Guide to Maritime Informatics

Description

In the last 25 years, information systems have had a disruptive effect on society and business. Up until recently though, the majority of passengers and goods were transported by sea in many ways similar to the way they were at the turn of the previous century. Gradually, advanced information technologies are being introduced, in an attempt to make shipping safer, greener, more efficient, and transparent. The emerging field of Maritime Informatics studies the application of information technology and information systems to maritime transportation. Maritime Informatics can be considered as both a field of study and domain of application. As an application domain, it is the outlet of innovations originating from data science and artificial intelligence; as a field of study, it is positioned between computer science and marine engineering. This new field’s complexity lies within this duality because it is faced with disciplinary barriers yet demands a systemic, transdisciplinary approach.  At present, there is a growing body of knowledge that remains undocumented in a single source or textbook designed to assist students and practitioners. This highly useful textbook/reference starts by introducing required knowledge, algorithmic approaches, and technical details, before presenting real-world applications.  The aim is to present interested audiences with an overview of the main technological innovations having a disruptive effect on the maritime industry, as well as to discuss principal ideas, methods of operation and applications, and future developments. The material in this unique volume provides requisite core knowledge for undergraduate or postgraduate students, employing an analytical approach with numerous real-world examples and case studies. Preface Acknowledgements Contents Acronyms Part I Maritime Data 1 Maritime Reporting Systems 1.1 Introduction 1.2 The Automatic Identification System 1.2.1 AIS Equipment 1.2.2 AIS Messages 1.2.3 Dynamic AIS Messages 1.2.4 Static AIS Messages 1.2.5 Example Dataset 1.2.6 AIS Processing Difficulties and Challenges 1.2.7 AIS Applications & Use Cases 1.2.8 Applications of AIS in the Book 1.3 VHF Data Exchange System (VDES) 1.3.1 VDES Components 1.3.2 VDES Applications 1.4 Long-Range Identification and Tracking 1.4.1 Comparison with AIS 1.4.2 LRIT Applications 1.5 The Vessel Monitoring System 1.6 Advanced Applications and Analytics Based on Maritime Reporting Systems and Data 1.6.1 Electronic Navigation (eNAV) 1.6.2 Maritime Situational Awareness 1.7 Conclusions 1.8 Bibliographical Notes References 2 Navigating the Ocean of Publicly Available Maritime Data 2.1 Introduction 2.2 Vessel-Related Data 2.2.1 Static and Rarely Changing Characteristics 2.2.2 Traffic Flow 2.3 Sea-Related Data 2.3.1 The Aquatic Environment Under the Surface of the Sea 2.3.2 The Aquatic Environment over the Surface of the Sea 2.3.3 Ecology, Marine Flora and Fauna 2.4 Land-Related Data 2.5 Map and Imagery-Related Data 2.6 Climate and Sea Conservancy-Related Data 2.6.1 Weather Conditions 2.6.2 The Climate System 2.6.3 The Impact of Human Activity on the Health of the Ocean 2.7 Discussion and Concluding Remarks References Part II Off-Line Maritime Data Processing 3 Maritime Data Processing in Relational Databases 3.1 Introduction 3.2 Systems for Spatial Data and Moving Objects 3.2.1 Handling Spatial Data 3.2.2 Spatial-Temporal and Movement Data in Databases 3.3 Building a Maritime Information System 3.3.1 PostgreSQL DBMS 3.3.2 PostGIS Spatial Extension 3.3.3 PGAdmin Management Tool 3.3.4 QGIS Visualization Tool 3.3.5 Getting the Maritime Dataset 3.4 Creation of the Maritime Database 3.4.1 The Database Schema and the Tables 3.4.2 Loading the Data into the Database 3.4.3 The Temporal Dimension of Data 3.4.4 Make It Faster ! 3.4.5 Make It Geographic ! 