Detection of oil slicks in the Persian Gulf using MODIS sensor images

The advances in technology have made it an alternative to traditional methods of monitoring, identifying and analyzing oil spills. SAR sensors are commonly used to detect oil spots, but their use of images is limited due to high costs, low crop width and poor time resolution. The MODIS sensor on the Terra and Okua platforms is taking pictures every two times from anywhere on the planet, with images at 250, 500, and 1000 meters resolution, which is a free and valuable resource for detecting oil spills. In this study, in order to detect oil spills during the three oil spill events in the years 2007, 2015, and 2016, oil spills were detected using surface-level images of MODIS. In the pre-processing stage, MODIS images were converted to atmospheric reflections. In order to detect oil spots, an indicator of oil spill detection was used to study the effect of oil spots on the concentration of water chlorophyll and phytoplankton, floating algae, water color, blue opacity and The surface water temperature was used from the indices and algorithms of OC3, CMI, FAI and SABI, NDVI, TWI and SST4 algorithms respectively. The results show that the oil spots in the OSI index output correspond to the pixels with the highest DN in the image per year, as well as oil spots, which reduce the concentration of chlorophylls, floating algae, water color and water surface temperature, and increasing the opacity of the water. For all indices and algorithms, oil spots are consistent with pixels with a minimum value of DNs. Among all the used methods, only the CMI for phytoplankton does not show any significant changes in the range of oil spills; therefore, it is suggested that the methods and indices used in this study be used to detect oil spots.