Valerio Tramutoli

Robust AVHRR techniques (RAT) for environmental monitoring: theory and applications

Many algorithms and data analysis techniques have been proposed up to now which make use of satellite observations within atmospheric widows mainly for clouds and surface parameters studies and for environmental monitoring applications. Quite all these algorithms are difficult to extend to different geographical, seasonal conditions, having generally poor performances and uncertain reliability especially when applied in environmental risk prevision, monitoring and/or mitigation. In this paper a new, robust (in a statistical sense), approach (RAT) to the use of NOAA/AVHRR observations is proposed and its successful application to different environmental emergencies illustrated also in expectation of next generation of satellite sounders devoted or usable for environmental monitoring purposes.

Robust Satellite Techniques (RST) for Natural and Environmental Hazards Monitoring and Mitigation: Theory and Applications

Several algorithms and data analysis techniques have been proposed using satellite observations (within atmospheric spectral windows) for cloud and surface parameters studies and for human environment monitoring applications. Quite all these algorithms are difficult to extend to different geographical, seasonal conditions, generally offering poor performances and uncertain reliability especially when applied in environmental risk prevision, monitoring and/or mitigation. In this paper the generalized satellite data analysis approach RST (Robust Satellite Technique) is described which extend the use of RAT (Robust AVHRR Techniques) approach -previously proposed by the same author in 1998 -to whatever satellite sensors. Successful RST applications are also described with reference to results so far achieved by using optical and microwaves passive sensors for volcanic eruption monitoring and prediction, forest fire detection, floods mapping, monitoring and early warning, possible earthquake precursors monitoring, oil spill detection and pipeline networks monitoring.

Evaluation of a new satellite-based method for forest fire detection

Advanced Very High Resolution Radiometer (AVHRR)-based fire detection methods are considered in this work in order to assess their effective usefulness in the framework of civil programmes for fire risk and damage mitigation. The discussion is divided into the evaluation of the most commonly used methods and the description of a new fire detection procedure which is proposed in this paper. Commonly used detection methods are based on using absolute threshold values for decision tests. These values usually match only with very local, uniform (in space and time) situations, and are often inadequate when applied to heterogeneous, or simply different, geographical areas or seasons. A high number of false alarms, so high as to make the satellite-based product not operationally utilizable, is the main disadvantage of the fixed-threshold approach. The new fire-detection procedure proposed here makes use only of historical AVHRR data in order to automatically produce local (in space and time) threshold values, suitable for fire-event detection also in very critical situations. High fire discrimination capabilities with low false-alarm rates, simple unsupervised implementation and, above all, flexibility for automatic extension to completely different geographic areas and observation conditions, are the main advantages associated with this new technique. Results obtained for different Italian areas have been successfully compared with ground observations made by the Italian Forestry Service. Tests made over a long observation period show that, on cloud-free regions, more than 75% of significant forest fires are detected with less than 20% of false alarms.

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.