Enhancing Oil Spill Interpretation Through Multisensor Fusion and Temporal Reconstruction: A Case Study Near the Strait of Gibraltar
Keywords: Oil spill detection, Marine remote sensing, Multisensor data fusion, Temporal reconstruction
Abstract. Oil spills in confined maritime corridors often evolve faster than any single satellite mission can observe. Their surface expression breaks apart, shifts direction, and reorganizes as winds, currents, and ship traffic interact with the drifting material. This often complicates the interpretation of individual images and create gaps in understanding how a spill progresses between satellite overpasses. This study examines whether combining Sentinel-1 and Sentinel-2 observations can provide a more coherent picture of its development of a spill event, using the case of an oil spill occurred near the Strait of Gibraltar in late August 2022 after a collision between the OS35 and the Adam LNG.
The preliminary analysis evaluated each sensor separately. Sentinel-1 highlighted changes in surface roughness, while Sentinel-2 revealed reflectance anomalies linked to modified optical properties of the water. Since neither dataset on its own offered a complete account of the surface conditions, a fusion procedure was applied to the closest pair of post-event images. The fused map displayed sharper boundaries and more spatial detail than the radar scene alone, offering a clearer outline of the affected area. To address the temporal mismatch between acquisitions, intermediate surfaces were also reconstructed for both sensors, producing estimated representations of the marine conditions at dates not directly observed.
Taken together, the fused and reconstructed products formed a more continuous sequence of the spill’s evolution, capturing both its fragmentation and its short-term reorganisation. Although the approach does not replace dedicated operational monitoring, it demonstrates that combining complementary satellite data can reduce ambiguity in single-sensor interpretation and strengthen situational awareness in regions where surface conditions change quickly and unpredictably.
