{"id":16405,"date":"2021-01-26T19:36:16","date_gmt":"2021-01-26T19:36:16","guid":{"rendered":"https:\/\/one.sightlinemg.com\/c4isrnet\/uncategorized\/2021\/01\/26\/how-to-see-in-the-darkand-why-we-need-to\/"},"modified":"2026-08-08T17:54:59","modified_gmt":"2026-08-08T17:54:59","slug":"how-to-see-in-the-darkand-why-we-need-to","status":"publish","type":"post","link":"https:\/\/one.sightlinemg.com\/c4isrnet\/opinion\/2021\/01\/26\/how-to-see-in-the-darkand-why-we-need-to\/","title":{"rendered":"How to see in the dark\u2014and why we need to"},"content":{"rendered":"\n

In August 2017, ongoing violence in the Rakhine state of Myanmar came to a boiling point after a coordinated attack by insurgents on several police posts and an army base. Government forces responded with \u201ca brutal attack against hundreds of thousands of unarmed men, women, and children in a grossly disproportionate response<\/a>\u201d against the minority Rohingya people that resulted in more than 740,000 fleeing the country to neighboring Bangladesh.<\/p>\n\n\n\n

Traditional optical satellite imagery showed evidence of the devastation, which was widely condemned by the international community. This type of imagery can be a powerful tool for the U.S. military in identifying everything from ground disturbances related to underground nuclear testing to human migration in times of crisis, but optical satellite imagery has its limits. It can\u2019t see through clouds or thick smoke, and has limited utility at night. So how do you see through visual impediments to understand what\u2019s happening on the ground?<\/p>\n\n\n\n

Synthetic aperture radar (SAR) data is one answer. While SAR has been regularly used by scientists who study environmental and other physical changes, it has not been widely employed as a tool for human rights monitoring\u2014but it should be, because it can make it harder for bad actors to hide their campaigns of destruction.<\/p>\n\n\n\n

SAR can capture images of the Earth\u2019s surface regardless of cloud cover, darkness or smoke. It does this by emitting electromagnetic waves and measuring the reflected signal, called backscatter. These waves have two properties: amplitude, or the strength of the signal, and phase, or the number of oscillation cycles in the signal. Comparing the phase across pairs of SAR images can reveal small, subtle changes in elevation or surface deformations.<\/p>\n\n\n\n

At Los Alamos National Laboratory, we analyzed public SAR data from the European Space Agency\u2019s Sentinel-1<\/a> satellite acquired during 2017 and 2018 in north Rakhine to detect the government\u2019s demolition of Rohingya villages conducted in the wake of the August 2017 attacks. Since typical Rohingya villages consist of thatched-roof houses surrounded by palm trees, we used a simple change-detection algorithm to detect deforestation at the locations of villages. That allowed us to identify land being cleared at the locations of destroyed villages, which supported reports of government forces\u2019 methods to erase any trace of the villages.<\/p>\n\n\n\n

We extracted additional evidence of the attacks on Rohingya villages from fire detections provided by NASA\u2019s Fire Information for Resource Management System. Comparing the locations and number of fires detected from periods of relative calm to the period of the attacks revealed an enormous spike in the overall number of fire detections, validating news reports.<\/p>\n\n\n\n

Similarly, at those same locations, we detected highly localized deforestation followed by increased agreement, or coherence, in phase across the two consecutive Sentinel-1 SAR data acquisitions. The initial SAR detections of deforestation over the villages correspond to the destruction and clearing of the area. Following this, the increase in coherence indicated a transition from a vegetated surface, to a cleared surface, to new building construction. We confirmed with optical imagery that this corresponded to the destruction of the villages and the subsequent construction of new buildings over their previous locations. Those buildings were advertised as \u201ctransition camps\u201d for the reintegrating of displaced Rohingya refugees, but have been reported to be in extremely poor condition and fenced in with watch towers and armed police.<\/p>\n\n\n\n

While the detection is not particularly challenging with high-resolution optical data, it can often be rendered impossible by cloud cover. Because SAR is cloud-penetrating and provides the potential for regular monitoring, we were able to track the destruction of the villages nearly every week, and the subsequent construction of \u201ctransit\u201d camps by Myanmar\u2019s government over these cleared areas.<\/p>\n\n\n\n

This demonstrated a new class of signatures of human conflict in SAR imagery and the potential use of these signatures to globally monitor conflict and destruction, which could directly support human rights monitoring and other intelligence-gathering operations.<\/p>\n\n\n\n

The next step is to develop more sophisticated, targeted methods using these data sources to provide more accurate, prompt monitoring tools, as well as new data science tools to autonomously search for these signatures and identify these events, even before they are known by human rights\u2019 monitors. In 2022, NASA, in partnership with India\u2019s space agency, will launch a SAR mission<\/a> to look at Earth\u2019s changing ecosystems. This mission will provide additional critical data that could be used to study geopolitical events and conflicts, as well as ecosystems.<\/p>\n\n\n\n

As highly localized, regional armed conflicts continue to be a defining part of global warfare\u2019s new normal, being able to see what\u2019s happening on the ground from above will be a critical tool for military intelligence, as well as human rights organizations, to hold governments and other groups accountable. By giving us the ability to \u201csee in the dark,\u201d SAR provides human rights\u2019 monitors another tool that could help make the world more transparent\u2014and, we hope, safer.<\/p>\n\n\n\n

Christopher X. Ren is a research scientist in the Intelligence and Space Research division at Los Alamos National Laboratory, which funded the work. Read the full study <\/i>here<\/i><\/a>.<\/i><\/p>\n\n\n\n

This version corrects the photo caption to say that the area pictured is the Rohingya refugee camp in Bangladesh.<\/i><\/p>\n\n\n\n