3INSAT, an ESA Business Applications funded project led by Ansaldo STS in Italy, recently helped to run the worlds first long-haul automated cargo train.

The fully-loaded autonomous train carried 28,000 tonnes of ore over 280 km between the Tom Price mine and the port of Cape Lambert in Western Australia, with Rio Tinto’s Operations Centre more than 1,500 km away in Perth mointoring the three locamotives used to drive the train, using satellite capabilities.

Each of the three locamotives was equipped with an onboard module relaying the trains position, speed and direction of travel back to the Rio Tinto Operations Centre via using satellite communication technology. Public areas and crossings were also fitted with cameras and monitors to allow continual monitoring of this historic journey.

Rio Tinto is using the 3INSAT inspired technology to automate much of the acitivty on the 1,700km jounrey between mines and ports in the Pilbara region. More than 200 locamotives use this route with an average journey of 800km taking 40hrs from loading to unloading.

This journey, as the world's first long-haul cargo train to be automated, signals the start of a new era of automated long-haul cargo train networks, which suit the remote areas of Western Australia.

3InSat innovations contributed to the rollout of the European’s first satellite applications on train control systems generating over 100 M€ revenues, raising some 20 M€ in R&D investments and to gave birth to ERSAT – a joint initiative between Ansaldo STS and RFI for adopting satellite applications on the local and regional lines. 

An unprecedented collaboration between industry, researchers and space agencies has generated new jobs and is at the core of a roadmap to exploit satellite applications on daily railway operations, improving the safety and the quality of the services for millions of passengers travelling on trains.

Sponsored by DigitalGlobe and the European Space Agency (ESA) Business Applications, the Earth Observation Challenge launched in April 2018, calling on developers, geoscientists, and innovative minds across Europe to submit tactical solutions using advanced geospatial technology for one of two challenges:

1. Identifying water bodies or water changes
2. Change characterization in urban areas

Participants received on demand access to the DigitalGlobe 18-year image library and ESA Sentinel-2 data via our cloud-based Geospatial Big Data platform (GBDX), which empowered them to develop and run algorithms at scale.

We are excited to announce our three winners:

Reservoir Monitor – Global, timely, and accurate monitoring of water resources is an essential component to improve management in water-scarce regions. Gennadii Donchyts, a data scientist, created a solution based on a fusion of medium and high-resolution, multi-temporal satellite imagery that estimates high-frequency surface water area changes in any reservoir on Earth. The use of a discriminative-generative method allows accurate detection of surface water extent even in satellite imagery.

Urban.Monitor – Rapid growth – without data, facts and efforts to ensure resilience – is exposing cities around the world to huge risks as a result of change that has not been prepared for.. We are committed to accurately mapping urban change using combined high and very-high satellite imagery. A team consisting of Konstantinos Karantzalos, Maria Papadomanolaki, and Maria Vakalopoulou created a deep learning framework that trains, predicts, and detects naturally occurring and man-made objects and their change to better understand the scale, pace and impact to the surrounding environment anywhere in the world.

Topolytics – Three people from Topolytics, a data and analytics business, are making industrial and commercial waste materials visible, verifiable, and valuable via two solutions: WasteMap is a geospatially-enabled big data platform for managing, visualizing and analyzing waste material flows, which leverages timely Earth observation (EO) data. WasteTrack combines live data from sensors and other sources to verify the movement of inbound and outbound waste and raw materials. Together, WasteMap and WasteTrack will enable stakeholders in the waste industry to better understand and optimize their processes and generate better commercial, environmental and investment decisions by maximizing the value and utility of secondary raw materials.

This challenge was designed to empower data scientists, businesses, academia and start-ups to build solutions and transform EO imagery into meaningful, geospatial context for business growth and global development purposes with GBDX Notebooks – and each submission delivered a brilliant idea. Congratulations to all the finalists, and thank you to all our participants for your incredible work!

The winners receive a cash prize, 90 days access to GBDX Notebooks, and access to ESA’s incubation network and business development resources.