Urban-Scale Human Mobility Modeling With Multi-Source Urban Network Data

Inferring Unmet Human Mobility Demand with Multi-source Urban Data

As the sharing economy has been increasing dramatically in the world, the mobile-hailed ridesharing companies like Uber and Lyft in the US, Didi Chuxing in China has begun to challenge traditional public transportation providers such as bus, subway or taxis. Ridesharing companies have shown their ability to provide the mobility services where public transit has failed. The human mobility demand...

Multi-modal Modeling of Urban Mobility

Design and efficacy of a routing protocol for mobile ad-hoc networks strongly depends on the underlying mobility pattern of the mobile nodes. Counter to the perception of mobility being random in time and space, we show that spatial modality is a key trait of human mobility. Most of the mobility of an individual can be captured by a small fraction of all locations, called spatial modes, visited...

Supersampling and Network Reconstruction of Urban Mobility

Understanding human mobility is of vital importance for urban planning, epidemiology, and many other fields that draw policies from the activities of humans in space. Despite the recent availability of large-scale data sets of GPS traces or mobile phone records capturing human mobility, typically only a subsample of the population of interest is represented, giving a possibly incomplete picture...

Measuring and modeling urban sprawl: Data, scale and spatial dependencies

3 D Urban Modeling from City - Scale Aerial Lidar Data

3D reconstruction from point clouds is a fundamental problem in both computer vision and computer graphics. As urban modeling is an important reconstruction problem that has various significant applications, this thesis investigates the complex problem of reconstructing 3D urban models from aerial LiDAR (Light Detection And Ranging) point cloud. In the first part of this thesis, an automatic ur...