Improving the RST-OIL algorithm for oil spill detection under severe sun glint conditions

In recent years, the risk related to oil spill accidents has significantly increased due to a global growth in offshore extraction and oil maritime transport. To ensure sea safety, the implementation of a monitoring system able to provide real-time coverage of large areas and a timely alarm in case of accidents is of major importance. Satellite remote sensing, thanks to its inherent peculiarities, has become an essential component in such a system. Recently, the general Robust Satellite Technique (RST) approach has been successfully applied to oil spill detection (RST-OIL) using optical band satellite data. In this paper, an advanced configuration of RST-OIL is presented, and we aim to extend its applicability to a larger set of observation conditions, referring, in particular, to those in the presence of severe sun glint effects that generate some detection limits to the RST-OIL standard algorithm. To test such a configuration, the DeepWater Horizon platform accident from April 2010 was selected as a test case. We analyzed a time series of Moderate Resolution Imaging Spectroradiometer (MODIS) images that are usually significantly affected by sun glint in the Gulf of Mexico area. The accuracy of the achieved results was evaluated for comparison with a well-established satellite methodology based on microwave data, which confirms the potential of the proposed approach in identifying the oil presence on the scene with good accuracy and reliability, even in these severe conditions

The VIIRS-Based RST-FLARE configuration: The Val d'Agri Oil Center Gas Flaring Investigation in between 2015-2019

The RST (Robust Satellite Techniques)-FLARE algorithm is a satellite-based method using a multitemporal statistical analysis of nighttime infrared signals strictly related to industrial hotspots, such as gas flares. The algorithm was designed for both identifying and characterizing gas flares in terms of radiant/emissive power. The Val d'Agri Oil Center (COVA) is a gas and oil pre-treatment plant operating for about two decades within an anthropized area of Basilicata region (southern Italy) where it represents a significant potential source of social and environmental impacts. RST-FLARE, developed to study and monitor the gas flaring activity of this site by means of MODIS (Moderate Resolution Imaging Spectroradiometer) data, has exported VIIRS (Visible Infrared Imaging Radiometer Suite) records by exploiting the improved spatial and spectral properties offered by this sensor. In this paper, the VIIRS-based configuration of RST-FLARE is presented and its application on the recent (2015-2019) gas flaring activity at COVA is analyzed and discussed. Its performance in gas flaring characterization is in good agreement with VIIRS Nightfire outputs to which RST-FLARE seems to provide some add-ons. The great consistency of radiant heat estimates computed with both RST-FLARE developed configurations allows proposing a multi-sensor RST-FLARE strategy for a more accurate multi-year analysis of gas flaring

Monitoring the Agung (Indonesia) ash plume of November 2017 by means of infrared Himawari 8 data

The Agung volcano (Bali; Indonesia) erupted in later November 2017 after several years of quiescence. Because of ash emissions, hundreds of flights were cancelled, causing an important air traffic disruption in Indonesia. We investigate those ash emissions from space by applying the RSTASH algorithm for the first time to Himawari-8 data and using an ad hoc implementation scheme to reduce the time of the elaboration processes. Himawari-8 is a new generation Japanese geostationary meteorological satellite, whose AHI (Advanced Himawari Imager) sensor offers improved features, in terms of spectral, spatial and temporal resolution, in comparison with the previous imagers of the MTSAT (Multi-Functional Transport Satellite) series. Those features should guarantee further improvements in monitoring rapidly evolving weather/environmental phenomena. Results of this work show that RSTASH was capable of successfully detecting and tracking the Agung ash plume, despite some limitations (e.g., underestimation of ash coverage under certain conditions; generation of residual artefacts). Moreover, estimates of ash cloud-top height indicate that the monitored plume extended up to an altitude of about 9.3 km above sea level during the period 25 November at 21:10 UTC-26 November at 00:50 UTC. The study demonstrates that RSTASH may give a useful contribution for the operational monitoring of ash clouds over East Asia and the Western Pacific region, well exploiting the 10 min temporal resolution and the spectral features of the Himawari-8 data

Advanced satellite technique for volcanic activity monitoring and early warning

Nowadays, satellite remote sensing is an important tool for volcanic activity monitoring, thanks to several operational satellite platforms providing data everywhere with high observational frequencies and generally at low cost. Among different techniques available, an advanced satellite method, named RST (Robust Satellite Technique), based on the multitemporal analysis of satellite data, has shown a high capability in volcanic activity monitoring. This approach has proved capable of identifying and tracking volcanic ash cloud and of correctly detecting and monitoring volcanic thermal anomalies. This paper analyzes some recent results, obtained applying this approach to the last eruptive events of Mt. Etna using both polar and geostationary satellites. In particular, for the first time, this approach is implemented on the present geostationary platform MSG-SEVIRI, with 15 min of temporal resolution. Preliminary results, together with a future potential of this implementation, are shown and discussed. Moreover, a differential RST index in time domain is also proposed for near real-time application, as a possible contribution to the development of an efficient early warning satellite system for volcanic hazard mitigation

