There exist many facets of error and uncertainty in digital spatial information. As error or uncertainty will not likely ever be completely eliminated, a better understanding of its impacts is necessary. Spatial analytical approaches, in particular, must somehow address data quality issues. This can range from evaluating impacts of potential data uncertainty in planning processes that make use of methods to devising methods that explicitly account for error/uncertainty. To date, little has been done to structure methods accounting for error.
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- Partial requirement for: Ph.D., Arizona State University, 2013Note typethesis
- Includes bibliographical references (p. 96-112)Note typebibliography
- Field of study: Geography