scholarly journals Multispectral UAS system for detecting, characterizing, and mapping oil spills on near shore environments

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Oscar Garcia ◽  
Jay Cho ◽  
Lisa DiPinto ◽  
Benjamin Shorr ◽  
brandi Todd ◽  
...  
Keyword(s):  
Real Time ◽  
Oil Spill ◽  
Oil Spills ◽  
Ultra Violet ◽  
Multispectral Data ◽  
Lake Washington ◽  
Near Shore ◽  
Long Wave Infrared ◽  
Operational Tool

Abstract We have developed a UAS system that collects multispectral data in order to characterize oil slick thicknesses and emulsification ratios. This system consists on a UAS that carries multiple cameras that integrate 10 wavelength band sensors ranging from Ultra-Violet (UV) to Long Wave Infrared (LW-IR). This system has been originally tested at OHMSETT and at the MC-20 site in the Gulf of Mexico. More recently this UAS was put in operation during the Lake Washington Wellhead blowout in Louisiana. In here we present examples of how this operational tool allowed oil spill responders to efficiently deploy containments of the floating oil (booming) and to monitor the collection of the oil on real time. Moreover, using a rapid classification algorithm, the multispectral data collected by our UAS allowed us to make a detailed high resolution classification of the oil detected on the shorelines of the affected areas. The UAS also delivered near real time oil detections that were used during the spill by the NOAA oil spill science coordinators through the ERMA system. This UAS has proven its ability to detect oil on ‘hard to reach areas’ and it offers a valuable option for the evaluation of affected areas impacted by the spill. We compared the SCAT surveys with the UAS oil detections and conclude the importance of adding this UAS tool as part of the operational assessment of the spill to determine the level of impact of the spill on the nearshore environment.

ECOLOGICAL AND GEOMORPHOLOGICAL ASSESSMENT OF THE VULNERABILITY OF THE COASTS OF THE KARA SEA TO THE OIL SPILL

2017 ◽  
Author(s):  
Alexander Ermolov ◽  
Alexander Ermolov
Keyword(s):  
Oil Spill ◽  
Oil Spills ◽  
International System ◽  
Kara Sea ◽  
Coastal Protection ◽  
Sensitivity Index ◽  
Oil Spill Response ◽  
Expert Assessments ◽  
International Systems

International experience of oil spill response in the sea defines the priority of coastal protection and the need to identify as most valuable in ecological terms and the most vulnerable areas. Methodological approaches to the assessing the vulnerability of Arctic coasts to oil spills based on international systems of Environmental Sensitivity Index (ESI) and geomorphological zoning are considered in the article. The comprehensive environmental and geomorphological approach allowed us to form the morphodynamic basis for the classification of seacoasts and try to adapt the international system of indexes to the shores of the Kara Sea taking into account the specific natural conditions. This work has improved the expert assessments of the vulnerability and resilience of the seacoasts.

scholarly journals OILSPILL AND LOOK-ALIKE SPOTS FROM SAR IMAGERY USING OTSU METHOD AND ARTIFICIAL NEURAL NETWORK

2020 ◽  
Vol 4 (11) ◽  
pp. 1-10
Author(s):  
M. Sornam
Keyword(s):  
Image Segmentation ◽  
Oil Spill ◽  
Oil Spills ◽  
Marine Ecosystem ◽  
Dark Spot ◽  
Oil Spill Detection ◽  
Otsu Method ◽  
Artificial Neural ◽  
Propagation Network

Oil spill pollution plays a significant role in damaging marine ecosystem. Discharge of oil due to tanker accidents has the most dangerous effects on marine environment. The main waste source is the ship based operational discharges. Synthetic Aperture Radar (SAR) can be effectively used for the detection and classification of oil spills. Oil spills appear as dark spots in SAR images. One major advantage of SAR is that it can generate imagery under all weather conditions. However, similar dark spots may arise from a range of unrelated meteorological and oceanographic phenomena, resulting in misidentification. A major focus of research in this area is the development of algorithms to distinguish ‘oil spills’ from ‘look-alikes’. The features of detected dark spot are then extracted and classified to discriminate oil spills from look-alikes. This paper describes the development of a new approach to SAR oil spill detection using Segmentation method and Artificial Neural Networks (ANN). A SAR-based oil-spill detection process consists of three stages: image segmentation, feature extraction and object recognition (classification) of the segmented objects as oil spills or look-alikes. The image segmentation was performed with Otsu method. Classification has been done using Back Propagation Network and this network classifies objects into oil spills or look-alikes according to their feature parameters. Improved results have been achieved for the discrimination of oil spills and look-alikes.

