1,720,993 research outputs found
A rst-based cloud mask for fire-related applications
No full textSatellite-based algorithms for fire detection and monitoring are generally applied after a preliminary phase of cloud-affected pixel identification in order to process only clear sky pixels. Performances of cloud masks usually available for satellite data are generally not suitable in fire-related applications because such products have been formerly developed for meteorological and/or climatological purposes. A not suitable cloud mask may be so responsible for omission errors, excluding cloudy contaminated pixels from further analysis, not only in case of opaque clouds, but also in the presence of semi-transparent clouds which, indeed, could permit a signal affected by fires to reach a satellite sensor. Conversely, if a cloud mask let reflective clouds out, false positives may be detected by a fire detection algorithm, due to their effect in the medium infrared (MIR) band. Since the “2nd Workshop on Geostationary Fire Monitoring and Applications”, the importance of a cloud mask tailored to fire-related applications has been clearly highlighted and our experience gained during several real time validation campaigns of the RST-FIRES algorithm (Robust Satellite Technique for Fire detection) confirmed that. In particular, in the first implementation of RST-FIRES on MSGSEVIRI data, the algorithm was applied only to pixels not declared as “cloudy” by the EUMETSAT CLM product. Unfortunately, CLM product showed to be not suitable for fire applications mainly because slipped off reflective clouds. In order to increase the reliability of the cloud detection phase, CLM product was combined with the RST-based OCA (One-channel Cloud-detection Approach) algorithm, only applied to two channels (one in the visible and the other one in the thermal infrared) so that it was indicated as OCA VIS-TIR. The higher reliability of this combined cloud detection scheme, as compared with the exclusive use of CLM product, showed to minimize false positives, while increasing omission errors because additional smoky pixels were flagged as “cloudy” and events under transparent clouds were undetected. This led us to develop a multispectral RST-based cloud detection scheme specifically tailored for fire-related applications. It was developed for discriminating spectral characteristics of different types of clouds, smoke, and clear-sky pixels following the heritage of the RST-based OCA VIS-TIR algorithm. The new cloud mask, named OCA MULTI-SPECTRAL, was preliminarily tested in the case of fire-affected pixels which, despite a strong MIR signal, were not detected because declared “cloudy” by the present scheme of cloud detection within the RST-FIRES system, based, as before mentioned, on the combination of EUMETSAT CLM product and OCA VISTIR. Performances of OCA MULTI-SPECTRAL have been also evaluated in comparison with the ones of the present cloud detection scheme. Some examples will be shown and discussed in this paper
Robust satellite techniques (RST) for seismically active areas monitoring: the case of 21st May, 2003 Boumerdes/Thenia (Algeria) earthquake
No full textIn the last decades, several authors have claimed a space-time correlation between increases of Earth's emitted Thermal Infra-Red (TIR) radiation and earthquake activity interpreting such TIR signals as seismic precursors. The main problems of such studies regard data analysis and interpretation, which are often done without a validation/confutation test. In this context, a robust data analysis technique (RST, i.e. Robust Satellite Techniques) was developed which permits a statistically based definition of an "anomaly" and uses a validation/confutation approach. This technique was already applied to satellite TIR surveys in seismic regions for tens of earthquakes occurred in Europe, Asia and America. In this work, the RST approach has been applied for the first time to the African region to assess its potentialities in different geographical and climatic conditions. Eight years of Meteosat TIR observations have been analyzed in order to characterize the TIR signal behaviour in absence of significant seismic activity. Boumerdes/Thenia (Algeria) earthquake (occurred on 21th May 2003, Mb= 6.8) has been considered as test case for validation purpose, while a relatively unperturbed period (no earthquakes with Mbges4) has been analyzed in the confutation phase. The results show in the area of interest positive space-time persistent TIR anomalies about one month before the main shock (validation). Such anomalies generally overlap the principal tectonic lineaments of the region, sometimes focusing in the vicinity of the earthquake epicentre. No significant (in terms of relative intensity and space-time pemstence) TIR anomalies were detected during less seismically perturbed periods (confutation)
Abrupt change in greenhouse gases emission rate as a possible genetic model of TIR anomalies observed from satellite in Earthquake active regions
No full textSeveral studies have been performed, in the past 25 years, on the basis of Thermal Infrared (TIR) satellite imagery, which suggest the existence of a relation between TIR anomalies and earthquake preparatory phenomena. Among the various genetic models, the increase of green-house gas (such as CO2, CH4, etc.) emission rates, have been suggested to explain the appearance of anomalous TIR signal transients in some relation with the place and time of earthquake occurrence. In
this
greenhouse gas emission can not be excluded among the main causes of TIR anomalies occurrence
paper the idea that an enhanced observed close to earthquake
is supported by different independent
