Satellite Imagery For

Maritime

maritime

Unrestricted Access To The Ocean

Detect Marine Vessels

Identify and track ships using 30 cm resolution and multiple daily collections

Search Large Areas

Utilise our tipping and cueing services to search vast stretches of ocean

Monitor Coastlines

Assess coastal erosion and respond to marine environmental emergencies

Very high resolution optical satellites offer a unique view of our oceans, seas, and coasts. They also provide a cost-effective and simple method of monitoring wide areas over maritime zones globally. They are an indispensable tool for managing the actions and events that impact on maritime safety, security, and sustainability.

There is a growing need for coverage and detection of large maritime areas, mainly in the exclusive economic zone (EEZ). Since physically accessing such a large area is practically impossible, satellite imagery offers an efficient and cost-effective solution. European Space Imaging works with many regulatory bodies monitoring EU waters to ascertain Maritime Situational Awareness in order to identify vessels, rescue lives  at sea and keep Europe and its citizens safe.

Monitoring the marine environment poses unique challenges of rapidly changing weather patterns and constantly moving vessels. We have tailored ordering, collection and rush delivery workflows to mitigate these challenges and maintain valuable partnerships with EU maritime authorities.

Locating "dark" vessels transporting heroin in the suez bay with satellite imagery

Read about this and more satellite imagery applications in the Maritime INCITE industry report, To See the See: Achieving Total Maritime Awareness Using Satellite Imagery

Vessel Identification

Very high resolution satellite data is a core component of marine monitoring services, and provides a cost-effective method for monitoring large and remote areas. It is sufficiently detailed to enable:

  • Identification of individual vessels
  • Detection of illegal fishing
  • Detection of pollution such as oil spills
  • Validation of AIS data
  • Detection of coastal erosion
  • Identification of algal blooms

Bathymetry

Monitoring change in coastal regions is critical to marine navigation and development, and an important parameter is water depth. Reflectance values from 8-band multispectral imagery is a non-invasive and extremely cost-effective tool for bathymetry in water depths up to 15 m. Bathymetric data supports:

  • Updating navigational maps
  • Marine habitat and benthic ecosystems monitoring
  • Assessment of at-risk properties or infrastructure
  • Classification of marine habitats
  • Oceanographic research (especially in remote areas)

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Maritime Situational Awareness

Marine vessel surveillance is crucial for maritime safety and environmental protection. When a ship has stopped transmitting an AIS location signal, it could be for a number of suspicious reasons.

When an organisation needs to locate or confirm the identity of a vessel at sea, tipping and cueing services and vessel detection software are the essential tools. Ships can be located in large areas of ocean using Synthetic-aperture Radar (SAR) satellite data and then carefully analysed used VHR optical satellite data to determine details such as vessel type, accurate measurements and identifying features.

Tipping-cueing

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See Every detail

Use the map controls to explore the Port of Taranto in TRUE 30 cm resolution.

Download The Maritime INCITE report

To See the See: Achieving Total Maritime Awareness Using Satellite Imagery

The definitive guide to acquiring and using satellite imagery in the maritime industry.

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Architecture of ResNet34-UNet model

UNet architecture for semantic segmentation with ResNet34 as encoder or feature extraction part. ResNet34 is used as an encoder or feature extractor in the contracting path and the corresponding symmetric expanding path predicts the dense segmentation output.

Architecture of VGG16-UNet model

UNet architecture for semantic segmentation with VGG16 as the encoder or feature extractor. VGG16 is used as an encoder or feature extractor in the contracting path and the corresponding symmetric expanding path predicts the dense segmentation output.

Architecture of ResNet34-FCN model

In this model, ResNet34 is used for feature extraction and the FCN operation remains as is. The feature of ResNet architecture is exploited where just like VGG, as the number of filters double, the feature map size gets halved. This gives a similarity to VGG and ResNet architecture while supporting deeper architecture and addressing the issue of vanishing gradients while also being faster. The fully connected layer at the output of ResNet34 is not used and instead converted to fully convolutional layer by means of 1×1 convolution.

Architecture of VGG16-FCN model

In this model, VGG16 is used for feature extraction which also performs the function of an encoder. The fully connected layer of the VGG16 is not used and instead converted to fully convolutional layer by means of 1×1 convolution.

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