Using Sentinel-2 imagery for detecting oil spills via spatial roughness of mixed normalized difference index

Abstract

The free and open access optical sensor data from the Sentinel-2 constellation can be used for supporting the operation of oil spill monitoring. It has several spectral bands from visible to shortwave infrared with medium to high resolution, which is suitable for detecting the oil spills. However, the spectral signature of the oil spill often has similar to the surrounding environment. Moreover, it also depends on many parameters, such as sensing angle, sea depth, wave characteristics, etc. In this paper, we propose the method for detecting the oil spill by using the Sentinel-2 images. It is based on the Mixed Normalized Difference Index (MNDI) derived from the Normalized Difference Vegetation Index (NDVI) and the Reversed version of the Normalized Difference Index (NDI) applied for the forest fire monitoring. This index will give the high variation values in the oil spill area, which can estimate the oil spill area by observing its spatial roughness. Four study areas in Saudi Arabia, Greece, Azerbaijan, and Indonesia were used to evaluate the detectable performance compared with the current methods. The visualized results show that our algorithm gives noticeable results and high contrast, including low noise, except the oil spills in Greece.