Data classification methods for preserving spatial patterns
- HafenCity University of Hamburg, Lab for Geoinformatics and Geovisualization (g2lab), Germany
Keywords: choropleth maps, data classification, spatial patterns
Abstract. The primary purpose of choropleth maps is to display or even to emphasize special relationships or patterns in the spatial distribution of attribute values. However, because classification methods commonly used and implemented in software packages (such as equidistance, quantiles, Jenks, etc.) are data-driven, a preservation of such spatial patterns is not guaranteed. Instead of such a data-driven approach in the following a task-oriented procedure is pursued: For typical patterns (local and global extreme values, large value differences to neighbours, spatial clusters, hot/cold spots) specific algorithms have been developed, implemented and tested.