Maritime trade represents a significant part of all global import-export trade. The traffic of containerships can be monitored through Automatic Identification System (AIS), due to the fact that the International Maritime Organization (IMO) regulation requires AIS to be fitted aboard all ships of 300 gross tonnage and upwards engaged on international voyages. The approach proposed by the authors aimed to extract value added information from an AIS dataset, with a focus on maritime economy. Using an AIS dataset of global position of containerships from 01/01/2012 to 31/12/2016, the paper focuses on space-time data cube creation and analysis for a better understanding of maritime trades trends. Data cube creation has been tested at different spatio-temporal bins dimension and on different specific topics (TEU classes, alliances, chokepoints and port areas), analysing the sensitivity on trend results, and highlighting how appropriate spatio-temporal bins dimensions are important to effectively highlight relevant trends. Results of the trend analysis are discussed and validated with the main data and information found over the period 2012–2016. The aim of this paper is to demonstrate the suitability of this approach applied to AIS data and to highlight its limitations. The authors can conclude that the approach used has proved to be adequate in describing the evolution of the global import-export trade.

SPATIO TEMPORAL DATA CUBE APPLIED TO AIS CONTAINERSHIPS TREND ANALYSIS IN THE EARLY YEARS OF THE BELT AND ROAD INITIATIVE – FROM GLOBAL TO LOCAL SCALE / Arco, E.; Ajmar, A.; Cremaschini, F.; Monaco, C.. - In: INTERNATIONAL ARCHIVES OF THE PHOTOGRAMMETRY, REMOTE SENSING AND SPATIAL INFORMATION SCIENCES. - ISSN 2194-9034. - XLIII-B4-2021:(2021), pp. 71-78. ((Intervento presentato al convegno XXIV ISPRS Congress tenutosi a Nizza, Francia nel 5-9 Luglio 2021 [10.5194/isprs-archives-XLIII-B4-2021-71-2021].

SPATIO TEMPORAL DATA CUBE APPLIED TO AIS CONTAINERSHIPS TREND ANALYSIS IN THE EARLY YEARS OF THE BELT AND ROAD INITIATIVE – FROM GLOBAL TO LOCAL SCALE

Arco, E.;Ajmar, A.;Cremaschini, F.;Monaco, C.
2021

Abstract

Maritime trade represents a significant part of all global import-export trade. The traffic of containerships can be monitored through Automatic Identification System (AIS), due to the fact that the International Maritime Organization (IMO) regulation requires AIS to be fitted aboard all ships of 300 gross tonnage and upwards engaged on international voyages. The approach proposed by the authors aimed to extract value added information from an AIS dataset, with a focus on maritime economy. Using an AIS dataset of global position of containerships from 01/01/2012 to 31/12/2016, the paper focuses on space-time data cube creation and analysis for a better understanding of maritime trades trends. Data cube creation has been tested at different spatio-temporal bins dimension and on different specific topics (TEU classes, alliances, chokepoints and port areas), analysing the sensitivity on trend results, and highlighting how appropriate spatio-temporal bins dimensions are important to effectively highlight relevant trends. Results of the trend analysis are discussed and validated with the main data and information found over the period 2012–2016. The aim of this paper is to demonstrate the suitability of this approach applied to AIS data and to highlight its limitations. The authors can conclude that the approach used has proved to be adequate in describing the evolution of the global import-export trade.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2911516