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Related Experiment Video

Updated: Jun 21, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

Published on: October 11, 2016

A model of clutter for complex, multivariate geospatial displays.

Maura C Lohrenz1, J Gregory Trafton, R Melissa Beck

  • 1Naval Research Laboratory, Code 7440.1, Stennis Space Center, MS 39529, USA. mlohrenz@nrlssc.navy.mil

Human Factors
|July 29, 2009
PubMed
Summary
This summary is machine-generated.

The novel color-clustering clutter (C3) model accurately predicts subjective clutter in geospatial displays. This model, based on color density and saliency, can improve the design of electronic maps and charts.

Related Experiment Videos

Last Updated: Jun 21, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)
12:26

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Published on: October 11, 2016

Area of Science:

  • Human-Computer Interaction
  • Data Visualization
  • Geospatial Information Systems

Background:

  • Clutter in complex data displays negatively impacts target search performance.
  • Existing clutter models have limitations in accurately assessing display clutter.
  • The color-clustering clutter (C3) model offers a novel approach to quantifying visual clutter.

Purpose of the Study:

  • To introduce and validate the color-clustering clutter (C3) model for measuring clutter in geospatial displays.
  • To compare the C3 model's performance against human subjective clutter ratings.
  • To assess the C3 model's convergent validity using empirical data.

Main Methods:

  • Two experiments were conducted involving subjective clutter ratings of information visualizations and aeronautical charts.
  • Empirical data from Experiment 1 were used to calibrate the C3 model's parameters.
  • Model predictions were correlated with human ratings in both experiments to assess validity.

Main Results:

  • Experiment 1 yielded a correlation of 0.76 between C3 model predictions and subjective clutter ratings.
  • Experiment 2 demonstrated a higher correlation of 0.86, outperforming a previous clutter model.
  • Analysis of outliers indicated potential areas for future refinement of the C3 model.

Conclusions:

  • The C3 model serves as a reliable predictor of perceived clutter in geospatial displays.
  • Geospatial clutter is significantly influenced by color density and saliency, key components of the C3 model.
  • Further enhancements to the C3 model can be achieved through pattern analysis techniques.