Estimating Displacement via Nighttime Satellite Imagery

Abstract

Nighttime satellite imagery provides data which may be useful in addressing the needs of people affected by war. Using Syria as a case study, I seek to build a tool which allows for estimating the number of people who flee a given city after a battle; to do this, I build a machine learning model which estimates a given city’s population by evaluating various different models which analyze different aspects/features of the lights over the city. With the results achieved, I hope to provide humanitarian organizations that operate in conflict zones with actionable information that is useful for planning their crisis response and relief efforts.