# A MODIS-Based Robust Satellite Technique (RST) for Timely Detection of Oil Spilled Areas
## 2 Materials and Methods  
The RST approach is an automatic change-detection scheme, which has already been applied with good accuracy in monitoring different natural and environmental hazards (see [47] and references herein). It is based on the use of historical series of satellite data for a complete signal characterization (spectral, spatial and temporal) followed by an anomaly detection step using automatically-generated local (i.e., for a specific time and place of observation) thresholds. In its application to oil spill detection, namely RST-OIL, TIR data acquired by AVHRR or MODIS have been used to detect different oil spills occurred in different areas in the past [20; 26; 27]. In this paper, we use MODIS 250 m spatial resolution optical data for the detection and the monitoring of oil spills. MODIS channel 1 acquires information in the 620-670 nm spectral range (VIS), while MODIS channel 2 within 841-876 nm (NIR). In one of the first studies based on visible data [35], the oil spill reflectance in the spectral range of MODIS channels 1 and 2 was found to be greater than the seawater reflectance, but not enough to permit an easy distinction under natural irradiation. More recent studies on optical models [37; 38; 40; 42] demonstrated that the acquisition angle, combined with a particular irradiation geometry, may enhance the reflectance contrast between oil and the surrounding water [13; 22; 25; 32]. One of the main problems related to the use of visible bands for detecting oil spills is that the signal reflected by the oil film is not unique but it may change depending on several factors (and on their mutual combinations) such as sun/satellite geometry and sea surface roughness. As a consequence, oil spill can appear, in VIS and NIR bands, less or more reflecting than seawater [37; 38; 40; 42]. It is referred to as a _\"positive\"_ contrast when the reflectance of oil spill is higher than that of the clear seawater and as a _\"negative\"_ one when the reflectance of oil spill is less than that of the clear seawater. In detail, when sea surface is flat, the contrast between oil and sea surface is always negative since the oil produce a reflectance decrease; on the other hand, roughness of the sea surface produces a positive contrast [37]. Concerning sun/satellite geometry, when observing the surface from the vertical direction, even a small surface roughness  
Figure 1: Oil spill localization (**left**) and EMSA Radarsat-1 Image of 18 June 2007 at 03:52 a.m. GMT (adapted from [46] over the area within the red box (**right**). Three main oil slicks are outlined with the green ellipses. results always in a positive contrast value: the contrast is most pronounced when the observer sees the oil slick close to the sun reflection (positive contrast) and when the slick is observed at a low angle, almost horizontally (negative contrast) [37]. Starting from previous considerations on oil spill spectral signatures, we applied the RST methodology to MODIS data. In order to identify the \"signal anomaly\" caused by the presence of oil on the clear seawater surface, two indices were computed (one for each MODIS channel x), as follows:  
\[\otimes_{\rho_{\mathrm{x}}}\left(\mathrm{x,y,t}\right)=\frac{\rho_{\mathrm{ x}}(\mathrm{x,y,t})-\mu_{\rho_{\mathrm{x}}}(\mathrm{x,y})}{\sigma_{\rho_{ \mathrm{x}}}(\mathrm{x,y})} \tag{1}\]  
where \(\rho_{\mathrm{x}}\) (x,y,t) is the reflectance (expressed in terms of Rayleigh-corrected reflectance - R\({}_{\mathrm{rc}}\)) measured in the MODIS channel x (i.e., 1 or 2) at the pixel (x,y) at time (t). Further, \(\mu_{\mathrm{px}}\)(x,y) and \(\sigma_{\mathrm{px}}\)(x,y) are the corresponding reference fields (temporal average and standard deviation, respectively) computed by analysing a long-term data set of cloud-free satellite records collected at location (x,y) in the same observational conditions (the same month of the year and the same time of acquisition) of the image under investigation.