Developing a satellite optical sensor based automatic system for detecting and monitoring oil spills

Abstract

Oil pollution at sea is one of the most critical and destructive consequences due to human activity in marine areas, with an impact on the environment that requires decades to be reabsorbed. Satellite based remote sensing systems could be implemented for a surveillance and monitoring network. At present, the SAR system is the most widely used sensor for this purpose as it offers day and night high resolution images and it is not influenced by the presence of cloud cover, dust or smoke over the scene. The operational capabilities of these kinds of sensors are limited by factors such as the low revisiting frequency over the scene, the data's high cost, and finally the inability to make a certain assessment of the nature of the detected event without collecting data from complementary instruments. SAR sensor limitations could be complemented by optical sensor capabilities. In particular, multispectral sensors like MODIS offer a high number of spectral bands to detect, identify, classify and describe an oil spill event, and guarantee daily image frequency. However, optical sensors are highly dependent on meteorological conditions over the study area, they offer only low and medium resolution images and, finally, dedicated algorithms for image processing do not exist at present. For these reasons, the optical sensors play only a subordinate role with reference to SAR sensors. This work shows the results achievable through the development of dedicated algorithms for automatic image processing from MODIS data, and a method to classify and describe oil spill events

Reflection-coefficient experimental extraction from S21- parameter for radar oil-spill detection application

“…As shown in (2) and 4, the reflectivity function is periodic where its period is dependent on the frequency of the electromagnetic wave used and the oil dielectric constant. With respect to the target application related to oil spill detection, oil property is not a design-controlled parameter.…”

“…Considering that these accidents are happening on a worldwide scale, either intentionally or not, and analysing their severe influence on the ecosystem, it is crucial to have oil spill detecting and monitoring systems for a quick intervention and danger containment. Oil spill detection and monitoring is currently done with the aid of several techniques and sensors, with the most recent ones done remotely using satellite [2][3][4][5][6][7] and airborne systems [8,9] . In 2016, the European Maritime Safety Agency (EMSA) launched the need to complement the satellite maritime surveillance systems -that can detect only 25% of pollution accidents-by drones [10] .…”

A Sediment Detection Analysis with Multi Sensor Satellites: Caspian Sea and Persian Gulf case studies

“…For detecting suspended sediments events in coastal sea and ocean waters, researchers can use low or high-spatial resolution satellites data such as those provide by: SeaWiFs [4], MERIS [6], GOCI image [7], Landsat [8], Sentinel-3 [9], MODIS [10]-Aqua and Terra [11]. In particular, multispectral sensors like MODIS offer a high number of spectral bands to detect, identify, classify, describe and guarantee daily image frequency [12].…”

Oil Spill Detection Analyzing “Sentinel 2” Satellite Images: A Persian Gulf Case Study

“…In this framework, surveillance is the observation of a spill to gather information that is used to detect, identify, assess and monitor an ongoing spill scenario. Surveillance not only requires observation but also the recording, documentation and dissemination of the information gathered and used as a preparedness measure to monitor areas with potential oil spill risk (water surrounding installations, shipping routes, pipelines) [10]. Oil reflection characteristic not only depends on its class but also on its thickness; moreover its wavelengths are clearly different from seawater [10].…”