Poland buys two observation satellites from France

Gastón Dubois

Satélites de observación / observation satellites Pléiades Neo

During French Armed Forces Minister Sébastien Lecornu’s trip to Warsaw on Tuesday, December 27, France and Poland signed an agreement for the sale of two French observation satellites.

On his first official visit to Poland since taking office last May, Sébastien Lecornu, Minister of the Armed Forces, met on Tuesday 27 December 2022 with his Polish counterpart, Mariusz Blaszczak. Among the highlights of this meeting was the signing of the agreement for the sale of two French observation satellites, for some 575 million euros. The launch of these satellites should take place in 2027.

The agreement covers the sale of the two Pléiades Neo satellites, designed and built by Airbus Defence and Space, a ground station for processing the intelligence images obtained, and access to the data provided by the French observation satellites, until the Polish constellation reaches operational status.

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Pléiades Neo

According to company data, these satellites are entirely funded, manufactured, owned and operated by Airbus Defence and Space. They represent a breakthrough in Earth observation, creating the company’s most advanced optical constellation for commercial, institutional and government customers.

The constellation, which will consist of four identical satellites capable of imaging at 30 cm resolution when fully deployed, will offer reactive tasking and the ability to visit any point on the globe at least twice a day. Each Pléiades Neo satellite will add half a million km² of imagery per day to the Airbus catalog.

Using innovative ground infrastructure, imagery collected by the Pléiades Neo constellation is easily accessible from Airbus’ OneAtlas digital platform, giving customers immediate access to both newly acquired and archived data, as well as extensive analysis.

The high-resolution Pléiades Neo imagery offers an unmatched level of detail, including increased visibility of small objects such as vehicles and road markings. This level of detection, recognition and identification provides more real-world data to image analysts and improves the reliability of machine learning capabilities.

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