Exploratory Trajectory Analysis for Massive Historical AIS Datasets

Data exploration is an essential task for gaining an understanding of the potential and limitations of novel datasets. This paper discusses the challenges related to exploring large Automatic Identification System (AIS) datasets. We address these challenges using trajectory-based analysis approaches implemented in distributed computing environments using Spark and GeoMesa. This approach enables the exploration of datasets that are too big to handle within conventional spatial database systems. We demonstrate our approach using a case study of 4 billion AIS records.