ESTIMATING MORTALITY OF SEABIRDS FROM OIL SPILLS

1987 ◽  
Vol 1987 (1) ◽  
pp. 547-551 ◽  
Author(s):  
R. Glenn Ford ◽  
Gary W. Page ◽  
Harry R. Carter
Keyword(s):  
Real Time ◽  
Emergency Response ◽  
Oil Spill ◽  
Potential Application ◽  
Damage Assessment ◽  
Oil Spills ◽  
Central California ◽  
Marine Oil ◽  
Large Numbers ◽  
Using Data

ABSTRACT From an aesthetic and damage assessment standpoint, the loss of seabirds may be one of the more important results of a marine oil spill. Assessment of the actual numbers of seabirds killed is difficult because the bodies of dead or incapacitated seabirds are often never found or recorded. We present a computer methodology that estimates the number of birds that come in contact with an oil spill and partitions these birds among four possible fates: (1) swimming or flying ashore under their own power; (2) carried out to sea by winds and currents; (3) carried inshore, but lost before being beached; and (4) beached by winds and currents. Beached birds are further divided into those that are recovered and those that are not. The accuracy of the methodology is examined using data for two recent spills in central California, each of which resulted in the beachings of large numbers of birds. The methodology also has potential application to real-time emergency response by predicting when and where the greatest numbers of bird beachings will occur.

ECOLOGICAL AND GEOMORPHOLOGICAL ASSESSMENT OF THE VULNERABILITY OF THE COASTS OF THE KARA SEA TO THE OIL SPILL

2017 ◽  
Author(s):  
Alexander Ermolov ◽  
Alexander Ermolov
Keyword(s):  
Oil Spill ◽  
Oil Spills ◽  
International System ◽  
Kara Sea ◽  
Coastal Protection ◽  
Sensitivity Index ◽  
Oil Spill Response ◽  
Expert Assessments ◽  
International Systems

International experience of oil spill response in the sea defines the priority of coastal protection and the need to identify as most valuable in ecological terms and the most vulnerable areas. Methodological approaches to the assessing the vulnerability of Arctic coasts to oil spills based on international systems of Environmental Sensitivity Index (ESI) and geomorphological zoning are considered in the article. The comprehensive environmental and geomorphological approach allowed us to form the morphodynamic basis for the classification of seacoasts and try to adapt the international system of indexes to the shores of the Kara Sea taking into account the specific natural conditions. This work has improved the expert assessments of the vulnerability and resilience of the seacoasts.

Oil Spill Buoys Research for the Oil Spill Accidents Emergency

2013 ◽  
Vol 331 ◽  
pp. 57-60
Author(s):  
Ping Zhao ◽  
Di Cui
Keyword(s):  
Real Time ◽  
Oil Spill ◽  
Maximum Degree ◽  
Oil Spills ◽  
Environment Protection ◽  
Ability Level ◽  
Time Dynamic ◽  
Oil Spill Response ◽  
Marine Oil Spills ◽  
Reliable Basis

Oil spill accidents are seen relatively frequent and becomes a severe threat to coastal and marine ecosystems and water quality. Thus, this purpose of paper is developed for the active surveillance and rapid response to marine oil spills is important and essential to environment protection. It may appears of leak places for the monitoring needs, and to achieved instant alarm technology and equipment, guarantees leak occurred timely obtained alarm information. In order toproviding oil spill accidents emergency quickly reaction time and prepared, the maximum degree reduce oil leak and accidents caused influences are ensured. Furthermore, the new oil leak forecast warning (tracking &alarm-monitor) technologies are provided.All-weather real-time dynamic system has the function of off-shore oil spill tracking, the spread of oil spill surveillance and the real-time alarm, timely, accurately grasp the oil spill accident happened at the time and place for relevant departments, quickly take emergency and rescue measures to provide reliable basis, promote the oil spill response ability level..

AUTOMATED SYSTEM FOR NEAR-REAL TIME PREDICTION OF OIL SPILLS FROM EU SATELLITE-BASED DETECTION SERVICE

2017 ◽  
Vol 2017 (1) ◽  
pp. 1574-1593 ◽  
Author(s):  
Rodrigo Fernandes ◽  
Francisco Campuzano ◽  
David Brito ◽  
Manuela Juliano ◽  
Frank Braunschweig ◽  
...  
Keyword(s):  
Real Time ◽  
Oil Spill ◽  
Hazard Assessment ◽  
Situational Awareness ◽  
Oil Spills ◽  
Oil Pollution ◽  
Warning System ◽  
Pollution Source ◽  
Google Earth ◽  
Automated System

