Jianbo Tang

1 week ago | tandfonline.com | Chen Ding |Jianbo Tang |Ming Zhang |Hang Wu

AbstractIdentifying urban functional zones (UFZs) is of great significance for urban planning and sustainable development. Current approaches typically focus on the recognition of static and single-label UFZs, failing to capture their dynamic nature and functional heterogeneity. In this study, we propose a multi-temporal collaborative graph neural network (MCGNN) model for dynamic urban functions identification with a multi-label strategy.