HW revision
Naya
RemoteSensing.docxRunning head: REMOTE SENSING 1
REMOTE SENSING 6
The Physical Basis for oil spill Detection from Remote Sensing Observations
Name
Institutional Affiliation
The Physical Basis for oil spill Detection from Remote Sensing Observations
Introduction
Minimizing the risks of oil spill disasters is critical in safeguarding the environment and reducing potential economic losses. Oil spill surveillance forms a significant part of oil spill disaster management. The advancements in remote sensing technologies have the potential to support the process of identification of parties that are responsible for pollution and detection of minor spills before they can result in a major damage (Jha, Levy & Gao, 2008). The number of sensors has been increasing tremendously in the last five decades. As such, there is need to undertake a comprehensive assessment of the already existing technologies of the detection of oil spill. An improved u7dnerstanding of the strengths and limitations of oil spill surveillance sensors can be an important step in the improvements of operational utilization of these sensors for oil spill response and disaster planning. Remote sensing technologies are increasingly being used for the physical detection of oil spills.
The Physical Basis for oil spill Detection from Remote Sensing Observations
The oil sector plays a critical role in improving the living standards of the modern society. This is especially true when it comes to provision of energy for transportation, industries, and other areas of operation (Jha, Levy & Gao, 2008). Due to the importance of oil in the society, millions of liters of oil are transferred everyday from the oil field to their final consumer destinations. This process makes oil vulnerable to potential spills during oil transportation and extraction. In addition, oil spills may take place during storing. Spillages commonly occur in water, ice, and land. The BP oil spill catastrophe that took place in the Gulf of Mexico indicates that oil spills can be highly dangerous to both humans and other diverse forms of life (Jha, Levy & Gao, 2008). Oil spills can be calamitous when winds, waves, and currents scatter a large oil spills over a large area within a short period of time.
There are various ways in which remote sensing techniques can be used to undertake oil spill detection and mapping. They include: passive means of detection and mapping, use of optical techniques, use of visible spectrum, as well as use of the infrared technology. The passive means of oil spill remote sensing involves the utilization of cameras in the visible and infrared spectra. In this mechanism wavelengths such as infrared and ultraviolet radiations are less commonly utilized (Fingas & Brown, 2018). On the other hand, optical techniques are commonly used because oil usually indicates minor optical properties in the region from the ultraviolet to near infrared. These are differential reflectance, and absorbance between oil and water in a specific spectral region. The differential reflectors often differ from one oil type and level of vaporization to another. Oil cannot be accurately identified with the use if just a single optical data in a visible region. This is particularly true when the location of the oil spill is unclear.
Figure 1: CCD Detectors and Optical Systems
Visible spectrum systems operate on the idea that oil and water have polarizing impacts on light. As such, the task of viewing oiled water with polarized lenses can be important in improving contrast, and hence oil detection. The light that has been reflected from a water surface reflects at an angle of 53 degrees (Fingas & Brown, 2018). Therefore, contrast can be enhanced by placing the detectors at that angle. The light that is directly reflected from the surface is comprised of most data on surface oil. This strategy can be efficacious in improving contrast by as high as 100 percent. Nonetheless, there are various obstacles that may pose interference with the utilization of visible light, darkness, sun glitter, and cloud covers. Sun glitters are normally mistaken for oil sheens. Therefore, sun glitters are challenging in visible remote sensing. They can be minimized with the utilization of signal processing strategies.
Figure 2: Spill Detection Through Visible Spectrum
Infrared systems are also commonly used for mapping and detection of oil spills. Oils of thickness that is wider than 10 um absorb light in the visible areas and re-radiate portions of these in the infrared spectrum, mainly within the 8 to 14 um wavelengths (Fingas & Brown, 2018). Solar-heated oil can emit infrared radiations since oil possesses greater infrared emissivity that water. Thick oil seems heated or hotter than the surrounding waters in infrared images, intermediate thickness layers of oil seem cool. On the other hand, thinner layers of oil seem not to be unique or differentiated for others. The transitional thicknesses are not commonly understood. However, the commonly held suggestions are that the differences between cold and hot layers range from 50 to 150 um. Further, the lowest level of thickness that can be identified ranges from 10 to 70 um (Fingas & Brown, 2018). The explanation for the cool slick phenomenon can be that a 20 to 50 um layer of oil on the water results in destructive interference of the IR wave fronts. This problem leads to significant reduction of the thermal radiation released.
Figure 3: Infrared Oil Spill Detection
Remote sensing technologies used in the management of coastal environments can also be applied in the detection of spills. This is especially true when oil spills affect the coastal environments and ecosystem such as coral reefs, wetlands, and estuaries (Klemas, 2010). For instance, multispectral and hyperspectral imagers are utilized to support the process of mapping the coastal land cover, concentrations of organic or inorganic matter that are suspended and dissolved in coastal waters (Klemas, 2010). In addition, thermal infrared scanners have the capacity to map the surface of the sea and its temperatures in an accurate manner. In so doing, it can chart coastal currents. Furthermore, microwave radiometers are technologies that have the capacity to measure the degree of ocean salinity, soil moisture, and other hydrological characteristics of the coastal environment. Other technologies include radar imagers, scatterometers, and altimeters (Klemas, 2010). These technologies can be instrumental in offering information on oceanic waves, ocean winds, and the height of the sea surface. Finally, the utilization of airborne light detection and ranging systems can support the generation of bathymetric maps even in situations in which there are moderately turbid coastal waters.
References
Fingas, M., & Brown, C. (2018). A review of oil spill remote sensing. Sensors, 18(1), 91.
Klemas, V. (2010). Remote sensing techniques for studying coastal ecosystems: An
overview. Journal of Coastal Research, 27(1), 2-17.
Jha, M., Levy, J., & Gao, Y. (2008). Advances in remote sensing for oil spill disaster
management: state-of-the-art sensors technology for oil spill surveillance. Sensors, 8(1),
236-255.
