Observing Marine Pollution with Synthetic Aperture Radar

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Validation of an automatic system to detect oil spills in X- and L-band SAR images

Satellite-borne SAR is used for sea surface observation and extraction of meteo-marine features as well as detection of oil slicks. In this paper we want to describe the activity based on the detection algorithm we developed in previous activities, able to identify oil spills in an automatic routinely way, as well as to evaluate detection reliability with a percentage value. Starting from that previous algorithm we developed for ERS and Envisat data, we extended its capabilities by identifying suitable radiometric parameters for L- and X-band data products. We tested our procedure on L- and X-band SAR images with the aim to assess their effectiveness in discriminating verified oil slicks found on sea surface

A generalised algorithm for oil spill detection on ers and envisat sar images

Different approaches have been proposed for detecting and classifying oil spills on SAR data. Several of these are based on training datasets which are used to characterize this phenomenon statistically. In case of images employed for the analysis having different pixel spacing or radiometric resolution to those used in the training set, a new classification template is required. A completely new training dataset and an algorithm optimisation are also needed. In the present paper we present an oil spill detection system which was originally developed for ERS. This has been generalised and put to use for processing ENVISAT data also. Performance of the classification process has been tested using a set of confirmed slicks, which were present on both ERS and ENVISAT images simultaneously. The results are here presented and discussed

River pollution remediation monitored by optical and infrared high-resolution satellite images

The Bormida River Basin, located in the northwestern region of Italy, has been strongly contaminated by the ACNA chemical factory. This factory was in operation from 1892 to 1998, and contamination from the factory has had deleterious consequences on the water quality, agriculture, natural ecosystems and human health. Attempts have been made to remediate the site. The aims of this study were to use high-resolution satellite images combined with a classical remote sensing methodology to monitor vegetation conditions along the Bormida River, both upstream and downstream of the ACNA chemical factory site, and to compare the results obtained at different times before and after the remediation process. The trends of the Normalised Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) along the riverbanks are used to assess the effect of water pollution on vegetation. NDVI and EVI values show that the contamination produced by the ACNA factory had less severe effects in the year 2007, when most of the remediation activities were concluded, than in 2006 and 2003. In 2007, the contamination effects were noticeable up to 6 km downstream of the factory, whereas in 2003 and 2006 the influence range was up to about 12 km downstream of the factory. The results of this study show the effectiveness of remediation activities that have been taking place in this area. In addition, the comparison between NDVI and EVI shows that the EVI is more suitable to characterise the vegetation health and can be considered an additional tool to assess vegetation health and to monitor restoration activities.Fil: Trivero, Paolo. Università del Piemonte Orientale “Amedeo Avogadro”; ItaliaFil: Borasi, Maria. Università del Piemonte Orientale “Amedeo Avogadro”; ItaliaFil: Biamino, Walter. Università del Piemonte Orientale “Amedeo Avogadro”; ItaliaFil: Cavagnero, Marco. Università del Piemonte Orientale “Amedeo Avogadro”; ItaliaFil: Rinaudo, Caterina. Università del Piemonte Orientale “Amedeo Avogadro”; ItaliaFil: Bonansea, Matias. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lanfri, Sofia. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentin