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.

scholarly journals Optimization on Emergency Materials Dispatching Considering the Characteristics of Integrated Emergency Response for Large-Scale Marine Oil Spills

2019 ◽  
Vol 7 (7) ◽  
pp. 214 ◽  
Author(s):  
Song Li ◽  
Manel Grifoll ◽  
Miquel Estrada ◽  
Pengjun Zheng ◽  
Hongxiang Feng
Keyword(s):  
Emergency Response ◽  
Oil Spill ◽  
Large Scale ◽  
Oil Spills ◽  
Marine Oil ◽  
Emergency Managers ◽  
Distribution Point ◽  
Dispatching Algorithm ◽  
Marine Oil Spills ◽  
The Difference

Many governments have been strengthening the construction of hardware facilities and equipment to prevent and control marine oil spills. However, in order to deal with large-scale marine oil spills more efficiently, emergency materials dispatching algorithm still needs further optimization. The present study presents a methodology for emergency materials dispatching optimization based on four steps, combined with the construction of Chinese oil spill response capacity. First, the present emergency response procedure for large-scale marine oil spills should be analyzed. Second, in accordance with different grade accidents, the demands of all kinds of emergency materials are replaced by an equivalent volume that can unify the units. Third, constraint conditions of the emergency materials dispatching optimization model should be presented, and the objective function of the model should be postulated with the purpose of minimizing the largest sailing time of all oil spill emergency disposal vessels, and the difference in sailing time among vessels that belong to the same emergency materials collection and distribution point. Finally, the present study applies a toolbox and optimization solver to optimize the emergency materials dispatching problem. A calculation example is presented, highlighting the sensibility of the results at different grades of oil spills. The present research would be helpful for emergency managers in tackling an efficient materials dispatching scheme, while considering the integrated emergency response procedure.

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.

A Model Based Approach to Radar Oil Spill Detection

2014 ◽  
Vol 2014 (1) ◽  
pp. 2228-2241
Author(s):  
Torstein Pedersen ◽  
Javier Perez ◽  
Jos Van Heseen
Keyword(s):  
Oil Spill ◽  
Oil Spills ◽  
Radar Image ◽  
Monitoring Systems ◽  
Multiple Sources ◽  
Threshold Detector ◽  
Ir Camera ◽  
Oil Spill Detection ◽  
Model Based ◽  
Primary Driver

ABSTRACT A typical oil spill recovery vessel has been historically outfitted with an oil spill detection (OSD) radar. During an oil spill recovery operation, there is a dedicated operator who is responsible for interpreting information from the radar image. Industry developments over the last several years now require that an OSD radar automatically detect and track an oil spill. There are two primary needs driving this development. The first is that OSD systems and operations are becoming more sophisticated; automatic OSD aids for a more efficient oil spill operation where an operator's attention may be directed to a potential spill. The automatic OSD also aids a multi-sensor system; one such example is where an OSD radar is used to steer an IR camera to a candidate spill for more detailed evaluation or validation. The other primary driver for automatic OSD is for monitoring systems, which serve for early warning. Monitoring systems may be found along coastal installations or oil platforms. The automatic spill detection functionality of an OSD system may be implemented in different levels of sophistication. Perhaps the simplest configuration is one that uses fixed thresholds relative to the image for alarming whether a region in a radar image is a spill or not. The benefit of simple threshold detector is that it is easy to implement in software. The weakness is that it is prone to both lower overall detection rate and high false alarm rate. A more robust automatic spill detection method is one that treats it as an image-processing problem. The paper here presents a model based OSD. Generation of confidence maps is central to the method and provides an indication of the likelihood of oil. Inputs to the confidence maps come from multiple sources, several of which are based on uniquely constructed models. Among these is a histogram comparator, which scans a radar image and compares the data to reference models from real oil spills. A discussion of the methods used focuses on (a) the necessary steps prior to the confidence map construction, (b) how the confidence maps are layered with inputs, (c) how the information in the confidence maps is transitioned into the detection of oil, (d) and finally alarming.

