1,721,008 research outputs found
On the potential of multi-temporal analysis of MODIS and AVHRR data for near real time mapping and monitoring of flooded areas
No full textFloods are devastating natural disasters which may cause very high costs in lives and damages. Among the other potential contributes, satellite remote sensing may help for mapping and monitoring flooded areas. In order to support flood risk management, information coming from satellite, especially during crisis phases, need to be timely provided. Besides, suitable techniques, able to reliably detect flooded areas with a low rate of false alarms, are requested. In this context, a new technique using visible AVHRR data has been recently proposed. In this work, in order to further confirm the reliability and the sensitivity of the proposed approach we analyze the August 2002 flood which hit wide territories of Germany. Afterwards, we exported
this
approach on MODIS data, in order to exploit the higher spatial resolution in the visible and near-infrared channels offered by such a sensor, for increasing the accuracy in both near real time flooded area mapping and monitorin
REAL TIME MONITORING OF FLOODED AREAS BY A MULTI-TEMPORAL ANALYSIS OF OPTICAL SATELLITE DATA
No full textOptical sensors aboard meteorological satellites are an excellent tool to monitor floods and support the flood risk management cycle, mainly thanks to their high temporal resolution, which allow us to obtain real time and frequently updated information on environmental changes. The RST (Robust Satellite Techniques) approach, an automatic change detection scheme, has been already applied using AVHRR (Advanced very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) data to detect and monitor flooded areas. Results achieved have shown its capability in automatically identify flooded areas with a low rate of false alarms, also discriminating permanent water from actual inundated areas. In this paper, in order to further assess the reliability and the sensitivity of the proposed approach in different conditions of observation, the RST methodology has been used to analyze the July 2007 and October 2008 floods occurred in the South Africa and Algeria regions
The 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
A MODIS-based Robust Satellite Techniques for near real time oil spill detection and monitoring.
No full textThe accidental release of oil into the oceans from
tankers may have remarkable ecological impact on maritime and coastal environments. Satellite remote sensing may be an useful tool for the monitoring of such a kind of marine hazards. In particular, MODIS sensor allows us a good combination of spectral-spatial-temporal resolution to provide frequent and detailed mapping of oil affected areas. Using data acquired in the first two MODIS channels, a new techniques for the near real time oil spill detection and monitoring has been recently proposed and applied, with encouraging results, to analyze several spill events. First results have, in fact, shown the potential of such an approach for a timely and continuous detection of these events. In this paper, we verify the sensitivity of such a technique in detecting also the presence of oil spill of low intensity and/or small extent, like those often related to illicit vessel discharges
Near real time oil spill detection and monitoring using satellite optical data
No full textTimely detection and continuously updated information are fundamental in reducing the ecological impact of the different sources of sea pollution. Satellite remote sensing, especially from meteorological platforms having a high temporal resolution and an easy data delivery, can be profitably used for a near real time sea monitoring. Recently, a new methodology for oil spill detection and monitoring, based on the general Robust Satellite Technique (RST) approach, has been proposed. This technique has shown, by using AVHRR Thermal Infrared (TIR) data, a good capability in automatically detect, with high level of reliability, oil spill presence. In this paper, such an approach has been exported for the first time to MODIS TIR data. Preliminary results obtained for an oil spill event occurred during Lebanon war in 2006, are shown and discussed
A Synthetic Aperture Radar-Based Robust Satellite Technique (RST) for Timely Mapping of Floods
Full text linkSatellite data have been widely utilized for flood detection and mapping tasks, and in recent years, there has been a growing interest in using Synthetic Aperture Radar (SAR) data due to the increased availability of recent missions with enhanced temporal resolution. This capability, when combined with the inherent advantages of SAR technology over optical sensors, such as spatial resolution and independence from weather conditions, allows for timely and accurate information on flood event dynamics. In this study, we present an innovative automated approach, SAR-RST-FLOOD, for mapping flooded areas using SAR data. Based on a multi-temporal analysis of Sentinel 1 data, such an approach would allow for robust and automatic identification of flooded areas. To assess its reliability and accuracy, we analyzed five case studies in areas where floods caused significant damage. Performance metrics, such as overall (OA), user (UA), and producer (PA) accuracy, as well as the Kappa index (K), were used to evaluate the methodology by considering several reference flood maps. The results demonstrate a user accuracy exceeding 0.78 for each test map when compared to the observed flood data. Additionally, the overall accuracy values surpassed 0.96, and the kappa index values exceeded 0.78 when compared to the mapping processes from observed data or other reference datasets from the Copernicus Emergency Management System. Considering these results and the fact that the proposed approach has been implemented within the Google Earth Engine framework, its potential for global-scale applications is evident
Space-time soil wetness monitoring by a multi-temporal microwave satellite records analysis.
