Visualizing patterns in spatially ambiguous point data

Visualizing patterns in spatially ambiguous point data

As technologies permitting both the creation and retrieval of data containing spatial information continue to develop, so do the number of visualizations using such data. This spatial information will often comprise a place name that may be “geocoded” into coordinates, and displayed on a map, frequently using a “heatmap-style” visualization to reveal patterns in the data. Across a dataset, howe...

Visualizing Spatially Varying Distribution Data

Box plot is a compact representation that encodes the minimum, maximum, mean, median, and quartile information of a distribution. In practice, a single box plot is ttrawn for each variable of interest. With the advent of more accessible computing power, we are now facing the problem of visualizing data where there is a distribution at each 2D spatial location. Simply extending the box plot tech...

Visualizing Interchange Patterns in Massive Movement Data

Massive amount of movement data, such as daily trips made by millions of passengers in a city, are widely available nowadays. They are a highly valuable means not only for unveiling human mobility patterns, but also for assisting transportation planning, in particular for metropolises around the world. In this paper, we focus on a novel aspect of visualizing and analyzing massive movement data,...

Detecting Clusters in Spatially Repetitive Point Event Data Sets

The analysis of point event patterns has a long tradition. Of particular interest are patterns of clustering or ‘hot spots’ and such cluster detection lies at the heart of spatial data mining. Certain classes of point event patterns have a significant proportion of the data having a tendency towards exact spatial repetitiveness. Examples are crime and traffic accidents. Spatial superimposition ...

Visualizing Communications Patterns in Nested Data-Parallel Computations