Snow Detection using In-Vehicle Video Camera with Texture-Based Image Features Utilizing K-Nearest Neighbor, Support Vector Machine, and Random Forest

2019 ◽  
Vol 2673 (8) ◽  
pp. 221-232 ◽  
Author(s):  
Md Nasim Khan ◽  
Mohamed M. Ahmed
Keyword(s):  
Real Time ◽  
Prediction Accuracy ◽  
Nearest Neighbor ◽  
Detection System ◽  
Weather Conditions ◽  
Video Camera ◽  
Image Features ◽  
Support Vector ◽  
K Nearest Neighbor ◽  
Weather Information

Snowfall negatively affects pavement and visibility conditions, making it one of the major causes of motor vehicle crashes in winter weather. Therefore, providing drivers with real-time roadway weather information during adverse weather is crucial for safe driving. Although road weather stations can provide weather information, these stations are expensive and often do not represent real-time trajectory-level weather information. The main motivation of this study was to develop an affordable in-vehicle snow detection system which can provide trajectory-level weather information in real time. The system utilized SHRP2 Naturalistic Driving Study video data and was based on machine learning techniques. To train the snow detection models, two texture-based image features including gray level co-occurrence matrix (GLCM) and local binary pattern (LBP), and three classification algorithms: support vector machine (SVM), k-nearest neighbor (K-NN), and random forest (RF) were used. The analysis was done on an image dataset consisting of three weather conditions: clear, light snow, and heavy snow. While the highest overall prediction accuracy of the models based on the GLCM features was found to be around 86%, the models considering the LBP based features provided a much higher prediction accuracy of 96%. The snow detection system proposed in this study is cost effective, does not require a lot of technical support, and only needs a single video camera. With the advances in smartphone cameras, simple mobile apps with proper data connectivity can effectively be used to detect roadway weather conditions in real time with reasonable accuracy.

Large-scale oil spills and flag-use within the global tanker fleet

2014 ◽  
Vol 42 (2) ◽  
pp. 119-126 ◽  
Author(s):  
DANA D. MILLER ◽  
KATHRYN TOOLEY ◽  
U. RASHID SUMAILA
Keyword(s):  
Oil Spill ◽  
Large Scale ◽  
Oil Spills ◽  
Patterns Of Failure ◽  
Time Period ◽  
Potential Association ◽  
International Obligations ◽  
Oil Tanker

SUMMARYWithin the global oil shipping sector, flag states that inadequately fulfil obligations to effectively exert jurisdiction over vessels flying their flags have been criticized for facilitating the existence of substandard ships. This paper examines the topic of flag-use and its potential association with oil spill risk. Flags most associated with accidental oil spills were identified through comparing the flag composition of the global oil tanker fleet with that of vessels that have been involved in the 100 largest tanker spills on record. Vessels flying flags of states that have exhibited consistent patterns of failure in compliance with international obligations, defined here as ‘flags of non-compliance’ (FoNCs), were found to be significantly more common amongst the vessels that have been involved in spill incidents. However, this was dependent on how the Liberian flag was qualified throughout the time period considered. If measures are being sought to reduce the risk of tanker involvement in large-scale oil spills further, vessel owners should be deterred from registering with FoNCs that are highly accessible to foreign owners, and political measures should be taken to put pressure on flag states that operate all other FoNCs to improve effective jurisdiction over ships flying these flags.

OIL SPILL RESPONSES - THE POLITICAL DIMENSION

2008 ◽  
Vol 2008 (1) ◽  
pp. 587-590 ◽  
Author(s):  
Ho Yew Weng
Keyword(s):  
National Security ◽  
Oil Spill ◽  
Large Scale ◽  
Oil Spills ◽  
Recipient Country ◽  
Asia Pacific ◽  
Efficient Manner ◽  
Political Dimension ◽  
Red Tape ◽  
Oil Spill Response

ABSTRACT There are always lessons to be learnt from every oil spill response. Similarly, critics are always quick to point out how a response was too slow, the inadequacy of equipment / manpower resources and, inevitably, how the response lacks proper coordination. Yet many of these common criticisms can be resolved if artificial ‘roadblocks and red tape’ are removed so that Responders can go about doing their jobs, providing prompt responses in mitigating damages caused by oil spills. This paper will discuss the challenges of mounting an international oil spill response in the Asia Pacific with specific references to political roadblocks and red tape put up by ‘recipient’ countries. Tier 3 Oil Spill Response organizations, namely Oil Spill Response and East Asia Response Limited (OSRL/EARL), regularly practices activations and resource deployments through exercises with different scenarios. These exercises can take the form of tabletop exercises or full scale deployment of equipment, recall of Members’ regional and worldwide teams. The larger scale exercises involve trans-boundary movement of people and equipment, including boats and aircrafts. OSRL/EARL has conducted large scale exercises successfully. Unfortunately, there are also times when red tape prevented the company from responding in the swift and efficient manner that it endeavors. Various reasons given are ‘national security’ and the need for very ‘high level approvals’ as the recipient country will be deemed to be calling outside assistance for a national incident. The paper will discuss some of OSRL/EARL'S experiences like:Response organizations refusing to participate in exercises due to ‘national security’ reasonsNational agencies refusing import of equipment due to taxation lawsProtracted approval processes, and sometimes outright refusal, for materials like dispersantRefusing entry of international aircraftsClearance and complicated permit requirements for Responders entering a country to assist in the response The challenge to remove these road blocks is an uphill task. OSRL/EARL has an on-going Advocacy program to engage and cooperate on these issues with Government Agencies and relevant bodies. The Author believes that the removal of ‘road blocks’ will expedite responses to oil spills.

