Project description

China is accused of incarcerating hundreds of thousands of Muslims in detention camps that are rising from the desert sands in Xinjiang. Reuters set out to quantify this expansion using a unique data gathering technique based on satellite imagery. Our forensic analysis of these facilities revealed they are expanding at a rapid rate.

What makes this project innovative?

Hundreds of satellite images were digitally scrutinised by running them through an algorithm to identify, count, trace and analyse solid building structures with great granularity. The end result was a data set exclusive to Reuters. This data formed the basis of a Reuters special report. This evidence was visualised in powerful information graphics and combined with strong photographs, high resolution satellite images, illustration, and long form narrative to make an immersive online presentation.

What was the impact of your project? How did you measure it?

The data sheds new light on one of China's most secretive locations. The crackdown there includes tight control over information and access to the region. Xinjiang is now one of the most heavily policed areas in the world, according to academics and human rights groups. The project spread widely on social media and was a huge hit with readers, who had never seen the camps in this level of detail before.

Source and methodology

Having identified 80 detention facilities using construction notices, Reuters focused its analysis on 39 that were clearly identifiable from satellite imagery. Hundreds of satellite images taken over years were digitally scrutinised by running them through an algorithm to identify, count, trace and analyse every single building structure in a given area. The building-by-building analysis revealed that the footprint of the built-up area had almost tripled between April 2017 and August 2018.

Technologies Used

GIS software, javascript, D3, Adobe creative suite, hand drawn illustration.

Project members

Christian Inton, Simon Scarr, Weiyi Cai, Jin Wu, Philip Wen, Thomas Peter, Peter Hirschberg



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