Robust satellite techniques (RST) for the thermal monitoring of earthquake prone areas: the case of Umbria-Marche October, 1997 seismic events

Several authors claim a space-time correlation between increases in Earth’s emitted Thermal Infra-Red (TIR) radiation and earthquake occurrence. The main problems of such studies regard data analysis and interpretation, which are often done without a validation/confutation control. In this context, a robust data analysis technique (RST, i.e. Robust Satellite Techniques) is proposed which permits a statistically based definition of TIR «anomaly » and uses a validation/confutation approach. This technique was already applied to satellite TIR surveys in seismic regions for about twenty earthquakes that occurred in the world. In this work RST is applied for the first time to a time sequence of seismic events. Nine years of Meteosat TIR observations have been analyzed to characterize the unperturbed TIR signal behaviour at specific observation times and locations. The main seismic events of the October 1997 Umbria-Marche sequence have been considered for validation, and relatively unperturbed periods (no earthquakes with Mb ≥ 4) were taken for confutation purposes. Positive time-space persistent TIR anomalies were observed during seismic periods, generally overlapping the principal tectonic lineaments of the region and sometimes focusing on the vicinity of the epicentre. No similar (in terms of relative intensity and space-time persistence) TIR anomalies were detected during seismically unperturbed periods

Seismically active area monitoring by robust TIR satellite techniques: a sensitivity analysis on low magnitude earthquakes in Greece and Turkey

International audienceSpace-time TIR anomalies, observed from months to weeks before earthquake occurrence, have been suggested by several authors as pre-seismic signals. Up to now, such a claimed connection of TIR emission with seismic activity has been considered with some caution by scientific community mainly for the insufficiency of the validation data-sets and the scarce importance attached by those authors to other causes (e.g. meteorological) that, rather than seismic activity, could be responsible for the observed TIR signal fluctuations. A robust satellite data analysis technique (RAT) has been recently proposed which, thanks to a well-founded definition of TIR anomaly, seems to be able to identify anomalous space-time TIR signal transients even in very variable observational (satellite view angle, land topography and coverage, etc.) and natural (e.g. meteorological) conditions. Its possible application to satellite TIR surveys in seismically active regions has been already tested in the case of several earthquakes (Irpinia: 23 November 1980, Athens: 7 September 1999, Izmit: 17 August 1999) of magnitude higher than 5.5 by using a validation/confutation approach, devoted to verify the presence/absence of anomalous space-time TIR transients in the presence/absence of seismic activity. In these cases, a magnitude threshold (generally M In this work, 9 medium-low magnitude (

Age-related male hypogonadism and cognitive impairment in the elderly: Focus on the effects of testosterone replacement therapy on cognition

Background. Epidemiological data report that male hypogonadism may play a role in cognitive impairment in elderly. However, the effect of testosterone replacement therapy (TRT) on cognitive abilities in this cluster of patients has not been well established. Methods. PubMed/MEDLINE, Google Scholar, Cochrane Library, and Web of Science were searched by using free text words and medical subject headings terms related with “male hypogonadism”, “late-onset hypogonadism”, elderly, cognition, “mild cognitive impairment”, memory, “testosterone replacement therapy” used in various combinations according to the specific clinical questions. Original articles, reviews, and randomized controlled trials written in English were selected. Results. A long-term TRT could improve specific cognitive functions, such as verbal and spatial memory, cognitive flexibility, and physical vitality. However, randomized controlled trials do not provide positive results, and in most of the cases TRT might not induce beneficial effects on cognitive function in elderly men. Discussion and conclusions. Since the lengthening of life expectancy, the prevalence rate of cognitive decline in elderly men is expected to increase remarkably over the next decade with considerable healthcare and economical concerns. Therefore, this remains a relevant clinical topic and further investigations are needed for clarifying the role of TRT especially in elderly men with hypogonadism

Hypothesized mechanisms explaining poor prognosis in type 2 diabetes patients with COVID-19: a review

Purpose: Epidemiological data suggest that comorbid patients, mostly those with type 2 diabetes (T2D), are predisposed to poor prognosis in Coronavirus disease 2019 (COVID-19), leading to serious healthcare concerns. The aim of the present manuscript is to review the main relevant mechanisms possibly contributing to worsen the clinical course of COVID-19 in T2D. Results: Poor glucose control, high glycaemic variability and diabetes-related comorbidities at baseline, particularly cardiovascular diseases and obesity, contribute in worsening the prognosis in the above-mentioned cluster of patients. Moreover, both a lower efficient innate immune system response and cytokine dysregulation predispose patients with T2D to impaired viral clearance and more serious pulmonary and systemic inflammation once the SARS-CoV-2 infection occurred. Inconclusive data are currently available for specifically indicate or contraindicate concurrent medications for managing T2D and its comorbidities in infected patients. Conclusions: T2D individuals should be considered as more vulnerable to COVID-19 than general population, and thus require adequate advices about hygienic tips to protect themselves during the pandemic. A careful management of glucose levels and diabetes-related comorbidities remains essential for avoiding further complications, and patient monitoring during the pandemic should be performed also at distance by means of telemedicine. Further studies are needed to clarify whether medications normally used for managing T2D and its associated comorbidities could have a protective or detrimental effect on COVID-19 clinical course

Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

International audienceSoil moisture is an important component of the hydrological cycle. In the framework of modern flood warning systems, the knowledge of soil moisture is crucial, due to the influence on the soil response in terms of infiltration-runoff. Precipitation-runoff processes, in fact, are related to catchment's hydrological conditions before the precipitation. Thus, an estimation of these conditions is of significant importance to improve the reliability of flood warning systems. Combining such information with other weather-related satellite products (i.e. rain rate estimation) might represent a useful exercise in order to improve our capability to handle (and possibly mitigate or prevent) hydro-geological hazards. Remote sensing, in the last few years, has supported several techniques for soil moisture/wetness monitoring. Most of the satellite-based techniques use microwave data, thanks to the all-weather and all-time capability of these data, as well as to their high sensitivity to water content in the soil. On the other hand, microwave data are unfortunately highly affected by the presence of surface roughness or vegetation coverage within the instantaneous satellite field of view (IFOV). Those problems, consequently, strongly limit the efficiency and the reliability of traditional satellite techniques. Recently, using data coming from AMSU (Advanced Microwave Sounding Unit), flying aboard NOAA (National Oceanic and Atmospheric Administration) satellites, a new methodology for soil wetness estimation has been proposed. The proposed index, called Soil Wetness Variation Index (SWVI), developed by a multi-temporal analysis of AMSU records, seems able to reduce the problems related to vegetation and/or roughness effects. Such an approach has been tested, with promising results, on the analysis of some flooding events which occurred in Europe in the past. In this study, results achieved for the HYDROPTIMET test cases will be analysed and discussed in detail. This analysis allows us to evaluate the reliability and the efficiency of the proposed technique in identifying different amounts of soil wetness variations in different observational conditions. In particular, the proposed indicator was able to document the actual effects of meteorological events, in terms of space-time evolution of soil wetness changes, for all the analysed HYDROPTIMET test cases. Moreover, in some circumstances, the SWVI was able to identify the presence of a sort of "early" signal in terms of soil wetness variations, which may be regarded as a timely indication of an anomalous value of soil water content. This evidence suggests the opportunity to use such an index in the pre-operational phases of the modern flood warning systems, in order to improve their forecast capabilities and their reliability

Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

Soil moisture is an important component of the hydrological cycle. In the framework of modern flood warning systems, the knowledge of soil moisture is crucial, due to the influence on the soil response in terms of infiltration-runoff. Precipitation-runoff processes, in fact, are related to catchment's hydrological conditions before the precipitation. Thus, an estimation of these conditions is of significant importance to improve the reliability of flood warning systems. Combining such information with other weather-related satellite products (i.e. rain rate estimation) might represent a useful exercise in order to improve our capability to handle (and possibly mitigate or prevent) hydro-geological hazards. <P style='line-height: 20px;'> Remote sensing, in the last few years, has supported several techniques for soil moisture/wetness monitoring. Most of the satellite-based techniques use microwave data, thanks to the all-weather and all-time capability of these data, as well as to their high sensitivity to water content in the soil. On the other hand, microwave data are unfortunately highly affected by the presence of surface roughness or vegetation coverage within the instantaneous satellite field of view (IFOV). Those problems, consequently, strongly limit the efficiency and the reliability of traditional satellite techniques. <P style='line-height: 20px;'> Recently, using data coming from AMSU (Advanced Microwave Sounding Unit), flying aboard NOAA (National Oceanic and Atmospheric Administration) satellites, a new methodology for soil wetness estimation has been proposed. The proposed index, called Soil Wetness Variation Index (<I>SWVI</I>), developed by a multi-temporal analysis of AMSU records, seems able to reduce the problems related to vegetation and/or roughness effects. Such an approach has been tested, with promising results, on the analysis of some flooding events which occurred in Europe in the past. <P style='line-height: 20px;'> In this study, results achieved for the HYDROPTIMET test cases will be analysed and discussed in detail. This analysis allows us to evaluate the reliability and the efficiency of the proposed technique in identifying different amounts of soil wetness variations in different observational conditions. In particular, the proposed indicator was able to document the actual effects of meteorological events, in terms of space-time evolution of soil wetness changes, for all the analysed HYDROPTIMET test cases. Moreover, in some circumstances, the <I>SWVI</I> was able to identify the presence of a sort of 'early' signal in terms of soil wetness variations, which may be regarded as a timely indication of an anomalous value of soil water content. This evidence suggests the opportunity to use such an index in the pre-operational phases of the modern flood warning systems, in order to improve their forecast capabilities and their reliability