Internal displacement continues to rise at an alarming pace, with 83.4 million people living in displacement at the end of 2024 (IDMC, 2025). As crises intensify and diversify, humanitarian actors face increasing pressure to generate timely, reliable, and actionable insights on population movements. This session presents an innovative, policy-driven framework that integrates traditional humanitarian data systems with emerging digital trace data, including mobile phone GPS signals and social media activity—to enhance how displacement is monitored and understood. The framework is detailed in the newly published report Dynamic Estimates of Displacement in Disaster Regions: A Policy-driven Framework Triangulating Data, developed by the University of Liverpool’s Geographic Data Science Lab in collaboration with IOM’s Displacement Tracking Matrix (DTM). This work demonstrates how triangulating multiple data sources can strengthen humanitarian analysis and operational decision-making. Drawing on case studies from Ukraine and Pakistan, and beyond, the session will illustrate how digital trace data can complement established monitoring tools by generating more dynamic, granular, and real-time estimates of displacement across both conflict and climate-related disaster settings. A panel discussion will examine the operational, ethical, and technical considerations for integrating diverse data streams at scale. By sharing lessons learned and actionable recommendations, this session aims to equip humanitarian practitioners, policymakers, and data specialists with pathways to advance responsible, data-driven approaches to displacement monitoring and crisis response.

displacement monitoring and crisis response.