Toward Quantitative Geocode Accuracy Metrics

Daniel W. Goldberg1, John P. Wilson2, Myles G. Cockburn3
1.Department of Computer Science University of Southern California Los Angeles, CA USA
2.Departments of Computer Science, and Geography University of Southern California Los Angeles, CA USA
3.Department of Preventive Medicine University of Southern California Los Angeles, CA USA
1. dwooldbe@usc.edu;2. jpwilson@usc.edu;3. mylesc@usc.edu

Abstract: Existing geocode quality metrics provide little utility for those interested in the spatial uncertainty associated with a geocoded location. The per-geocode metrics describe aspatial characteristics of individual aspects of the geocoding process, while the per-dataset spatial metrics provide only general information that may not apply to a single geocode of interest. In this paper we develop a method for describing the certainty of a geocoded (latum as a spatial probability surface based on an uncertainty propagation model which takes into account the certainty stemming from each portion of the geocoding process. This surface-based geocode output structure provides a more truthful view of the uncertainty present in these data and will enable more realistic estimates of information derived from them in such tasks as environmental exposure modeling.

Keywords: geocode; uncertainty, spatialprobabilty distributions

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