1,721,020 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
Improving flood monitoring by RAT (Robust AVHRR Technique) approach: the case of April 2000 Hungary flood.
No full textIn the past, satellite remote sensing techniques have been widely used within the flood risk management cycle. In particular, there have been many demonstrations of the operational use of satellite data for detailed monitoring and mapping of floods and for post-flood damage assessment. When frequent situation reports are requested (e. g. in the emergency phase or for early warning purposes) to assist civil protection activities, high temporal resolution satellites (mainly meteorological, with revisiting times from hours to minutes) can play a strategic role. In this paper, a new Advanced Very High Resolution Radiometer (AVHRR) technique for monitoring flooded areas is presented. Its performances are evaluated in comparison with other well-known approaches, analysing the flood event that occurred in Hungary during April 2000 involving the Tisza and Timis Rivers. The preliminary results seem to indicate the benefits of such a new technique, especially when different observational conditions are considered. In fact, compared with previously proposed techniques, the proposed approach: (a) is completely automatic (i.e. unsupervised with no need for operator intervention); (b) improves flooded-area detection capabilities strongly reducing false alarms; and (c) automatically discriminates (without the need for ancillary information) flooded areas from permanent water bodies. Moreover, it is globally applicable and, because of the complete independence on the specific satellite platform, is easily exportable to different satellite package
Implementation of a Robust Satellite Technique (RST ASH) On Msg-Seviri Data for timely detection and near real- time monitoring of volcanic ash clouds from space
No full textThe RSTASH algorithm is a specific configuration of the Robust Satellite Techniques (RST) multitemporal approach developed for detecting and tracking ash clouds from space. This algorithm was originally proposed and tested with success on AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) data, and has been recently implemented on data provided by Japanese geostationary satellites (MTSAT). In this work, the preliminary results achieved exporting RSTASH on MSG-SEVIRI (Meteosat Second Generation - Spinning Enhanced Visible and Infrared Imager) data to study the Eyjafjallajökull eruptions of April- May 2010, which caused an unprecedented air traffic disruption in Northern and central Europe, are reported. This study was carried testing RSTASH in critical observational conditions (e.g. high view angles, cold background, frequent and diffuse cloud coverage), using for the first time an optimized configuration of this algorithm for daytime conditions, and assessing its potential in monitoring ash clouds in real time, exploiting the high temporal resolution of SEVIRI (15 minutes). Outcomes of this work show that RSTASH may be profitably used for an automated and accurate identification of ashaffected areas also at high latitude regions. Accurate detection, in fact, is a mandatory step before to characterize ash clouds from a quantitative point of view by means of retrieval analyses. These results encourage a full implementation of this algorithm on SEVIRI data, in view of a its possible usage in operational contexts
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)
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Implementation of the RST (Robust Satellite Techniques) approach on MSG-SEVIRI data: applications for volcanic activity monitoring
No full textThe Robust Satellite Techniques (RST) is a multitemporal approach of satellite data analysis proposed to study different natural/environmental hazards, including high risk volcanic phenomena. In particular, both thermal features and ash emissions may be investigated by RST, by using two specific configurations of such an approach. These algorithms have been tested on different volcanic areas exploiting data provided by polar satellite sensors, such as the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS), showing a high trade-off between reliability and sensitivity of detection. In this work, the RST exportability on data provided by the Spinning Enhanced Visible Infrared Imager (SEVIRI), onboard Meteosat Second Generation (MSG) satellites, is assessed, by studying some recent eruptive events of Etna (Italy) and Grimsvotn (Iceland) volcanoes. Outcomes of this work confirm that the RST-based algorithms may give an important contribution for mitigating volcanic hazards during major eruptions, especially in the framework of integrated and automated early warning systems
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
A new algorithm to detect desert dust outbreaks using MSG-SEVIRI data
No full textThe strong impact of dust outbreaks on human activities has significantly increased the interest of scientific community in developing efficient monitoring systems capable of detecting them, supporting activities devoted to mitigate their effects. In this work, the performances of an innovative algorithm for
dust detection, named RSTDUST, based on the successful Robust Satellite Techniques (RST) multitemporal
approach, are further assessed, analyzing some intense Saharan dust outbreaks which affected Mediterranean region in May 2008. This algorithm is further experimented here analyzing data provided by SEVIRI (Spinning Enhanced Visible and Infrared Imager), which offers the
opportunity of promptly detecting dust events (close to the source) and of monitoring their space-time
evolution in real time, thanks to its temporal resolution of 15 minutes. Outcomes of this study, which are compared to some independent ground- and satellite-based aerosol products, confirm that RST DUST may represent an effective tool for automatically identifying Saharan dust from space both over land and sea areas. This work encourages further experimentations of such an algorithm in different geographic regions by using different satellite sensor data, to better assess its potential in monitoring dust events in operational contexts
A Multi-temporal Robust Satellite Technique (RST) for forest fire detection
No full textIn this work, an innovative approach, based on a multi-temporal satellite data analysis, named RST (Robust Satellite Technique), which has already been successfully applied for the monitoring of major natural and environmental risks, has been proposed for the detection of forest fires in near real time. RST is applied in the case of some important forest fires occurred in Northern Italy in recent years using MIR sensors onboard polar (NOAA-AVHRR) and geostationary (MSG-SEVIRI) satellites, moreover, in order to assess the technique performances, also a comparison with well-established MODIS fire algorithm is carried out
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