Webinar recording

Why Satellite Imagery, AIS Data, and Machine Learning are Making Waves in Maritime Surveillance

Learn about maritime surveillance

Monitoring maritime activity is of utmost importance for geospatial solutions from fleet management to dark vessel detection. But to build maritime surveillance solutions that offer accurate, timely, and actionable insights, we need the right data.

Understanding the benefits, overcoming the limitations, and leveraging the complementary nature of optical imagery, radar data, and AIS information is key.


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Get a blueprint

Learn how to build your own maritime surveillance solutions directly from industry-leading developers.

Gain a competitive advantage

Gain a competitive advantage

Understand when and how to successfully bring together optical imagery, SAR imagery, and AIS data.

Receive deep, technical insights

Receive deep, technical insights

Learn about the entire geospatial solution development process, from data access to algorithm development.

exactEarth and CCRi

Building a Port Boundary Layer Using exactEarth’s AIS Data and CCRi Machine Learning and AI

Taylor Nicholls, Director, Data Products and Services exactEarth & Eric Nallon, Data Scientist, CCRi

Maritime AIS data is commonly used to identify trends in trade, tourism and commodities. Using AIS and port boundaries gives analysts critical information about when a vessel arrives and departs from a location of interest. We provided insights into how we generate our port boundary layer and what steps we have taken to improve on the existing World Port Index (WPI). While the WPI provides port information based on static single points, our version uses polygons to delineate the boundaries and is regularly updated to account for port expansion or changes in bathymetry.

exactEarth’s historical AIS (Automatic Identification System) data was used as the baseline for this layer to gain insights into the historical port data. The AIS data was filtered and clustered to apply especially to ports and layered on top of the WPI for further improvements.


The Search for Dark Vessels: Fusing AIS Signals and Deep Learning-Based Ship Detection

Dr. Markus Müller, Lead Data Science Engineer

In this presentation, we explored how the fusion of different types of satellite data can be used to derive insights unattainable from only one source of information. The use case is the identification of so-called dark vessels, i.e., ships and boats, which cannot be tracked by Automatic Identification System (AIS) signals alone. To this end, Airbus's ship detection algorithm using deep learning on satellite imagery is combined with AIS data from ExactEarth. We showed how to run such an analysis in an automated manner using the UP42 Python SDK.

Why Is Synthetic Aperture Radar (SAR) Interesting for Maritime Object Verification and Identification?

Dr. Ron Hagensieker, CEO and Founder

This talk gave an overview of SAR’s relevant technical properties, current applications in detection, as well as its limitations and potentials. For example, what are feasible ship sizes to detect, and how detailed might container load be evaluated according to recent scientific publications? The applicability for different use cases of the most common data products was discussed, and different SAR acquisition modes were introduced. The presentation concluded with an outlook of upcoming SAR missions, the effects of recent advances in ML on maritime applications including security implications, and analytical possibilities.