# A MODIS-Based Robust Satellite Technique (RST) for Timely Detection of Oil Spilled Areas
## 3 Results and Discussion  
### RST Implementation  
On the day of the event, 18 June 2007, the first MODIS image available for the area affected was the Terra one acquired at 9:15 a.m. GMT. The corresponding red-green-blue (RGB) image (Figure 3) was generated using the georeferenced R\({}_{\mathrm{rc}}\) at 645 (R), 555 (G), and 469 (B) nm produced for such MODIS-Terra data. Unfortunately, the whole area affected by the event was covered by clouds, masking the sea surface and preventing a reliable analysis. Owing to the high revisiting time offered by sensors aboard weather satellites such as MODIS, the same area was sampled by Aqua at 10:50 a.m. GMT as shown in Figure 4 (with the same RGB combination of the previous figure). Figure 2: RST reference fields computation flowchart. In this image, thanks to the different conditions of the observation in terms of sun-satellite geometry and atmosphere contribution from the previous Terra acquisition, very few elongated areas characterized by a positive contrast are clearly evident, approximately at the same positions of the oil spill reported by EMSA (green ellipses in Figure 4). Some clouds are also present, more evident in the northwest corner of the image. By making a spatial profile on the related MODIS R\({}_{\rm rc}\) channel 1 and 2 images (depicted in grey tones in Figure 5a,b) in correspondence to the area within one of the green ellipses (Z-Z' blue transect in Figure 5a,b), an increase of the reflectance is visible (Figure 5c), which reaches values higher than the one produced by the very low, thin stratocumulus (signal with a high frequency variability in the right part of the graph). The increase in reflectance is really relevant, up to 0.1%, which is very high for clean seawater. Figure 4: MODIS-Aqua true color R\({}_{\rm rc}\) RGB image of 18 June 2007 at 10:50 a.m. GMT. The green ellipses indicate the same areas already highlighted in Figure 1.  
Figure 3: MODIS-Terra true color R\({}_{\rm rc}\) RGB image of 18 June 2007 at 09:15 a.m. GMT. The green ellipses indicate the same areas already highlighted in Figure 1.  
The signal behavior shown in Figure 5c suggests that the indices presented in this work (cf. Equation (1)) should exhibit very high positive values in correspondence to the areas with such a high increase in reflectance. The outputs produced by the implementation of the two indices are plotted in Figure 6. In detail, in these images, the R\({}_{\mathrm{rc}}\) channel 1 (or 2) signal is plotted in the background in grey tones, while only the pixels characterized by the highest \(\otimes_{\mathrm{px}}\) values have been highlighted in blue. Such a strategy has to be preferred in the detection phase because it allows undeniably identifying the presence of oil-affected areas. These areas were identified by the proposed approach when using the signal measured in MODIS channel l with a very high signal-to-noise (S/N) ratio value, namely higher than 26 (Figure 6a). Considering Equation (1), this means that the deviation of the signal observed at the pixel level with respect to the temporal mean is (at least) 26 times higher than the historically observed local variability, namely the standard deviation signal previously computed. In detail, four anomalous pixels were detected as certainly polluted by oil in the total absence of false alarms. The presence of the oil spill was detected by RST with a higher S/N value (\(\otimes_{\mathrm{ch2}}>49\)) at channel 2 than at channel 1 (Figure 6b). The higher signal absorption by water in the NIR than in the VIS regions explains this difference, enhancing the contrast between reflecting bodies and the surrounding seawater. Also, in this case, the unique oil spill-affected pixel (commonly identified by the VIS approach) was detected in the total absence of false alarms. Once the presence of the oil spill is detected for certain, the \"adjustability\" (tunability) of the RST technique allows us to map the intensity and the structure of the detected anomalies in detail (Figure 7).