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Techniques for the Visualization of Positional Geospatial Uncertainty

Geospatial data almost always contains some amount of uncertainty due to inaccuracies in its acquisition and transformation. While the data is commonly visualized (e.g. on digital maps), there are unanswered needs for visualizing uncertainty along with it. Most research on effectively doing this addresses uncertainty in data values at geospatial positions, e.g. water depth, human population, or land-cover classification. Uncertainty in the data’s geospatial positions themselves (positional uncertainty) has not been previously focused on in this regard. In this thesis, techniques were created for visualizing positional uncertainty using World Vector Shoreline as an example dataset. The techniques consist of a shoreline buffer zone to which visual effects such as gradients, transparency, and randomized dots were applied. They are viewed interactively via Web Map Service (WMS). In clutter testing with human subjects, a transparency-gradient technique performed the best, followed by a solid-fill technique, with a dots-density-gradient technique performing worst.

Identiferoai:union.ndltd.org:uno.edu/oai:scholarworks.uno.edu:td-2830
Date20 December 2013
CreatorsBarré, Brent A.
PublisherScholarWorks@UNO
Source SetsUniversity of New Orleans
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceUniversity of New Orleans Theses and Dissertations

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