Combining multiple maps of line features to infer true position

Jarrett J. Barber, Steven D. Prager

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Map positional error refers to the difference between a feature's coor-dinate pair on a map and the corresponding true, unknown coordinate pair. In a geographic information system (GIS), this error is propagated through all operations that are functions of position, so that lengths, areas, etc., are uncertain. Often, a map's metadata provides a nominal statement on the positional error of a map, and such information has frequently been used to study the propagation of error through such operations. This article presents a statistical model for map positional error, incorporating positional error metadata as prior information, along with map coordinates, and, in particular, the information contained in the linearity of features. We demonstrate that information in the linearity of features can greatly improve the precision of true location predictions.

Original languageEnglish (US)
Pages (from-to)625-658
Number of pages34
JournalBayesian Analysis
Volume3
Issue number3
DOIs
StatePublished - 2008
Externally publishedYes

Fingerprint

Line
Metadata
Linearity
Geographic Information Systems
Prior Information
Geographic information systems
Statistical Model
Categorical or nominal
Propagation
Unknown
Prediction
Demonstrate

Keywords

  • GIS
  • Linear features
  • Lines
  • Maps
  • Positional error

ASJC Scopus subject areas

  • Applied Mathematics
  • Statistics and Probability

Cite this

Combining multiple maps of line features to infer true position. / Barber, Jarrett J.; Prager, Steven D.

In: Bayesian Analysis, Vol. 3, No. 3, 2008, p. 625-658.

Research output: Contribution to journalArticle

Barber, Jarrett J. ; Prager, Steven D. / Combining multiple maps of line features to infer true position. In: Bayesian Analysis. 2008 ; Vol. 3, No. 3. pp. 625-658.
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