Date of Award
Fall 12-2013
Degree Type
Thesis
Degree Name
M.S.
Degree Program
Computer Science
Department
Computer Science
Major Professor
Abdelguerfi, Mahdi
Second Advisor
Ioup, Elias
Third Advisor
Hoque, Tamjidul
Fourth Advisor
Tu, Shengru
Abstract
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.
Recommended Citation
Barré, Brent A., "Techniques for the Visualization of Positional Geospatial Uncertainty" (2013). University of New Orleans Theses and Dissertations. 1720.
https://scholarworks.uno.edu/td/1720
Rights
The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.