ABSTRACT 2017-244: The state-of-the-art in both operational oceanography, remote sensing, and computational capacity, enables now the possibility of developing near-real time, holistic automated services capable of dramatically improving maritime situational awareness to responding to oil spill emergencies. Based on the European satellite-based oil spill and vessel detection service – CleanSeaNet (EMSA – European Maritime Safety Agency), which distributes oil pollution detection standardized notification packages in less than 30 minutes, a new automated early warning system (EWS) for near-real time modelling and prediction of the detected oil spills was developed. This EWS provides 48-hour oil spill forecasts + 24-hour backward simulations, delivering results 5–10 minutes after the reception of the oil spill detection notifications. These forecasts are then distributed in multiple formats and platforms (e.g. Google Earth, e-mail). The oil spill fate and behaviour model used in this EWS is part of MOHID modelling system, and is coupled offline with metocean forecast solutions, taking advantage of autonomous models previously run in multiple institutions. The system is currently able to integrate various metocean forecasting systems, being agnostic about the data sources and applied locations, as long as their outputs comply with commonly adopted formats, including CF compliant files or CMEMS (Copernicus Marine Environment Monitoring Service). The EWS is currently operational in western Iberia, supporting Portuguese Maritime Authority, and is being expanded to neighbourhood regions (from Spain and Morocco) with high resolution metocean models (MARPOCS project funded by European Union Humanitarian Aid & Civil Protection). Taking advantage of the coupling of MOHID oil spill model and CleanSeaNet, an oil spill hazard assessment is made in the Portuguese continental coast, based on the cumulative analysis of drift model simulations from previously detected spills using metocean model data, for a period between 2011–2016. Although this EWS doesn’t replace on-demand operational oil spill forecasting systems, it supports maritime authorities with a fast first-guess forecast solution, allowing:Anticipation of tactical response (including visual inspection of the spill) and mitigation of the pollution episode;A more effective identification of the pollution source, and in case of suspected illegal spill, earlier actions towards effective prosecution of the polluter;In the other hand, the hazard assessment generated is a valuable instrument for the development of efficient planning and prevention strategies. The EWS can be connected to any satellite-based detection service (inside or outside Europe) as long as the detected oil slicks are automatically distributed in a structured and standardized data format similar to CleanSeaNet.

scholarly journals Oil Spill Monitoring of Shipborne Radar Image Features Using SVM and Local Adaptive Threshold

Algorithms ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 69 ◽  
Author(s):  
Jin Xu ◽  
Haixia Wang ◽  
Can Cui ◽  
Baigang Zhao ◽  
Bo Li
Keyword(s):  
Real Time ◽  
Oil Spill ◽  
Large Scale ◽  
Oil Spills ◽  
Adaptive Threshold ◽  
Image Features ◽  
Radar Image ◽  
Support Vector ◽  
Effective Wave ◽  
Local Adaptive Threshold

In the case of marine accidents, monitoring marine oil spills can provide an important basis for identifying liabilities and assessing the damage. Shipborne radar can ensure large-scale, real-time monitoring, in all weather, with high-resolution. It therefore has the potential for broad applications in oil spill monitoring. Considering the original gray-scale image from the shipborne radar acquired in the case of the Dalian 7.16 oil spill accident, a complete oil spill detection method is proposed. Firstly, the co-frequency interferences and speckles in the original image are eliminated by preprocessing. Secondly, the wave information is classified using a support vector machine (SVM), and the effective wave monitoring area is generated according to the gray distribution matrix. Finally, oil spills are detected by a local adaptive threshold and displayed on an electronic chart based on geographic information system (GIS). The results show that the SVM can extract the effective wave information from the original shipborne radar image, and the local adaptive threshold method has strong applicability for oil film segmentation. This method can provide a technical basis for real-time cleaning and liability determination in oil spill accidents.

Development of a New Spilled Oil Tracking Autonomous Buoy

2011 ◽  
Vol 45 (2) ◽  
pp. 43-51 ◽  
Author(s):  
Hidetaka Senga ◽  
Naomi Kato ◽  
Hiroyoshi Suzuki ◽  
Muneo Yoshie ◽  
Isamu Fujita ◽  
...  
Keyword(s):  
Real Time ◽  
Oil Spill ◽  
Oil Recovery ◽  
Wind Direction ◽  
Oil Spills ◽  
Wind Effect ◽  
Oceanographic Data ◽  
Simulation Results ◽  
Ocean Environment ◽  
Spilled Oil

