**2. Oil spill monitoring system**

In this section, we present a brief overview of the state-of-the-art techniques used for oil spill monitoring in relation to the sensors used and to the platforms operated during the oil spill. Then, we motivate our new proposed solution by listing the system features, the required functionalities for an effective contingency plan, and how our solution differs from relevant state-of-the-art techniques. For more details about oil spill surveillance systems, the reader is encouraged to refer to [12–14].

#### **2.1 Sensors**

### *2.1.1 Visual sensors*

Despite many shortcomings, passive sensors that operate in the visible region of the light are still used in oil spill remote sensing. The effect of some environmental conditions such as sun glint and wind sheen would lead to a misinterpretation by creating a resemblance to oil sheens, which is considered a limitation of such sensors [1]. Another drawback is that visual sensors cannot operate at night because they are using sunlight reflectance for operation. In addition, they require cloudless and clear weather requirements. Given the limitations of visual sensors for oil spill detection, and since they are not able to provide thickness information or oil classification, these sensors are not used alone for oil spill monitoring. For example, in [15], optical remote sensing images are combined with visible infrared imager radiometer suite (VIIRS) images in a semi-automatic fashion to extract oil slick features. The technique is tested in the North-West of the Gulf of Mexico. However, this method cannot be fully automated and requires human intervention to set a proper threshold for feature extraction. Optical sensors are rather used to document the spill and to provide a frame of reference for other sensors [16, 17].

#### *2.1.2 Infrared sensors*

Infrared passive sensors are relatively cheap remote-sensing technologies that can be used to detect oil spills [18]. The emissivity of the oil in the thermal infrared red region is lower than the emissivity of the water. This is how the thick oil could be distinguished from the background water by absorbing the infrared radiation from the sun and appearing as a hot spot compared with the cold background for the water [1]. An opposite phenomenon is observed during the night when the heat loss from the oil layer is faster compared with the water. This is the reason why they appear cooler at night [19]. However, false-positive results could be obtained by misinterpreting the thermal radiation from seaweeds. In addition, infrared sensors require the absence of cloud and heavy fog for good operation [1, 2, 20]. Infrared sensors can detect oil films with 10s–100 s um thickness. However, the brightness of the infrared sensing-based imagery does not vary with slick thicknesses in the mm range. Therefore, we cannot rely on infrared sensors to yield slick thickness measurements [13, 21, 22]. Chen et al. [23] shows that thermal infrared sensors that are mounted on helicopters can detect oil spills in the accident of the Dalian Xingang oil pipeline explosion in July 2010. Similarly, [24] shows that using MODIS thermal infrared data, the information obtained from the sea surface temperature identifies the oil film from seawater. This technique is applied to the Jiyyeh spill when Israel bombarded storage tanks in Lebanon during the war of 2006, where around 15,000 tons of heavy fuel oil spilled into the Mediterranean Sea [24, 25].

#### *2.1.3 Ultraviolet sensors*

Very thin oil films have a strong reflectance in the ultraviolet region compared with seawater. This allows the use of ultraviolet sensors for oil spill detection when the thickness is not greater than 10 um. Also, look-alikes such as sun glints, wind slicks, and biogenic material challenge ultraviolet sensors for oil spill detection [1, 3]. Huang et al. [26] proposed adaptive thresholding for chemical spill detection (not oil

### *Recent Advances in Oil-Spill Monitoring Using Drone-Based Radar Remote Sensing DOI: http://dx.doi.org/10.5772/intechopen.106942*

specifically) from ultraviolet images, which shows a distinction between the chemicals and the water background. Desbiens et al. [27] used ultraviolet range for remote detection of hydrocarbons such as benzene. Generally, fewer ultraviolet sensors are being used for oil spills in today's remote sensing because of the low relevance of thin slicks to oil spill cleanup [3, 13, 28].

#### *2.1.4 Passive microwave radiometer sensors*

Compared with water, the oil emits stronger microwave radiation and appears brighter in the background. Passive microwave radiometers [29–32] are used for both oil spill detection and thickness estimation [13]. The need to acquire knowledge about weather conditions, the low spatial resolution of this sensor, and the a-priori knowledge required about the oil characteristics all influence the microwave brightness and decrease the effectiveness of microwave radiometers for oil spill monitoring [1]. Furthermore, the main issue with this technology tends to be the cyclical relationship between the microwave brightness of the slick and its thickness. Currently, available models can only measure limited thickness ranges [14]. For example, using a multifrequency passive microwave radiometer, the measured thickness range is limited between 0.1 and 1.5 mm as reported in [33], or the results were underestimating the real thickness values as in [30] where the calibration methodology and the selection of frequencies limited the measured thickness to a maximum of 1 mm. The only commercial tools currently available for measuring slick thickness are the Optimare 3–5 channel microwave instruments. They can provide thickness up to 3 mm only [13]. Given the requirement of a dedicated aircraft to mount this sensor, in addition to their high cost, it is complicated to put them into operation. Currently, the microwave sensor is not being used for oil detection and slick imaging [13].

#### *2.1.5 Radar sensors*

With the absence of oil slicks, a bright image is obtained by radar sensors for clean seawater. Once the oil is spilled into seawater, the ocean capillary waves are reduced, and radar reflections are decreasing. Dark spots are obtained in radar imaging. This allows for oil spill detection [34]. Synthetic aperture radar (SAR) and side-looking airborne radar (SLAR) are the two most common types of radar, which are used for oil spill remote sensing [35]. Imaging SAR systems [36–39] are off-nadir instruments whose backscattering over the ocean is primarily due to Bragg scattering at relevant incident angles. The synthetic aperture radar technique is highly prone to false targets, however, and is limited to a narrow range of wind speeds when small ocean waves do not yield a difference between the oiled area and the sea [2]. SAR techniques are not used for oil thickness estimations nor for oil classification. Being widely mounted on space-borne platforms, the radar is a very useful active sensor for a synoptic view of the oil spill over a wide scene [1].

#### **2.2 Platforms: Airborne to satellites to complementary drones**

Most recent techniques using one sensor, or a combination of sensors, are done remotely using airborne systems [40, 41] or satellites [42–47]. Radar satellites provide a selection of resolutions and polarizations [13]. Serious efforts have been made to replace airborne remote sensing with satellite remote sensing. However, satellites face the limitations of overpass frequency and low spatial resolution [12], and the long

time required for processing the dataset, potentially disrupting oil spill contingency planning. This limitation has been improved using satellite constellations. A revisit time within a few hours can be provided by a larger number of SAR satellites. Airborne systems, despite their high cost due to aircraft dedication, can be used directly when needed for real-time dataset processing [1]. In addition, they provide flexibility in terms of deployment time and choices of sensors. Therefore, a combination of satellite and airborne sensors is used in many countries in northern Europe for oil spill surveillance. The strategic planning is based on satellite imagery that provides a synoptic view of the oil spill, whereas airborne sensors are used for short-term or tactical responses [9]. Contrarily to visible and radar sensors, due to the high atmospheric absorption and scattering, many sensors including the infrared and the fluorosensors are not suitable to be operated on a space-borne platform [34, 48].

Despite all the effort done using space-borne platforms, only 25% of the pollution cases are detected by satellite systems. For a quick response and rapid intervention, the European Maritime Safety Agency (EMSA) has proposed using drones as complementary systems in satellite maritime surveillance [49]. Aerial surveillance could be improved significantly through the introduction of drones because it is a quick assessment tool for oil spill accidents [50]. In addition, drone-based tools will be particularly valuable as it provides high spectral resolution, at a relatively low cost.