3.4.6 Integrating Contextual Data 3.4.7 Executing Spatial Queries 3.4.8 Extending PostgreSQL Functions 3.5 Understanding Vessel Movements with Trajectory-Based Queries 3.5.1 Characterising Port Areas Through Spatial Partitioning 3.5.2 Detecting and Clustering Ship Stops 3.5.3 Extracting Trajectory Tracks and the Navigation Graph 3.5.4 Managing Data Quality Using Constraints 3.6 Summary and Conclusion 3.7 Bibliographical Notes References 4 Maritime Data Analytics 4.1 Introduction 4.1.1 Mobility Data Analytics 4.1.2 What Is Special About Maritime Data 4.1.3 Chapter Structure 4.2 Preparing the Maritime Data for Analytics Purposes 4.2.1 Getting Familiar with the Data 4.2.2 Data Cleansing and Transformation 4.2.3 Getting from Locations to Trajectories 4.3 Discovering Knowledge from Maritime Data 4.3.1 Cluster Analysis 4.3.2 Group Behaviour 4.3.3 Hot-Spot Analysis 4.3.4 Frequent Route—Network Discovery 4.3.5 Data-Driven Predictive Analytics 4.4 Conclusions 4.5 Bibliographical Notes References 5 Visual Analytics of Vessel Movement 5.1 Introduction 5.2 Exploration of the Data Properties 5.3 Transformations of Movement Data 5.4 Detection and Analysis of the Anchoring Events 5.4.1 Data Selection and Preparation 5.4.2 Detection and Extraction of Anchoring Events 5.4.3 Exploration of the Anchoring Events in Relation to Strait Passing 5.4.4 Temporal Distribution of the Anchoring Events 5.4.5 Exploration of the Anchoring Events in the Context of the Trajectories 5.4.6 Exploration of the Traffic Through the Strait 5.5 Discussion and Conclusion 5.6 Bibliographical Notes References Part III On-Line Maritime Data Processing 6 Online Mobility Tracking Against Evolving Maritime Trajectories 6.1 Introduction 6.2 Using AIS Messages for Monitoring Trajectories of Vessels 6.2.1 Dynamic AIS Messages as Streaming Data 6.2.2 Trajectories Reconstructed from Dynamic AIS Messages 6.3 Background 6.3.1 Trajectory Simplification 6.3.2 Geostream-Aware Monitoring Applications 6.3.3 Processing Maritime Trajectories 6.4 Online Noise Reduction from Dynamic AIS Messages 6.5 Annotating Mobility Events Along Vessel Trajectories 6.5.1 Online Tracking of Moving Vessels 6.5.2 Detecting Trajectory Events 6.6 Discussion 6.7 Conclusion 6.8 Bibliographical Notes References 7 Link Discovery for Maritime Monitoring 7.1 Motivation 7.2 Spatial and Temporal Relations 7.3 Basic Concepts of Link Discovery 7.3.1 Blocking 7.3.2 Generalization of Blocking 7.4 Special Topics, Extensions and Generalizations 7.4.1 Use of Approximations 7.4.2 Handling Data Skew 7.4.3 Handling Empty Space 7.4.4 Handling the Temporal Dimension 7.5 Common Issues in Link Discovery 7.6 Application on Real-Life Data 7.6.1 Data Set Analysis 7.6.2 Applying Link Discovery 7.6.3 Summary 7.7 Bibliographical Notes References 8 Composite Maritime Event Recognition 8.1 Introduction 8.2 Run-Time Event Calculus 8.3 Maritime Patterns 8.3.1 Building Blocks 8.3.2 Maritime Situational Indicators 8.4 Empirical Analysis 8.4.1 Accuracy 8.4.2 Efficiency 8.5 Summary 8.6 Biliographical Notes References Part IV Applications 9 Uncertainty Handling for Maritime Route Deviation 9.1 Introduction 9.2 Maritime Anomaly Detection and Route Deviation 9.2.1 Synthetic Maritime Route Extraction 9.2.2 The Vessel to Route Association Problem 9.2.3 Uncertainty in Maritime Anomaly Detection 9.3 Uncertainty Handling 9.3.1 Information Deficiencies 9.3.2 Some Uncertainty Theories: A Brief Overview 9.4 Uncertainty Representation and Reasoning Techniques 9.4.1 URRT#1: Pattern matching—Euclidean 9.4.2 URRT#2: Pattern Matching—Mahalanobis 9.4.3 URRT#3: Probability-based—Bayesian 9.4.4 URRT#4: Probability-based - Non-Bayesian 9.4.5 URRT#5: Transferable Belief Model (TBM) Model-Based 9.4.6 URRT#6: Belief Functions—Database Query 9.5 Quantitative Comparison 9.5.1 Evaluation Criteria 9.5.2 Dataset of Tracklets 9.5.3 Results and Discussion 9.6 Conclusions 9.7 Bibliographical Notes References 10 Maritime Network Analysis: Connectivity and Spatial Distribution 10.1 Introduction 10.2 Data and Methodology 10.2.1 Background 10.2.2 From AIS Data to Maritime Network 10.2.3 Network Visualization 10.3 Network Topology and Connectivity 10.3.1 Global Structure and Hierarchical Effects 10.3.2 Multiplexity and Assortativity 10.4 Maritime Network and Spatial Embedding 10.4.1 Substructures Within the European Maritime Network 10.4.2 Flowmap of the European Maritime Network 10.5 Summary 10.6 Bibliographical Notes References 11 Shipping Economics and Analytics 11.1 Introduction 11.2 Tracking of Trade Flows 11.2.1 Classification of Voyages 11.2.2 Aggregating Cargo Volumes 11.3 Analytics for Freight Trading 11.3.1 Monitoring Market Balance Using AIS Data 11.3.2 Monitoring Vessel Speeds 11.3.3 Monitoring Port Congestion 11.3.4 Monitoring Unemployed Ships 11.4 Limitations and Summary 11.5 Bibliographical Notes References