**6. Look-alikes keystone issue in SAR data**

The term frequently refers to an oil spill in the ocean. Oil spills can have devastating effects on the marine environment, including killing wildlife and polluting the water [6, 20, 23, 25]. In particular, an oil spill is a type of pollution that occurs when a liquid petroleum hydrocarbon is released into the environment as a result of human activity. Crude oil, refined petroleum products (like gasoline or diesel fuel) or byproducts, ship bunkers, oily waste, or waste mixed with oil are some of the different components that make up the oil. Pollution from the oil spill is challenging to remove. Natural oil seeps are another source of oil entering the marine environment. Although the majority of oil pollution caused by humans occurs on land, seagoing oil tankers have received the majority of public attention and regulatory attention. Unrelated to the oil spill, there are dark patches [9, 21, 22].

SAR satellite data is typically regarded as the most effective and superior satellite sensor for finding oil spills. Nevertheless, oil spill thickness estimation and oil type identification cannot be done with SAR data. The ability to distinguish between oil spills and look-alikes is the main issue with SAR data for oil spill detection. In actuality, both show up in SAR data as dark patches. Natural dark patches are referred to as "oil slick look-alikes" in this context. Natural films and slicks, ice, threshold wind speed regions (wind speeds of 3 m/s), wind protection from the land, rain cells, shear zones, internal waves, and other phenomena are examples of look-alikes (**Figure 6**). In a strict sense, an oil spill only refers to man-made slicks connected to crude petroleum and the products it produces, such as heavy and light fuel [9, 22, 24].

Currently, the SAR sensor is unable to differentiate between the various pollutants. However, for the large Sea Empress oil spill, there is a good correlation between the largest reduction in backscatter and the thickest oil as determined by visual

*Introductory Chapter: Issues with Oil Spills and Remote Monitoring DOI: http://dx.doi.org/10.5772/intechopen.110559*

**Figure 6.** *Look-alike in SAR data.*

observations for a constrained range of wind speeds (5–6 m/s). This suggests that a single SAR frequency may not be sufficient to estimate the thickness of the oil spill. When selecting features to distinguish between oil spills and lookalikes, these experiences must be taken into consideration. To distinguish between oil spills and look-alikes, physical, geometrical, and geographical parameters must be used, as well as significant characteristics like wind speed [9, 16–24].
