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            <resTitle>Global Fixed Offshore Infrastructure</resTitle>
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    <idPurp>SAR (Synthetic-aperture radar) offshore infrastructure data between 2017 to 3 months ago that were detected with satellite imagery and classified with deep learning.</idPurp><idAbs>&lt;p&gt;&lt;strong&gt;Overview&lt;/strong&gt;&lt;br /&gt;Offshore fixed infrastructure is a global dataset that uses AI and machine learning to detect and classify structures throughout the world’s oceans. Classification labels (oil, wind, and unknown) are provided, as well as confidence levels (high, medium, or low) reflecting our certainty in the assigned label. Detections can be filtered and colored on the map using both label and confidence level.&lt;br /&gt;The data is updated monthly, and new classified detections are added at the beginning of every month. Viewing change using the time is simple, and allows anyone to recognize the rapid industrialization of the world’s oceans. For example, you can easily observe the expansion of wind farms in the North and East China Seas, or changes in oil infrastructure in the Gulf of Mexico or Persian Gulf.&lt;br /&gt;By overlaying the existing map layers, you can explore how vessels interact with oil and wind structures, visualize the density of synthetic aperture radar (SAR) and Visible Infrared Imaging Radiometer Suite (VIIRS) vessel detections around infrastructure, or determine which marine protected areas (MPAs) contain wind, oil, or other infrastructure types. These are only examples of the types of questions we can now ask. Offshore fixed infrastructure is a first of its kind dataset that not only brings to light the extensive industrialization of our oceans but enables users across industries to use this information in research, monitoring and management.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Use cases&lt;/strong&gt;&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Maritime domain awareness&lt;ul&gt;&lt;li&gt;Infrastructure locations can support maritime domain awareness, and understanding of other activities occurring at sea.&lt;/li&gt;&lt;li&gt;Infrastructure data supports assessments of ocean industrialization, facilitating monitoring of areas experiencing build-up or new development&lt;/li&gt;&lt;/ul&gt;&lt;/li&gt;&lt;li&gt;Monitoring vessels&lt;ul&gt;&lt;li&gt;Infrastructure locations can be used to analyse the behaviour of vessels associated with infrastructure, including grouping vessels based on their interaction with oil and wind structures.&lt;/li&gt;&lt;li&gt;Interactions between vessels and infrastructure can help quantify the resources required to support offshore industrial activity&lt;/li&gt;&lt;li&gt;The impacts of infrastructure on fishing, including attracting or deterring fishing, can be analysed.&lt;/li&gt;&lt;/ul&gt;&lt;/li&gt;&lt;li&gt;Marine protected areas (MPAs) and marine spatial planning&lt;ul&gt;&lt;li&gt;During the planning stage in the designation of new protected areas, knowing the location of existing infrastructure will be vital to understand which stakeholders shall be included in the consultation process, to understand potential conflicts, and identify easy wins.&lt;/li&gt;&lt;/ul&gt;&lt;/li&gt;&lt;li&gt;Environmental impacts&lt;ul&gt;&lt;li&gt;Infrastructure locations can be used to help detect marine pollution events, and to differentiate between types of pollution events (e.g. pollution from vessels versus pollution from platforms)&lt;/li&gt;&lt;/ul&gt;&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&lt;strong&gt;Caveats&lt;/strong&gt;&lt;br /&gt;&amp;nbsp;&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Sentinel-1 and Sentinel-2 satellites do not sample most of the open ocean.&lt;ul&gt;&lt;li&gt;Most industrial activity happens relatively close to shore.&lt;/li&gt;&lt;li&gt;The extent and frequency of SAR acquisitions is determined by the mission priorities.