An empirical study of algorithms for point-feature label placement
ACM Transactions on Graphics (TOG)
Continuous cartogram construction
Proceedings of the conference on Visualization '98
Designing Pixel-Oriented Visualization Techniques: Theory and Applications
IEEE Transactions on Visualization and Computer Graphics
CartoDraw: A Fast Algorithm for Generating Contiguous Cartograms
IEEE Transactions on Visualization and Computer Graphics
Visual Data Mining in Large Geospatial Point Sets
IEEE Computer Graphics and Applications
RecMap: Rectangular Map Approximations
INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
IEEE Computer Graphics and Applications
Shape Simplification Based on the Medial Axis Transform
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
Visual analytics of time dependent 2D point clouds
Proceedings of the 2009 Computer Graphics International Conference
Analyzing statistical relationships between global indicators through visualization
ICTD'09 Proceedings of the 3rd international conference on Information and communication technologies and development
GPU-accelerated 2D point cloud visualization using smooth splines for visual analytics applications
Proceedings of the 24th Spring Conference on Computer Graphics
Proportions in categorical and geographic data: visualizing the results of political elections
Proceedings of the International Working Conference on Advanced Visual Interfaces
Visual boosting in pixel-based visualizations
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
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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.