), huge tephra columns (up to 10–11 km above sea level), lava and pyroclastic flows, expanding 2–4 km towards East and South. The last event, which was characterised by about 3 days of almost continuous eruptive activity (30 March–1 April), generated the most lasting lava fountain (8–9 h). During some paroxysms, volcanic ash led to the temporary closure of the Vincenzo Bellini Catania International Airport. Heavy ash falls then affected the areas surrounding the volcano, in some cases reaching zones located hundreds of kilometres away from the eruptive vent. In this study, we investigate the Mt. Etna paroxysms mentioned above through a multi-platform satellite system. Results retrieved from Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Spinning Enhanced Visible and Infrared Imager (SEVIRI), starting from outputs of the Robust Satellite Techniques for Volcanoes (RSTVOLC), indicate that the 17th paroxysm (31 March–1 April) was the most powerful, with values of radiative power estimated around 14 GW. Moreover, by the analysis of SEVIRI data, we found that the 5th and 17th paroxysms were the most energetic. The Multispectral Instrument (MSI) and the Operational Land Imager (OLI), providing shortwave infrared (SWIR) data at 20/30 m spatial resolution, enabled an accurate localisation of active vents and the mapping of the areas inundated by lava flows. In addition, according to the Normalized Hotspot Indices (NHI) tool, the 1st and 3rd paroxysm (18 and 28 February) generated the largest thermal anomaly at Mt. Etna after June 2013, when Landsat-8 OLI data became available. Despite the impact of clouds/plumes, pixel saturation, and other factors (e.g., satellite viewing geometry) on thermal anomaly identification, the used multi-sensor approach allowed us to retrieve quantitative information about the 17 paroxysms occurring at Mt. Etna. This approach could support scientists in better interpreting changes in thermal activity, which could lead to future and more dangerous eruptions

RST analysis of MSG-SEVIRI TIR radiances at the time of the Abruzzo 6 April 2009 earthquake

Space-time fluctuations of Earth's emitted Thermal Infrared (TIR) radiation have been observed from satellite months to weeks before earthquakes occurrence. The general RST approach has been proposed in order to discriminate normal (i.e. related to the change of natural factor and/or observation conditions) TIR signal fluctuations from anomalous signal transient possibly associated to earthquake occurrence. In this work RST approach is applied to the Abruzzo 6 April 2009 event (M(L)=5.8) by using for the first time MSG-SEVIRI (Meteosat Second Generation -Spinning Enhanced Visible and Infrared Imager) thermal infrared observations. A validation/confutation analysis has been performed in order to verify the presence/absence of anomalous space-time TIR transients in the presence/absence of significant seismic activity. March-April 2009 has been analyzed for validation purposes. Relatively unperturbed periods (no earthquakes with M(L)>= 5) have been taken for confutation. A specific TIR anomalies space-time persistence analysis as well as a cloud coverage distribution test have been introduced in order to eliminate artifacts and outliers both in the validation and confutation phases. Preliminary results show clear differences in TIR anomalies occurrence during the periods used for validation and confutation purposes. Quite clear TIR anomalies appear also to mark main tectonic lines related to the preparatory phases of others, low magnitude (M(L)similar to 4) earthquakes, occurred in the area

Using RST approach and EOS-MODIS radiances for monitoring seismically active regions: a study on the 6 April 2009 Abruzzo earthquake

In the last few years, Robust Satellite data analysis Techniques (RST) have been proposed and successfully applied for monitoring major natural and environmental risks. Among the various fields of application, RST analysis has been used as a suitable tool for satellite TIR surveys in seismically active regions, devoted to detect and monitor thermal anomalies possibly related to earthquake occurrence. In this work, RST has been applied, for the first time, to thermal infrared observations collected by MODIS (Moderate Resolution Imaging Spectroradiometer) - the sensor onboard EOS (Earth Observing System) satellites - in the case of Abruzzo (Italy) earthquake occurred on 6 April 2009 (M(L)similar to 5.8). First achievements, shown in this work, seem to confirm the sensitivity of the proposed approach in detecting perturbations of the Earths emission thermal field few days before the event. The reliability of such results, based on the analysis of 10 years of MODIS observations, seems to be supported by the results achieved analyzing the same area in similar observation conditions but in seismically unperturbed periods (no earthquakes with M(L)>= 5) that will be also presente