What is it about?

The paper discusses Urbane, a visual analytics system designed to help city planners, architects, and policymakers explore and understand urban data. With the rise of large spatio-temporal datasets from urban environments, Urbane allows users to visualize and interact with this data in a meaningful way. One of the key features of Urbane is its ability to handle complex spatial queries quickly, thanks to a technique called Raster Join. This method leverages the power of graphics hardware (GPUs) to process data efficiently, enabling users to explore data interactively without long wait times. Urbane’s interface includes a Map View for visualizing data geographically and a Data Exploration View for comparing multiple datasets. Users can zoom in on specific areas, filter data, and even drill down to analyze data at the building level. Overall, Urbane aims to make data-driven decision-making more accessible and effective for those shaping the future of our cities.

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This page is a summary of: Interactive Visual Exploration of Spatio-Temporal Urban Data Sets using Urbane, May 2018, ACM (Association for Computing Machinery),
DOI: 10.1145/3183713.3193559.
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