Baseline of Next-Generation Arctic Marine Shipping Assessments - Oldest Continuous Pan-Arctic Satellite Automatic Identification System (AIS) Data Record of Maritime Ship Traffic, 2009-2016

The Arctic is prominent in the history of the International Maritime Organization (IMO), following the RMS Titanic disaster in 1912 and soon signing in London of the Convention for the Safety of Life at Sea in 1914. Eighty years later, the IMO initiated a process to manage shipping in ice-covered oc...

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Main Authors: Berkman, Paul Arthur, Fiske, Greg, Lorenzini, Dino
Format: Dataset
Language:English
Published: NSF Arctic Data Center 2020
Subjects:
Online Access:https://dx.doi.org/10.18739/a2bv79w4v
https://arcticdata.io/catalog/view/doi:10.18739/A2BV79W4V
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spelling ftdatacite:10.18739/a2bv79w4v 2023-05-15T14:30:16+02:00 Baseline of Next-Generation Arctic Marine Shipping Assessments - Oldest Continuous Pan-Arctic Satellite Automatic Identification System (AIS) Data Record of Maritime Ship Traffic, 2009-2016 Berkman, Paul Arthur Fiske, Greg Lorenzini, Dino 2020 text/xml https://dx.doi.org/10.18739/a2bv79w4v https://arcticdata.io/catalog/view/doi:10.18739/A2BV79W4V en eng NSF Arctic Data Center AMSA AIS record Arctic ship traffic dataset Dataset 2020 ftdatacite https://doi.org/10.18739/a2bv79w4v 2021-11-05T12:55:41Z The Arctic is prominent in the history of the International Maritime Organization (IMO), following the RMS Titanic disaster in 1912 and soon signing in London of the Convention for the Safety of Life at Sea in 1914. Eighty years later, the IMO initiated a process to manage shipping in ice-covered oceans. In concert with the IMO Guidelines for Ships Operating in Arctic Ice-Covered Waters in 2002 and their 2004 release of the Arctic 2004 Arctic Climate Impact Assessment, the Arctic Council initiated the Arctic Marine Shipping Assessment (AMSA), which issued its final report in 2009. The goal of this chapter is to build on AMSA as a case study of informed decisionmaking through the steps of questions to generate data, which are then integrated into evidence to reveal options (without advocacy), informing decisions by relevant institutions to address a ‘continuum of urgencies’ that involve shipping in the new Arctic Ocean with its transformed sea-ice cap, assessing whether shipping is increasing as sea ice is decreasing (‘ship-ice hypothesis’). Primary sources of data for AMSA involved ship tracking from ground-station Automatic Identification System (AIS), shore-based radar systems and details of fishing vessels as well as other smaller ships provided by the Arctic nations. However, Arctic ship traffic fundamentally changed the year of the AMSA report, when satellite AIS records began providing continuous, synoptic, pan-Arctic coverage of individual ships with data pulsed over seconds to minutes. This chapter reveals the oldest and longest continuous satellite AIS record (from 1 September 2009 through 31 December 2016), applying the ‘spacetime cube’ (which also was unavailable during AMSA) with more than 120,000,000 satellite AIS messages from SpaceQuest Ltd. to begin addressing synoptic questions with any level of granularity from points to regions to pan-Arctic over time. Future questions can be considered to assess ship attributes (including vessel flag state, size and type) in view of biophysical and socio-economic variables, recognizing that shipping and sea ice are recognized as primary drivers of change in the Arctic Ocean. Contributions to these assessments come from all areas of science (inclusively defined as the study of change), across the natural and social sciences with Indigenous knowledge in an holistic (international, interdisciplinary and inclusive) manner to achieve Arctic sustainability across generations. As a practical outcome in a user-defined manner, this chapter reveals characteristics of next-generation Arctic marine shipping assessments, revealing patterns and trends that can be applied to informed decisionmaking about the governance mechanisms and built infrastructure as well as operations for multilateral stability and sustainable development in the new Arctic Ocean. Dataset Arctic Climate Impact Assessment Arctic Council Arctic Arctic Ocean Ice cap Sea ice ice covered waters DataCite Metadata Store (German National Library of Science and Technology) Arctic Arctic Ocean
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic AMSA
AIS record
Arctic ship traffic
spellingShingle AMSA
AIS record
Arctic ship traffic
Berkman, Paul Arthur
Fiske, Greg
Lorenzini, Dino
Baseline of Next-Generation Arctic Marine Shipping Assessments - Oldest Continuous Pan-Arctic Satellite Automatic Identification System (AIS) Data Record of Maritime Ship Traffic, 2009-2016
