Use of airborne hyperspectral images to assess the spatial distribution of oil spilled during the Trecate blow-out (Northern Italy)

Remo Bianchi; Rosa Maria Cavalli; Carlo M. Marino; Stefano Pignatti; Mautizio Poscolieri

doi:10.1117/12.227199

24 November 1995 Use of airborne hyperspectral images to assess the spatial distribution of oil spilled during the Trecate blow-out (Northern Italy)

Remo Bianchi, Rosa Maria Cavalli, Carlo M. Marino, Stefano Pignatti, Mautizio Poscolieri

Author Affiliations +

Proceedings Volume 2585, Remote Sensing for Agriculture, Forestry, and Natural Resources; (1995) https://doi.org/10.1117/12.227199
Event: Satellite Remote Sensing II, 1995, Paris, France

Abstract

On February 1994 a large area close to Trecate was affected by an oil blow-out from an AGIP rig located within the Ticino Regional Park. One month later an airborne survey has been carried out in the framework of the CNR Lara Project, by utilizing the Daedalus AA5000 MIVIS spectrometer with 102 channels from visible to thermal infrared. Different authors stress, for oil slicks discrimination, the utility of laser and microwaves based techniques, but the high spatial and spectral MIVIS resolutions can improve the detection of the relative coverage by spilled oil. This task has been performed by applying hyperspectral unmixing methods to the MIVIS calibrated data, obtaining an oil fractional image with respect to other chosen end-members. The analysis has shown a good agreement between the results of the unconstrained unmixing technique applied to MIVIS data and the ground truths, offering a tool useful to quantify in a synoptic overview the effects of oil spills over land, by relating the ppm of oil with the oil hyperspectral information gathered by MIVIS.

Citation Download Citation

Remo Bianchi, Rosa Maria Cavalli, Carlo M. Marino, Stefano Pignatti, and Mautizio Poscolieri "Use of airborne hyperspectral images to assess the spatial distribution of oil spilled during the Trecate blow-out (Northern Italy)", Proc. SPIE 2585, Remote Sensing for Agriculture, Forestry, and Natural Resources, (24 November 1995); https://doi.org/10.1117/12.227199

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