observations: 1) The increase of Earth’s TIR radiation to be expected as a consequence of an increase (from 2 to 20 times its normal level) of atmospheric CO2 concentration has been evaluated by using MODTRAN Radiative Transfer code. A significant (more than 10 K in brightness temperature) TIR signal increase is to be expected as soon as local CO2 concentration becomes 3 times higher. 2) TIR anomalies observed by applying the well known Robust Satellite Technique (RST) to long historical series of Meteosat TIR observations performed over seismic areas characterized by different prevailing degassing activity: in areas dominated by diffusing gases heavier than air (as CO2) anomalous TIR patterns seem to clearly follow morphological lineaments (e.g. tectonic faults); in areas dominated by diffusing gases lighter than air (as CH4) anomalous TIR patterns flood wide areas, diffusing
around with morphological lineaments
A decade of RST applications to seismically active areas monitoring by TIR satellite observations
No full textIn order to discriminate normal (i.e. related to the change of natural factor and/or observation conditions) fluctuations of Earth’s emitted Thermal Infrared (TIR) radiation from anomalous transients possibly associated to earthquake occurrence, since 2001 a Robust Satellite Technique (RST; Tramutoli, 1998; 2005; 2007) approach has been applied. After the first tests performed by using TIR sensors on board polar satellites it was quite evident the advantage offered by the use of geostationary platforms in studies like these, which do not require the higher spatial resolution offered by polar sensors but strongly benefit of the reduced “observational noise” (in terms of view angles, ground resolution cells stability and image collection times) guaranteed by geostationary platforms (e.g. Filizzola et al., 2004). Since then, tens of earthquakes occurred in Europe, Asia, Africa and America have been studied by analyzing long terms (up to 10 years and more) time series of TIR images acquired by geostationary satellites (like MFG, MSG, GOES, MTSAT). In all cases a validation/confutation approach was always applied in order to verify the presence/absence of anomalous space-time TIR transients in presence/absence of significant seismic activity. Main achievements in more than 10 years using RST approach for seismic area monitoring will be presented and discussed by comparing results obtained on different earthquakes which happened in different geographic areas and using different satellite sensors
Robust Satellite Techniques (RST) For Saharan Dust Monitoring
No full textSaharan dust has been particularly studied for its relevant climatological implications and for damage mitigation purposes. Due to dust-clouds optical properties - which are very similar to those exhibited by low/thin meteorological clouds, as well as by clouds fringes - their identification during the day is still the main problem which is made more intricate because of the fairly high visible reflectance of Saharan background. In this paper the problem of identifying Saharan dust clouds, distinguishing them from small, low or thin, meteorological clouds, is faced by combining spatial and spectral signatures in the visible and thermal infrared AVHRR remotely sensed radiances. Spatial structure analysis, performed on AVHRR (Advanced Very High Resolution Radiometer) imagery, for different typologies of meteorological and dust clouds over Saharan desert background, permitted to explain why discrimination strategies based on sounders, like METEOSAT-IR, having spatial resolution lower than 5 km, become effective only at larger scale (with better results beyond 60 km). In the main time a more marked spatial signature, at a scale shorter than 5 km, has been recognized which suggests that an early detection of sandstorm sources could be possible, in daytime, by using sounders having at least 1 km spatial resolution in the visible spectral range. A new algorithm is proposed which mainly relies on a preliminary variogram analysis of the peculiar texture exhibited, in the daytime, by low height dust clouds and their shadows over the desert background. Reference fields computed following the general RAT (Robust AVHRR Technique) approach - now named RST) - have been used in order to automatically identify llocal (i.e. depending on the location and on the time of observation) thresholds to be applied in the detection phases both to visible and thermal infrared radiances. Global coverage, low-cost and high repetition rate offered by NOAA-AVHRR, EOS-MODIS and MSG-SEVIRI satellite packages, have been considered for possible implementations in an operational monitoring context and their performance evaluated even by comparison with traditional (single image, fixed threshold) techniques. Higher sensitivity, very low false alarm rate, easy exportability to different geographic areas as well as different satellite sensors, are the main advantage exhibited by the proposed method after tests performed on several events occurred in Northern Africa and Middle East
A New Approach for Detecting and Monitoring Saharan Dusts from Space
No full textThe Saharan region has long been indicated as the main source in the world of soil dust in the atmosphere. Saharan dust storms are particularly investigated because they represent a potential risk for human health and cause damages and disruptions to the transport routes and communication. They can have direct implications (strictly related to the desertification processes affecting the Sub Saharan region) on the Earth’s climatic system and/or on the precipitation regimes. In recent years, in addition to the ground monitoring systems, several satellite techniques have been proposed to detect and monitor Saharan dust clouds. The success of these methodologies, as those exploiting the reverse absorption behaviour shown by silicate particles, in comparison with ice crystals and water droplets, at 11 and 12 μm wavelengths (split-window), is strongly dependent on the observational conditions (day/night, land/sea, etc.) and on the specific aerosol properties (mainly size distribution and complex refractive index). In particular, although dust and meteorological clouds generally show a different spectral behaviour in the split window bands, an effective discrimination of these features still represent a major issue. In this paper, a Robust Satellite data analysis Technique (RST), which already highlighted good performances in detecting desert dust aerosol, has been further tested, analyzing an important Saharan dust event affecting Mediterranean basin in May 2010, with results compared to those provided by two traditional split window methods. Outcomes of this study, achieved using, for the first time, daytime infrared MSG-SEVIRI (Meteosat Second Generation-Spinning Enhanced Visible and Infra-red Imager) data, confirm that RST, thanks to a good trade-off between sensitivity and reliability of detection, may profitably be used for monitoring Saharan dust events from space in different observational conditions
RST-FIRES, an exportable algorithm for early-fire detection and monitoring: description, implementation, and field validation in the case of the MSG-SEVIRI sensor
No full textWildfires are a worldwide phenomenon with local and global effects. Many satellite-based methods for fire detection and monitoring have been developed to exploit data acquired by sensors onboard polar orbiting platforms. Their relatively low temporal resolution (hours) is, however, decidedly not adequate for detecting short-living events or fires characterised by a marked diurnal cycle and rapid evolution times. Geostationary satellites have very high temporal resolution of 30 to 2.5 min and could, in principle, be more suitable for providing timely alerts and facilitating possible mitigation actions. However, such short revisit times are coupled with spatial resolutions of 3–5 km, which are coarser than those of the polar orbiting sensors generally having 1 km capability in the infrared region. This could represent a significant limitation for small fire detection and precise localization. However, unlike polar orbiting systems, the geostationary attitude assures very stable observational conditions at the pixel level, including fixed view angles, same time of day, and same ground resolution cell dimensions. This can be crucial for fire-detection methods based on multi-temporal analyses. This work describes in detail the Robust Satellite Techniques for FIRES detection and monitoring (RST-FIRES), a multi-temporal change-detection technique, and its application to the data of Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board the Meteosat Second Generation (MSG) platform. Its performance in terms of reliability and sensitivity was verified by > 20,000 SEVIRI images collected throughout the day during a four-year-collaboration with the regional Civil Protection Departments and other Local Authorities of two Italian regions which provided about 950 near real-time ground and aerial checks of the RST-FIRES detections. The results indicate a mean commission error rate of 18%, ranging from 3% to 30% according to the specific experimental campaign, with an average omission error of 44%, ranging from 3% to 66% depending on the campaign and the validation source used. This study fully demonstrates the added value of the RST-FIRES technique for the early warning of fire events. During the considered validation campaigns, RST-FIRES provided the sole fire alert in 348 cases; in further 227 cases, its warnings were given > 1 h before any other source of information was provided. Finally, this paper presents and discusses a comparison among RST-FIRES and other SEVIRI-based fire detection products. On the whole, RST-FIRES is shown to be 3 to 70 times more sensitive than all of the other considered SEVIRI-based products. This satisfactory result was not completely unexpected, considering the quite high false positive rate exhibited by RST-FIRES and the fact that other algorithms were designed to work in a wider area, from continental to the SEVIRI full disk
The use of MSG-SEVIRI for rapid detection of security-related events
No full textNew fields of application have been discovered for data acquired by geostationary satellite sensors,
like MSG-SEVIRI (Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager),
beyond their original meteorological and climatologic scopes. Unexpected MSG-SEVIRI potentials
have been, for instance, revealed in different security-related applications. In fact, several accidents
(e.g., pipeline sabotages, bombing, etc.), responsible for injuries to citizens and damages to critical
infrastructures, often cannot be avoid or foreseen, but a rapid detection of their effects may allow to
timely intervene and prevent more terrible consequences. Meteorological satellites like MSG-SEVIRI,
characterized by a high temporal repetition rate, give the possibility to rapidly detect abrupt thermal
transients related to dangerous explosions. Anyway, if MSG-SEVIRI data may provide information at
an adequate temporal resolution (from 15 to 5 minutes, over areas acquired in Rapid Scanning
Service mode), a suitable technique is to be used to identify, in a reliable fashion (i.e., no false
alarms), actual accidents. The multi-temporal change detection algorithm, RST (Robust Satellite
Techniques), may assure such a reliability because it is based on the characterization (in space and
time) of the medium infrared (MIR) satellite signal, so that it is possible, for example, to distinguish
“temporary heat sources” (hot spots related to actual accidents) from “permanent heat sources” (e.g.,
normally hot areas in correspondence of refineries chimneys).
