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    HNS, Oil and Inert Pollution: Trajectory Modelling and Monitoring (DRIFTER).

    Objetives       Partners       Links       Results

     

    The success in the management of a marine pollution accident that involves a spill depends on several factors such as the ability to detect the spills, the capabilities to follow the movement of the slicks, and the capabilities to predict the fate and behaviour of the pollutant over time. Different approaches and technologies can be applied for those purposes that will support the decision making process in terms of equipment deployment and protection of sensitive areas. The use of trackers (buoys and dyes) is common to follow the location of spills on a continuous way. However, their behaviour is not exactly the same of the followed product being necessary to know the difference of the drift between the real spill and the tracer. Modeling tools allow for analyzing and forecasting the motion of pollutants but calibration and validation studies are needed to improve their reliability. In the other hand, Synthetic Aperture Radar (SAR) has demonstrated to be a suitable tool for monitoring of oil spills at sea. Nevertheless, the discrimination of oil spill in SAR images can be complicated by other phenomena which resembles oil spill.

    Although the effectiveness of all these technologies that contribute to a better localization and follow up of slicks has been demonstrated during recent spill events, limitations and gaps still remain and deserve additional efforts. DRIFTER approaches these gaps and focuses on the development and improvement of detections and forecasting technologies.


    OBJECTIVES: (volver arriba)

       The specific objectives are the following:

    1. Improvement of the capability to follow up spills by:

        i) Identification of the most suitable drifting buoys to be used for the different types of spills.

        ii) Exploration of application of dyes to mark a colorless slick of chemical.

        iii) Application of satellite and remote sensing technologies.

    2. Improvement of the capability to forecast drifts of oil, hazardous noxious substances (HNS) and inert.

    3. Review, identification and adaptation of oil spill monitoring and forecasting technologies to predict the behaviour and drifts of HNS and inert.

    4. Elaboration of protocols for data exchange and management.

    5. Wide dissemination of results to stakeholders and end-users.


     EXPECTED RESULTS AND IMPACT:

    The expected outcomes of the project are of high applicability and include among others guidelines for drifters and dyes application, wind and wave coefficients, operational models, good practices protocols for communication and data exchange, new algorithms for segmentation, characterization and discrimination of oil spills, spectral studies of the different pollutants and information on the most adequate bands for their detection. They will be transferred to key stakeholders and organizations in charge of spill response by using different channels of communication: partner web sites, participation in conferences and congresses, publication of scientific articles and organization of a Workshop at the end of the project. Moreover, a site of reference will be created on INTECMAR web site that will include field measurement observation data obtained with the different models as well as the coefficients and their technical features. Data will be downloaded from this website to be used by other researchers working on this field. This site will be kept operational after the project lifetime.

    The project approaches are of immediate relevance for other coastal areas. A solid knowledge of trackers behaviour and dyes performance can be useful, no matter where they are used, in order to have the real position of the spill in a continuous way. The expected development and improvement of modelling tools will provide the knowledge and technology required to more easily predict the trajectory and behaviour pollutants in other regions as they are scalable and adaptable to different geographic areas. Information on Drifter outcomes will be distributed to a wide range of policy makers and stakeholders from coastal EU countries.


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    Partners: (volver arriba)

    Coordination:

        - CETMAR - Centro Tecnologico del Mar, Spain

    CETMAR

    Partners:

        - METEOGALICIA, Spain

    METEOGALICIA

        - INTECMAR - Instituto Tecnologico para el Control del Medio Marino de Galicia, Spain

    INTECMAR

        - University of Vigo, Spain

    <>TGIS

                - CEDRE, France

              CEDRE

                - IST - Instituto Superior Tecnico, Portugal

               IST

               

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    Links: (volver arriba)

    <>   Demonstration

    web page

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    Results:  (volver arriba)

    In the framework of DRIFTER project, it has been developed a semiautomatic oil spill detection system from Advanced Syntethic Aperture Radar (ASAR) for the Galician area. The system includes different algorithms for segmentation, characterization and discrimination. It allows working with ASAR Width Swath images (around 150 meters resolution), which are adequate to detect oil spills in open ocean areas, and also with ASAR Full Resolution (FR) images (up to 12.5 meters resolution), which might be useful to detect oil on coastal areas and in the inner parts of the Galician Rias.
    The system also admits the possibility of incorporating additional data which allow us to create masks that can be used as an aid to identify look-alikes. Masks might be applied before the segmentation step in order to obtain a look-alikes dataset to train the classification algorithms and to verify the results of that classification.
    All the algorithms have been developed using gvSIG, a free Geographic Information System (GIS) software based on JAVA language. The tools have been incorporated as an extension called SIDEGA-SAR.

    Short description (manual) of SIDEGA-SAR >>

    For more detailed information about application SIDEGA-SAR contact with:

    Luis Vilas

    Applied Phisics Department
    Laboratory of Remote Sensing and GIS
    University of Vigo, Spain



                                                                

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