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 …

The spatial time series generated by city sensors allow us to observe urban phenomena like
environmental pollution and traffic congestion at an unprecedented scale. However …

Arguably the most representative application of artificial intelligence, autonomous driving
systems usually rely on computer vision techniques to detect the situations of the external …

Dynamic visual experience is the most common way for people to perceive a cityscape.
Previous research reviews on cityscapes have mainly focused on spatial planning, social …

While cities around the world are looking for smart ways to use new advances in data
collection, management, and analysis to address their problems, the complex nature of …

Exploring large virtual environments, such as cities, is a central task in several domains,
such as gaming and urban planning. VR systems can greatly help this task by providing an …

Over the past decade, there has been a significant increase in the development of visual
analytics systems dedicated to addressing urban issues. These systems distill intricate …

Visual exploration of spatial data relies heavily on spatial aggregation queries that slice and
summarize the data over different regions. These queries comprise computationally …

Urban design is a highly visual discipline that requires visualization for informed decision
making. However, traditional urban design tools are mostly limited to representations on 2D …

Large scale shadows from buildings in a city play an important role in determining the
environmental quality of public spaces. They can be both beneficial, such as for pedestrians …