Statistical real-time model for performance prediction of ship detection from microsatellite electro-optical imagers

For locating maritime vessels longer than 45 meters, such vessels are required to set up an Automatic Identification System (AIS) used by vessel traffic services. However, when a boat is shutting down its AIS, there are no means to detect it in open sea. In this paper, we use Electro-Optical (EO) imagers for noncooperative vessel detection when the AIS is not operational. As compared to radar sensors, EO sensors have lower cost, lower payload, and better computational processing load. EO sensors are mounted on LEO microsatellites. We propose a real-time statistical methodology to estimate sensor Receiver Operating Characteristic (ROC) curves. It does not require the computation of the entire image received at the sensor. We then illustrate the use of this methodology to design a simple simulator that can help sensor manufacturers in optimizing the design of EO sensors for maritime applications

Ship-Iceberg Discrimination in Sentinel-2 Multispectral Imagery by Supervised Classification

The European Space Agency Sentinel-2 satellites provide multispectral images with pixel sizes down to 10 m. This high resolution allows for fast and frequent detection, classification and discrimination of various objects in the sea, which is relevant in general and specifically for the vast Arctic environment. We analyze several sets of multispectral image data from Denmark and Greenland fall and winter, and describe a supervised search and classification algorithm based on physical parameters that successfully finds and classifies all objects in the sea with reflectance above a threshold. It discriminates between objects like ships, islands, wakes, and icebergs, ice floes, and clouds with accuracy better than 90%. Pan-sharpening the infrared bands leads to classification and discrimination of ice floes and clouds better than 95%. For complex images with abundant ice floes or clouds, however, the false alarm rate dominates for small non-sailing boats

Tracked to protect - Spatiotemporal dynamics of recreational boating in sensitive marine natural areas

In many coastal areas, high numbers of recreationists may exceed ecological capacities. Careful monitoring of visitor flows is a first prerequisite for coastal area management. We show how AIS ship data can be translated into interpretable information on recreational boats and investigate whether AIS can provide monitoring information when compared to nature conservation policy targets. In the Wadden Sea UNESCO World Heritage Site we used nearly 9 million data points to create spatiotemporal patterns for the 2018 recreation season. We combined this with shipping lanes and bathymetry data and compared the resulting patterns with nature protection regulations. Our results show that most of the traffic is concentrated around tidal channels. We also show that exceeding speed limits is not predominant behaviour, but the effect of speeding on birds and seals might be more severe than the data suggests. We mapped favourite tidal flat moor activities, and observed where this occurs in Marine Protected Areas. We conclude that AIS analysis can provide valuable recreational boating monitoring, relevant to sensitive coastal area management in the entire Dutch Wadden Sea for the full recreational season. Broader integration of AIS with radar data and ecological data can add to the power of using AIS