In many applications, data is collected and indexed by geo-spatial location. Discovering interesting patterns through visualization is an important way of gaining insight about such data. A previously proposed approach is to apply local placement functions such as PixelMaps that transform the input data set into a solution set that preserves certain constraints while making interesting patterns more obvious and avoid data loss from overplotting. In experience, this family of spatial transformations can reveal fine structures in large point sets, but it is sometimes difficult to relate those structures to basic geographic features such as cities and regional boundaries. Recent information visualization research has addressed other types of transformation functions that make spatially-transformed maps with recognizable shapes. These types of spatial-transformation are called global shape functions. In particular, cartogram-based map distortion has been studied. On the other hand, cartogram-based distortion does not handle point sets readily. In this study, we present a framework that allows the user to specify a global shape function and a local placement function. We combine cartogram-based layout (global shape) with PixelMaps (local placement), obtaining some of the benefits of each toward improved exploration of dense geo-spatial data sets
Visualization of Geo-spatial Point Sets via Global Shape Transformation and Local Pixel Placement
Christian Panse,Mike Sips,D. Keim,S. North
Published 2006 in IEEE Transactions on Visualization and Computer Graphics
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PUBLICATION RECORD
- Publication year
2006
- Venue
IEEE Transactions on Visualization and Computer Graphics
- Publication date
2006-09-01
- Fields of study
Geography, Computer Science, Medicine
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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