Arctic Maritime Traffic and Risk

Transcription

1 Arctic Maritime Traffic and Risk Data Driven Risk Analysis Mark A. Stoddard, Dalhousie University MASS2014, St. John s, NL, Oct. 29 th, 2014

2 The Canadian Arctic presents a unique operating environment where first hand experience is limited, risks are not widely understood, and boundaries and responsibilities are uncertain, even among friends. 28 October

3 OUTLINE A few Pragmatic Assumptions What are we trying to accomplish with our risk analysis? Who is it intended to support? How will it improve the situation? What data will we draw on?

4 Pragmatic Assumptions Risks to ships are well understood by existing Arctic ship operators The real risk is from single voyage or new operators Risks from ships are well known, BUT, because of the diverse stakeholders involved the risk remains poorly understood (hard to calculate, visualize, and communicate) Determining the risk of maritime activity (planned or observed) will be integral to sustaining increased ship operations in the Arctic.

5 What are we trying to accomplish with Risk? Identify relevant cross-domain data sources and integrate data representations and ontologies Fixed and controlled vocabularies and descriptions Examine existing risk frameworks and calculations, such as the Polar Operational Limit Assessment Risk Indexing System POLARIS Develop and test new concepts for calculation, visualization, and communication of voyage / route risk in the Canadian Arctic.

6 Who is it intended to support? Shipping companies Insurance companies Standards organizations Ice Navigators Government agencies with need to assess risk of maritime activity (planned or observed) Academia (This is still a research activity!)

7 How will this improve the situation? We are trying to develop quantitative risk analysis tools that can be part of a real-time system rather than just be part of the planning process. Tools to compute, visualize and communicate route / voyage risk Tools to help stakeholders interpret the situation picture We will explore and engage stakeholders in the development of a flexible data representation and ontology supporting arctic maritime risk analysis

8 What data will we rely on? 3 year of historical satellite AIS Government sources of spatial data (charts, maps, ice chart, atmospherics (local and global), etc.) Private sources of spatial data Open sources of data (data.gc.ca / MEOPAR / Arctic NET) Ocean Networks / World Ocean council (Arctic ocean and climate data) Dalhousie Ocean Tracking Network / Big Data Institute

9 Risk Analysis HARD HARDER Risk = Probability of Occurrence * Consequence Risk Analysis Process to evaluate likelihoods of various impacts for uncertain future scenarios Our work will examine a range of maritime activities (planned or observed) in relation to multiple risk factors Ice, bathymetry, historical incidence, historical traffic, etc. Multicriteria Risk Analysis will allow us to consider multiple COA s and examine how each reacts to a set of risk factors

10 Arctic Maritime Traffic Analysis Risk Visualization 28 October

11 Arctic Maritime Traffic Analysis Risk Visualization 28 October

12 Arctic Maritime Traffic Analysis Anomaly Taxonomy Classification Category Observation Kinematic Anomaly Motion Speed - High speed - Low speed - Stopped Track - Off planned route - Abrupt end - Unusual course Location Vs Map - Outside shipping lane - Activity zone mismatch - Infringing closed zone Vs History - Outside historical route - First time transit October 28,

13 Arctic Maritime Traffic Analysis Anomaly Detection and Risk Classification Category Observation Risks Factors to Ship Motion Speed - High speed - Low speed - Stopped Operational Risks - Ice breaker availability - SAR asset availability Kinematic Anomaly Track - Off planned route - Abrupt end - Unusual course Environment - Currents, wind, tides - Water and Air Temperature - Visibility and daylight - Drifting ice Location Vs Map - Outside shipping lane - Activity zone mismatch - Infringing closed zone Infrastructure - ERR infrastructure locations - Navigational Aids and charts Human Resource Vs History - Outside historical route - First time transit - Local experience and expertise - Crew fatigue - Scheduled progress October 28,

14 QUESTIONS?