Extracting Global Shipping Networks from Massive Historical Automatic Identification System Sensor Data: A Bottom-Up Approach
Article dans une revue avec comité de lecture
The increasing availability of big Automatic Identification Systems (AIS) sensor data offers great opportunities to track ship activities and mine spatial-temporal patterns of ship traffic worldwide. This research proposes a data integration approach to construct Global Shipping Networks (GSN) from massive historical ship AIS trajectories in a completely bottom-up way. First, a DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm is applied to temporally identify relevant stop locations, such as marine terminals and their associated events. Second, the semantic meanings of these locations are obtained by mapping them to real ports as identified by the World Port Index (WPI). Stop events are leveraged to develop travel sequences of any ship between stop locations at multiple scales. Last, a GSN is constructed by considering stop locations as nodes and journeys between nodes as links. This approach generates different levels of shipping networks from the terminal, port, and country levels. It is illustrated by a case study that extracts country, port, and terminal level Global Container Shipping Networks (GCSN) from AIS trajectories of more than 4000 container ships in 2015. The main features of these GCSNs and the limitations of this work are finally discussed.
Files in this item
Showing items related by title, author, creator and subject.
Risk Assessment of the Overseas Imported COVID-19 of Ocean-Going Ships Based on AIS and Infection Data Article dans une revue avec comité de lectureWANG, Zhihuan; YAO, Mengyuan; MENG, Chenguang; CLARAMUNT, Christophe (MDPI, 2020)Preventing and controlling the risk of importing the coronavirus disease (COVID-19) has rapidly become a major concern. In addition to air freight, ocean-going ships play a non-negligible role in spreading COVID-19 due to ...
Design of a spatial database to analyze the forms and responsiveness of an urban environment using an ontological approach Article dans une revue avec comité de lectureSILAVI, Tolue; HAKIMPOUR, Farshad; CLARAMUNT, Christophe; NOURIAN, Farshad (Elsevier, 2015)This paper introduces a spatial database and ontology-enabled framework that models and operationalizes the relation between urban forms and their responsiveness to the needs of its user. The objective is to offer a framework ...
Article dans une revue avec comité de lectureAFYOUNI, Imad; RAY, Cyril; CLARAMUNT, Christophe; ILARRI, Sergio (Lavoisier, 2015)Cet article développe une représentation de données spatiales d’un environnement intérieur dit “indoor” qui tient compte des dimensions contextuelles centrées sur l’utilisateur et aborde les enjeux de gestion de données ...
Article dans une revue avec comité de lectureLE YAOUANC, Jean-Marie; SAUX, Eric; CLARAMUNT, Christophe (Springer Verlag, 2010)The modeling of a landscape environment is a cognitive activity that requires appropriate spatial representations. The research presented in this paper introduces a structural and semantic categorization of a landscape ...
A qualitative modelling approach for the representation of trajctories: application to the analysis of flight patterns Article dans une revue avec comité de lectureWU, Jing; CLARAMUNT, Christophe; BELOUAER, Lamia; DENG, Min (Taylor & Francis, 2015)Over the past few years a series of computational and semantic frameworks have been developed to model and represent the spatial and temporal properties of moving entities. Despite the interest of these contributions it ...