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Management of environmental streaming data to optimize Arctic shipping routes.

  • Zhihua Zhang
    ,
  • M. James C. Crabbe
  • Shandong University
    ,
  • University of Oxford
    ,
  • Shanxi University
Research Output: Contribution to journal Article Peer-review

Open access

Sustainable Development Goals

  • SDG 14 - Life Below Water
    SDG 14 Life Below Water

Abstract

Dynamic accurate predictions of Arctic sea ice, ocean, atmosphere, and ecosystem are necessary for safe and efficient Arctic maritime transportation; however a related technical roadmap has not yet been established. In this paper, we propose a management system for trans-Arctic maritime transportation supported by near real-time streaming data from air-space-ground-sea integrated monitoring networks and high spatio-temporal sea ice modeling. As the core algorithm of integrated monitoring networks, a long short-term memory (LSTM) neural network is embedded to improve Arctic sea ice mapping algorithms.Since the LSTM is localized in time and space, it can make full use of streaming data characteristics. The sea ice–related parameters from satellite remote sensing raw data are used as the input of the LSTM, while streaming data from shipborne radar networks and/or buoy measurements are used as training datasets to enhance the accuracy and resolution of environmental streaming data from outputs of LSTM. Due to large size of streaming data, the proposed management system of trans-Arctic shipping should be built on a cloud distribution platform using existing wireless communications networks among vessels and ports. Our management system will be used by the ongoing European Commission Horizon 2020 Programme “ePIcenter.”

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Article number

1441

Pages from-to (Number of pages)

Pages 1441

Journal (Volume, Issue Number)

Arabian Journal of Geosciences (Volume 14, Issue 15)

Publication milestones

  • Accepted/In press - 26/06/2021
  • Published - 20/07/2021

Publication status

Published - 20/07/2021

ISSN

1866-7511

External Publication IDs

  • handle.net: 10547/625061
  • Scopus: 85110989141

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