Triangulating digital trace and traditional data for displacement monitoring

Advancing data-driven solutions for humanitarian response.

Internal displacement remains one of the most pressing humanitarian challenges of our time. At the end of 2024, an unprecedented 83.4 million people were living in internal displacement worldwide (IDMC, 2025). This scale of movement highlights the urgent need for innovative, data-driven solutions to track and understand displacement dynamics.

Traditional data systems, such as surveys and administrative records, are essential for crisis response. Yet, as disaster disrupt population systems triggering mobility, these data systems often fall short in providing real-time, granular insights needed for effective policy and humanitarian action.

A report, co-produced by the Geographic Data Science Lab at the University of Liverpool in partnership with the International Organization for Migration’s Displacement Tracking Matrix (DTM) and led by Dr Elisabetta Pietrostefani, explores how digital trace data—including mobile phone GPS signals and social media activity—can complement traditional sources. By triangulating diverse data streams, we demonstrate how this approach improves the accuracy and responsiveness of displacement monitoring.

Drawing lessons from recent crises, such as the war in Ukraine and the 2022 floods in Pakistan, the report outlines a scalable framework for integrating real-time, high-resolution data into humanitarian decision-making. It provides technical insights, open datasets and replicable methodologies to support global efforts in building resilient, rights-based solutions for displaced populations.