AUTOMATED ANALYSIS AND FUSION OF MULTI-SPECTRAL DATAIN AIRBORNE OIL SPILL REMOTE SENSING*

摘要

During the last thirty years, aerial surveillance of marine oil spills has become a multinationaleffort, especially for the deterrence of potential polluters and support of oil spill clean-upcrews. For many years, the main effort has been directed towards developing sensors withenhanced spill monitoring capabilities which explains the existing large number of wellestablishedoil spill remote sensors. Recently, more attention has been paid to the automatedderivation of high-level information from airborne remotely sensed multi-spectral oil spill data. Inthis paper, we present an algorithmic framework for automated analysis and fusion of multispectraloil spill data acquired by the German maritime surveillance aircraft. It is shown howinfrared/ultraviolet, microwave radiometer and imaging laser fluorosensor data can be convertedinto high-level information using single-sensor data processing and multi-sensor data fusion. It isalso explained how this can improve the usability of the maritime surveillance system. In thiscontext two concepts are introduced: (1) the internal data processing and (2) the externalinformation processing. While the internal processing of pollution data is spatially limited to thesurveillance aircraft, the external information processing includes the transfer of the internallyderived high-level information products to ground stations and aspects such as GIS integration andAIS communication. This paper describes the automated internal data processing in terms ofanalysis and fusion of multi-spectral oil spill data and outlines opportunities of externalinformation processing.