Journal cover Journal topic
Proceedings of the ICA
Journal topic
Articles | Volume 4
Proc. Int. Cartogr. Assoc., 4, 95, 2021
https://doi.org/10.5194/ica-proc-4-95-2021
Proc. Int. Cartogr. Assoc., 4, 95, 2021
https://doi.org/10.5194/ica-proc-4-95-2021

  03 Dec 2021

03 Dec 2021

Data classification methods for preserving spatial patterns

Jochen Schiewe Jochen Schiewe
  • 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.

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