This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: How do we form a picture of conflicts? A new study published in the journal Nature explores how different types of data can be combined to give a fuller understanding of armed conflicts.
Lead author Valerie Sticher uses the examples of Ukraine and Myanmar to explain the advantages and limitations of automatically analyzed satellite data. The impression is not misleading. We can see that there are more armed conflicts worldwide than at any time since the end of the Cold War in 1989.
In addition, violence against civilians is increasing. Casualty figures are a very important indicator because loss of life is among the most severe consequences of war. But violent conflicts have many other consequences—for example, people are displaced or their livelihoods are destroyed.
Data on casualty figures is based on textual data, primarily from media reports. However, this type of data often has gaps when it comes to incorporating other forms of violence into the analysis of a conflict. Satellite data from conflict regions has been in use for some time.
What is new, however, is that we now have the ability to analyze satellite data automatically and thus collect data systematically. In our study, we combined text-based and satellite-derived data from two regions—Ukraine and Myanmar—and examined how conflict dynamics evolve spatially and over time. This sheds light on where different types of data have their strengths and weaknesses, and how we might combine them effectively.
In Myanmar, text-based sources indicate that the worst massacres against the Rohingya occurred during the first week. Satellite-derived damage data, however, shows that violence continued for months afterward. This changes how we understand the dynamics of the conflict.
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