1,721,087 research outputs found
A retrospective analysis of the Shinmoedake (Japan) eruption of 26–27 January 2011 by means of Japanese geostationary satellite data
Full text linkDuring the sub-plinian eruptions of Mt. Shinmoedake (Japan) on 26–27 January 2011 a significant amount of ash
was emitted into the atmosphere, destroying thousands of hectares of farm land, causing air traffic disruption,
and forcing the closure of four railroad lines located around the volcano. In this work, a retrospective analysis
of these eruptive events is presented, exploiting the high temporal resolution of the Japanese Multi-functional
Transport Satellites (MTSAT) data to study thermal volcanic activity, to identify and track volcanic ash, and to determine
the cloud-top height, inferring information about eruption features and space-time evolution. We show
that a strong and sudden increase in the thermal signal occurred at Mt. Shinmoedake as a consequence of above
mentioned eruptive events, generating hot spots timely detected by the RSTVOLC algorithm for the first time implemented
here on data provided by geostationary satellites. This study also shows that the emitted ash plume,
identified by means of the RSTASH algorithm, strongly fluctuated in altitude, reaching a maximum height around
7.4 km above sea level, in agreement with information provided by the Tokyo VAAC. The plume heights derived
in this work, by implementing the widely accepted cloud-top temperature method, appear also compatible with
the values provided by independent weather radar measurements, with the main differences characterizing the
third sub-plinian event that occurred in the afternoon of 27 January. The estimates of discharge rate, the temporal
trend of ash affected areas, and the results of thermal monitoring reported in this work seem to indicate that the
third sub-plinian event was the least intense. In spite of some limitations, this study confirms the potential of
Japanese geostationary satellites in effectively monitoring volcanoes located in the West Pacific region, providing
continuous information also about such critical parameters of ash clouds as the plume height. Such information is
useful not only for driving numerical models, forecasting ash dispersion into the atmosphere, but also for characterizing
eruption features and dynamics
Monitoring soil wetness variation by a multi-temporal passive microwave technique
No full textMicrowave remote sensing offers emerging capabilities to monitor global hydrological processes. In particular, in the last years the potential in soil moisture retrieval has been largely demonstrated. Recently, an innovative Soil Wetness Variation Index (SWVI) has been proposed, using data acquired by the microwave radiometer AMSU1 which flies aboard NOAA2 satellites. SWVI is based on a general approach for multi-temporal satellite data analysis (RST-Robust Satellite Techniques) which, by means of a change detection technique applied over long-term multi-temporal satellite records, is able to identify anomalous values of the observed signal. Such an approach has already demonstrated, in several studies carried out on extreme flooding events which occurred in Europe in the past few years, its capability in reducing spurious effects generated by natural/observational noise. In this work, preliminary results obtained applying this approach to the flooding event which affected some European countries (luring the summer 2002, are presented. Preliminary outcomes seem to confirm the efficiency of the proposed indicator in monitoring soil wetness variations in the space-time domain without need auxiliary or ancillary information
A Multi-Sensor Exportable Approach for Automatic Flooded Areas Detection and Monitoring by a Composite Satellite Constellation
Full text linkTimely and frequently updated information about flood-affected areas and their space-time evolution are often crucial in order to correctly manage the emergency phases. In such a context, optical data provided by meteorological satellites, offering the highest available temporal resolution (from hours to minutes), could have a great potential. As cloud cover often occurs reducing the number of usable optical satellite images, an appropriate integration of observations coming from different satellite systems will surely improve the probability to find cloud-free images over the investigated region. To make this integration effective, appropriate satellite data analysis methodologies, suitable for providing congruent results, regardless of the used sensor, are envisaged. In this paper, a sensor-independent approach (RST, Robust Satellites Techniques-FLOOD) is presented and applied to data acquired by two different satellite systems (Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration platforms and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Earth Observing System satellites) at different spatial resolutions (from 1 km to 250 m) in the case of Elbe flood event occurred in Germany on August 2002. Results achieved demonstrated as the full integration of AVHRR and MODIS RST-FLOOD products allowed us to double the number of satellite passes daily available, improving continuity of monitoring over flood-affected regions. In addition, the application of RST-FLOOD to higher spatial resolution MODIS (250 m) data revealed to be crucial not only for mapping purposes but also for improving RST-FLOOD capability in identifying flooded areas not previously detected at lower spatial resolution
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
Robust Satellite Techniques for oil spill detection and monitoring.
No full textIn this article, a new satellite technique for oil spill detection and monitoring is fully presented and discussed. It is based on the general RST (Robust Satellite Techniques) approach applied to Advanced Very High Resolution Radiometer (AVHRR) observations in the thermal infrared region of the electromagnetic spectrum. The proposed approach, which exploits the analysis of multi-temporal satellite records, seems to be able to detect the anomalous signals on the sea due to the oil polluted areas with excellent reliability (0% of false alarms) and good sensitivity in different observational conditions. Its performances have also been evaluated in comparison with another well-known AVHRR approach, analysing the spill event which happened during the Gulf War off the Kuwait and Saudi Arabia coasts in January 1991. The results confirm the reliability of the proposed approach which promises to offer new economically sustainable opportunities for building a near-real-time monitoring system for oil spills on a global scale. Moreover, in order to further assess the exportability of the proposed approach in different observational and environmental conditions, outcomes obtained by applying it to the Seki-Baynunah event affecting the Gulf of Oman in March 1994 are also shown
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
Monitoring space-time soil wetness variations by a multi-temporal microwave satellite records analysis
No full textIn the last few years, remote sensing observations have become an useful tool for providing hydrological information, including the quantification of the main physical characteristics of the catchments, such as topography and land use, and of their variables, like soil moisture or snow cover. Moreover, satellite data have also been largely used in the framework of hydro-meteorological risk assessment and mitigation.
Recently, an innovative Soil Wetness Variation Index (SWVI) has been proposed, using data acquired by the microwave radiometer AMSU (Advanced Microwave Sounding Unit), flying aboard NOAA (National Oceanic and Atmospheric Administration) polar satellites.
The proposed index, 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 past years.
In this paper, preliminary results obtained by the analysis of data related to the flooding event occurred in Europe during April 2006 are presented. Preliminary outcomes achieved seem to demonstrate the efficiency of the proposed indicator in detecting soil wetness variations in the space-time domain without the need of auxiliary or ancillary information
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