A processing chain, based on the RST approach, has been also developed for automatically
identifying, on MSG-SEVIRI images, harmful events. Maps of thermal anomalies may be generated
every 15 minutes over a selected area, together with *.kml files for a rapid visualization of the accident
position on GoogleEarth® environment. RST applied to MSG-SEVIRI in security field has been tested
in different contexts and involved infrastructures such as the case of the Moscow gas pipeline
explosion (9th May 2009), attacks to civil and military targets in Libya during operation “Odyssey
Dawn” and 2011 civil war as well as several cases of Iraqi pipeline sabotages. In detecting such
sabotages, RST applied to MSG-SEVIRI data not only demonstrated its capabilities in detecting
accidents without false alarms in areas (like Iraq) hosting many refineries, but also in giving “precise
information” about event time occurrence and, sometimes, even in “correcting” ground reports. In this
paper some examples will be shown
On the potential of Robust Satellite Techniques (RST-FIRES) for forest fire detection and monitoring
No full textSatellite remote sensing has become an important tool for fire detection and monitoring, thanks to
several satellite platforms orbiting around Earth providing repetitive information at a global scale
and generally at low cost. Several algorithms have been proposed in order to detect forest fires
from space. Multi-channel threshold algorithms use the MIR channel (around 3.5-4.0mm) of
satellite sensors like AVHRR (Advanced Very High Resolution Radiometer) in order to identify
potential fires, the TIR channel (around 11 μm) in order to remove possible clouds, and spectral
difference temperature T=TMIR-TTIR in order to isolate fires from background. Contextual
algorithms use, instead, initial thresholds in order to identify potential fires, and compute the
spatial average and standard deviation of the spectral difference TMIR-TTIR for background pixels ,
in order to confirm or reject fires. These methods perform well under specific obervational
conditons, but generally show several limitations. In this paper an original multi-temporal
approach for forest fire detection and monitoring, named RST-FIRES, will be tested in different
fire regimes (winter/summer fires), in comparison with traditional satellite methods. Moreover, its
potential in timely detecting the beginning of fires, using data provided by geostationary satellites
like MSG-SEVIRI (Meteosat Second Generation-Spinning Enhanced Visible and Infrared
Imager), will also be assessed and discussed
Identification of dust outbreaks on infrared msg-seviri data by using a Robust Satellite Technique (RST)
Full text linkDust storms are meteorological phenomena of great interest for scientific community because of their potential impact on climate changes, for the risk that may pose to human health and due to other issues as desertification processes and reduction of the agricultural production. Satellite remote sensing, thanks to global coverage, high frequency of observation and low cost data, may highly contribute in monitoring these phenomena, provided that proper detection methods are used.
In this work, the known Robust Satellite Techniques (RST) multitemporal approach, used for studying and monitoring several natural/environmental hazards, is tested on some important dust events affecting Mediterranean region in May 2004 and Arabian Peninsula in February 2008. To perform this study, data provided by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) have been processed, comparing the generated dust maps to some independent satellite-based aerosol products. Outcomes of this work show that the RST technique can be profitably used for detecting dust outbreaks from space, providing information also about areas characterized by a different probability of dust presence. They encourage further improvements of this technique in view of its possible implementation in the framework of operational warning systems
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