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Abstract Drifting icebergs can threaten navigation and marine operations and are prevalent in a number of regions that have active oil and gas exploration and development. Satellite synthetic aperture radar (SAR) is naturally applicable to map and monitor icebergs and sea ice due its ability to capture images day or night, as well as through cloud, fog and various wind conditions. There are several notable examples of its use to support operations, including Grand Banks, Barents Sea, offshore Greenland and Kara Sea. New constellations of satellites and the increasing volume of satellite data becoming available present a new paradigm for ice surveillance, in terms of persistence, reliability and cost. To fully extract the value of the data from these constellations, automation and cloud-based processing must be implemented. This will allow more timely and efficient processing, lowering monitoring costs by at least an order of magnitude. The increase in data persistence and processing capability allows large regions to be monitored daily for ice incursions, thus increasing safety and efficiency during offshore operations in those regions. The process of automating SAR-based iceberg surveillance involves creating a process flow that is robust and requires limited human intervention. The process flow involves land-masking, target detection, target discrimination and product dissemination. Land masking involves the removal of high-clutter land from the imagery to eliminate false detection from these locations. Target detection usually involves an adaptive threshold to separate true targets from the background ocean clutter. A constant false alarm rate (CFAR) is a standard technique used in radar image processing for this purpose. Target discrimination involves an examination of the distinct features of a target to determine if they match the features of icebergs, vessels or other ‘false alarms’ (e.g., marine wildlife, clutter). The final stage is the production of an output surveillance product, which can be a standard iceberg chart (e.g., MANICE) or something that can be ingested into a GIS system (e.g., ESRI shapefile, Google KML). The target discrimination phase is one of the most important phases because it provides feedback to operations about the presence of targets of interest (icebergs and vessels). The authors have used computer vision techniques successfully to train target classifiers. Standard techniques usually result in classifier accuracies of between 85%-95%, depending on the resolution of the SAR (higher resolutions produce more accurate results) and the availability of multiple polarizations. To see if new machine learning techniques could be applied to increase classifier accuracy, a dataset of 5000 ship and iceberg targets were extracted from Sentinel-1 multi-channel data (HH,HV). The images were collected in several regions (Greenland, Grand Banks, and Strait of Gibraltar). Validation either came by way of supporting information from the offshore operations, or was inferred by location. An online machine learning competition was hosted by Kaggle, a company that conducts online competitions on behalf of their clients. The detection data were made available by Kaggle to the broad internet community. Kaggle has a loyal following of data scientists who regularly participate in Kaggle competitions. The competition was hosted over a three-month period; over 3300 teams participated in the competition. The competition produced an improved classifier over standard computer vision techniques; the top three competitors had 4-5 stage classifiers that increased classification accuracy by approximately 5%.
- North America > Canada (0.46)
- North America > Greenland (0.45)
- North America > United States > Texas (0.28)
- (2 more...)
The Identification of Extreme Ice Features in Satellite Imagery
Zakharov, Igor (C-CORE) | Power, Desmond (C-CORE) | Bobby, Pradeep (C-CORE) | Randell, Charles (C-CORE)
Abstract P>Sea ice monitoring is an important field of scientific research and relevant to operational applications. One of the major engineering challenges in undertaking production developments in Arctic offshore regions is the frequent presence of extreme ice features that pose a hazard to facilities and surrounding subsea infrastructure. The information on extreme ice features (i.e., ridges, icebergs etc.) is important from the standpoint of potential ice load levels on fixed structures and ice scouring of seafloor facilities. Satellite observation has been shown to be useful for extracting and characterizing ice regimes. Sea ice can be monitored using satellite imagery acquired by different types of sensors: microwave radiometer, optical instrument and synthetic aperture radar (SAR). The outputs of sea ice monitoring may include various ice parameters such as edge, thickness, concentration, classification, iceberg detection, and ice statistics. This paper describes application of high and low resolution SAR imagery for sea ice monitoring and to resolve local features and extend the statistical baseline to larger regions because extreme ice features may be invisible or ambiguous with other ice features in these data. The use of higher resolution imagery allows for easier detection of ice features and provides sufficient spatial detail necessary for detecting ice features from sea ice, identification and estimation of size and geometry of ice floes and icebergs. It was demonstrated that SAR sensors with multiple resolution lead to a better understanding of ice conditions including ice edge, concentration, floe statistics, and other ice features such as icebergs. A technique based on SAR interferometry was used for identification of iceberg in sea ice as well as for extracting iceberg topography.
