Cities are inherently dynamic. Interesting patterns of behavior typically manifest at several key areas a city over multiple temporal resolutions. Studying these can greatly help variety experts ranging from planners and architects to human behavioral experts. Recent technological innovations have enabled the collection enormous amounts data that in studies. However, techniques using sets focus on understanding context city, thus failing capture dynamic aspects city. The goal this work is...

Architects working with developers and city planners typically rely on experience, precedent data analyzed in isolation when making decisions that impact the character of a city. These are critical enabling vibrant, sustainable environments but must also negotiate range complex political social forces. This requires those shaping built environment to balance maximizing value new development its neighborhood. As result architects focused two issues throughout decision process: a) what defines...

Major League Baseball (MLB) has a long history of providing detailed, high-quality data, leading to tremendous surge in sports analytics research recent years. In 2015, MLB.com released the StatCast spatiotemporal data-tracking system, which been used approximately 2,500 games since its inception capture player and ball locations as well semantically meaningful game events. This article presents visualization infrastructure help query facilitate analysis this new tracking data. The goal is...

Large scale shadows from buildings in a city play an important role determining the environmental quality of public spaces. They can be both beneficial, such as for pedestrians during summer, and detrimental, by impacting vegetation blocking direct sunlight. Determining effects requires accumulation over time across different periods year. In this paper, we propose simple yet efficient class approach that uses properties sun movement to track changing position within fixed interval. We use...

Vector fields analysis traditionally distinguishes conservative (curl-free) from mass preserving (divergence-free) components. The Helmholtz-Hodge decomposition allows separating any vector field into the sum of three uniquely defined components: curl free, divergence free and harmonic. This is usually achieved by using mesh-based methods such as finite differences or elements. work presents a new meshless approach to for 2D discrete fields. It embeds SPH particle-based framework. proposed...

Exploring large virtual environments, such as cities, is a central task in several domains, gaming and urban planning. VR systems can greatly help this by providing an immersive experience; however, common issue with viewing navigating city the traditional sense that users either obtain local or global view, but not both at same time, requiring them to continuously switch between perspectives, losing context distracting from their analysis. In paper, our goal allow navigate points of...

While cities around the world are looking for smart ways to use new advances in data collection, management, and analysis address their problems, complex nature of urban issues overwhelming amount available have posed significant challenges translating these efforts into actionable insights. In past few years, visual analytics tools significantly helped tackle challenges. When analyzing a feature interest, an expert must transform, integrate, visualize different thematic (e.g., sunlight...

Visual analytics systems can greatly help in the analysis of urban data allowing domain experts from academia and city governments to better understand cities, thus enable operations, informed planning policies. Effectively designing these is challenging requires bringing together methods different domains. In this paper, we discuss challenges involved a visual system interactively explore large spatio-temporal sets give an overview our research that combines visualization management tackle...

Sunlight and shadow play critical roles in how urban spaces are utilized, thrive, grow. While access to sunlight is essential the success of environments, shadows can provide shaded places stay during hot seasons, mitigate heat island effect, increase pedestrian comfort levels. Properly quantifying large environments key tackling some important challenges facing cities today. In this paper, we propose Deep Umbra, a novel computational framework that enables quantification at global scale....

Abstract Urbanization has amplified the importance of three‐dimensional structures in urban environments for a wide range phenomena that are significant interest to diverse stakeholders. With growing availability 3D data, numerous studies have focused on developing visual analysis techniques tailored unique characteristics environments. However, incorporating third dimension into analytics introduces additional challenges designing effective tools tackle data's complexities. In this paper,...

Over the past decade, there has been a significant increase in development of visual analytics systems dedicated to addressing urban issues. These distill intricate analysis workflows into intuitive, interactive representations and interfaces, enabling users explore, understand, derive insights from large complex data, including street-level imagery, street networks, building geometries. Developing systems, however, is challenging endeavor that requires considerable programming expertise...

There is a growing expectation for high performance design in architecture which negotiates between the requirements of client and physical constraints building site. Clients projects often challenge architects to maximize view quality since it can significantly increase real estate value. To pursue this challenge, typically move through several revision cycles identify set options satisfy these expectations coordination with other goals project. However, reviewing large quantity within...

The recent explosion in the number and size of spatio-temporal data sets from urban environments social sensors creates new opportunities for data-driven approaches to understand improve cities. Visual analytics systems like Urbane aim empower domain experts explore multiple sets, at different time space resolutions. Since these rely on computationally-intensive spatial aggregation queries that slice summarize over regions, an important challenge is how attain interactivity. While...

Urban planning is increasingly data driven, yet the challenge of designing with at a city scale and remaining sensitive to impact human as important today it was for Jane Jacobs. We address this Mosaic,a tool exploring urban fabric through spatially temporally dense set 7.7 million street-level images from New York City, captured over period year. Working in collaboration professional practitioners, we use Mosaic investigate questions accessibility mobility, preservation retrofitting. In...

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 spatiotemporal datasets create opportunities for new visualizations engage experts from different domains study dynamic behavior spaces this under explored dimension. However, designing is challenging, it requires visual strategies support analysis time-varying data referent city geometry. Although been used analytics,...

This work introduces a scalable topological data structure for manifold tetrahedral meshes called Compact Half-Face (CHF). It provides high degree of scalability, since it is able to optimize the memory consumption/execution time ratio different applications and by using features its levels. An object-oriented API class inheritance virtual instantiation enables unique interface each function at any level. CHF requires very few memory, simple implement easy use, substitutes pointers container...

Abstract Advances in technology coupled with the availability of low‐cost sensors have resulted continuous generation large time series from several sources. In order to visually explore and compare these at different scales, analysts need execute online analytical processing (OLAP) queries that include constraints group‐by's multiple temporal hierarchies. Effective visual analysis requires be interactive. However, while existing OLAP cube‐based structures can support interactive query...

Computational fluid dynamics in simulation has become an important field not only for physics and engineering areas but also simulation, computer graphics, virtual reality even video game development. Many efficient models have been developed over the years, when many contact interactions must be processed, most present difficulties or cannot achieve real-time results executed. The advent of parallel computing enabled development strategies accelerating simulations. Our work proposes a new...

We present a novel algorithm for 2D vector field reconstruction from sparse set of points-vectors pairs. Our approach subdivides the domain adaptively in order to make local piecewise polynomial approximations field. It uses partition unity blend those together, generating global approximation The flexibility this scheme allows handling data very different sources. In particular, work presents important applications proposed method velocity and acceleration fields' analysis, particular fluid...

Abstract. Sharing mobility systems have become part of a sociodemographic trend that has pushed shared modes from the fringe to mainstream transportation systems. Carsharing is mode transport, where service offered in which several people share access and use set vehicles. This relatively new urban gives users for short periods rental, thus providing benefits using private vehicles, while avoiding inherent property charges vehicle. The objective article searches identification selection...