Nicola Pergola

A First Assessment of the SMOS Soil Moisture Product With In Situ and Modeled Data in Italy and Luxembourg

The European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission was launched on November 2, 2009. Providing accurate soil moisture (SM) estimation is one of its main scientific objectives. Since the end of the commissioning phase, preliminary global SMOS SM data [Level 2 (L2) product] are distributed to users. In this paper, we carried out a first assessment of the reliability of this product through a comparison with in situ observed and modeled SM over three different sites: One is located in Luxemburg, and two are located in Italy. The period from August 1, 2010, to July 1, 2011, has been analyzed, giving us the opportunity to evaluate the satellite response to different SM states. The selected period is important for hydrological predictions as it is typically characterized by a sequence of transitions from dry to wet and from wet to dry conditions. In order to compare SMOS and ground SM measurements, a two-step approach has been applied. First, an exponential filter has been applied to approximate root-zone SM, and second, a cumulative distribution function matching has been employed to remove systematic differences between satellite and in situ observations and model simulations of SM. Our results indicate rather good reliability of the filtered and bias-corrected SM estimates derived from the first SMOS L2 products. Bearing in mind that an updated/advanced version of the SMOS SM product has been recently produced, our preliminary results already seem to confirm the potential of SMOS for monitoring of water in soils.

SANA: Sub-pixel automatic navigation of AVHRR imagery

An automatic method (SANA) for sub-pixel navigation of Advanced Very High Resolution Radiometer (AVHRR) imagery is proposed. It progressively corrects satellite attitude and reduces navigation errors all over the scene by using an iterative approach. Tests performed on more than 400 AVHRR passes over Europe, demonstrate the above mentioned method capability to obtain, with no human intervention, a final navigation accuracy within 1 pixel. Main characteristics of such a method are its processing speed as well as its full exportability to other satellite packages.

AVHRR automated detection of volcanic clouds

A new satellite‐based technique has recently been proposed which seems suitable for an automatic detection of volcanic clouds in daytime conditions. In this paper the robustness of such a new approach, in particular in detecting early eruptive clouds, is evaluated, on several eruptive events at Mt Etna, by using five years of Advanced Very High Resolution Radiometer (AVHRR) data. The detection scheme is discussed together with its possible extension to night‐time monitoring and the improvements expected by its application to the next generation of satellite sensors (in particular Spinning Enhanced Visible and Infrared Imager (SEVIRI)) with enhanced spectral and temporal resolution. The proposed approach seems to overcome the limitations related to other proposed methods which, in some conditions (very fresh eruptive clouds, cold‐backgrounds, etc.), give false or missed detection and will no longer be applicable to the next generation of Geostationary Operational Environmental Satellites (GOES) due to the planned reduction of their thermal infrared channels until 2010.

On the Exportability of Robust Satellite Techniques (RST) for Active Volcano Monitoring

Satellite remote sensing has increasingly become a crucial tool for volcanic activity monitoring thanks to continuous observations at global scale, provided with different spatial/spectral/temporal resolutions, on the base of specific satellite platforms, and at relatively low costs. Among the satellite techniques developed for volcanic activity monitoring, the RST (Robust Satellite Techniques) approach has shown high performances in detecting hot spots as well as in automatically identifying ash plumes, effectively discriminating them from weather clouds. This method, based on an extensive, multi-temporal analysis of long-term time series of homogeneous satellite records, has recently been implemented on EOS-MODIS and MSG-SEVIRI data for which further performance improvements are expected. These satellite systems, in fact, offer improved spectral and/or temporal resolutions. In this paper, some preliminarily results of these analyses are presented, both regarding hot spot identification and ash cloud detection and tracking. The potential of RST, to be used within early warning systems devoted to volcanic hazard monitoring and mitigation, will also be discussed.

A Multi-temporal Robust Satellite Technique (RST) for Forest Fire Detection

In 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.

