  Human mobility research concerns spatiotemporal individual and population
movement. Accurate modeling and prediction of human mobility can provide
opportunities to monitor, manage and optimize human movement for improved
social-economic benefit. In this paper, we adopt the dynamic mode decomposition
algorithm to model population human mobility using visitor flow data between
different states in the United States from 2019 to 2021 [1]. We train multiple
DMD models with different low rank structures, and evaluate their modeling
accuracy and predictability on novel testing data.
