1,721,028 research outputs found
Improving the RST-OIL algorithm for oil spill detection under severe sun glint conditions
Full text linkIn 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
Mount Etna field and laboratory spectroscopy (300-2500 nm): implications for Mars exploration.
No full textThe VIIRS-Based RST-FLARE configuration: The Val d'Agri Oil Center Gas Flaring Investigation in between 2015-2019
Full text linkThe 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
Robust Satellite Techniques for Detecting Preseismic Thermal Anomalies
No full textSeveral satellite techniques have been proposed in recent decades to monitor geophysical phenomena possibly associated with earthquakes. Among them, several studies suggest the existence of a relation between space–time anomalies of Earth’s thermally emitted radiation (usually referred as “TIR anomalies”) and earthquake occurrence.
More recently a robust approach has been proposed which seems to be suitable for recognizing space–time anomalies in the measured TIR signal even in the presence of highly variable contributions coming from Earth’s surface and atmosphere (due for instance to meteorological factors) as well as from specific observational conditions. This Chapter presents that approach together with a modality of its implementation in the framework of an operational multiparametric system for a time‐Dependent Assessment of Seismic Hazard (t‐DASH)
AMPLIFICAZIONE DI SITO IN ARGILLE,CONTENUTO IN CACO3 e loro riconoscimento da piattaforma aerea
No full textSignificant Cases of Preseismic Thermal Infrared Anomalies
No full textFrom appropriate identification and real‐time integration of independent observations we expect to improve significantly our present capability to assess the seismic hazard in the short term (from weeks to days before an earthquake). One specific observation (e.g. anomaly in one parameter) sometimes can be used as a trigger or as a reference point (in the space and/or time domain) for activating/improving analysis on other independent parameters whose systematic computation otherwise could be computationally very expensive or impossible. In this chapter, we briefly exemplify these advantages, and the utility of the Robust Satellite Technique (RST) approach. The RST data analysis approach has been implemented on daily TIR satellite records collected over three different
areas (Italy, Greece, and Turkey) by the geostationary satellite sensor Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat Second Generation (MSG) satellite, in order to evaluate its possible contribution to an improved multiparametric system for a time‐dependent assessment of seismic hazard
Field and laboratory spectroscopy (300-2500 nm) on Mount Etna, a possible terrestrial analogue of Mars surface rocks
No full textStatistical Correlation Analysis Between Thermal Infrared Anomalies Observed From MTSATs and Large Earthquakes Occurred in Japan (2005–2015)
No full textThe literature often reports space–time relations between the abnormal variations of different kinds of nonseismological (i.e., geophysical, geochemical, and atmospheric) parameters and the occurrence of earthquakes. The integration of such observations with seismological ones could improve
the quality of the seismic hazard assessment in the medium-short term (months to days). Each considered parameter has, in principle, its capabilities to provide useful (and utilizable) information about seismic processes. Therefore, to define a system based on different observations, the first step is to estimate the
informative contribution that each considered parameter could provide. In this paper, we will evaluate the potential of Significant Sequence of Thermal Anomalies (SSTAs). In particular, we adopted the broadly used Robust Satellite Techniques (RST) data analysis methodology to identify SSTAs over 11 years (June 2005 to December 2015) of nighttime satellite images acquired by MTSAT satellites over Japan. Aiming at reducing the false-positive rate, we introduced and tested an innovative configuration of the RST, whichis here presented. We executed a correlation analysis between SSTAs and Japanese earthquakes with
MJMA ≥ 6 by applying suitable constraints concerning space, time, and magnitude. The analysis highlights (a) the occurrence of just 29 SSTAs in the 11-year period of observation, (b) 18 SSTAs (i.e., 62%) occur in an apparent space–time relation to earthquakes, and (c) 13 of them occur before the quake. Results of the random test analysis, based on error diagrams, confirm a noncasual correlation between “RST-based satellite thermal anomalies” and earthquake occurrences. In particular, for MJMA ≥ 6.5 earthquakes, probability gain is up to better than 4.3 as compared with the random guess
Monitoring the Agung (Indonesia) Ash Plume of November 2017 by Means of Infrared Himawari 8 Data
Full text linkThe 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
- …