- North America > Canada (0.47)
- North America > United States > Texas (0.30)
- Government > Space Agency (0.73)
- Information Technology (0.63)
Abstract The oil and gas industry is increasingly focusing its interests andactivities on areas that are prone to ice cover, in the form of sea ice andicebergs. The authors have noticed two significant trends with respect to theice charting to support operations in oil and gas operations:At present, companies who require ice information are developing their owninternal practices based on different experiences. No industry-wide standards exist for ice charting in this sector. As a consequence, the authors have embarked on a project to address thisdeficiency by identifying minimum standards and best practices for theprovision of ice information derived from satellites for companies operating inthe polar and sub-polar regions. The development of a guideline governing icecharts is the primary focus of this project. The project has identifiedrequirements through the oil and gas project lifecycle, has matched these todifferent regions and has categorised satellite-derived ice information byservices and products. The project has reviewed current practices and willestablish a guideline with input and validation from the industry, taking intoaccount current constraints and future opportunities. Ice charting guidelineswill provide clear options to industry. Companies will be able to buildprocesses and systems around guidelines and can be assured that compliantservice providers will be compatible with their systems. Guidelines will alsoincrease access of the market to service providers, leading to increasedcompetition and lower costs. Ultimately, the knowledge of ice chartingcapabilities will be well documented so that they are not lost with staffattrition. This paper presents an overview of the ice charting guidelinesproject and its objectives, schedule, status and deliverables. This project isbeing coordinated through the Oil and Gas Earth Observation Group (OGEO) of theInternational Association of Oil and Gas producers (OGP) with initial seedfunding from the European Space Agency and Shell E&P International. Index Terms—ice charting, ice information, sea ice, icebergs, guideline Introduction The oil and gas industry are increasingly focusing their interests andactivities on areas that are prone to ice cover, in the form of sea ice andicebergs. At present, the approach being taken by companies who require iceinformation is to develop their own internal practices based on differentexperiences. No industry-wide standards exist. In this project, we aim toaddress this deficiency, by identifing minimum standards and best practices forthe provision of ice information derived from satellites for companiesoperating in the polar and sub-polar regions
- Geophysics > Seismic Surveying (0.47)
- Geophysics > Electromagnetic Surveying (0.47)
- Information Technology > Information Management (0.48)
- Information Technology > Communications > Networks (0.41)
Abstract The analysis of historical satellite data, both radar and optical, areuseful for understanding the nature of ice conditions in Arctic regions andunderstanding the risk they pose for exploration and development. Archivesatellite data are available at no cost and can be analyzed to assess theseverity and variability of iceberg concentrations and their behavior. National ice centres have been providing charts of sea ice conditions, whichcan be analyzed to understand probabilities of encountering ice of variousconcentrations and the lengths of the open water season. The outputs ofthese analyses are useful for understanding the risk of operating in Arcticregions and for developing an ice management plan. Introduction Satellite radar and optical imagery are essential tools for understandingsea ice and iceberg conditions in frontier Arctic and sub-Arctic regions. Satellite synthetic aperture radar (SAR) imagery can be collected day or night, are relatively independent of environmental conditions, can be collectedthrough fog and cloud cover and provide information over remote areas at noadditional cost. There is a substantial archive of low resolution imageryavailable and there is a growing number of sensors available for newacquisitions. Optical imagery, when available, are excellent forproviding detailed information on ice features such as sea ice ridges andiceberg sizes. Low resolution optical data are collected continuously, medium resolution data is available close to shore and high resolution imagescan be acquired from a large number of sensors. Historic satellite data are used to develop an understanding of the severityand variability of ice conditions in an area. This information serves asan input for the design of structures and selection of vessels that can beutilized in an area as well for development of an ice management plan anddefining the operational window. New image acquisitions are an important part of the detection component ofan operational ice management plan. Surveillance in certain marginal icezones, such as the Grand Banks, do not rely on satellite imagery since they areclose to shore and reconnaissance can be carried out almost exclusively usingplatform radar and vessel and aerial surveillance. However, the costs ofthis approach grow in remote areas and satellite SAR data have been used inaddition to platform radar to support operations in new Arctic explorationregions.
A Constellation Of Satellites For Enhanced Mapping Of Sea Ice
Davidson, Malcolm (European Space Agency) | Walker, Nick (European Space Agency) | Williams, Chris (eOsphere) | Power, Desmond (C-CORE) | Ramsay, Bruce (Consultant) | Partington, Kim (Polar Imaging Limited) | Barber, David (University of Manitoba) | Arkett, Matt (Canadian Ice Service) | De Abreu, Roger (Canada Centre for Remote Sensing)
Abstract In conducting safe and cost effective operations in ice prone waters, icemanagement and risk mitigation practices are integral to operations. A criticalelement in ice management is the mapping and characterisation of sea ice. Satellite synthetic aperture radar (SAR) is a standard tool used by icecharting agencies to map the extent of sea ice. Wide-swath SAR has become thepreferred sensor of choice for ice mapping and the collection of data regardingice parameters. SAR provides a high degree of information content on basic iceparameters such as concentration, type and topography. SAR can be used tocharacterise different sea ice types, such as multi-year versus first year ice, and the use of multiple SAR frequencies (L, C and X-Band) can reduceinterpretation ambiguities during the melt season. The advent ofmulti-frequency and polarization SAR systems, acting as a constellation, isseen as an important next step in the evolution of sea ice monitoring. Theevaluation of a SAR ice constellation is an interesting challenge since aquantitative evaluation is necessary. As a consequence, a sea ice backscattertool has been developed that provides a figure of merit estimation of iceclassification from a constellation scenario. The authors have used its sea-icebackscatter tool to simulate various ice constellation scenarios. Thesescenarios will be presented in the context of their utility and versatility inoil and gas operations. The implementation of a SAR ice constellation providesthe opportunity to significantly expand the ice information extractioncapabilities, over and above that of these systems acting alone. In the contextof its use within Arctic resource development, SAR constellations offerenhanced ice charting to the oil and gas industry. Index Terms—Sentinel-1, SAR, sea-ice, backscatter, constellations Introduction In conducting safe and cost effective operations in ice prone waters, icemanagement and risk mitigation practices are integral to operations. A criticalelement in ice management is the mapping and characterisation of sea ice. Satellite synthetic aperture radar (SAR) is a standard tool used by icecharting agencies to map the extent of sea ice. Wide-swath SAR has become thepreferred sensor of choice for ice mapping and the collection of data regardingice parameters. SAR provides day-night, all-weather capability and relativelyhigh resolution. Additionally, SAR can provide a high degree of informationcontent on basic ice parameters such as concentration, type and topography.