Jan Brus - User study for representing the spatial data uncertainty in land cover maps with use of intrinsic and extrinsic methods
- 1. User study for representing the spatial data uncertainty in land cover maps with use of intrinsic and extrinsic methods Jan BRUS www.geoinformatics.upol.cz
- 2. Question about quality of outputs • • • • Are the map true? How about the quality of presented data? What about the subjectivity? Will reader know about the positional and other errors caused by data manipulation? • Study focused on uncertainty visualisations intuitiveness www.geoinformatics.upol.cz
- 3. Sources of Uncertainty – data quality elements • Lineage (description of the source material from which the data were derived and the methods of derivation) • Positional accuracy (resolution of the measurement) • Attribute accuracy (both measurement accuracy and class assignment accuracy) • Logical consistency (describing the fidelity of relationships inside data structure) • Completeness (relationship between the objects represented and the abstract universe) • Currency (time currency, time relevance) • Credibility (reliability of information source, experiences) • Subjectivity (amount of human judgments in the information) • Interrelatedness (source independence) www.geoinformatics.upol.cz
- 4. Is uncertainty visualisation necessary? • Isn’t better to provide geoinformation with some kind of uncertainty? • Isn‘t maps (geovisualizations) with information about data uncertainty confusing? • What‘s the right/good way of uncertainty visualization? • What‘s better in a real decision process? www.geoinformatics.upol.cz
- 5. Approach in uncertainty visualizations Examples Usability testing www.geoinformatics.upol.cz
- 8. Representation of Uncertainty • Presenting the data sets with different associated uncertainty • positional accuracy • attribute accuracy • subjectivity • How best to represent the data? • How to best reflect reflect the uncertainty? www.geoinformatics.upol.cz
- 9. Laboratory setup • SMI RED 250 eye-tracker with 120 Hz sampling rate • SMI Experiment Center - design of experiment • SMI BeGaze, OGAMA, R software - data analyses • remote eye tracker most practical method of ET • illuminator/eye camera module placed below line of sight • all participants were recorded and have to speak during testing • evaluation of right and wrong answers was based on post processing of recorded video www.geoinformatics.upol.cz
- 10. Study and experiments • the aim of our study was to evaluate the effect of uncertainty visualisations on eye movements and performance in maprelated tasks • the study involved decision making questions where the participants were presented with several uncertainty visualisation methods based on intrinsic and extrinsic methods • finding areas with the least or most uncertainty of selected land cover class – based on intuitiveness • additive factor of the study also compared user performance with and without the use of the legend www.geoinformatics.upol.cz
- 11. Testing details • user perception of uncertainty visualizations derived from photointerpretation of land cover classes • maps without legend – intuitiveness of uncertainty methods • 14 participants – 8 uncertainty methods as stimuli • dependent variables were represented by following metrics derived from the analysis of eye-tracking data: – fixation duration – number of fixation – fixation count, saccade count – and more www.geoinformatics.upol.cz
- 12. Delineation of uncertainty – entropy approach • Land Facet Corridor Tools for ArcGIS • can be used for each map layer • combination of entropies • showing most uncertain • map algebra (Wellmann and Regenauer-Lieb, 2012 www.geoinformatics.upol.cz
- 13. Entropy calculation • concept of entropy was applied to landcover classes www.geoinformatics.upol.cz
- 14. Methods examples hillshade - positive hillshade - negative glyphs transparent dots - size transparent grid grid - width of line transparency quadtree www.geoinformatics.upol.cz
- 17. Results wrong answer right answer 2 5 6 5 7 8 6 10 12 9 8 9 7 6 8 4 hillshade positive hillshade negative glyphs www.geoinformatics.upol.cz transparent dots transparent grid grid - width of line transparency quadtree
- 18. Results Fixation Lenght 350 300 250 200 Mean 150 Median 100 50 0 hillshade positive hillshade negative glyphs www.geoinformatics.upol.cz transparent dots transparent grid grid - width of line transparency quadtree
- 19. Results Number of Fixations 70 60 50 40 30 20 10 0 hillshade - positive hillshade negative glyphs www.geoinformatics.upol.cz transparent dots transparent grid grid - width of line transparency quadtree
- 21. Results • As a top rated when compared to all methods and metrics have been examined methods: • transparent grid • transparent circles • problem with implementation these methods • quantification of uncertainty based on blur or transparency • Semantic Depth of Field (Kosara, 2011) • partly method grid - width of line • and quadtree method www.geoinformatics.upol.cz
- 22. Problems • • • • • • small amount of respondents respondents not domain experts very specific task – can be domain depended difficult visualisation methods same area (rotated and fliped) target group mostly cartographers and geoinformatics professionals • not statistically proved • long interpretation of results from recorded video www.geoinformatics.upol.cz
- 23. Conclusion and future • in our study we try to capture the uncertainty visualisation connected with land cover classes • study focused more on uncertainty visualisations methods • this should bring more adequate results to uncertainty visualisation community • it is clear that uncertainty visualizations will have great importance in optimization of cartographic products and presenting geographic data in the future • comparison of different uncertainty visualization methods • proofing and confirming results from the past research www.geoinformatics.upol.cz
- 24. Conclusion and future • same method for different studies • more respondents • combination of different spatial quality components in one visualisation www.geoinformatics.upol.cz
- 25. Thank you for your attention… jan.brus@upol.cz www.geoinformatics.upol.cz The presentation has been completed within the project CZ.1.07/2.2.00/28.0078 “InDOG” which is co-financed from European Social Fund and State financial resources of the Czech Republic.