Ship Detection and Categorization - gap analysis

P34: Ship detection and categorization

Download the product sheet gap analysis 

Maturity score

Mean: 2.7

STD: 0.47

Constraints and limitations

·   Smaller vessels and low-profile ships may be challenging to detect or classify.

·   Cloud presence but it can be overcome by using SAR imagery.

·   Challenging to separate individual vessels in overcrowded ports or regions with high maritime traffic.

Relevant user needs

UN17: Need near real-time tracking of marine vessels to understand their routes and estimate fuel usage

R&D gaps

·   High cost of VHR satellite imagery

·   For near-real time, Automatic Identification System (AIS) data is needed. EO is a complement to permit detecting unreported ships, but real-time tracking is not possible yet with the current technology

Potential improvements drivers

·  Price models

·  More investigation of fusing EO with AIS data

Utilisation level review

Utilisation score

Mean: 2.00

STD: 1.26

No utilisation

·  Unavailability of freely available sources of the EO product.

·  Unacceptable reliability and accuracy of the EO product.

·  Users’ lack of EO knowledge and skills to utilize the EO product.

·  Unawareness of the existence of this EO product.

Low utilisation

Medium utilisation

·  We would not state full technical and usability requirements are met. This remains viable depending on the financial offer and use case.

High utilisation

·  Only this product satisfies the technical and usability requirements.

Critical gaps related to relevant user needs

Utilisation gap

UN17: Need near real-time tracking of marine vessels to understand their routes and estimate fuel usage.