Mapping vessel behaviour and cargo flows

Since the introduction of the AIS (Automated Identification System) in 2004/05 we have seen a dramatic increase in the information flow from terrestrial and satellite-based receivers about the location and itineraries of the world fleet. The project exploits such information about the location and itineraries of the world fleet. AIS messages include real-time information on the coordinates and speed of ships, as well as information on draught, the next port of call and estimated time of arrival. The value of proper utilisation of this information is huge - for instance in the context of optimisation of ship operations, chartering and transport planning - yet our advancement of knowledge in this area has met substantial R&D challenges. This is in part due to the huge amounts of high frequency data received, requiring fast and scalable IT solutions, but mainly due to inconsistent quality and data coverage requiring advanced algorithms for interpolation of positions and extrapolation of future itineraries. In addition, ascertaining key issues such as cargo type and size remains an art rather than a science, particularly for the smaller vessel sizes. CARGOMAP is an interdisciplinary project that connects the AIS expertise at CMR Computing with shipping economics expertise at the Norwegian School of Economics (SNF/NHH). The objective of CARGOMAP is to verify the quality and limitations of AIS data as a basis for national transport planning and to develop solutions for extracting information from AIS data that will enable better seaborne transportation planning. This involves firstly assessing AIS data quality and geographical coverage and, secondly, to use AIS data in case studies. The first case study assesses the impact of environmental regulations on transport costs by comparing vessel behaviour within and outside the low-sulphur-fuel area in the North Sea. Results indicate that introduction of low sulphur fuel areas does not affect speed, but induce some changes in the sailing pattern. The stricter regulation introduced in January 2015 did not change the result. An analysis of the world wide movements of the VLCC fleet we also found that the sailing speed is reflecting ship specific factors whereas the effect of changing macroeconomic factors is insignificant. The second case study looks at port connectivity and trade flows within Norwegian territorial waters. Third, we have established methodologies and algorithms to visualise trading patterns based on the AIS data provided by individual vessels. The algorithms allow interactive filtering of data for example for visualising the movements of one specific ship type only, or for filtering by draught to visualise transport routes for laden versus vessels sailing in ballast.

Since the first online network of ground stations receiving Automated Identification System (AIS) messages from vessels in 2004/05 we have seen a dramatic increase in the information flow from terrestrial and satellite-based receivers about the location a nd itineraries of the world fleet. The commercial value of this information is huge - for instance in the context of optimization of ship operations, chartering and transport planning - yet our advancement of knowledge in this area has met substantial R &D challenges. This is in part due to the huge amounts of high-frequency data received, requiring fast and scalable IT solutions, but mainly due to inconsistent quality and data coverage requiring advanced algorithms for interpolation of positions and ex trapolation of future itineraries. In addition, ascertaining key issues such as cargo type and cargo size remain an art rather than science, particularly for the smaller vessel sizes. The two-year researcher project CARGOMAP seeks to narrow the knowle dge gap in this area by connecting Norway's leading research groups on the processing of AIS data - CMR Computing, DNV GL and the Norwegian Coastal Authority - and shipping economics and market modeling at the Norwegian School of Economics (SNF/NHH). The objective of CARGOMAP is to verify the quality and limitations of AIS data as a basis for national transport planning and to develop solutions for extracting information from AIS data that will enable better seaborne transportation planning and a transfe r of goods from land to sea. Output from the project is anticipated to be better systems for the processing of AIS data, for detecting misinformation and anomalous vessel behaviour, and for the estimation and visualisation of cargo flows, fleet utilisati on, and port connectivity within Norwegian territorial waters. Implementing the results will assist the Norwegian maritime industry in moving towards a more sustainable, efficient and reliable sea transport system.