LAUSR

ABSTRACT Social, economic, and environmental statistical data associated with geographic points are currently globally available in large amounts. When conventional thematic maps, such as proportional symbol maps or point diagram maps, are used to represent these data, the maps appear cluttered if the point data volumes are relatively large or cover a relatively dense region. To overcome these limitations, we propose a new type of thematic map for statistical data associated with geographic points: the point grid map. In a point grid map, an input point data set is transformed into a grid in which each point is represented by a square grid cell of equal size while preserving the relative position of each point, which leads to a clear and uncluttered appearance, and the grid cells can be shaded or patterned with symbols or diagrams according to the attributes of the points. We present an algorithm to construct a point grid map and test it with several simulated and real data sets. Furthermore, we present some variants of the point grid map.