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For the past two years, Airbus has entrusted us with the annotation of satellite images for key elements recognition.
Innovation manager

Satellite image annotations for key items recognition

Airbus in a few words 

  • Airbus SE is Europe number one and the World number two in the aerospace and defence industry.
  • Founded in 1970, Airbus currently employs more than 130,000 people.
  • Airbus Defence and Space (ADS) is one of the three divisions of Airbus Group, specializing in military aircraft, drones, missiles, space launchers and artificial satellites. 
  • The OneAtlas platform, which provides quick and easy access to quality satellite imagery, layers and analysis for a wide range of use cases.

Isahit in a nutshell:

  • First ethical data labeling platform for AI and data processing in Europe
  • 2000 projects with over 1700 HITers
  • HITers established in over 39 countries
  • 300+ satisfied customers

Airbus defense and space mission: 

Democratize access to satellite imagery to help users solve the challenges of our world, such as:

  • Economic
  • Environmental
  • Defense and security
  • Food supply

Today, artificial intelligence can automatically detect objects and changes between satellite images.

OneAtlas Data, the platform used by Airbus Defense and Space

One Atlas Data is a platform for quick and easy access to high-quality satellite imagery, layers and analysis for a wide range of use cases.

OneAtlas Data provides access to a combination of high and very high optical resolution with SPOT and Pleiades. Both offer daily revisit capability, ensuring efficient monitoring.

Use case example: Satellite imagery dataset for aircraft detection


This worldwide training dataset consists of more than 25.000 annotated aircrafts on 0.5m.

It includes:

  • Small aircrafts
  • leisure 
  • private jets 
  • regional commercial
  • Large commercial
  • Helicopters
  • Fighter jets
  • Bombers
  • Other military

Artificial Intelligence model trained on this will detect aircrafts on 0.5m resolution images with a performance of:

> 85% in detection rate 

> 90% in precision rate

Challenges encountered

- Experts are not available and data scientists should not annotate all data 

- Need for massive and consistent annotations in a short time

- Quality must be assured

To obtain massive and consistent annotations in a short time, Airbus chose crowdsourcing, which allows to outsource the workload to hundreds of remote contributors. 

The solution: outsourcing with impact thanks to isahit

In order to meet these challenges, isahit appeared to be the most appropriate solution as it offers : 

  • More than 1000 active contributors in 39 different countries, able to respond to annotation needs in a short time
  •  A very demanding quality review:

Isahit implements a very strict project monitoring, throughout its realization, trains these contributors and implements tests upstream to ensure that a constant quality is maintained.

  • Great agility and ability to adapt resources to changing needs

In addition, Airbus shares the same values as isahit and supports its mission: to make tech and AI a work and training opportunity for women around the world.


Two years into our collaboration, we are mutually excited to report the following: 

  • 500,000 annotations made by our contributors: Bounding boxe oriented / Bbox classic / Polygon
  • On the flow project
  • 55 HITers worked on the project (self confidence, money to finance their project, digital skills) 
  • 53h of training provided (specific labeling tools but also nlp projects, google sheet, google doc, linkedin)

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