Topology Density Map for Urban Data Visualization and Analysis
| Autor: | Shuang-Hua Yang, Zezheng Feng, Haotian Li, Huamin Qu, Wei Zeng |
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| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
Computer science business.industry Scalar (mathematics) Computer Science - Human-Computer Interaction 020207 software engineering 02 engineering and technology Topology Network topology Directed acyclic graph Computer Graphics and Computer-Aided Design Weighted Voronoi diagram Human-Computer Interaction (cs.HC) Visualization Euclidean distance Data visualization Signal Processing 0202 electrical engineering electronic engineering information engineering Computer Vision and Pattern Recognition business Scalar field Software |
| Zdroj: | IEEE transactions on visualization and computer graphics. 27(2) |
| ISSN: | 1941-0506 |
| Popis: | Density map is an effective visualization technique for depicting the scalar field distribution in 2D space. Conventional methods for constructing density maps are mainly based on Euclidean distance, limiting their applicability in urban analysis that shall consider road network and urban traffic. In this work, we propose a new method named Topology Density Map, targeting for accurate and intuitive density maps in the context of urban environment. Based on the various constraints of road connections and traffic conditions, the method first constructs a directed acyclic graph (DAG) that propagates nonlinear scalar fields along 1D road networks. Next, the method extends the scalar fields to a 2D space by identifying key intersecting points in the DAG, dividing the underlying territory into planar regions using a weighted Voronoi diagram, and calculating the scalar fields for every point. Two case studies demonstrate that the Topology Density Map supplies accurate information to users and provides an intuitive visualization for decision making. An interview with domain experts demonstrates the feasibility, usability, and effectiveness of our method. 11 pages, 10 figures |
| Databáze: | OpenAIRE |
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