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Handling Attribute Accuracy in Spatial Data Using a Heuristic Approach

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dc.contributor.advisor Wong, David
dc.contributor.author Sun, Min
dc.creator Sun, Min en_US
dc.date.accessioned 2014-09-29T18:05:45Z
dc.date.available 2014-09-29T18:05:45Z
dc.date.issued 2014-08 en_US
dc.identifier.uri https://hdl.handle.net/1920/8975
dc.description.abstract In mapping and analyzing geographical phenomena, data are usually portrayed to be accurate without error. However, spatial data are often estimates derived from surveys, and are associated some levels of uncertainty (i.e. standard error) which make the estimates are unreliable. Ignoring uncertainty information in estimates may produce misleading results and generate spurious spatial patterns or relationships. Approaches dealing with spatial data quality have been developed decades ago, but they are mostly limited to visualize the variation of reliability, failing to incorporate data quality information in mapping and analysis. Without taking steps to address the uncertainty and its propagation in mapping and data analysis, the derived products and results may be misleading.
dc.format.extent 152 pages en_US
dc.language.iso en en_US
dc.rights Copyright 2014 Min Sun en_US
dc.subject Geographic information science and geodesy en_US
dc.subject Geography en_US
dc.subject choropleth map en_US
dc.subject confidence level en_US
dc.subject heuristic en_US
dc.subject spatial aggregation en_US
dc.subject standard error en_US
dc.subject visual analytics en_US
dc.title Handling Attribute Accuracy in Spatial Data Using a Heuristic Approach en_US
dc.type Dissertation en
thesis.degree.level Doctoral en
thesis.degree.discipline Earth Systems and Geoinformation Sciences en
thesis.degree.grantor George Mason University en


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