No full textIn the last few years, remote sensing observations have become a useful tool for providing hydrological information, including the quantification of the main physical characteristics of the catchment, such as topography and land use, and of its variables, like soil moisture or snow cover. Moreover, satellite data have also been largely used in the framework of hydro-meteorological risk mitigation.
Recently, an innovative Soil Wetness Variation Index (SWVI) has been proposed, using data acquired by the microwave radiometer AMSU (Advanced Microwave Sounding Unit) which flies aboard NOAA (National Oceanic and Atmospheric Administration) satellites.
SWVI is based on a general approach for multi-temporal satellite data analysis (RAT – Robust AVHRR Techniques). This approach exploits the analysis of long-term multi-temporal satellite records in order to obtain a former characterization of the measured signal, in term of expected value and natural variability, providing a further identification of signal anomalies by an automatic, unsupervised change-detection step. 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 paper, the proposed approach is applied to the analysis of the flooding event which occurred in Europe (primarily in NW Spain) in June 2000. Results obtained, in terms of reliability as well as efficiency in space–time monitoring of soil wetness variation, are presented. Future prospects, in terms of exportability of the methodology on the new dedicated satellite missions, like ESA-SMOS and NASA-HYDROS, are also discussed
RST-BASED FLOODED AREA MAPPING AND MONITORING IN NEAR REAL-TIME BY USING MODIS DATA
No full textFlood forecast and mitigation actions need updated and timely information about precise location, extent and dynamic evolution of the flooding event. Remote sensing technology, based on microwave and optical satellite data, is currently capable of giving reliable contributions towards a rapid detection of affected areas in order to improve flood hazards management and to study remote areas where ground-based observation systems are still lacking. For a near real time monitoring and mapping of flooded areas, fundamental during the crisis and post-crisis phases to support civil protection activities, frequent observations of the Earth’s surface can be derived from optical sensors aboard meteorological satellites.
Recently, a new Robust Satellite Technique using AVHRR (Advanced very High Resolution Radiometer) observations has been proposed for mapping and monitoring flooded areas, providing good results. Afterwards, the same approach has been exported on MODIS (Moderate Resolution Imaging Spectroradiometer) data, in order to investigate if its higher spatial resolution in visible and near-infrared channels might be exploited to increase the accuracy in both near real time detection and mapping of flooded areas. Preliminary results confirmed the reliability and the sensitivity of the proposed approach but further analyses have to be carried out in order to better assess the actual reliability and efficiency of such a technique. To this aim, in this paper, the extreme flooding event which hit wide territories of Germany and Czech Republic, during the August 2002, has been studied
ROBUST SATELLITE TECHNIQUES FOR VOLCANIC ERUPTIONS MONITORING
No full textThrough this paper the robust approach to monitoring volcanic aerosols by satellite is applied to an extended set of events affecting Stromboli and Etna volcanoes to assess its performance in automated detection of eruptive clouds and in monitoring pre-eruptive emission activities. Using only NOAA/AVHRR data at hand (without any specific atmospheric model or ancillary ground-based measurements) the proposed method automatically discriminates meteorological from eruptive volcanic clouds and, in several cases, identified pre-eruptive anomalies in the emission rates not identified by traditional methods. The main merit of this approach is its effectiveness in recognising field anomalies also in the presence of a highly variable surface background as well as its intrinsic exportability not only on different geographic areas but also on different satellite instrumental packages. In particular, the possibility to extend the proposed method to the incoming new MSG/SEVIRI satellite package (which is going to fly next year) with its improved spectral (specific bands for SO 2 ) and temporal (up to 15 min) resolutions has been evaluated representing the natural continuation of this work
Rst-based oil spill detection and monitoring using optical data.
No full textOil spills in the sea is one of the most serious hazard for coastal and marine environments. The main
contribution to oceans oil pollution is related to operational discharge from tankers (e.g. oil dumped during cleaning operations) that spread in the sea the equivalent of one full-tanker disaster every week. In order to reduce the environmental impact of such a kind of hazards, timely detection and continuously updated information are fundamental and satellite remote sensing could give an important contribution in such a direction. In particular meteorological satellite, thanks to their high temporal resolution and to an easy data delivery, can be profitably used for a near real time sea monitoring. Recently, two new methodologies for oil spill detection and monitoring, both based on the general Robust Satellite Technique (RST) approach, have been proposed. The first one, based on the multi-temporal analysis of AVHRR Thermal Infrared (TIR), have shown good capability in automatically detect, with high level of reliability, oil spill presence. The second one, by using MODIS visible (VIS) data, have been applied, with encouraging results, for a detailed mapping of the oil slick. In this paper we have exported the RST AVHRR TIR approach to MODIS TIR data in order to guarantee the availability of both the methodologies and their specific advantages (high reliability in TIR channels, better spatial resolution in the VIS) by using a single multispectral sensor. Preliminary results obtained applying the proposed methodology for an oil spill event occurred during Lebanon war in 2006 are shown and discussed
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