Department of Environment Research, Fujairah Research Centre, Sakamkam Road, Fujairah, United Arab Emirates
Research Article
Effective Oil Spill Monitoring Approach over the Gulf of Oman by Using Advanced Machine Learning and Data Mining Tools
Author(s): Aishah Saeed Jumah Alabdouli, Muhammed Sirajul Huda Kalathingal, Shaher Bano Mirza* and Fouad Lamghari Ridouane
Oil spills negatively impact the environment by endangering marine ecosystems, and coastal surroundings. The
environmental damage from an oil spill by a tanker, pipeline, or offshore rig can be devastating almost immediately
and can last for decades. Consequently, the purpose of this study is to detect oil spills in the Gulf of Oman. To find
oil spills, Sentinel-2 spectral imageries are used. Sentinel-2 divides the image into N grids and uses Sentinel-2 band
ratio for mapping oil spills to execute instance segmentation using a Yolov7 to accomplish oil spill detection in a
single step. In our experiment, the trained Yolov7 instant segmentation model was able to produce exceptionally
accurate intersection over union results, correctly identifying 91% of the actual oil spill. These results explain the
potential of artificial intelligence and significant impact that c.. View more»