&lt;/li&gt;&lt;li&gt;For more info see: &lt;a target='_blank' href='https://www.nature.com/articles/s41586-023-06825-8/figures/5' rel='nofollow ugc noopener noreferrer'&gt;https://www.nature.com/articles/s41586-023-06825-8/figures/5&lt;/a&gt;&lt;/li&gt;&lt;/ul&gt;&lt;/li&gt;&lt;li&gt;We do not provide detections of infrastructure within 1 km of shore&lt;ul&gt;&lt;li&gt;We do not classify objects within 1 km of shore because it is difficult to map where the shoreline begins, and ambiguous coastlines and rocks cause false positives.&lt;/li&gt;&lt;li&gt;The bulk of industrial activities, including offshore development with medium-to-large oil rigs and wind farms, occur several kilometers from shore.&lt;/li&gt;&lt;/ul&gt;&lt;/li&gt;&lt;li&gt;False positives can be produced from noise artifacts.&lt;ul&gt;&lt;li&gt;Rocks, small islands, sea ice, radar ambiguities (radar echoes), and image artifacts can cause false positives&lt;/li&gt;&lt;li&gt;Detections in some areas including Southern Chile, the Arctic, and the Norwegian Sea have been filtered to remove noise.&lt;/li&gt;&lt;/ul&gt;&lt;/li&gt;&lt;li&gt;Spatial coverage varies over time, which can produce different detections results year on year - &lt;a target='_blank' href='https://share.cleanshot.com/yG0qfF' rel='nofollow ugc noopener noreferrer'&gt;Example&lt;/a&gt;&lt;ul&gt;&lt;li&gt;Infrastructure detentions from 2017-01-01 to near real time are available, and updated on a monthly basis.&lt;/li&gt;&lt;/ul&gt;&lt;/li&gt;&lt;li&gt;Labels can change over time&lt;ul&gt;&lt;li&gt;The label assigned to a structure is the greatest predicted label averaged across time. As we get more data, the label may change, and more accurately predict the true infrastructure type.&lt;/li&gt;&lt;/ul&gt;&lt;/li&gt;&lt;li&gt;Global datasets aren’t perfect&lt;ul&gt;&lt;li&gt;We’ve done our best to create the most accurate product possible, but there will be infrastructure that isn’t detected, or has been classified incorrectly. This will be most evident when working at the project level.&lt;/li&gt;&lt;li&gt;We strongly encourage users to provide feedback to the research team so that we may improve future versions of the model. All feedback is greatly appreciated.&lt;/li&gt;&lt;/ul&gt;&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&lt;strong&gt;More information&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;All code developed for the paper, including SAR detection, deep learning models, and analyses is open source and freely available at &lt;a target='_blank' href='https://github.com/GlobalFishingWatch/paper-industrial-activity' rel='nofollow ugc noopener noreferrer'&gt;https://github.com/GlobalFishingWatch/paper-industrial-activity&lt;/a&gt;. All the data generated and used by these scripts can reference the following data repos:&lt;br /&gt;Analysis and Figures: &lt;a target='_blank' href='https://doi.org/10.6084/m9.figshare.24309475' rel='nofollow ugc noopener noreferrer'&gt;https://doi.org/10.6084/m9.figshare.24309475&lt;/a&gt;&lt;br /&gt;Training and Evaluation: &lt;a target='_blank' href='https://doi.org/10.6084/m9.figshare.24309469' rel='nofollow ugc noopener noreferrer'&gt;https://doi.org/10.6084/m9.figshare.24309469&lt;/a&gt;&lt;br /&gt;&amp;nbsp;&lt;/p&gt;</idAbs><resConst><Consts><useLimit>&lt;p&gt;&lt;img src='https://licensebuttons.net/l/by/3.0/88x31.png' /&gt;&amp;nbsp;&lt;/p&gt;&lt;p&gt;This work is licensed under a Creative Commons by Attribution 4.0 International (CC BY 4.0) license. See Credits and Map for Attribution.&lt;br /&gt;&amp;nbsp;&lt;a target='_blank' href='https://creativecommons.org/licenses/by/4.0/legalcode' rel='nofollow ugc noopener noreferrer'&gt;&lt;strong&gt;View License Deed&lt;/strong&gt;&lt;/a&gt; | &lt;a target='_blank' href='https://creativecommons.org/licenses/by/4.0/legalcode' rel='nofollow ugc noopener noreferrer'&gt;&lt;strong&gt;View Legal Code&lt;/strong&gt;&lt;/a&gt;&lt;/p&gt;</useLimit></Consts></resConst></dataIdInfo>
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