Nowadays, various data collected in urban context provide unprecedented opportunities for
building a smarter city through urban computing. However, due to heterogeneity, high …

Visualisation research explores techniques for conveying information in a meaningful way to
allow users to make sense of data. This paper aims to review state-of-the-art information …

Urban forms at human-scale, ie, urban environments that individuals can sense (eg, sight,
smell, and touch) in their daily lives, can provide unprecedented insights on a variety of …

Deep learning methods are being increasingly used for urban traffic prediction where
spatiotemporal traffic data is aggregated into sequentially organized matrices that are then …

We propose TimeTables, a novel prototype system that aims to support data exploration,
using embodiment with space-time cubes in virtual reality. TimeTables uses multiple space …

Visual analytics has been widely studied in the past decade. One key to make visual
analytics practical for both research and industrial applications is the appropriate definition …

Observing the relationship between two or more variables over space and time is essential
in many domains. For instance, looking, for different countries, at the evolution of both the life …

Most of the techniques involved in customer clustering and segmentation are based on
conventional methods of quantitative analysis or traditional data mining approaches such as …

Geographic regression models of various descriptions are often applied to identify patterns
and anomalies in the determinants of spatially distributed observations. These types of …

Recent technological innovations have led to an increase in the availability of 3D urban
data, such as shadow, noise, solar potential, and earthquake simulations. These …