AbstractOil spills cause tremendous damage to the ocean environment, which the unfettered drifting of spilled oil exacerbates. If the exact location of drifting oil could be identified in real time beginning when the oil spill first occured, then drifting oil could be recovered at sea before washing ashore. In addition, if meteorological and oceanographic data around the drifting oil could be obtained, the accuracy of an oil drifting simulation would be enhanced by data assimilation, and oil recovery machines could be adequately deployed along coasts where spilled oil washes ashore based on the simulation results. We developed a spilled oil tracking autonomous buoy I (SOTAB-I), which tracks spilled oil autonomously and transmits useful data in real time. Sea trials using the SOTAB-I showed that it has efficient tracking procedures. The trials also showed that the drift of spilled oil is strongly affected by wind.In order to take into account the wind effect, a new SOTAB, which has a sail with a changeable size and direction, was developed, and sea trials were carried out. The experimental results revealed that the drifting velocity of the SOTAB-II was 3.1%-3.8% of the wind velocity along the wind direction. When the sail was completely furled, the drifting direction of the new SOTAB-II was different from that of the imaginary drifting oil. However, the drifting direction was decreased when the sail was completely unfurled. These results show the efficiency of the sail attached to the SOTAB-II.

scholarly journals Exploring the capabilities of TM and AVIRIS sensor images for oil spill detection in marine and ocean waters

2018 ◽  
Vol 7 (2) ◽  
pp. 72-87
Author(s):  
Qadir Ashournejad ◽  
Saham Mirzaei ◽  
Seyyed Javad Hoseini
Keyword(s):  
Remote Sensing ◽  
Oil Spill ◽  
Oil Spills ◽  
Oil Pollution ◽  
Atmospheric Correction ◽  
Spectral Unmixing ◽  
Spectral Signature ◽  
Multispectral Data ◽  
Ocean Ecosystem ◽  
End Members

Oil spills are major water polluting sources. Due to its devastating effects on the sea and ocean ecosystem, detecting oil pollution in the shortest time and with the highest confidence level is necessary. Remote sensing being a suitable option, the capability of Landsat multispectral data and airborne hyper-spectral data from the AVIRIS sensor was investigated for study of the 2001 oil spill in the Gulf of Mexico. In this study, a part of the 2001 oil spill data was processed in terms of cloud spots,bad pixel and atmospheric correction. The pixel purity index was used to extract the end -members of water and oil spill and the linear spectral unmixing method was used for mapping of water from oil spills. The results show that the AVIRIS image is able to detect the type and thicknesses of oil spill, due to its ability to cover the diagnostic spectral signature of oil.Keywords: Monitoring, oil spill, remote sensing, Landsat, AVIRIS.

Optimized Airborne Oil Spill Remote Sensing: POSEIDON, the Quantitative Approach

2017 ◽  
Vol 2017 (1) ◽  
pp. 1594-1611
Author(s):  
Guilherme Pinho ◽  
Alessandro Vagata ◽  
Theo Hengstermann
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
Oil Spill ◽  
Oil Spills ◽  
Response Strategy ◽  
Geographical Information ◽  
Web Based ◽  
Incident Command ◽  
Automated Processing ◽  
The Right

ABSTRACT Aerial surveillance is becoming a foundation on the overall oil spill response strategy due to the ability to plan and tactically position response resources in the optimal areas of oil migration. It takes a complete multitasking approach to effectively respond to oil spills. While much of the regulatory focus to date has been on the resources on the sea - vessels, skimmers, dispersants - the reality is that they are only one of the components and not necessarily the most important in combating oil spills. It is imperative to determine the location of oil that is most recoverable, and give quantitative information - thickness, volume, area, classification - whether day or night. Having the right information at the right time optimizes dramatically the use of all the response resources. And assess the effectiveness of the response and make an accurate natural resources damage assessment is critical and requires as well quantitative and timely information. In the past the main effort has been directed towards developing airborne sensors with enhanced spill monitoring capability. Recently, more and more attention has been paid to the automated processing of oil spill data acquired by integrated airborne sensor platforms. Automated processing and real time relay of immediately usable information to the Incident Command Center is critical during all phases of response. This paper focuses on advanced data processing and presents ways of improving the usability of airborne multi-sensor oil spill monitoring systems. In this context, is given an overview of currently existing oil spill remote sensing technology like infrared/ultraviolet line scanners, microwave radiometers, laser fluorosensors and radar system. The paper presents POSEIDON, a system for network-based real-time data acquisition, analysis and fusion of multi-sensor data. Also, a method for the distribution of oil spill data and related data products using web-based geographical information systems is described; automated generation of thematic maps of the oil spill scene along with their real-time web-based distribution is becoming more important in marine incident management.

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