topic_facet AMSA
AIS record
Arctic ship traffic
description The Arctic is prominent in the history of the International Maritime Organization (IMO), following the RMS Titanic disaster in 1912 and soon signing in London of the Convention for the Safety of Life at Sea in 1914. Eighty years later, the IMO initiated a process to manage shipping in ice-covered oceans. In concert with the IMO Guidelines for Ships Operating in Arctic Ice-Covered Waters in 2002 and their 2004 release of the Arctic 2004 Arctic Climate Impact Assessment, the Arctic Council initiated the Arctic Marine Shipping Assessment (AMSA), which issued its final report in 2009. The goal of this chapter is to build on AMSA as a case study of informed decisionmaking through the steps of questions to generate data, which are then integrated into evidence to reveal options (without advocacy), informing decisions by relevant institutions to address a ‘continuum of urgencies’ that involve shipping in the new Arctic Ocean with its transformed sea-ice cap, assessing whether shipping is increasing as sea ice is decreasing (‘ship-ice hypothesis’). Primary sources of data for AMSA involved ship tracking from ground-station Automatic Identification System (AIS), shore-based radar systems and details of fishing vessels as well as other smaller ships provided by the Arctic nations. However, Arctic ship traffic fundamentally changed the year of the AMSA report, when satellite AIS records began providing continuous, synoptic, pan-Arctic coverage of individual ships with data pulsed over seconds to minutes. This chapter reveals the oldest and longest continuous satellite AIS record (from 1 September 2009 through 31 December 2016), applying the ‘spacetime cube’ (which also was unavailable during AMSA) with more than 120,000,000 satellite AIS messages from SpaceQuest Ltd. to begin addressing synoptic questions with any level of granularity from points to regions to pan-Arctic over time. Future questions can be considered to assess ship attributes (including vessel flag state, size and type) in view of biophysical and socio-economic variables, recognizing that shipping and sea ice are recognized as primary drivers of change in the Arctic Ocean. Contributions to these assessments come from all areas of science (inclusively defined as the study of change), across the natural and social sciences with Indigenous knowledge in an holistic (international, interdisciplinary and inclusive) manner to achieve Arctic sustainability across generations. As a practical outcome in a user-defined manner, this chapter reveals characteristics of next-generation Arctic marine shipping assessments, revealing patterns and trends that can be applied to informed decisionmaking about the governance mechanisms and built infrastructure as well as operations for multilateral stability and sustainable development in the new Arctic Ocean.
format Dataset
author Berkman, Paul Arthur
Fiske, Greg
Lorenzini, Dino
author_facet Berkman, Paul Arthur
Fiske, Greg
Lorenzini, Dino
author_sort Berkman, Paul Arthur
title Baseline of Next-Generation Arctic Marine Shipping Assessments - Oldest Continuous Pan-Arctic Satellite Automatic Identification System (AIS) Data Record of Maritime Ship Traffic, 2009-2016
title_short Baseline of Next-Generation Arctic Marine Shipping Assessments - Oldest Continuous Pan-Arctic Satellite Automatic Identification System (AIS) Data Record of Maritime Ship Traffic, 2009-2016
title_full Baseline of Next-Generation Arctic Marine Shipping Assessments - Oldest Continuous Pan-Arctic Satellite Automatic Identification System (AIS) Data Record of Maritime Ship Traffic, 2009-2016
title_fullStr Baseline of Next-Generation Arctic Marine Shipping Assessments - Oldest Continuous Pan-Arctic Satellite Automatic Identification System (AIS) Data Record of Maritime Ship Traffic, 2009-2016
title_full_unstemmed Baseline of Next-Generation Arctic Marine Shipping Assessments - Oldest Continuous Pan-Arctic Satellite Automatic Identification System (AIS) Data Record of Maritime Ship Traffic, 2009-2016
title_sort baseline of next-generation arctic marine shipping assessments - oldest continuous pan-arctic satellite automatic identification system (ais) data record of maritime ship traffic, 2009-2016
publisher NSF Arctic Data Center
publishDate 2020
url https://dx.doi.org/10.18739/a2bv79w4v
https://arcticdata.io/catalog/view/doi:10.18739/A2BV79W4V
geographic Arctic
Arctic Ocean
geographic_facet Arctic
Arctic Ocean
genre Arctic Climate Impact Assessment
Arctic Council
Arctic
Arctic Ocean
Ice cap
Sea ice
ice covered waters
genre_facet Arctic Climate Impact Assessment
Arctic Council
Arctic
Arctic Ocean
Ice cap
Sea ice
ice covered waters
op_doi https://doi.org/10.18739/a2bv79w4v
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