**4. Monitoring an oil spill with optical remote sensing: potential**

Research on the utilization of remote sensing technology for oil spill pollution detection has been ongoing for more than a decade. Optical and microwave sensors have been examined in several studies for oil spill detection and monitoring in several coastal water. Because of its wide area coverage and day and night all-weather capabilities, SAR deployed on satellites is now an essential instrument in oil spill monitoring. However, the majority of research on airborne remote sensing methods is not included. Although there have been a few attempts to use optical data, the main satellite or airborne data source primarily used for oil spill detection is the microwave sensor [1, 6, 22].

The most popular technique for remote sensing is optical. Due to their low cost and availability as commercial-off-the-shelf (COTS) items, cameras—both still and video—are widely used. Now, affordable digital single-reflex (SLR) cameras and camcorders are readily available. In the visible range (between 400 and 700 nm), oil has a higher surface reflectance than water, but it exhibits fewer general absorption tendencies [6, 22].

The oil that is "optically thick" absorbs solar energy and releases it again as thermal energy, primarily in the 8–12 μm spectral range [18–20]. Infrared images show that thick oil is hot, intermediate thicknesses are cool, and thin oil or sheen cannot be seen. In the evening, the opposite is seen. Although the precise thicknesses at which these transitions take place are unknown, scientific evidence indicates that the minimum detectable layer occurs between 10 and 70 μm and that the transition between the hot and cool layers happens between 50 and 150 μm. Due to the difference in emissivity between oil (0.94–0.97) and water, when the oil and water are at the same actual temperature, the oil will appear to be cooler (0.98). The infrared temperature difference between oil and water can be used to detect oil spills, and the magnitude of the difference is correlated with the thickness of the layer [1, 17, 18, 22].

Therefore, infrared sensors in the 8–12 μm range are now far more reliable and accurate than traditional infrared scanners. In this view, the "thermal infrared region," with wavelengths between 8 and 12 μm, is where infrared remote sensing has most frequently been used. Mid-band IR system tests (3–5 μm) have shown that these sensors might be useful. No spectral structure is present in this region, according to specific studies in the thermal infrared (812 μm) [17, 18, 22].

However, oil detection using infrared technology is not foolproof due to potential interferences and false positives, so the use of both IR and UV together can offer a more conclusive sign of the presence of oil than either method by itself. UV sensors are not used in operational response modes and would not play a significant role unless they are used in conjunction with IR technologies [1, 6, 17, 18, 22]. The Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument may be used to keep track of oil spills. MODIS has a broad spectral range and two bands with a moderate resolution of 250 m and 500 m. On the other hand, using multiple wavelengths can give you more information to tell the difference between oil spills and slicks caused by algal blooms. However, in a tropical region like Malacca Straits, where there is a lot of cloud cover, the MODIS data has a lot of problems because of heavy cloud cover [17, 18, 20, 21]. The use of hyperspectral sensors for oil spill monitoring has the potential to offer precise material identification and a more accurate assessment of their abundance. A hyperspectral sensor's more than 200 wavelengths allow for the exploitation of the spectral signature of oil and the differentiation of various oil types. This can reduce the frequency of false alarms caused by ocean features resembling oil in appearance and color [1, 22].

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

In this regard, a signature matching method based on airborne hyperspectral imaging is more precise than conventional techniques, where analysis is based on a visual interpretation of the oil's color and its appearance in the satellite image. There is not a commercial hyperspectral sensor in orbit right now. One example of a space-borne technology demonstrator that was launched in 2000 is the NASA EO-1 Hyperion hyperspectral sensor. However, its narrow swath width of only 7.5–100 km is its main disadvantage [20, 22].

The oil absorbs solar energy and releases some of it as thermal energy back into the atmosphere. This oil cannot be detected by IR sensors, which perceive thick oil slicks as hot and intermediate thicknesses of oil as cool. A thick spill can appear cooler than the surrounding water at night because it dissipates heat more quickly. Oil can quickly absorb and release thermal energy, whereas water has a slower rate of heat absorption and release. Oil slicks can cool off more quickly than the surrounding water as a result, and IR sensors can detect this temperature difference. To identify the presence of oil slicks in water bodies, IR sensors are crucial tools [22].

The NOAA Advanced Very High-Resolution Radiometer (AVHRR) has visible and infrared sensors with early detection and monitoring capabilities for oil spills. The 1991 Persian Gulf War's oil spills were investigated. The oil spills might not have a temperature signature that is noticeably different from the surrounding water at night, but the IR channel was able to detect thick and thin oil layers as well as the boundary between water and oil. Only in very favorable lighting and sea conditions were oil spills visible in the images [1, 22].

Another passive sensor is an MWR. The instrument is weather-insensitive because it only detects microwave radiation from the ocean in the cm to mm range. Oil slicks appear as bright objects on a darker sea because they emit microwave radiation that is stronger than the water. Oil slicks can have strong surface-emissivity signatures, but since determining the thickness of oil slicks requires a spatial resolution of tens to hundreds of meters, aircraft sensors are the most appropriate choice for this type of sensor for oil spill thickness monitoring [1, 6, 22].

Several studies for the monitoring and detection of oil spills compare SAR and optical sensors. For instance, the SAR data have the lowest backscatter levels in regions with algal blooms, whereas the SeaWiFS measures high levels of chlorophyll in these regions. Needless to say, different data sets could be used to distinguish between oil spills and look-alike phenomena like algal blooms [9, 22–24].
