Topology Density Map for Urban Data Visualization and Analysis

Density map is an effective visualization technique for depicting the scalar field distribution in 2D space. Conventional methods constructing density maps are mainly based on Euclidean distance, limiting their applicability urban analysis that shall consider road network and traffic. In this work, we propose a new method named Topology Map, targeting accurate intuitive context of environment. Based various constraints connections traffic conditions, first constructs directed acyclic graph (DAG) propagates nonlinear fields along 1D networks. Next, extends to space by identifying key intersecting points DAG calculating every point, yielding weighted Voronoi diagram like effect division. Two case studies demonstrate Map supplies information users provides decision making. An interview with domain experts demonstrates feasibility, usability, effectiveness our method.