Related Experiment Video
Updated: May 23, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)
Published on: October 11, 2016
Enhanced Spatial Stability with Hilbert and Moore Treemaps
Abstract:
Treemaps are a well known and powerful space-filling visualisation method for displaying hierarchical data. Many alternative treemap algorithms have been proposed, often with the aim being to optimise performance across several criteria, including spatial stability to assist users in locating and monitoring items of interest. In this paper, we demonstrate that spatial stability is not fully captured by the commonly used "distance change" (DC) metric, and we introduce a new "location drift" (LD) metric to more fully capture spatial stability. An empirical study examines the validity and usefulness of the location drift metric, showing that it explains some effects on user performance that distance change does not. Next, we introduce "Hilbert" and "Moore" treemap algorithms, which are designed to achieve high spatial stability. We assess their performance in comparison to other treemaps, showing that Hilbert and Moore treemaps perform well across all stability metrics.
Related Concept Videos
Stability of structures
Plotting of Topographic Maps
Multimachine Stability
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
Methods of Obtaining Topography
Orthogonal Trajectories
Topographic Surveying and Contours