Emergence of urban growth patterns from human mobility behavior

Spatiotemporal Patterns of Urban Human Mobility

The modeling of human mobility is adopting new directions due to the increasing availability of big data sources from human activity. These sources enclose digital information about daily visited locations of a large number of individuals. Examples of these data include: mobile phone calls, credit card transactions, bank notes dispersal, check-ins in internet applications, among several others....

Emergence in Urban Growth

Exploring Spatial-Temporal Patterns of Urban Human Mobility Hotspots

Understanding human mobility patterns provides us with knowledge about human mobility in an urban context, which plays a critical role in urban planning, traffic management and the spread of disease. Recently, the availability of large-scale human-sensing datasets enables us to analyze human mobility patterns and the relationships between humans and their living environments on an unprecedented...

Extracting Dynamic Urban Mobility Patterns from Mobile Phone Data

The rapid development of information and communication technologies (ICTs) has provided rich resources for spatio-temporal data mining and knowledge discovery in modern societies. Previous research has focused on understanding aggregated urban mobility patterns based on mobile phone datasets, such as extracting activity hotspots and clusters. In this paper, we aim to go one step further from id...

Dissecting the Spatial Structure of Cities from Human Mobility Patterns to Define Functional Urban Boundaries

Since the industrial revolution, accelerated urban growth has overflown administrative divisions, merged cities into large built extensions, and blurred the boundaries between urban and rural land-uses. These traits, present in most of contemporary metropolis, complicate the definition of cities, a crucial issue considering that objective and comparable metrics are the basic inputs needed for t...