Two years of operational use of Subpixel Automatic Navigation of AVHRR scheme: accuracy assessment and validation

Abstract Automated techniques for satellite imagery navigation and co-location are especially required for environmental monitoring activities intensively using satellite data. In this work are presented the results obtained after 2 years of operational use of the Subpixel Automatic Navigation of AVHRR (SANA) scheme. An automatic method for accuracy assessment of satellite navigation techniques, which permits a preliminary evaluation of their performances, dealing with a large collection of test images is also proposed. The navigation accuracy assessment, performed by using a selection of small islands as reference points, is discussed. Results achieved over more than 400 Advanced Very-High-Resolution Radiometer (AVHRR) scenes confirm that the SANA scheme is a very accurate one (computed mean navigation error is generally about one AVHRR pixel). Furthermore, because of its high processing speed, it can be considered a suitable tool for intensive satellite data processing in multitemporal analyses, especially required for environmental studies as well as for operational monitoring purposes.

Improving flood monitoring by the Robust AVHRR Technique (RAT) approach: the case of the April 2000 Hungary flood

In 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 packages.

INVESTIGATING THE TEMPORAL FLUCTUATIONS IN SATELLITE ADVANCED VERY HIGH RESOLUTION RADIOMETER THERMAL SIGNALS MEASURED IN THE VOLCANIC AREA OF ETNA (ITALY)

The time dynamics of long-term time series of satellite thermal signal, measured at Mount Etna, has been investigated. The signal has been analyzed by means of a recently proposed multi-temporal and robust technique (RST), which has already shown to be better capable to detect and monitor volcanic hotspots, compared to traditional satellite approaches. The temporal fluctuations of the thermal signal detected by RST over a long series (1995-2005) of Advanced Very High Resolution Radiometer (AVHRR) satellite data, have been characterized by means of the correlation function and the power spectrum analysis, which have shown the presence of correlation structures in the thermal time series recorded in the crater area.

A Robust Multitemporal Satellite Technique for Volcanic Activity Monitoring: Possible Impacts on Volcanic Hazard Mitigation

Among the natural hazards, volcanoes represent one of major risk for both population and surrounding infrastructures, causing every year significant economical and environmental damages. Satellite remote sensing, thanks to multispectral data, high observational frequencies and global coverage, represents an important tool for volcanic activity monitoring, especially in remote areas where traditional techniques are generally inadequately applied. A new multitemporal satellite approach named RST (Robust Satellite Techniques) applied to several recent eruptions of Mount Etna and Stromboli volcanoes has shown to be suitable to correctly identifying and tracking volcanic ash plumes as well as to successfully detecting and monitoring volcanic thermal anomalies strongly reducing false alarm occurrences. In this paper, some recent RST results, confirming the high reliability and sensitivity of the proposed approach in volcanic activity monitoring together with its full exportability on different satellite platforms and geographic locations will be shown and discussed.

Assessment of the Robust Satellite Technique (RST) for volcanic ash plume identification and tracking

Volcanic clouds pose a serious threat for both aircrafts and passengers because of ash, which may cause serious damages to the flight control systems and to jet engines. Starting from 2007, an automatic satellite monitoring system has been implemented at IMAA (Institute of Methodologies of Environmental Analysis) to identify and track volcanic ash plumes using NOAA-AVHRR data. This system is capable of providing reliable information about possible volcanic ash plumes over a region of interest (ROI) within a few minute after the sensing time, thanks to the implementation of a robust multi-temporal approach of satellite data analysis named RST (Robust Satellite Technique). This approach has already shown a high potential in successfully identifying and tracking volcanic ash clouds compared to traditional techniques, both in its standard (i.e. two-channel) and advanced (i.e. three-channel) configuration. In this paper, RST performances for ash plume detection and monitoring will be further assessed, showing some recent results obtained during December 2006 and analyzing a time series of satellite observations carried out over Mount Etna area for different months in different observational conditions. In order to validate and assess RST performances, a long-term time domain analysis is in progress, also investigating periods mainly characterised by quiescent phases (i.e. with no ash emission episodes). Preliminary results of such a statistical analysis will be presented and the possible contribution of this satellite monitoring system in supporting management of strong eruptive crisis will also be discussed.