scholarly journals Large-Scale Detection and Categorization of Oil Spills from SAR Images with Deep Learning

2020 ◽  
Vol 12 (14) ◽  
pp. 2260 ◽  
Author(s):  
Filippo Maria Bianchi ◽  
Martine M. Espeseth ◽  
Njål Borch
Keyword(s):  
Deep Learning ◽  
Oil Spill ◽  
Large Scale ◽  
Oil Spills ◽  
Sar Images ◽  
Oil Spill Detection ◽  
Learning Framework ◽  
Large Scale Data ◽  
Human Operators ◽  
Scale Detection

We propose a deep-learning framework to detect and categorize oil spills in synthetic aperture radar (SAR) images at a large scale. Through a carefully designed neural network model for image segmentation trained on an extensive dataset, we obtain state-of-the-art performance in oil spill detection, achieving results that are comparable to results produced by human operators. We also introduce a classification task, which is novel in the context of oil spill detection in SAR. Specifically, after being detected, each oil spill is also classified according to different categories of its shape and texture characteristics. The classification results provide valuable insights for improving the design of services for oil spill monitoring by world-leading providers. Finally, we present our operational pipeline and a visualization tool for large-scale data, which allows detection and analysis of the historical occurrence of oil spills worldwide.

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.

Industry and Government Roles in Addressing Historic Properties in Oil Spill Response: Lessons Learned From A Recent Exercise and Incidents

2001 ◽  
Vol 2001 (1) ◽  
pp. 693-697
Author(s):  
Tina M. Toriello ◽  
Jan Thorman ◽  
Pamela Bergmann ◽  
Richard Waldbauer
Keyword(s):  
Emergency Response ◽  
Oil Spill ◽  
Large Scale ◽  
Oil Spills ◽  
Lessons Learned ◽  
Hazardous Substances ◽  
Hazardous Substance ◽  
National Response ◽  
Response Team ◽  
Oil Spill Response

ABSTRACT This paper focuses on industry and government roles for addressing historic properties during oil spill response. In 1997, the National Response Team (NRT) developed a Programmatic Agreement on Protection of Historic Properties during Emergency Response under the National Oil and Hazardous Substances Pollution Contingency Plan (PA) (National Response Team, 1997). At the 1999 International Oil Spill Conference (IOSC), U.S. Department of the Interior (DOI) representatives discussed the development and implementation of the PA, which is intended to ensure that historic properties are appropriately taken into account during the planning for and conducting of emergency response to oil spills and hazardous substance releases. Following the 1999 IOSC, DOI and Chevron representatives began a dialog regarding industry and government roles under the PA. Chevron invited the DOI representatives to participate in an October 1999 large-scale, industry-led spill exercise; a precedent-setting drill that included historic properties protection as a key objective. This 2001 paper focuses on how industry and government have worked together to protect historic properties, government roles in PA implementation, and lessons learned. As an example of what industry can do to support the protection of historic properties during planning and response activities, this paper describes Chevron's Historic Properties Program, a program managed under its emergency spill response environmental functional team (EFT). A discussion of lessons learned focuses on the need for clear definition of industry and government roles, and the benefits of building a foundation of cooperation between industry and government to protect historic properties. Of particular importance is the inclusion of historic properties in all aspects of oil spill preparedness and response, including planning, drills, training, and response organization structure and staffing. Experience from incident response in Alaska has shown that the PA assists Federal On-Scene Coordinators (FOSCs) and responsible parties, while also protecting historic properties, when the FOSC is prepared to implement the PA promptly and effectively.

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