# Improving the RST-OIL Algorithm for Oil Spill Detection under Severe Sun Glint Conditions
## 1 Introduction  
Among the different pollution sources that may affect marine ecosystems, oil spills are one of the most dangerous from an environmental point of view, especially when they involve a coastal habitat. Oil contamination can affect the sea environment in different ways, such as by natural leakages (crude oil coming from sedimentary rocks), discharges resulting from routine operations on ships, and due to large accidents involving tankers and/or oil extraction platforms [1]. Apart from a few situations where natural oil seeps may even support benthic ecosystems [2], oil spills can cause irreversible damage to marine ecosystems, not only in terms of seawater and coastal zone pollution, but also regarding the health of the flora and fauna living in the area. Considering only spills related to anthropic activity, in the last few decades, the number of large spills (>700 tons) related to tanker accidents, as well as the number of medium-sized ones (7-700 tons), have decreased significantly [3]. Despite such a reduction, large spills are still able to affect, in terms of volume, the total amount of oil dispersed annually in the sea [3]. Even in the case of such accidents, the success of the actions aimed at reducing the environmental after-effects is strictly linked to the timeliness of the identification and the accuracy in predicting the displacement (and/or dispersion) [4]. In this framework, the development of efficient monitoring systems able to provide timely information about the seawater status is essential. Remote sensing has become an integral part of modern response systems [5] to oil spill accidents, and several techniques based on different data have been developed to address this aim. Synthetic Aperture Radars (SAR) are the most widely used satellite systems for marine pollution control, due to their capability to identify oil spills with good sensitivity and a high spatial resolution (up to 1 m) [5; 6; 7; 8; 9; 10; 11; 12]. SAR systems allow for almost all-day and all-weather detection that is not dependent on the presence of a natural source of electromagnetic radiation and is not affected by the cloud presence. However, their operational use in a continuous monitoring procedure is mainly limited to their low repetition time (from a few days to dozens of days, at mid latitudes and for a single satellite), specific wind range speed conditions, and a possible look-alike presence [5; 6; 7; 8; 9; 10; 11; 12]. Cosmo-SkyMed [13] and the recent Sentinel-1 Copernicus missions, both working in a satellite constellation configuration, allowed the issues to be reduced due to the low repetition time, which allows for more frequent temporal sampling (from 12 h up to 5-6 days). In this context, passive optical sensors, on-board meteorological satellites, and constellations of low Earth orbiting polar satellites could represent a good alternative. Even if with lower spatial resolutions (from 250 m up to 3 km) than SAR systems, optical sensors guarantee a higher temporal resolution (up to a few hours for polar satellites and a few minutes for geostationary ones), which is more useful for real-time monitoring of areas affected by oil pollution risk. Their usability is, however, influenced by cloud cover, in which the presence may hamper any sea surface acquisition. Up until now, techniques developed for oil spill detection in the optical region have generally exploited a particular observational geometry and have used the difference between measured signals (e.g., brightness temperature or spectral reflectance) over the oil-affected areas and the neighboring clean sea surface. However, the use of fixed thresholds sometimes makes it difficult to discriminate between oil-originated signals and normal sea surface fluctuations when different environmental and observational conditions are considered [5; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24].