Marine pollution in the sensible North and Baltic Sea forces an international aerial surveillance. Within this framework the German aerial surveillance operates an advanced instrumentation on board of two 'Dornier 228' aircrafts. The instrumentation consists of a set of state-of-the-art imaging remote sensors, like side looking airborne radar (SLAR), IR/UV line scanner and particularly a microwave radiometer (MWR) and a laser-fluoro-sensor (LFS). The most important aim is to detect oil discharges on the water surface, emitted accidentally or illegally. In case of discharge, the pollution has to be classified and quantified with a high accuracy. Another aim is to monitor biological and hydrological parameters, as there are the concentration of chlorophyll and dissolved organic matter (DOM) or the growth of phytoplancton.This paper describes the set of instruments and their potential to fulfill these demands. The SLAR operates to locate oil discharges and phytoplancton, whereas the IR/UV scanner allows to distinct the detected area. The IR/UV and especially the MWR sensor allow to quantify the thickness of the oil film. Finally, the LFS classifies the oil species as well as organic material. Emphasis is placed on the results of the sensor measurements and their synergy effects. The combination of the sensor data yields value added information for the operational users.An use of satellite data to improve the operational surveillance will be discussed. The potential and limitations of satellite and airborne data for the surveillance tasks will be compared.

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In many European countries air-and spaceborne remote sensing data is operationally used for oil spill monitoring. For the Baltic Sea the yearly results of the aerial surveillance are collected by the Helsinki Commission (HELCOM) and for the North Sea by the Bonn Agreement Secretariat. To improve knowledge of the oil spill situation in the North Sea and the Baltic Sea these data sets were analyzed and visualized. If a geographical phenomenon may be reasonably modeled as point data is largely a question of scale. Oil spills on a sea basin level (North Sea, Baltic Sea) can be considered as point data. During the analysis we are essentially looking for patterns in the data. However, to combine oil spill surveillance results from different countries the data must be standardized. For standardization purposes it is important to have information about the surveillance effort, which means for instance the number of pollution control flights per year and the area covered or the number of acquired and analyzed satellite. Special incidents (e.g. accidents) may lead to a multitude of oil spills in a certain period of time which has to be considered during the analysis. The data was visualized taking into account additional information and available information about the surveillance activities. Kernel estimation was used to calculate oil spill density estimation. First results are promising. The strongest impediment is the unavailability of information for data standardization.