Positional uncertainty in manually digitized map data

Paul V. Bolstad, Paul Gessler, Thomas M. Lillesand

Research output: Contribution to journalArticlepeer-review

61 Scopus citations


Digital map coordinates represent the locations of real world entities. As such, differences can exist between the ‘true' and digital database coordinates of those entities. This paper reports on a statistical characterization of positional error in manually-digitized and map-registered point data, the relative contribution of point type and operator to digitization error, and the effects of map media type on the positional uncertainty associated with registration. Manually-digitized point data were collected by four operators from mylar and paper maps. Point locations for a number of different feature types were sampled from United States Geological Survey (USGS) 1:24 000 scale maps. Linear models were used to estimate the variance components due to among-operator, map media, point type and registration effects. The statistical distribution of signed distance deviations for manually-digitized data was leptokurtic relative to a random normal variate. Unsigned deviations averaged 0-054 mm. Squared distance deviations were not different from a Chi-square random variate. Variance components indicate that among-operator differences in positional uncertainty were large and statistically significant, while differences among point type were small and non-significant. Signed distance deviations associated with a first-order affine followed a normal distribution. Unsigned distance deviations associated with a first-order affine transformation averaged 0068 mm, and squared distance deviations were distributed as a Chi-square. Differences in transformation accuracy were not related to type of map media.

Original languageEnglish (US)
Pages (from-to)399-412
Number of pages14
JournalInternational Journal of Geographical Information Systems
Issue number4
StatePublished - Jan 1 1990


Dive into the research topics of 'Positional uncertainty in manually digitized map data'. Together they form a unique fingerprint.

Cite this