Using GO to observe the operational status of suspected Chinese “re-education” camps
Trying to understand trends in the construction rates and operational status of specific facilities in non-permissive environments can be time-consuming and difficult. other than having on the ground intelligence, satellite imagery may be used to explore these challenges. However, imagery still requires a human analyst to sift through imagery and identify additional construction manually before any contextual analysis can even take place.
Orbital Insight leverages computer vision algorithms to automatically classify land-use changes as well as detect objects. This automated analysis quickly helps gather more information, allowing analysts and users to focus on contextual analysis rather than just quantifiable trends.
By automatically classifying land use, a user can quantify landuse classes as well as more easily detect changes between time ranges. Automatically detected changes over a multitude of camps allow an analyst to focus on the context surrounding those changes and pick which ones to evaluate more closely. Construction of these facilities provides information around the build-up, or break down, of the overall “Re-education” camp policies within China.
By analyzing historical imagery, and obtaining future imagery to come, a user has more time to create context surrounding a set of events or an issue. Using cloud computing and a robust imagery ingestion pipeline, 41 suspected Chinese re-education camps are analyzed in the do-it-yourself analytics platform, GO.
Additionally, automatically identifying cars at scale helps humanitarian and NGO organizations achieve another level of transparency in otherwise non-permissive environments. Car detections are used as a proxy for worker activity at foreign facilities of interest, and in this case, are observed at suspected camp parking lots and surrounding areas. Combined, car counts and landuse classification datasets help users to more efficiently understand what is happening in specific areas of interest (AOIs).
Background on Re-education Camps in Xinjiang
Up to an estimated one million people have been interned without trial, throughout Xinjiang Uighur Autonomous Region (XUAR), according to Amnesty International. XUAR has a large Muslim population, and following China’s regulations on “de-extremification” policies, camps were used to “re-educate” portions of the population. The reasoning, according to the Chinese government, was to combat religious extremism (Sudworth, 2019). Critics of Chinese policies argue human rights violations are taking place, while China maintains that Islamic extremists and separatists are to blame for unrest in the region, and therefore this is a way to make the region more peaceful (“China changes law to recognise ‘re-education camps’ in Xinjiang,” 2018). These events have also received global attention, with some countries praising China for taking action against extremism, and others condemning the camps (“Which Countries Are For or Against China’s Xinjiang Policies?, The Diplomat,” 2019). With scant evidence of what actually goes on inside the camps and opposing views of camps’ function, anecdotal evidence proves to be one of the only other sources of information.
Recently, China claimed it closed many of these suspected camps (Buckley & Myers, 2019). To attain a better understanding of if this is true, Orbital Insight can use GO to measure construction, employee parking lots, and potential destruction of suspected camp locations. This is a first step for analysts and non-governmental organizations (NGOs) to understand these locations’ operational status.
Landuse aggregation and landuse change detection projects were created in Orbital Insight’s GO platform and analyzed Planet imagery. The results were exported and visualized in QGIS 3.0. These results can also be accessed via an API and integrated with other analytic models. Metadata such as square meters per polygon and construction/destruction changes can be analyzed and tracked automatically over time.
Object Detection: Car Detector
Based on the time series of these areas, raw car counts increase during construction and maintain a relatively high state once construction is complete. This would indicate that the facility is now in operation and employees of the facility are coming to work on a daily basis. These counts can be monitored in conjunction with LUCD to better understand when construction is complete and the facility is in operation. Conversely, if car counts decline, it could indicate a camp closure, which would verify the latest Chinese government claims of the facility shutting down.
GO can be used to automatically track the rate of construction for foreign areas of interest in relatively non-permissive environments. The outputs allow for rapid interoperability for other analysis models concerning quantitative metrics, allowing users and analysts to focus on contextual and qualitative analysis.
Landuse change detection, in conjunction with car detection counts, can give insight into construction completion and/or facility operational status. Cars may indicate facility employees, indicating the facility’s status as well as how many workers it takes to operate a facility. By proxy, understanding employee numbers may also be an indication of how many non-employees are at the camp.
The automatically detected data generated by GO may be an indicator of a camp’s operational status. Therefore, with contextual analysis, the data may help prove or disprove Chinese claims that facilities are closing.
Buckley, C., & Myers, S. L. (2019, August 9). China Said It Closed Muslim Detention Camps. There’s Reason to Doubt That. The New York Times. Retrieved from https://www.nytimes.com/2019/08/09/world/asia/china-xinjiang-muslim-detention.html
China changes law to recognise “re-education camps” in Xinjiang. (2018, October 10). Retrieved September 9, 2019, from South China Morning Post website: https://www.scmp.com/news/china/politics/article/2167893/china-legalises-use-re-education-camps-religious-extremists
Sudworth, J. (2019, June 21). Searching for truth in China’s “re-education” camps. BBC News. Retrieved from https://www.bbc.com/news/blogs-china-blog-48700786
Which Countries Are For or Against China’s Xinjiang Policies? | The Diplomat. (n.d.). Retrieved September 9, 2019, from https://thediplomat.com/2019/07/which-countries-are-for-or-against-chinas-xinjiang-policies/