Detection of Oil Pollution Using SAR and Optical Remote Sensing Imagery: A Case Study of the Persian Gulf

The coastal regions in the Persian Gulf are renowned for having the largest oil reserves. Pipelines, as a means of oil transportation, are one of the most common options for transporting petroleum products in these regions. Hence, the risk of oil spill pollution has become a vital challenge for local authorities, which has gradually increased since the last decade. Therefore, it is essential to use a method for timely detection of oil spills to prevent environmental damage. In this study, Sentinel-1 SAR data and Sentinel-2 image have been used for timely detection of oil slicks in the Persian Gulf. The area of oil pollution that extracted from Sentinel-2 (optical data), Sentinel-1 (SAR data), and field data is 114.7, 98.5, and 124.7 square kilometres, respectively. The results indicated that the object-based image analysis (OBIA) method using optical data had better results than using SAR data. In addition, the results indicated that the OBIA could be used as a method to produce ground truth map. Therefore, this research demonstrates the applicability of remote sensing data to recognize oil spill pollution on the surface of the water with the applicability of Sentinel-1 and Sentinel-2 data.