LAUSR

Abstract Commuting is an essential part of urban life. Long commutes have negative impacts on individuals and society, such as stress, loss of productivity, traffic congestion and air pollution. However, researchers often face the challenge of lack of data such as commute distance, duration, departure/arrival time, and origins/destinations in countries such as China. This study uses points of interest (POIs) to estimate employment locations, and implements a gravity-based model to estimate interzonal commuting patterns in central Shanghai, China. The results reveal a “busy corridor” in the west of the central city, especially during the morning peak hours. This pattern corresponds well with reported real-time traffic conditions in Shanghai. Our methodology offers a promising alternative for studying commuting patterns when such data are limited.